tag:blogger.com,1999:blog-20345784722184541502024-03-05T08:01:47.563-08:00See Reason: Looking at the World through Science and ReasonI go through life looking at everything objectively and rationally, whether I like it or not. You can come too.Shawnhttp://www.blogger.com/profile/06311618271709855605noreply@blogger.comBlogger12125tag:blogger.com,1999:blog-2034578472218454150.post-48829475705887862052022-06-27T00:04:00.039-07:002022-06-27T03:07:16.893-07:00What is “Sentient AI?”<div style="text-align: left;">Recently, as anyone who has managed to find this post is likely to know, a <a href="https://www.washingtonpost.com/technology/2022/06/11/google-ai-lamda-blake-lemoine/">Google engineer was placed on leave after raising concerns that they may have created a sentient artificial intelligence (AI)</a>, called LaMDA (Language Model for Dialog Applications).</div><p class="MsoNormal" style="font-size: medium;">This story made waves in the popular press, with many people outside the field wondering if we had at last created the sci-fi holy grail of AI: a living machine. Meanwhile, those involved in cognitive science or AI research were quick to point out the myriad ways LaMDA fell short of what we might call “sentience.”</p><p class="MsoNormal" style="font-size: medium;">Eventually, <a href="https://slate.com/technology/2022/06/google-ai-sentience-lamda.html">enough</a> <a href="https://www.theatlantic.com/ideas/archive/2022/06/google-lamda-chatbot-sentient-ai/661322/">popular</a> <a href="https://www.cnn.com/2022/06/13/tech/google-ai-not-sentient/index.html">press</a> <a href="https://www.msnbc.com/opinion/msnbc-opinion/google-s-ai-impressive-it-s-not-sentient-here-s-n1296406">articles</a> <a href="https://www.wired.com/story/lamda-sentient-ai-bias-google-blake-lemoine/">came</a> <a href="https://www.newscientist.com/article/2323905-has-googles-lamda-artificial-intelligence-really-achieved-sentience/">out</a> <a href="https://www.lifewire.com/no-googles-ai-isnt-self-aware-experts-say-5441624">to</a> <a href="https://mashable.com/article/google-ai-racist-sexist-bias">firmly</a> <a href="https://www.businessinsider.com/google-engineer-thinks-artificial-intelligence-bot-has-become-sentient-2022-6">establish</a> <a href="https://www.bloomberg.com/news/articles/2022-06-14/google-has-more-pressing-ai-problems-than-sentient-bots">that</a> <a href="https://www.cnbc.com/2022/06/15/ai-wont-be-sentient-for-decades-says-stanford-researcher.html">anyone</a> <a href="https://fortune.com/2022/06/13/google-ai-researchers-sentient-chatbot-claims-ridiculed-by-experts/">who</a> <a href="https://www.popsci.com/technology/google-ai-chatbot-sentience/">thought</a> <a href="https://iai.tv/articles/googles-ai-is-not-sentient-not-even-slightly-auid-2153">there</a> <a href="https://cosmosmagazine.com/technology/google-ai-lamda-sentient/">might</a> <a href="https://bigthink.com/13-8/google-ai-engineer-sentient/">be</a> <a href="https://www.insidehook.com/daily_brief/tech/google-sentient-artificial-intelligence">a</a> <a href="https://www.vice.com/en/article/3ad8gk/googles-ai-isnt-sentient-but-it-is-biased-and-terrible">modicum</a> <a href="https://www.jewishexponent.com/2022/06/22/googles-sentient-ai-cant-count-in-a-minyan-but-it-still-raises-ethical-dilemmas/">of</a> <a href="https://www.nature.com/articles/d41586-022-01663-6">sentience</a> <a href="https://www.ocregister.com/2022/06/14/google-debate-over-sentient-bots-overshadows-deeper-ai-issues/">in</a> <a href="https://www.lawfareblog.com/cyberlaw-podcast-podcast-sentient">LaMDA</a> <a href="https://garymarcus.substack.com/p/nonsense-on-stilts?utm_source=twitter&sd=pf&s=r">was</a> a fool, the victim of their own credulity for wanting to anthropomorphize anything capable of language. That previous sentence has 23 hyperlinks to different articles with various angles describing why having a sentience conversation about LaMDA is some flavor of naïve, ridiculous, stupid, or all of the above, if you’d like to see those arguments.</p><p class="MsoNormal" style="font-size: medium;">It's not necessary to add yet another piece about whether or not LaMDA is sentient to the internet (though we will touch on that more later). At this point, it’s likely every possible argument has been made. Far more interesting is to use this opportunity to explore a more fundamental question: what would sentient AI be, and how would we recognize it?</p><p class="MsoNormal" style="font-size: medium;"><o:p></o:p></p><h2 style="text-align: left;">Always Check With Captain Picard First</h2><h1><o:p></o:p></h1><p class="MsoNormal" style="font-size: medium;">Before we get into details, let’s first look at perhaps one of the best scenes and the finest bits of acting Patrick Stewart ever delivered as Captain Picard, a case quite literally about whether or not an AI (in this case, Data) was sentient.</p><p class="MsoNormal" style="font-size: medium;"><o:p></o:p></p><div class="separator" style="clear: both; text-align: center;"><iframe allowfullscreen="" class="BLOG_video_class" height="521" src="https://www.youtube.com/embed/vjuQRCG_sUw" width="627" youtube-src-id="vjuQRCG_sUw"></iframe></div><p class="MsoNormal" style="font-size: medium;">This scene is essentially a TLDR; for this entire post. We’ll go into more detail on several of these topics, including describing what properties a sentient AI might need to possess in a scientifically verifiable way. But like so many things, Star Trek was decades ahead of its time here (and also like so many things, authors like <a href="https://en.wikipedia.org/wiki/I,_Robot">Isaac Asimov</a> and <a href="https://en.wikipedia.org/wiki/Do_Androids_Dream_of_Electric_Sheep%3F">Phillip K. Dick</a> were decades ahead of Star Trek getting there). Captain Picard’s argument points out a fundamental issue most have trying to identify sentience: they can’t define what they are looking for.</p><p class="MsoNormal" style="font-size: medium;"><o:p></o:p></p><h2 style="text-align: left;">What is Sentience?</h2><h1><o:p></o:p></h1><p class="MsoNormal" style="font-size: medium;">If you read enough articles on LaMDA, and indeed on the more general idea of human-like general AI, you might notice a surprising trend. Even when the speaker is someone engaged in research which seeks to create intelligent systems, even when they state a belief that human-level AI is possible (<a href="https://research.aimultiple.com/artificial-general-intelligence-singularity-timing/">even if it might take a long time</a>), they often provide vague or qualitative definitions of sentience. On the one hand they do not doubt sentient AI is possible, and on the other, they say little to nothing substantive about how we might recognize it. </p><p class="MsoNormal" style="font-size: medium;">As Carissa Véliz, associate professor of philosophy at the Institute for Ethics in AI at the University of Oxford, wrote in a <a href="https://slate.com/technology/2022/06/google-ai-sentience-lamda.html">Slate article</a>:</p><p class="MsoNormal" style="font-size: medium; margin-bottom: 0.0001pt; margin-left: 0.5in; margin-right: 0.5in;">To be sentient is to have the capacity to feel. A sentient creature is one who can feel the allure of pleasure and the harshness of pain. It is someone, not something, in virtue of there being “something it is like” to be that creature, in the words of philosopher Thomas Nagel.</p><p class="MsoNormal" style="font-size: medium;">Or from Gary Marcus, founder and CEO of Geometric Intelligence and author of books including "Rebooting AI: Building Artificial Intelligence We Can Trust," in a <a href="https://garymarcus.substack.com/p/nonsense-on-stilts">blog post</a>:</p><p class="MsoNormal" style="font-size: medium; margin-bottom: 0.0001pt; margin-left: 0.5in; margin-right: 0.5in;">To be sentient is to be aware of yourself in the world; LaMDA simply isn’t. It’s just an illusion, in the grand history of ELIZA a 1965 piece of software that pretended to be a therapist (managing to fool some humans into thinking it was human), and Eugene Goostman, a wise-cracking 13-year-old-boy impersonating chatbot that won a scaled-down version of the Turing Test.</p><p class="MsoNormal" style="font-size: medium;">Or from Melanie Mitchell, Davis Professor of Complexity at the Santa Fe Institute, and the author of “Artificial Intelligence: A Guide for Thinking Humans,” <a href="https://www.msnbc.com/opinion/msnbc-opinion/google-s-ai-impressive-it-s-not-sentient-here-s-n1296406">as reported by MSNBC</a>:</p><p class="MsoNormal" style="font-size: medium; margin-bottom: 0.0001pt; margin-left: 0.5in; margin-right: 0.5in;">There's no real agreed-upon definition for [sentience]. Not only for artificial intelligence, but for any system at all. The technical definition might be having feelings, having awareness and so on. It's usually used synonymously with consciousness, which is another one of those kinds of ill-defined terms. </p><p class="MsoNormal" style="font-size: medium; margin-bottom: 0.0001pt; margin-left: 0.5in; margin-right: 0.5in;">But people have kind of a sense, themselves, that they are sentient; you feel things, you feel sensations, you feel emotions, you feel a sense of yourself, you feel aware of what's going on all around you. It's kind of a colloquial notion that philosophers have been arguing about for centuries.</p><p class="MsoNormal" style="font-size: medium;">Notice that these (admittedly poetic) descriptions of sentience shift the burden of defining or detecting it on to other nebulous concepts, like “feeling” or “awareness” or “consciousness.” Why is it that even people who work in AI, people trying to build the kinds of systems they think could one day become sentient, nonetheless have a difficult time defining what a sentient AI would look like? <a href="https://en.wikipedia.org/wiki/I_know_it_when_I_see_it">Like pornography to the Supreme Court</a>, the “I know it when I see it” definition seems to be the consensus answer. For practical purposes, this kind of definition is insufficient, because it will suffer greatly from our own biases about what “seems” sentient.</p><p class="MsoNormal" style="font-size: medium;">If we want to have a more constructive notion of what makes something sentient, we need to establish something more workable than a hand wave at what sentience might be. To do that, we will look at sentience in a new way: </p><p class="MsoNormal" style="font-size: medium; margin-bottom: 0.0001pt; margin-left: 0.5in; margin-right: 0.5in;"><b>“Sentience” is not a property an entity possesses. It is a label applied to ascribe motivation to an entity’s behaviors.</b></p><p class="MsoNormal" style="font-size: medium;">This definition has several important components. First, it rejects the notion that sentience is an innate property of any entity – what we might call “intrinsic sentience.” As we’ve seen, attempts to define sentience as some sort of nebulous “feeling” or “sense of self” are not truly definitions. They simply pass the buck for defining sentience on to whatever might be meant by a feeling or a sense. Second, it defines sentience as a label applied to that entity by external agents: what we might call “extrinsic sentience.” Third, the purpose those agents have in applying the label is to explain why the entity may be exhibiting certain behaviors in the first place. Together, these second and third components make the application of the label “sentient” to an entity <i>relative to an external observer</i>, and thereby imply the value of applying that label to an entity is only in how that external observer decides it should affect the treatment of the entity. </p><p class="MsoNormal" style="font-size: medium;">We will go through these three aspects in more detail shortly. First, however, it’s important to provide more explanation for why intrinsic definitions of sentience are not a very productive approach.<o:p></o:p></p><h2 style="text-align: left;">Suitcase Words</h2><h1><o:p></o:p></h1><p class="MsoNormal" style="font-size: medium;">Typical definitions of sentience make it into what Marvin Minsky called a “suitcase word:” a container into which we bundle a bunch of things we don’t understand, close it up, give it a name, and pretend like we have accomplished something. He most famously <a href="https://www.edge.org/conversation/marvin_minsky-consciousness-is-a-big-suitcase">described consciousness as a suitcase word</a> (and I HIGHLY recommend reading that interview in its entirety), In many ways, discussion of sentience and consciousness are intertwined (or even the same thing), and as such, Minsky’s arguments regarding consciousness apply equally well to sentience. Intrinsic definitions of concepts that are suitcase words attempt to layer more meaning on top of an already nebulous base, to the extent that they are meaningless in any kind of scientific context. </p><p class="MsoNormal" style="font-size: medium;">Why is it so damning if sentience is a suitcase word? After all, our experience of being sentient is complicated, and truly hard to describe. We can’t pin it down precisely, one might argue, because fully understanding it strains the limits of our ability to understand ourselves. Sentience is a big, powerful thing, and perhaps we shouldn’t try to reduce it to something specific.</p><p class="MsoNormal" style="font-size: medium;">The problem, then, is that leaves us only with <i>our personal experience </i>as a framework to understand sentience. Because everyone’s personal experience of being sentient is different (or at a minimum, it’s impossible to know if two people’s experiences are the same or not), this approach does not yield a concrete, testable (therefore scientific) definition of sentience. It produces a definition in which, hopefully, allusions to a personal experience are enough for another person to understand what is being defined.</p><p class="MsoNormal" style="font-size: medium;">Because definitions of sentience based on personal experience rely on allusions to personal experience, they lead to efforts to define sentience intrinsically. Yet despite numerous attempts, there is no accepted intrinsic definition of sentience. Philosophers and scientists have proposed and debated possibilities for millennia, with no consensus found thus far. This means one of two things: either we are incapable (so far) of understanding sentience as an intrinsic property, or sentience is not an intrinsic property. </p><p class="MsoNormal" style="font-size: medium;">While I am fully on board with the <a href="http://seereason.blogspot.com/2021/10/ai-medicine-and-xenocomplexity-beyond.html">concept that humans might not be capable of understanding everything about the universe</a>, whichever of those two possibilities about intrinsic sentience are true, from a practical standpoint, continued efforts to frame sentience intrinsically will not lead to a productive definition or use, because both are searching to define an indefinable object.<o:p></o:p></p><h2 style="text-align: left;">The Homunculus Theory of Sentience</h2><h1><o:p></o:p></h1><p class="MsoNormal" style="font-size: medium;">The reliance on subjective experience or ineffable qualities to define sentience intrinsically embodies the “homunculus theory” of sentience: the belief that, if you keep digging deep enough, you will eventually find an atomic self, an irreducible sentient core of our beings. Setting aside arguments that this core is a soul (this may not be the site for you if you’d make that claim), the homunculus theory of sentience lacks an actual definition for what this core is. Is it part of the brain? A collection of memories? A pattern of neural activations that recurs every time we think about “ourselves?” No proposals like this are backed by science. Not unlike <a href="https://freakonomics.com/podcast/robert-sapolsky-i-dont-think-we-have-any-free-will-whatsoever/">Robert Sapolsky’s argument</a> that there must not be free will, because at no point can our brain spontaneously do anything except follow the laws of physics, there is no discrete part of our mental faculties you can draw a neat border around and say “here, this is the sentient part that comes up with spontaneous thoughts.” In the most generous intrinsic case, sentience is a continuous, emergent property of our mental processes, an advantageous evolutionary illusion that helps coordinate our survival and pass on our genes, not a monolithic output of a discrete mental faculty – meaning there isn’t anything in particular to “look for” to find the origin of sentience.</p><p class="MsoNormal" style="font-size: medium;">Nonetheless, <i>homunculus theory feels right</i>. It feels like a way to define sentience because it matches the way it feels to be a person. We <i>do</i> feel that we are an irreducible whole, like a pilot sitting in the cockpit of a biological body, looking out the windshield and reading our instruments and pulling levers. That pilot is the homunculus. But from <a href="https://en.wikipedia.org/wiki/Phineas_Gage">Phineas Gage</a> to <a href="https://www.youtube.com/watch?v=4RksLFJ7A2M">social media influencers</a> to <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3797360/">doctors</a> to <a href="https://www.lesswrong.com/posts/GBXKZujXSZe84aAL9/the-homunculus-problem">optical illusions</a>, there are numerous examples of people’s “self” being more mutable, rudimentary, or deterministic than the level on which we feel the homunculus operates. Despite all these examples, however, homunculus theory remains extremely powerful, even among philosophers and scientists, in no small part because there are no alternative explanations that match our subjective experience of sentience. <i>We feel like an atomic sentience</i>, regardless of whether any independent evidence supports that feeling. This feeling also provides a useful, if imprecise, way to test for sentience in a human-centric world: to what extent can I <a href="https://fortelabs.co/blog/a-pattern-recognition-theory-of-mind/">pattern-match</a> the actions of another entity to my own, such that I can imagine they have their own sentient homunculus just like mine? </p><p class="MsoNormal" style="font-size: medium;">A pattern-matching approach like this creates biases in assessing sentience. First, a person supposes anything similar enough to them (other people, or perhaps even advanced animals) to display behavior they could imagine doing themselves must also have a homunculus. Second, a person assumes that the possession of a homunculus is essential for sentience. When combined, these biases cause us to assume anything<i> (a) whose actions we can explain, </i>or<i> (b) whose functional details we understand, </i>must not be sentient. Machine intelligences fall victim to both assumptions.<o:p></o:p></p><h2 style="text-align: left;">Why Machine Intelligences Don’t Feel Sentient</h2><h1><o:p></o:p></h1><p class="MsoNormal" style="font-size: medium;">A machine intelligence takes actions we can mostly explain, at least in terms of fulfilling the goals it was trained to pursue (assuming it’s a supervised system or otherwise trained). LaMDA has been described as “<a href="https://www.theatlantic.com/ideas/archive/2022/06/google-lamda-chatbot-sentient-ai/661322/">auto-correct on steroids</a>,” and indeed, any chatbot one could imagine constructing today could probably be described that way. Chatbots are pattern recognizers, and as we know that’s how they work, we write off their achievements as simply the results of sophisticated pattern recognition.</p><p class="MsoNormal" style="font-size: medium;">Ironically, pattern recognition is among humanity’s strongest skills, if not the strongest, and there is no way to prove whether another person is sentient or a sophisticated pattern matcher using an intrinsic definition of sentience (see Captain Picard's efforts above). <a href="https://en.wikipedia.org/wiki/Turing_test">The Turing test</a> was predicated on our inability to do distinguish between these two scenarios. Yet because we know chatbots were designed and trained to recognize patterns in language, to us, that’s all they seem to be doing – even if we can’t prove whether we are doing anything more than pattern recognition ourselves.</p><p class="MsoNormal" style="font-size: medium;">We also understand the mechanisms by which a machine intelligence functions. Neural networks are extremely complex, and it’s not always possible to understand exactly what role each calculation and simulated neuron play in a behavior. Yet we still understand the mathematics that underlie these networks, how to construct them to achieve desired capabilities, and how to train them to exhibit seemingly intelligent behavior. We know that layered combinations of simulated neurons (which, at this point, bear only a passing resemblance to biological neurons) are capable of modeling extremely complicated nonlinear mappings of inputs to outputs, and this modeling can produce results that seem very intelligent. Since we understand how these systems function, our natural conclusion is they are rather mechanical and basic, in contrast to systems whose function we don’t fully understand, such as our own minds (which are, admittedly, far more complex than any artificial neural network ever created… so far). Our ability to explain their function removes the gaps in understanding into which we can bundle concepts we don’t know how to define.</p><p class="MsoNormal" style="font-size: medium;">For these reasons, it seems unlikely the homunculus theory of sentience would <i>ever </i>conclude a machine intelligence was sentient. We know both how to explain the actions of a machine intelligence and how it functions, and so there isn’t enough mystery left for us to ascribe any of its behavior to a nebulously defined intrinsic sentience. Homunculus theory expects there to be something <i>more </i>than just a set of explainable actions and functional responses at the core of a sentient being. It only ascribes an entity sentience when something unexplainable can be found within it, something complex and hard to define but easily alluded to. This bias forms because our most natural description of sentience is through our personal experience with it: that there is a core “us” within which our sentience lives. A homunculus. So, we assume anything else that’s sentient must be equally hard for us to explain or describe, and have a homunculus that yields its sentience. We might visualize this point of view like this:</p><p class="MsoNormal" style="font-size: medium;"></p><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiTw0XYhgSyvp0MfWX9Vq8SqQY3BWaG0Z6CBDJmstYaB6pBMSwduoQJc9ADN-H2Hbe1aQf_SF3LUo8jgfUOn7CNW92GGUUCqMmnT7roXRaEvWeuC5cZvXUrvslEtYyepfcXx7Yp2H34I7ajjjKSwldVXc-BdVHU1buhOG27o1EP08Y4zICxTUkok_WU/s3256/Sentience.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="2363" data-original-width="3256" height="464" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiTw0XYhgSyvp0MfWX9Vq8SqQY3BWaG0Z6CBDJmstYaB6pBMSwduoQJc9ADN-H2Hbe1aQf_SF3LUo8jgfUOn7CNW92GGUUCqMmnT7roXRaEvWeuC5cZvXUrvslEtYyepfcXx7Yp2H34I7ajjjKSwldVXc-BdVHU1buhOG27o1EP08Y4zICxTUkok_WU/w640-h464/Sentience.png" width="640" /></a><span style="text-align: left;"> </span></div><p></p><p class="MsoNormal" style="font-size: medium;">We privilege the properties of our own complexity because of our inability to describe it well. In other words, any sufficiently indescribable intelligence is indistinguishable from sentience.<o:p></o:p></p><h2 style="text-align: left;">An Extrinsic Definition of Sentience</h2><h1><o:p></o:p></h1><p class="MsoNormal" style="font-size: medium;">Rather than letting our subjective experiences of sentience guide our efforts to decide whether another entity is sentient, we can cast sentience in a more productive way. Instead of looking for sentience as some object or property contained within an entity, we will simply use “sentient” to describe an entity exhibiting a collection of behaviors, constructing an extrinsic definition of sentience. </p><p class="MsoNormal" style="font-size: medium;">What are the behaviors that would lead us to call something sentient? Certainly, this question can be (and has been) debated extensively, but for now, here is a reasonable starting point:</p><p class="MsoListParagraphCxSpFirst" style="mso-list: l0 level1 lfo1; text-indent: -0.25in;"></p><p style="text-align: left;"></p><p style="text-align: left;"></p><ul style="text-align: left;"><li><span style="font-size: medium;"><b style="text-indent: -0.25in;">Goal-Seeking</b><span style="text-indent: -0.25in;">. The entity identifies and pursues goals.</span></span></li></ul><ul style="text-align: left;"><li><span style="font-size: medium;"><b style="text-indent: -0.25in;">Intelligence. </b><span style="text-indent: -0.25in;">The entity performs problem solving tasks which require causal understanding of multiple interacting components.</span></span></li></ul><ul style="text-align: left;"><li><span style="font-size: medium;"><b style="text-indent: -0.25in;">Justification</b><span style="text-indent: -0.25in;">. The entity provides logical reasoning to explain its actions.</span></span></li></ul><ul style="text-align: left;"><li><span style="font-size: medium;"><b style="text-indent: -0.25in;">Sense of Self</b><span style="text-indent: -0.25in;">. The entity acts in ways that show its conception of itself as a discrete entity.</span></span></li></ul><ul style="text-align: left;"><li><span style="font-size: medium;"><b style="text-indent: -0.25in;">Self-Awareness</b><span style="text-indent: -0.25in;">. The entity acts in opinionated or nuanced ways that indicate it understands its place in its surroundings or the world.</span></span></li></ul><ul style="text-align: left;"><li><span style="font-size: medium;"><b style="text-indent: -0.25in;">Consistency</b><span style="text-indent: -0.25in;">. The entity’s above properties do not change absent stimulus or abruptly over time.</span></span></li></ul><p></p><p></p><!--[if !supportLists]--><o:p></o:p><p></p><p class="MsoListParagraphCxSpMiddle" style="mso-list: l0 level1 lfo1; text-indent: -0.25in;"><!--[if !supportLists]--><o:p></o:p></p><p class="MsoListParagraphCxSpMiddle" style="mso-list: l0 level1 lfo1; text-indent: -0.25in;"><!--[if !supportLists]--><o:p></o:p></p><p class="MsoListParagraphCxSpMiddle" style="mso-list: l0 level1 lfo1; text-indent: -0.25in;"><!--[if !supportLists]--><o:p></o:p></p><p class="MsoListParagraphCxSpMiddle" style="mso-list: l0 level1 lfo1; text-indent: -0.25in;"><!--[if !supportLists]--><o:p></o:p></p><p class="MsoListParagraphCxSpLast" style="mso-list: l0 level1 lfo1; text-indent: -0.25in;"><!--[if !supportLists]--><o:p></o:p></p><p class="MsoNormal" style="font-size: medium;">Interestingly, these are many of the same kinds of properties an intrinsic definition of sentience would say a homunculus has. However, importantly, here, <i>the properties are described in terms of an entity’s actions</i>, not qualities the entity possesses. In other words, an intrinsically defined sentience <i>has</i> these kinds of qualities; an extrinsically defined sentience <i>exhibits</i> these qualities.</p><p class="MsoNormal" style="font-size: medium;">It may seem like a minor distinction, but extrinsically defined sentience eliminates the biases created by the homunculus theory. The question of sentience is not searching through the source code of a machine learning model or dissecting the brain of some alien lifeform, hunting for irreducible gems of sentience. In fact, we can’t even search our own brains for such gems, because they don’t exist. Instead, tests for sentience should not focus on <i>how </i>sentience is being achieved; they should focus on <i>if </i>sentience is being achieved. An extrinsic definition of sentience is the only form of definition which creates a testable definition in the scientific sense. Relatedly, the Turing test has taken a lot of criticism in the LaMDA debate, in large part because people have misconstrued its purpose: it was designed to test an extrinsic definition of sentience, not an intrinsic one.<o:p></o:p></p><h2 style="text-align: left;">So, is LaMDA Sentient?</h2><h1><o:p></o:p></h1><p class="MsoNormal" style="font-size: medium;">While I have not ever interacted with LaMDA myself, from the reports about it, it seems to come up short on at least two counts for extrinsic sentience. LaMDA’s statements suggest it may be meeting the Justification, Sense of Self, and Self-Awareness categories, but it doesn’t seem to meet the Goal-Seeking or Intelligence criteria. It’s also not clear whether it meets Consistency criteria, though this could also simply be because of the relatively small, edited amount of information which has been made public. This is an admittedly odd combination of outcomes (for example, because it seems Sense of Self and Self-Awareness are easier to achieve than Goal-Seeking or Intelligence?), but appears to best reflect the state of the field nonetheless.</p><p class="MsoNormal" style="font-size: medium;">However, we now have an extrinsic definition of sentience, which does not let our understanding of why or how a machine intelligence functions prevent us from recognizing its sentience. This extrinsic definition of sentience is not a suitcase word. It’s a list of behaviors which, together, comprise both necessary and sufficient criteria to be called sentient. Of course, by reducing it to a list of behaviors, we have removed the mystique of what being “sentient” means. If it feels like reducing sentience to such a mundane list of behaviors, rather than that deep, indescribable sense of consciousness we subjectively feel, is somehow oversimplifying it or removing a critical holistic component from the definition of sentience, well, that’s why the homunculus theory has been hindering our ability to make progress discussing sentience for millenia.</p><p class="MsoNormal" style="font-size: medium;">This extrinsic definition of sentience is even more helpful because it doesn’t merely describe how to assess the sentience of a human-created machine intelligence. It could be applied to any entity or system displaying the constituent behaviors. Is a dog sentient? Is an alien lifeform sentient? Is Earth sentient? Is some hypothetical self-organizing cloud of space dust sentient? We can interpret the behavior of such entities, without referenece to their structure or function, to try and make that decision. And if we have essentially removed any special meaning from the word “sentience” by using it simply to refer to a set of behaviors, well, that is by design. It is not a goal to retain undefinable qualities in sentience (or anything else for that matter). Eliminating those kinds of vagaries is consistent with the long history of scientific and philosophical progress, and allows us to consider what rights, protections, and benefits should come with being “sentient” without regard to how sentience is achieved.<o:p></o:p></p><p class="MsoNormal" style="font-size: medium;">In fact, ascribing of great importance to whether an entity is sentient is largely a problem of our own making. Any ethical, moral, or legal consequences of an entity being sentient are thes consequences of values we have imbued into the concept of sentience historically, largely understood intrinsically. Our tendency to describe sentience intrinsically has connected our quest to define the sentience homunculus to these ethical, moral, and legal questions. If sentience is defined intrinsically, it is important to know how to find the component of the entity that yields sentience in order to decide if it is ethical to terminate it, for example. But because intrinsic definitions of sentience ultimately do not make any particular concrete, testable statements about sentience (there is no homunculus to find), practical applications of an intrinsic definition of sentience will never move past philosophical debate about the nature of sentience and how to detect it.</p><p class="MsoNormal" style="font-size: medium;">An extrinsic definition of sentience is not only practical. It is also the only means by which a test for sentience can be defined. While an extrinsic definition may feel it loses some of the “magic” of the subjective experience of sentience, attempts to preserve that ineffable quality of experiencing sentience only hinder our ability to understand sentience as anything other than magic, certainly not a very useful scientific approach. By using an extrinsic definition of sentience, one day, when something just a bit more sophisticated than LaMDA comes along, we can recognize its sentience without digging around for a specific nugget of sentience within it. Such definitions might also help us recognize other hard-to-define qualities – such as <a href="https://phys.org/news/2018-04-opinion-ai-hal-real-emotions.html">emotions</a>, <a href="https://www.newscientist.com/article/mg25033420-900-can-a-robot-ever-be-conscious-and-how-would-we-know-if-it-were/">consciousness</a> (<a href="https://www.scientificamerican.com/article/a-test-for-consciousness/">like this!</a>), or <a href="https://www.khanacademy.org/science/biology/intro-to-biology/what-is-biology/a/what-is-life">being alive</a> – through extrinsic means as well.<o:p></o:p></p><div class="separator" style="clear: both; text-align: center;"><br /></div><br /><br />Shawnhttp://www.blogger.com/profile/06311618271709855605noreply@blogger.com0tag:blogger.com,1999:blog-2034578472218454150.post-61045092132662253232021-10-18T12:40:00.002-07:002022-06-23T12:42:02.687-07:00AI, Medicine, and Xenocomplexity: Beyond Human-Understandable Data<p><span style="background-color: white; caret-color: rgb(41, 41, 41); color: #292929; font-family: charter, Georgia, Cambria, "Times New Roman", Times, serif; font-size: 20px; letter-spacing: -0.05999999865889549px;">Medical applications for Artificial Intelligence (AI) and Deep Learning (DL) have drawn a lot of attention from investors, the media, and the public at large. Whether helping us </span><a class="ay acc" href="https://www.radiologytoday.net/archive/rt0118p10.shtml" rel="noopener ugc nofollow" style="box-sizing: inherit; caret-color: rgb(41, 41, 41); font-family: charter, Georgia, Cambria, "Times New Roman", Times, serif; font-size: 20px; letter-spacing: -0.05999999865889549px;" target="_blank">better interpret radiological images</a><span style="background-color: white; caret-color: rgb(41, 41, 41); color: #292929; font-family: charter, Georgia, Cambria, "Times New Roman", Times, serif; font-size: 20px; letter-spacing: -0.05999999865889549px;">, </span><a class="ay acc" href="https://www.pharmacytimes.com/view/ai-can-help-identify-potential-adverse-effects-from-drug-drug-interactions" rel="noopener ugc nofollow" style="box-sizing: inherit; caret-color: rgb(41, 41, 41); font-family: charter, Georgia, Cambria, "Times New Roman", Times, serif; font-size: 20px; letter-spacing: -0.05999999865889549px;" target="_blank">identify potentially harmful drug interactions</a><span style="background-color: white; caret-color: rgb(41, 41, 41); color: #292929; font-family: charter, Georgia, Cambria, "Times New Roman", Times, serif; font-size: 20px; letter-spacing: -0.05999999865889549px;">, </span><a class="ay acc" href="https://www.nature.com/articles/d43747-021-00045-7" rel="noopener ugc nofollow" style="box-sizing: inherit; caret-color: rgb(41, 41, 41); font-family: charter, Georgia, Cambria, "Times New Roman", Times, serif; font-size: 20px; letter-spacing: -0.05999999865889549px;" target="_blank">discover new therapeutic targets</a><span style="background-color: white; caret-color: rgb(41, 41, 41); color: #292929; font-family: charter, Georgia, Cambria, "Times New Roman", Times, serif; font-size: 20px; letter-spacing: -0.05999999865889549px;">, or simply </span><a class="ay acc" href="https://hbr.org/2018/12/using-ai-to-improve-electronic-health-records" rel="noopener ugc nofollow" style="box-sizing: inherit; caret-color: rgb(41, 41, 41); font-family: charter, Georgia, Cambria, "Times New Roman", Times, serif; font-size: 20px; letter-spacing: -0.05999999865889549px;" target="_blank">organize medical information</a><span style="background-color: white; caret-color: rgb(41, 41, 41); color: #292929; font-family: charter, Georgia, Cambria, "Times New Roman", Times, serif; font-size: 20px; letter-spacing: -0.05999999865889549px;">, AI and DL are beginning to impact real care given to real patients. Because these systems learn from examining data, rather than being programmed to follow specific logic, it is often challenging to understand why they make the decisions they make. Furthermore, recent results suggest the role of AI in medicine is transitioning to a new phase, in which AI enables us to do more than merely solve known problems in an automated way. AI is enabling us to solve </span><strong class="uc he" style="box-sizing: inherit; caret-color: rgb(41, 41, 41); color: #292929; font-family: charter, Georgia, Cambria, "Times New Roman", Times, serif; font-size: 20px; letter-spacing: -0.05999999865889549px;">“xenocomplex” problems</strong><span style="background-color: white; caret-color: rgb(41, 41, 41); color: #292929; font-family: charter, Georgia, Cambria, "Times New Roman", Times, serif; font-size: 20px; letter-spacing: -0.05999999865889549px;">: problems so difficult, humans have a hard time identifying a solution or even fully articulating the problem itself. To fully translate these capabilities into better outcomes, we must recognize and come to terms with the ways in which AI may be able to solve problems we don’t fully understand.</span></p><p><img alt="" class="ae acn aco" height="560" loading="lazy" role="presentation" src="https://miro.medium.com/max/700/1*6RpO7MXOjoE-_v1AGN7BAA.jpeg" width="700" /></p><h1 class="acp acq zl bv kz acr acs act th acu acv acw tm tn acx to tr ts acy tt tw tx acz ty ub aea by" data-selectable-paragraph="" id="72b6" style="box-sizing: inherit; color: #292929; font-family: sohne, "Helvetica Neue", Helvetica, Arial, sans-serif; font-size: 22px; line-height: 28px; margin: 3.14em 0px -0.37em;">Primer: What Is Deep Learning?</h1><p class="pw-post-body-paragraph abh abi zl uc b abj aeb wa abl abm aec wd abo abp aed abr abs abt aee abv abw abx aef abz aca acb qe by" data-selectable-paragraph="" id="13ec" style="box-sizing: inherit; color: #292929; font-family: charter, Georgia, Cambria, "Times New Roman", Times, serif; font-size: 20px; letter-spacing: -0.003em; line-height: 32px; margin: 0.86em 0px -0.46em; word-break: break-word;">If you’re already familiar with AI and DL, this section will mostly be review. But if not, let’s begin with some background.</p><p class="pw-post-body-paragraph abh abi zl uc b abj abk wa abl abm abn wd abo abp abq abr abs abt abu abv abw abx aby abz aca acb qe by" data-selectable-paragraph="" id="e4c6" style="box-sizing: inherit; color: #292929; font-family: charter, Georgia, Cambria, "Times New Roman", Times, serif; font-size: 20px; letter-spacing: -0.003em; line-height: 32px; margin: 2em 0px -0.46em; word-break: break-word;"><a class="ay acc" href="https://en.wikipedia.org/wiki/Artificial_intelligence" rel="noopener ugc nofollow" style="box-sizing: inherit;" target="_blank">Artificial Intelligence (AI)</a> is a broad term and simply refers to systems that (a) are non-human, and (b) display behavior that is “intelligent,” in that their behavior is a reasonable effort to pursue some goal. <a class="ay acc" href="https://en.wikipedia.org/wiki/Machine_learning" rel="noopener ugc nofollow" style="box-sizing: inherit;" target="_blank">Machine Learning (ML)</a> is a sub-domain of AI, which specifically refers to AI systems which “learn” how to pursue goals — how to appear intelligent — through examining data. <a class="ay acc" href="https://en.wikipedia.org/wiki/Deep_learning" rel="noopener ugc nofollow" style="box-sizing: inherit;" target="_blank">Deep Learning (DL)</a> is a further sub-domain of ML, in which learning is performed by a many-layered neural network examining multitudes of example datasets.</p><p class="pw-post-body-paragraph abh abi zl uc b abj abk wa abl abm abn wd abo abp abq abr abs abt abu abv abw abx aby abz aca acb qe by" data-selectable-paragraph="" id="4d3c" style="box-sizing: inherit; color: #292929; font-family: charter, Georgia, Cambria, "Times New Roman", Times, serif; font-size: 20px; letter-spacing: -0.003em; line-height: 32px; margin: 2em 0px -0.46em; word-break: break-word;">DL is a form of ML called <a class="ay acc" href="https://en.wikipedia.org/wiki/Supervised_learning" rel="noopener ugc nofollow" style="box-sizing: inherit;" target="_blank">Supervised Learning</a>, which simply means that while the learning algorithm is being trained on its data, the data is labeled. The algorithm is told, for example, whether or not there is a cat in the picture it is examining, or is given a text transcript of an audio file. (As you might expect, another major form of ML, <a class="ay acc" href="https://en.wikipedia.org/wiki/Unsupervised_learning" rel="noopener ugc nofollow" style="box-sizing: inherit;" target="_blank">Unsupervised Learning</a>, is when the algorithm doesn’t have labels for the data with which it is working.) Having a lot of well-labeled training data is a major factor in creating a well-performing supervised learning system, especially for DL systems.</p><p class="pw-post-body-paragraph abh abi zl uc b abj abk wa abl abm abn wd abo abp abq abr abs abt abu abv abw abx aby abz aca acb qe by" data-selectable-paragraph="" id="f444" style="box-sizing: inherit; color: #292929; font-family: charter, Georgia, Cambria, "Times New Roman", Times, serif; font-size: 20px; letter-spacing: -0.003em; line-height: 32px; margin: 2em 0px -0.46em; word-break: break-word;">Graphically, the hierarchy of methods looks like this:</p><p class="pw-post-body-paragraph abh abi zl uc b abj abk wa abl abm abn wd abo abp abq abr abs abt abu abv abw abx aby abz aca acb qe by" data-selectable-paragraph="" id="f444" style="box-sizing: inherit; color: #292929; font-family: charter, Georgia, Cambria, "Times New Roman", Times, serif; font-size: 20px; letter-spacing: -0.003em; line-height: 32px; margin: 2em 0px -0.46em; word-break: break-word;"><img alt="" class="ae acn aco" height="531" loading="lazy" role="presentation" src="https://miro.medium.com/max/700/1*sHFmi18VGYxxoEdP1bQSkQ.png" style="caret-color: rgb(0, 0, 0); color: black; letter-spacing: normal;" width="700" /></p><p class="pw-post-body-paragraph abh abi zl uc b abj abk wa abl abm abn wd abo abp abq abr abs abt abu abv abw abx aby abz aca acb qe by" data-selectable-paragraph="" id="d873" style="box-sizing: inherit; color: #292929; font-family: charter, Georgia, Cambria, "Times New Roman", Times, serif; font-size: 20px; letter-spacing: -0.003em; line-height: 32px; margin: 2em 0px -0.46em; word-break: break-word;">Owing to their large body of well-labeled data, some of the greatest successes seen in DL have been in classic AI fields of study: image recognition, speech recognition, machine translation, natural language processing. In other classic areas, like playing chess or go, researchers devised clever means of training DL systems that essentially allowed the system to generate its own large, well-labeled training datasets.</p><p class="pw-post-body-paragraph abh abi zl uc b abj abk wa abl abm abn wd abo abp abq abr abs abt abu abv abw abx aby abz aca acb qe by" data-selectable-paragraph="" id="4f7f" style="box-sizing: inherit; color: #292929; font-family: charter, Georgia, Cambria, "Times New Roman", Times, serif; font-size: 20px; letter-spacing: -0.003em; line-height: 32px; margin: 2em 0px -0.46em; word-break: break-word;">Other than access to plenty of training data, these successes have another thing in common: they all are within domains humans understand well. Most people can easily tell if there is a cat in a picture or what words are in a speech (assuming they speak the language). People trained to do more difficult tasks can translate one language to another, play chess or go, or drive a car safely. Within their narrow domain, these AI’s are “doing things humans do,” but in an automated, often superior, way compared to humans.</p><h1 class="acp acq zl bv kz acr acs act th acu acv acw tm tn acx to tr ts acy tt tw tx acz ty ub aea by" data-selectable-paragraph="" id="d6aa" style="box-sizing: inherit; color: #292929; font-family: sohne, "Helvetica Neue", Helvetica, Arial, sans-serif; font-size: 22px; line-height: 28px; margin: 3.14em 0px -0.37em;">Xenocomplexity and Challenging Domains</h1><p class="pw-post-body-paragraph abh abi zl uc b abj aeb wa abl abm aec wd abo abp aed abr abs abt aee abv abw abx aef abz aca acb qe by" data-selectable-paragraph="" id="e679" style="box-sizing: inherit; color: #292929; font-family: charter, Georgia, Cambria, "Times New Roman", Times, serif; font-size: 20px; letter-spacing: -0.003em; line-height: 32px; margin: 0.86em 0px -0.46em; word-break: break-word;"><a class="ay acc" href="https://en.wikipedia.org/wiki/Artificial_neural_network" rel="noopener ugc nofollow" style="box-sizing: inherit;" target="_blank">Neural networks</a> are based on an idealized, simplified model of human neurons and neurological organs. While we can build powerful neural networks with ease, we often have difficulty pinning down why a neural network comes to a particular conclusion. When a neural network claims “there is a cat here” in a photo or translates “chez moi” to “my house,” we often can’t point at any specific chain of logic that led it to conclude that. We can easily tell if it got the answer right or not, but not why it got that answer. Neural networks suffer from a problem of inscrutability.</p><p class="pw-post-body-paragraph abh abi zl uc b abj abk wa abl abm abn wd abo abp abq abr abs abt abu abv abw abx aby abz aca acb qe by" data-selectable-paragraph="" id="bd6a" style="box-sizing: inherit; color: #292929; font-family: charter, Georgia, Cambria, "Times New Roman", Times, serif; font-size: 20px; letter-spacing: -0.003em; line-height: 32px; margin: 2em 0px -0.46em; word-break: break-word;">Their inscrutability arises because DL systems are not programmed to execute a specific problem-solving algorithm. They are programmed to learn and, even if data contain thousands or millions of interconnected variables, develop the ability to draw conclusions in complex, hyperdimensional space. This capability means a DL system can operate in a far more complex problem space than humans typically do. Neural networks have the potential to solve problems beyond human capacity. There is no reason DL systems must be confined to problems humans-solvable problems like identifying cats. In fact, there is no reason DL systems must be confined to solving problems humans can even articulate as problems in the first place.</p><p class="pw-post-body-paragraph abh abi zl uc b abj abk wa abl abm abn wd abo abp abq abr abs abt abu abv abw abx aby abz aca acb qe by" data-selectable-paragraph="" id="9019" style="box-sizing: inherit; color: #292929; font-family: charter, Georgia, Cambria, "Times New Roman", Times, serif; font-size: 20px; letter-spacing: -0.003em; line-height: 32px; margin: 2em 0px -0.46em; word-break: break-word;">For one example, DL systems have made significant progress on difficult problems in the field of chaos theory. Chaos theory is the formal study of chaotic systems; that is, systems whose development is extremely difficult to predict from their initial conditions. There are lots of examples of chaotic systems (remember Ian Malcolm with drops of water on his hand in Jurassic Park?). One problem chaos theorists use to develop and test new models is predicting the spread of a fire front. For several decades, researchers made steady, incremental progress using complex equations and ever-increasing computation to predict the evolution of a fire front. These equations consumed large numbers of connected variables and enabled them to predict the fire’s development a short time in the future, but the number and interconnectedness of their variables inevitably lead prediction to diverge from observation.</p><p class="pw-post-body-paragraph abh abi zl uc b abj abk wa abl abm abn wd abo abp abq abr abs abt abu abv abw abx aby abz aca acb qe by" data-selectable-paragraph="" id="2434" style="box-sizing: inherit; color: #292929; font-family: charter, Georgia, Cambria, "Times New Roman", Times, serif; font-size: 20px; letter-spacing: -0.003em; line-height: 32px; margin: 2em 0px -0.46em; word-break: break-word;">Then, in 2018, <a class="ay acc" href="https://www.quantamagazine.org/machine-learnings-amazing-ability-to-predict-chaos-20180418/" rel="noopener ugc nofollow" style="box-sizing: inherit;" target="_blank">researchers at the University of Maryland</a> employed a DL technique called reservoir computing to create a model that could predict <span class="aeh" style="box-sizing: inherit; font-style: italic;">eight times</span> further into the future than all previous results. Importantly, their model had no human-coded knowledge about fire fronts or the complicated equations used to study them. All it had was a powerful learning model fed data generated by many fire front simulations, from which it learned to become good at predicting the behavior of future fire fronts given some initial conditions.</p><p class="pw-post-body-paragraph abh abi zl uc b abj abk wa abl abm abn wd abo abp abq abr abs abt abu abv abw abx aby abz aca acb qe by" data-selectable-paragraph="" id="e318" style="box-sizing: inherit; color: #292929; font-family: charter, Georgia, Cambria, "Times New Roman", Times, serif; font-size: 20px; letter-spacing: -0.003em; line-height: 32px; margin: 2em 0px -0.46em; word-break: break-word;">This result was a great achievement, and demonstrates a technique that may prove useful for making predictions in other chaotic systems, like the weather, heart arrhythmias, earthquakes, or supply chain disruptions. However, more fundamentally, it suggests another possibility: that humans are not intelligent enough to comprehend the true complexity of these systems. Perhaps the number of variables is too vast, or their connections are too nuanced, or the system is so complicated we are unable to reduce it to a system of rules we can grasp. Describing a system as “chaotic” may say more about our limitations as understanders of phenomena, rather than about the phenomena themselves. These phenomena can be described as xenocomplex: fundamentally too complex for humans to comprehend.</p><h1 class="acp acq zl bv kz acr acs act th acu acv acw tm tn acx to tr ts acy tt tw tx acz ty ub aea by" data-selectable-paragraph="" id="0223" style="box-sizing: inherit; color: #292929; font-family: sohne, "Helvetica Neue", Helvetica, Arial, sans-serif; font-size: 22px; line-height: 28px; margin: 3.14em 0px -0.37em;">Xenocomplexity, AI, and Medicine</h1><p class="pw-post-body-paragraph abh abi zl uc b abj aeb wa abl abm aec wd abo abp aed abr abs abt aee abv abw abx aef abz aca acb qe by" data-selectable-paragraph="" id="3519" style="box-sizing: inherit; color: #292929; font-family: charter, Georgia, Cambria, "Times New Roman", Times, serif; font-size: 20px; letter-spacing: -0.003em; line-height: 32px; margin: 0.86em 0px -0.46em; word-break: break-word;">If we turn back to biology and medicine, we can see some inklings of problems which may exhibit xenocomplexity.</p><p class="pw-post-body-paragraph abh abi zl uc b abj abk wa abl abm abn wd abo abp abq abr abs abt abu abv abw abx aby abz aca acb qe by" data-selectable-paragraph="" id="7d22" style="box-sizing: inherit; color: #292929; font-family: charter, Georgia, Cambria, "Times New Roman", Times, serif; font-size: 20px; letter-spacing: -0.003em; line-height: 32px; margin: 2em 0px -0.46em; word-break: break-word;">For example, in 2020, <a class="ay acc" href="https://www.nature.com/articles/d41586-020-03348-4" rel="noopener ugc nofollow" style="box-sizing: inherit;" target="_blank">Google used a DL system called AlphaFold</a> to achieve breakthrough results predicting protein structure, an extremely challenging though not formally chaotic problem. Like fire front growth prediction, the field of protein folding prediction had a long history, with a biennial competition for researchers to benchmark their algorithms against each other. Also like DL’s breakout predicting fire front development, AlphaFold’s 2020 blockbuster performance predicting protein structure dwarfed all previous approaches. Since that time, efforts by researchers and companies to exploit DL to design new proteins have exploded. AlphaFold’s dramatic success suggests it may be operating in a much more complex decision space than the best human minds were able to bring to bear, and that operating within this degree of complexity greatly improves the ability to successfully predict protein structure. These are aspects of a xenocomplex problem.</p><p class="pw-post-body-paragraph abh abi zl uc b abj abk wa abl abm abn wd abo abp abq abr abs abt abu abv abw abx aby abz aca acb qe by" data-selectable-paragraph="" id="5efe" style="box-sizing: inherit; color: #292929; font-family: charter, Georgia, Cambria, "Times New Roman", Times, serif; font-size: 20px; letter-spacing: -0.003em; line-height: 32px; margin: 2em 0px -0.46em; word-break: break-word;">In another example, at Phase Genomics, our <a class="ay acc" href="https://www.businesswire.com/news/home/20211018005750/en/Phase-Genomics-Announces-Next-Generation-Cytogenomics-Platform-to-Advance-Precision-Diagnosis-and-Treatment-in-Reproductive-Genetics-and-Oncology" rel="noopener ugc nofollow" style="box-sizing: inherit;" target="_blank">CytoTerra cytogenetics platform</a>employs DL to examine reams of structural data about the human genome to detect mutations implicated in cancer, infertility, and more. Due to a variety of factors, such as their small size, subtlety, complex rearrangement, cryptic nature, or presence in only a fraction of cells, many of these mutations are invisible to other techniques. Making sense of a complex phenotype related to these mutations, such as cancer or infertility, requires making sense of a large, complex body of genomic data and seems to confound human-authored logic. Hyperdimensional analysis models, like neural nets, seem far more successful at analyzing such data — another aspect of a xenocomplex problem.</p><p class="pw-post-body-paragraph abh abi zl uc b abj abk wa abl abm abn wd abo abp abq abr abs abt abu abv abw abx aby abz aca acb qe by" data-selectable-paragraph="" id="e769" style="box-sizing: inherit; color: #292929; font-family: charter, Georgia, Cambria, "Times New Roman", Times, serif; font-size: 20px; letter-spacing: -0.003em; line-height: 32px; margin: 2em 0px -0.46em; word-break: break-word;">Protein folding and interpreting genetic data may very well be xenocomplex problems, too challenging for humans to formulate and solve ourselves, and thus better suited to analysis by learning algorithms capable of operating in a more complex mathematical setting than us. It’s likely that as we continue to apply powerful AI methods to medicine, we will discover other xenocomplex problems. Xenocomplex medical problems deepen the question of how we will use AI in medical contexts: what if both the solution and the problem itself are inscrutable?</p><h1 class="acp acq zl bv kz acr acs act th acu acv acw tm tn acx to tr ts acy tt tw tx acz ty ub aea by" data-selectable-paragraph="" id="25a7" style="box-sizing: inherit; color: #292929; font-family: sohne, "Helvetica Neue", Helvetica, Arial, sans-serif; font-size: 22px; line-height: 28px; margin: 3.14em 0px -0.37em;">Should We Let AI Diagnose Xenocomplex Medical Issues?</h1><p class="pw-post-body-paragraph abh abi zl uc b abj aeb wa abl abm aec wd abo abp aed abr abs abt aee abv abw abx aef abz aca acb qe by" data-selectable-paragraph="" id="a8c1" style="box-sizing: inherit; color: #292929; font-family: charter, Georgia, Cambria, "Times New Roman", Times, serif; font-size: 20px; letter-spacing: -0.003em; line-height: 32px; margin: 0.86em 0px -0.46em; word-break: break-word;">There are a variety of possible answers to what we should do about xenocomplex problems in biology and medicine. In some cases, such as protein design, there is an easy answer: use DL to assist in designing the protein, make the protein, then test the protein. If the protein works, it’s not terribly relevant how it was designed. However, this becomes more challenging when resolving a xenocomplex problem itself delivers potential medical benefit. If an AI system predicts an otherwise healthy patient is at significant risk for heart failure, is it appropriate to treat them prophylactically? If an AI system claims a patient’s cancer is caused by a certain mutation requiring radical treatment, should that treatment begin?</p><p class="pw-post-body-paragraph abh abi zl uc b abj abk wa abl abm abn wd abo abp abq abr abs abt abu abv abw abx aby abz aca acb qe by" data-selectable-paragraph="" id="4667" style="box-sizing: inherit; color: #292929; font-family: charter, Georgia, Cambria, "Times New Roman", Times, serif; font-size: 20px; letter-spacing: -0.003em; line-height: 32px; margin: 2em 0px -0.46em; word-break: break-word;">The most common and comfortable answer to these kinds of questions, so far, has been that a doctor should review the results of any such AI-based test, and make the final recommendation. However, as AI continues to advance, it is inevitable that some systems will make diagnoses or recommendations based upon evidence that is not apparent or even understandable to a human physician. It’s likely that they will begin to detect and diagnose conditions that we do not know exist today, due to limitations in our ability to understand complex data. In such circumstances, a human reviewing results is at best a rubber stamp and at worst actively doing harm to the patient by second-guessing a system operating in a xenocomplex domain which they cannot comprehend. Including a human in the diagnostic process of a system like this would violate the physicians mandate to, first, do no harm.</p><p class="pw-post-body-paragraph abh abi zl uc b abj abk wa abl abm abn wd abo abp abq abr abs abt abu abv abw abx aby abz aca acb qe by" data-selectable-paragraph="" id="dbf0" style="box-sizing: inherit; color: #292929; font-family: charter, Georgia, Cambria, "Times New Roman", Times, serif; font-size: 20px; letter-spacing: -0.003em; line-height: 32px; margin: 2em 0px -0.46em; word-break: break-word;">Such a dilemma has been anticipated in numerous forms in science fiction. For example, in <span class="aeh" style="box-sizing: inherit; font-style: italic;">I, Robot</span>, Isaac Asimov imagines how an extremely sophisticated AI might subtly guide humanity towards true happiness, even in defiance of what humanity might think would make it happier. In the <span class="aeh" style="box-sizing: inherit; font-style: italic;">Star Trek: TNG </span>episode “Hero Worship,” Data rapidly consumes a large amount of information and concludes, in contradiction to what everyone else on the <span class="aeh" style="box-sizing: inherit; font-style: italic;">Enterprise </span>believed, that the correct solution to a dangerous threat was to drop the shields rather than funnel all available power into them. Captain Picard, in that moment, trusted what his AI-powered officer recommended, even if he did not know why, and save the ship. As a human audience, we (and perhaps even the crew of the <span class="aeh" style="box-sizing: inherit; font-style: italic;">Enterprise</span>) are finally treated to Data’s explanation that the threat was a harmonic power amplification, but one could easily imagine a similar situation in which Data understood a problem only perceptible with his vast computational abilities. When it comes to our healthcare, will we trust our AI-powered systems?</p><p class="pw-post-body-paragraph abh abi zl uc b abj abk wa abl abm abn wd abo abp abq abr abs abt abu abv abw abx aby abz aca acb qe by" data-selectable-paragraph="" id="35f5" style="box-sizing: inherit; color: #292929; font-family: charter, Georgia, Cambria, "Times New Roman", Times, serif; font-size: 20px; letter-spacing: -0.003em; line-height: 32px; margin: 2em 0px -0.46em; word-break: break-word;">Of course, this is not to suggest AI-based systems should be thought of as infallible just because they operate on xenocomplex problems. However, it means that humans inserting themselves in the decision-making process for xenocomplex problems, at some point, on the balance, is detrimental. For every one incorrect decision they catch, for example, they might revert ten correct ones.</p><p class="pw-post-body-paragraph abh abi zl uc b abj abk wa abl abm abn wd abo abp abq abr abs abt abu abv abw abx aby abz aca acb qe by" data-selectable-paragraph="" id="923e" style="box-sizing: inherit; color: #292929; font-family: charter, Georgia, Cambria, "Times New Roman", Times, serif; font-size: 20px; letter-spacing: -0.003em; line-height: 32px; margin: 2em 0px -0.46em; word-break: break-word;">Medicine is by nature risk averse, and deciding what to do about these kinds of issues is not easy. Yet it’s an ethical question we as a society will have to address. Certainly, these kinds of tests will need to prove their accuracy and efficacy, like any other kind of diagnostic tool. At least for the foreseeable future, it will remain important for doctors and other appropriately trained medical staff to provide a sanity check on these methods. And yet, at some point, probably by the end of this decade and certainly by the end of the next, we will have to decide how we want to live with AI-powered diagnostic systems that understand us and our diseases better than we do ourselves. It is both exciting and a little frightening, but if we can embrace AI in medicine (with a dose of skepticism), the benefits to human health will be tremendous.</p><p><br /></p>Shawnhttp://www.blogger.com/profile/06311618271709855605noreply@blogger.com0tag:blogger.com,1999:blog-2034578472218454150.post-63388657257747018272021-06-15T11:50:00.015-07:002022-05-24T02:25:54.456-07:00Capitalism and Greedy Algorithms<p style="text-align: left;"><span face="Calibri, sans-serif">Capitalism: you hate it, you love it, you love to hate it, and you hate to love it. As the dominant, or at least most successful, economic system of </span><a href="https://en.wikipedia.org/wiki/History_of_capitalism" style="color: #954f72; font-family: Calibri, sans-serif;">the last 3-5 centuries</a><span face="Calibri, sans-serif"> (depending how you want to </span><a href="https://www.imf.org/external/pubs/ft/fandd/2015/06/basics.htm" style="color: #954f72; font-family: Calibri, sans-serif;">define capitalism</a><span face="Calibri, sans-serif">), it has been an integral part of the socioeconomic fabric for innumerable successes and tragedies. For almost any take you might conceive someone having on capitalism, if you look around enough, you’ll likely find someone has already written about it (maybe even this one!).</span></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">A common trope, of course, is the “greedy capitalist,” the evil banker or industrialist or business owner ruthlessly exploiting those beneath them for their own profit. Gordon Gekko <a href="https://youtu.be/VVxYOQS6ggk" style="color: #954f72;">infamously lauded the goodness of greed</a>, kicking off a generation of bloodthirsty blue-shirted hostile takeover artists who saw economics in brutal Darwinian terms.<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><o:p> </o:p></p><table align="center" cellpadding="0" cellspacing="0" class="tr-caption-container" style="margin-left: auto; margin-right: auto;"><tbody><tr><td style="text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEh-Sy9MxkBmZdYCqnaaqm18ULPkDIN2e2sZ8ja-WLeZLRv3th8PPkiI0jIVJJ8dqs5e8LjNw8dsL72oh6ug8nhJe_22PZAVA7Sz32i8UJkL4GYRlcSiuaOU5dgkG7Jf0KxZw8hLWwKX0ME/s615/MDthen-2.jpg" style="margin-left: auto; margin-right: auto;"><img border="0" data-original-height="409" data-original-width="615" height="426" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEh-Sy9MxkBmZdYCqnaaqm18ULPkDIN2e2sZ8ja-WLeZLRv3th8PPkiI0jIVJJ8dqs5e8LjNw8dsL72oh6ug8nhJe_22PZAVA7Sz32i8UJkL4GYRlcSiuaOU5dgkG7Jf0KxZw8hLWwKX0ME/w640-h426/MDthen-2.jpg" width="640" /></a></td></tr><tr><td class="tr-caption" style="text-align: center;"><span face="Calibri, sans-serif" style="font-size: 12pt; text-align: start;">Blue shirt + white collar + power tie + suspenders + gold Cartier = hide ya assets, hide ya balance sheet, hide ya sales projections, cause they takin over e'rybody's companies out here</span><span style="text-align: start;"></span></td></tr></tbody></table><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">This post is not about that kind of greed, or that kind of capitalism for that matter. Here, we’re going to look at the ways capitalism resembles what we call in computer science a “greedy algorithm.” And, once we understand that, we will talk about why capitalism has had so many historical successes, why it has nonetheless had major failures, and what kinds of improvements or alternatives might make it better.<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">First, we have to define “capitalism” and “greedy algorithms.”<o:p></o:p></p><h2 style="text-align: left;">Capitalism: Solving the Problem of Human Economic Activity</h2><h1 style="break-after: avoid; color: #2f5496; font-family: "Calibri Light", sans-serif; font-size: 16pt; font-weight: normal; margin: 12pt 0in 0in;"><o:p></o:p></h1><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">Capitalism has a long history, <a href="https://medium.com/the-innovation/is-it-time-to-invent-a-new-economic-system-ed40a7225cba" style="color: #954f72;">evolving (arguably) from feudalism and mercantilism</a> as the role and importance of private property in the structure of Western society developed. Adam Smith published <i><a href="https://en.wikipedia.org/wiki/The_Wealth_of_Nations" style="color: #954f72;">The Wealth of Nations</a> </i>in 1776 (Murica!), laying out the foundational model for how a capitalist economies worked.<i> </i>Modern capitalism <a href="https://www.khanacademy.org/humanities/whp-1750/xcabef9ed3fc7da7b:unit-4-labor-and-society/xcabef9ed3fc7da7b:4-1-labor/a/the-emergence-of-industrial-capitalism-beta" style="color: #954f72;">really got going in the 19<sup>th</sup> century</a> as the Industrial Revolution took off, and America’s recovery from existential capitalist shocks such as a <a href="https://www.thoughtco.com/financial-panics-of-the-19th-century-1774020" style="color: #954f72;">series of panics in the 1800’s</a> and the <a href="https://en.wikipedia.org/wiki/Great_Depression" style="color: #954f72;">Great Depression</a> seemed to demonstrate its resilience and power. The <a href="https://www.history.com/topics/cold-war/fall-of-soviet-union" style="color: #954f72;">collapse of the Soviet Union</a> marked, in political if not economic terms, capitalism’s victory over its chief ideological rival, communism (well, that’s the story we tell ourselves, <a href="https://www.umass.edu/pubaffs/chronicle/archives/02/10-11/economics.html" style="color: #954f72;">even if it’s not quite accurate</a>).<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">But this is not a history lesson, and I am not a historian. You can find any number of books about the history of capitalism for those kinds of details. As a computer scientist, my primary skillset is framing problems rigorously and figuring out algorithmic ways to solve them. So, if we do that, what is capitalism?<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">At its root, capitalism is a solution to a problem. Solutions are best understood through their problems. Thus, to understand capitalism, we need to understand what problem it is trying to solve: coordinating human economic activity.<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">Obviously, “coordinating human economic activity” is an even broader topic of study than just the history of capitalism, maybe so broad it’s essentially formless. So, we’re not going to talk about its details or history. Instead, we’re going to simply establish what the “problem of human economic activity” is.<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">The problem of human economic activity (PHEA) is simply this: how do we commodify our needs and desires?<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">There are three important components to this problem: “commodify,” “needs,” and “desires.” By “commodify,” we mean create some kind of mutual, structured understanding of how things can be valued and exchanged (we mean “commodify” purely descriptively and without judgement, not in the Marxist use of the term). There are many ways to do this, of course, but any solution to PHEA must have a proposal for how to commodify things. Sometimes it might be pretty loose. For example, in a simple bartering system, the individual participants in a transaction personally assign whatever value they want to something, then exchange it however they want. Other times it might be pretty strict; perhaps an authoritarian system would assign values from some central authority, and only permit transactions through a centrally run clearing house. There are even solutions whose proposed form of commodification is the <i>lack </i>of commodification: in a nihilist-anarchist system, maybe the only form of valuation and exchange would be through the use of persuasion or force.<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">The next two components, “needs” and “desires,” are closely related. So closely related, I almost didn’t separate them, because in many systems, there is no real distinction between them. Is a cheeseburger a need or a desire? On one hand, it’s food, and everyone needs food. On the other hand, it’s a rather luxurious form of food (“beef and dairy, <a href="https://www.statista.com/topics/4880/global-meat-industry/" style="color: #954f72;">wow you must be rich</a>” says the weaver from 1785), and you could certainly survive with less. However, I decided to separate them into two classes, because some systems do try to draw a distinction between them. In a communist system, for example, it might be decided that anything that is classified as a “desire” is inherently unfair unless everyone in the society first has their “needs” met, and then also receives a roughly equal amount of their “desires.”<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">Using this definition of PHEA, we can easily see how capitalism is a proposed solution. How do we commodify our needs and desires? By supporting a strong concept of private property and creating free markets where they can be exchanged. With everything we might need or desire encapsulated within private property, we have an obvious, universal means of obtaining and exchanging anything: using the means available to you in the free market, convince whoever owns the thing you want to give it to you.<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">By this mechanism, capitalism also dodges the problem of needing to draw a distinction between needs and desires. One person’s need is another’s desire, and that’s fine, because it’s all still just private property. And to ensure efficient, accurate commodification, we make sure all transactions happen freely, openly, and honestly on the market. Whenever private property changes hands, others see it, and it helps them understand the value of the private property they and others have. Every exchange on the free market, by definition, is fair, because no one else proposed an alternative transaction that one party preferred more than the transaction they accepted.<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">What could possibly go wrong?<o:p></o:p></p><h2 style="text-align: left;">Greedy Algorithms: Solving Hard Problems</h2><h1 style="break-after: avoid; color: #2f5496; font-family: "Calibri Light", sans-serif; font-size: 16pt; font-weight: normal; margin: 12pt 0in 0in;"><o:p></o:p></h1><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">In computer science, we anthropomorphize a class of algorithms by describing them as “<a href="https://en.wikipedia.org/wiki/Greedy_algorithm" style="color: #954f72;">greedy</a>.” The algorithms are not, of course, literally greedy, because they don’t have emotions (<a href="https://en.wikipedia.org/wiki/The_Emotion_Machine" style="color: #954f72;">nor do we</a>, really, but that’s a whole other story). The algorithms simply use a tactic which strikes us greedy to do something very difficult: solve hard problems.<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">Before we say more about greedy algorithms, which, naturally, are a kind of solution, let’s talk about the problems they solve first (again, solutions are best understood through their problems). One of the most important and interesting subfields of computer science is <a href="https://plato.stanford.edu/entries/computational-complexity/" style="color: #954f72;">complexity theory</a>, which is essentially the formal study of how hard different problems are.<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">Some kinds of problems are really simple. For example, suppose I asked you to solve this problem: “Given a letter of the alphabet, tell me the next letter of the alphabet.” This is an easy problem for a typical adult to solve, requiring just one step to solve it: you think of the next letter. We say this kind of problem can be solved in “<a href="https://en.wikipedia.org/wiki/Time_complexity#Constant_time" style="color: #954f72;">constant time</a>” because, no matter what letter I give you, it always takes the same number of steps to solve. Even if I make the problem a bit harder, like asking for the fifth letter after rather than the next letter, the solution is still in constant time. You might have to count letters on your fingers or say the alphabet in your head (which, of course, an actual computer wouldn’t need to), but it still takes you the same number of steps to answer the question, no matter what letter I give you. The <i>optimal</i> solution to the problem is still found in constant time, so we say the problem can be solved in constant time (or, colloquially, we also say the problem is constant time).<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">Now, here’s a harder problem: “Given a list of words, tell me all the words that have the most copies of the letter E.” This is also a relatively simple problem to solve, but it’s not as easy as just telling the next letter of the alphabet. You have to count up how many E’s appear in each word, then pick those words with the most copies. Crucially, you have to look at <i>each </i>word to count up the E’s. If I give you a list of 10 words, you have to examine 10 words. If I give you 10 million words, you have to examine 10 million words. Since the difficulty of the problem scales linearly with the number of words I give you, the problem requires “<a href="https://en.wikipedia.org/wiki/Time_complexity#Linear_time" style="color: #954f72;">linear time</a>” to solve. And linear time, we can see, is associated with more complex problems than constant time.<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">The complexity of problems turns out to form a wide array of classes. For example, suppose I gave you a list of words and asked you to <a href="https://www.geeksforgeeks.org/sorting-algorithms/" style="color: #954f72;">sort</a> them alphabetically. This problem can be shown to be solvable using what we call “<a href="https://en.wikipedia.org/wiki/Time_complexity#Quasilinear_time" style="color: #954f72;">log-linear time</a>,” meaning the amount of time it takes to solve is proportional to the product of (a) the number of words and (b) the logarithm of that number. Or, suppose I hand you a list of alphabetically sorted words, and ask you to determine if a given word is in the list. This problem can be solved in “<a href="https://en.wikipedia.org/wiki/Time_complexity#Logarithmic_time" style="color: #954f72;">logarithmic time</a>” using an algorithm called <a href="https://www.geeksforgeeks.org/binary-search/" style="color: #954f72;">binary search</a>. There are lots and lots and lots and lots of problems people have studied like this; it’s what people are actually doing when they say they are “building an algorithm” (like, if you want to <a href="https://www.youtube.com/watch?v=LhF_56SxrGk" style="color: #954f72;">zoom in and enhance</a>).<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">For all of the above problems, the solutions we described have one thing in common: they can ultimately be solved in an amount of time which is some kind of polynomial function on the number of inputs. “Linear time,” “log-linear time,” “constant time,” and even things we haven’t mentioned like “n-squared time” or “n to the one-hundredth power time,” are all polynomial-time solutions. Any problem which can be solved in polynomial time is said to have an “<a href="https://cs.stackexchange.com/questions/210/why-polynomial-time-is-called-efficient" style="color: #954f72;">efficient solution</a>,” because, eventually, a polynomial time solution scales in a reasonably efficient manner. These problems are so important we have a name for them: “<a href="https://en.wikipedia.org/wiki/P_(complexity)" style="color: #954f72;">P</a>.” Problems with efficient (aka polynomial time) solutions belong to the set P.<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">There are also problems that may or may not have solutions requiring polynomial time, but for which we can check if a solution is correct in polynomial time. We call these problems “<a href="https://en.wikipedia.org/wiki/NP_(complexity)" style="color: #954f72;">NP</a>” (note: P is a subset of NP because of that “may or may not” bit). For example, suppose I gave you a really large number (like, many billions) and <a href="https://en.wikipedia.org/wiki/Integer_factorization" rel="" target="_blank">told you it was the product of two prime numbers</a>. If that's all I tell you, it would take you a long time to find those two prime numbers. But if I also gave you the two prime numbers, you could easily check whether their product equalled the number I gave you at first (<a href="https://en.wikipedia.org/wiki/RSA_(cryptosystem)" target="_blank">RSA cryptography</a> is in fact based on this property). This dynamic is what places a problem in NP: even if we don't know an efficient way to generate a solution, we do know an efficient way to verify a solution.</p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">Going further, there are problems for which we actually know of no efficient (aka polynomial time) solution, nor even an efficient way to check if a result is correct. We call these problems “<a href="https://en.wikipedia.org/wiki/NP-completeness" style="color: #954f72;">NP-complete</a>.” Problems that are NP-complete only have known solutions which are worse than polynomial time (on a normal computer), such as exponential time, and further, they do not have a known efficient solution for verifying whether a proposed solution is optimal or not. For example, a solution may require “two raised to the n-power time” to solve or to verify, which is worse, eventually, than any possible polynomial time solution.<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">Importantly, notice I say that <i>we know of </i>no polynomial time solutions or verifications to problems that are NP-complete. We don’t actually know for sure none exist. It’s possible no one has been smart enough yet to figure one out. However, there is a <a href="https://en.wikipedia.org/wiki/P_versus_NP_problem" style="color: #954f72;">long-standing, well-founded, mostly accepted assertion</a> that there exist problems in NP which have no polynomial time solution. But it is not yet proven, one way or another, whether this assertion, formally written as “P ≠ NP,” is correct. Incidentally, “P ≠ NP” is quite literally a million-dollar question: if anyone ever proves or disproves “P ≠ NP,” they will <a href="https://www.claymath.org/millennium-problems/p-vs-np-problem" style="color: #954f72;">win a cool million dollars</a>.<i><o:p></o:p></i></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">NP-complete problems are fascinating, but for people who build stuff, they are also annoyingly common. One of the most famous NP-complete problems is called the <a href="https://www.youtube.com/watch?v=SC5CX8drAtU" style="color: #954f72;">Traveling Salesman Problem</a> (TSP). In this problem, a salesman has a list of cities he has to visit for sales calls, and he wants to do the least amount of driving to do it. He wants to find the shortest route to drive that visits all the cities.<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">On its surface, this problem seems simple. Just start at the first city on the list, then drive to the one closest to that, then the one closest to that, etc., etc., until you’re done. However, it turns out this naïve solution can go horribly wrong. Let’s look an example. Suppose this map shows the list of cities the salesman has to visit, starting from city A:<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiXuIA2n_DrJu58LgT-4zA1mvsZjaEpAE8UkoeccIkuyfnD20j4i7fbPOv3pV2cGTGZP72DX-7pBWog-R_33aB8LhJ1W409wVloBUxihAepCJx7392r_3UlO5pOP7bKVKakfNCXP9fiUbI/s876/TSP_island0.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="832" data-original-width="876" height="608" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiXuIA2n_DrJu58LgT-4zA1mvsZjaEpAE8UkoeccIkuyfnD20j4i7fbPOv3pV2cGTGZP72DX-7pBWog-R_33aB8LhJ1W409wVloBUxihAepCJx7392r_3UlO5pOP7bKVKakfNCXP9fiUbI/w640-h608/TSP_island0.png" width="640" /></a></div><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">If we follow our naïve algorithm, what happens? Well, the first step is easy: go to B.<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiBdpXd1fKEQ1hIBbsAEA9y9MP93xAlmphMUrWiu_4SZj52_EW3DbVB8JatvCykCfaSqjlQARv2bw1Nt2wWgQl4cI_RpQEea2vxIzNPUJKmV-eoPBhicxC73zo4wEYEXtgH7mbwXqWokas/s876/TSP_island1.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="832" data-original-width="876" height="608" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiBdpXd1fKEQ1hIBbsAEA9y9MP93xAlmphMUrWiu_4SZj52_EW3DbVB8JatvCykCfaSqjlQARv2bw1Nt2wWgQl4cI_RpQEea2vxIzNPUJKmV-eoPBhicxC73zo4wEYEXtgH7mbwXqWokas/w640-h608/TSP_island1.png" width="640" /></a></div><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">And the next step looks pretty straightforward too: head to C.<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjUAmjg9q1NlKtAYmQOBgL9PGKbW1C1h1vL7_6UsuVtxGUjH-ZzQqXoQURjKB5M5U1Q9ujpkdx6DPy1_Gg0MZ-I0UPsHIZYFTquiWtf8Cn11cAf72HqdhYuvuGsapkErE-Meud30hA-5h8/s876/TSP_island2.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="832" data-original-width="876" height="608" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjUAmjg9q1NlKtAYmQOBgL9PGKbW1C1h1vL7_6UsuVtxGUjH-ZzQqXoQURjKB5M5U1Q9ujpkdx6DPy1_Gg0MZ-I0UPsHIZYFTquiWtf8Cn11cAf72HqdhYuvuGsapkErE-Meud30hA-5h8/w640-h608/TSP_island2.png" width="640" /></a></div><br /><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">Now, we will see the greedy algorithm make the salesman do something he will later regret. City E is the next closest city, so he goes there.<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjwnlnS01u-vfXLagO_cljFmOMXz2yLV3JlV9iZCe-Rdp-2DpXNDZHdmXsv8_GB3mvbO2v_mk9zbDWFdYqMskVt8JnrQTawc3goqwAz-UjYYCsucwGb1IUhUf70mWgUGzIyizbEU6guf-s/s876/TSP_island3.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="832" data-original-width="876" height="608" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjwnlnS01u-vfXLagO_cljFmOMXz2yLV3JlV9iZCe-Rdp-2DpXNDZHdmXsv8_GB3mvbO2v_mk9zbDWFdYqMskVt8JnrQTawc3goqwAz-UjYYCsucwGb1IUhUf70mWgUGzIyizbEU6guf-s/w640-h608/TSP_island3.png" width="640" /></a></div><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">From E, it’s an easy hop up to D.<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiMZKIlU8uO6xwrNgGnb87y2vW1i6Cp_FS1FNIKTNFR2z1sbejTLSzGo6w4SI93-cOBE5dNFnR-hTEcnUTZ2xDP1kJ9_gXwGDmVuxA-MW2YGLIzhTbtatMeevgN0tjjKpcrUtKpZm3DpfQ/s876/TSP_island4.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="832" data-original-width="876" height="608" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEiMZKIlU8uO6xwrNgGnb87y2vW1i6Cp_FS1FNIKTNFR2z1sbejTLSzGo6w4SI93-cOBE5dNFnR-hTEcnUTZ2xDP1kJ9_gXwGDmVuxA-MW2YGLIzhTbtatMeevgN0tjjKpcrUtKpZm3DpfQ/w640-h608/TSP_island4.png" width="640" /></a></div><br /><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">And finally, our salesman makes the trip down to the last city, F.<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><div class="separator" style="clear: both; text-align: center;"><a href="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj7_KaRmaxgAglFK5e9x16YTwn858Dj20d48wARe6s-pymETqHsnx9TKkGg1aAmCjA8RvEuQIjia8ROgm_vB0gx7C7AB5M0rVYWhJPxhrBfLsFQ1SmNHpuWT8Hx678dcnOiY9TZgyvREm0/s876/TSP_island5.png" style="margin-left: 1em; margin-right: 1em;"><img border="0" data-original-height="832" data-original-width="876" height="608" src="https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEj7_KaRmaxgAglFK5e9x16YTwn858Dj20d48wARe6s-pymETqHsnx9TKkGg1aAmCjA8RvEuQIjia8ROgm_vB0gx7C7AB5M0rVYWhJPxhrBfLsFQ1SmNHpuWT8Hx678dcnOiY9TZgyvREm0/w640-h608/TSP_island5.png" width="640" /></a></div><span face="Calibri, sans-serif"> </span><br /><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">Where was the mistake? Well, if you look at that route from D to F, you’ll notice the salesman has to go right back past city E. Certainly, if he were smart enough, he could have gone to D from C instead of going to E, and then just swing by E on his way down to F. While the greedy algorithm found a decent solution, it could have done better. This turns out to be a <a href="https://brilliant.org/wiki/greedy-algorithm/" style="color: #954f72;">common pattern with greedy algorithms</a>: they find good but not optimal solutions to hard problems (except for in trivial cases).<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">So, as we can see, the naïve approach doesn’t always work. After rigorous study of this problem, no one—like, no one, not the smartest person who ever lived or anyone else—has found an efficient (aka polynomial time) solution to TSP. Our best algorithm takes slightly worse than exponential time to find a solution: the amount of time it takes to solve the problem increases (slightly worse than) exponentially with the number of cities. Roughly speaking, if you want to add a tenth city, you have to double the work it would take to figure out nine cities. And adding an eleventh city doubles the time again. Twelfth city? Double it again. Practically speaking, problems like this are very difficult to solve in any kind of real world system (unless, maybe, you have a <a href="https://www.forbes.com/sites/startswithabang/2020/05/28/this-90-year-old-math-problem-shows-why-we-need-quantum-computers/?sh=640f4e711c5d" style="color: #954f72;">powerful quantum computer</a>).<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">These problems don’t plague salesmen alone. For example, robots assisting with fulfilling orders in a warehouse have to solve problems like this: “Given a list of orders containing items scattered around the warehouse, what’s the best route to take to collect them?” In, say, a huge Amazon warehouse processing tens of thousands of orders an hour with hundreds or thousands of robots, there are a lot of exponentially difficult problems to solve, all while preventing robots from crashing into each other too.<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">One could imagine some genius central control program, planning and coordinating an efficient dance involving all of the robots, making sure they each follow the shortest path to collect all their items, and delicately timed so they never crash. But imagine how difficult that problem is to solve! Thousands of overlapping traveling salesmen, each needing efficient routes, and each needing to be timed and routed to avoid getting too close each other. And if a robot breaks down, the central controller needs to send in an extraction team to remove the damaged robot, adjust all the other robots’ paths to avoid it, and re-route a robot or two to finish up whatever work the broken robot didn’t get to. This is an extremely daunting set of overlapping NP-complete problems and contingency plans.<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">So, of course, this is not how the robots work. There is no central master planning everything for all robots. Implementations vary, but all of them rely to some extent on decentralized robots making their own pathfinding and anti-collision decisions. Each robot might be provided with a set of items to collect by a central planner, but it’s up to the robot from there. This federated decision system is also a form of a naïve algorithm for solving a hard problem. Rather than explicitly determining a globally optimum solution, individual agents are configured to make locally optimum decisions that, typically, also accrue to a solution that approaches the global optimum.<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">And at the end of the day, we all get our packages, because, often, it is <i>not necessary </i>to solve these problems completely, totally optimally. A “good enough” solution is often, well, good enough. If the salesman has to drive a little farther than he might have, fine. If the robot didn’t get the items in exactly the best possible order because it had to swerve to avoid another robot, the world can keep spinning.<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">What does a “good enough” solution to TSP often look like? Well, our naïve solution of course! That approach generates a reasonable itinerary almost all of the time, especially for actual, real-world scenarios. And when it doesn’t there are plenty of techniques that can use a decent greedy solution as a starting point and then improve it to be more optimal.<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">This naïve approach is common enough we give it a special name: … (wait for it) … a greedy algorithm. The algorithm is “greedy” because, at every step, it takes whatever next step is the best locally. It doesn’t look at the overall state of the world, or where it’s been, or where it can get to from where it’s going in the future. It just happily makes the best local choice it can find. This is an extremely simple thing to do. All it needs to do, at every step, is look at the cities it could go to next and pick the one that’s closest. Usually that’s a reasonable choice. In other words, greedy algorithms are a great way to <i>approximate</i> optimal solutions to hard problems.<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">Now that CS301 is over, where were we… oh, right. I hope it is now obvious capitalism is a greedy algorithm solving PHEA, so obviously we can come up with better solutions. Clear as mud? No? OK, then let me explain.<o:p></o:p></p><h2 style="text-align: left;">Capitalism is a Greedy Algorithm to Solve PHEA</h2><h1 style="break-after: avoid; color: #2f5496; font-family: "Calibri Light", sans-serif; font-size: 16pt; font-weight: normal; margin: 12pt 0in 0in;"><o:p></o:p></h1><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">We defined capitalism earlier as proposed solution to PHEA in which private property, backed by strong rights, is exchanged on the free market. That is how capitalism commodifies needs and desires.</p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"> </p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">What does it mean to say that approach is a greedy algorithm? It means that capitalism does not seek to find some globally optimum way to solve PHEA. Instead, it relies on simpler, lower-level decisions that can be made solely by looking at more easily measured local improvements. Like an army of robots in a warehouse individually making greedy item-collecting decisions, individual humans making their own decisions in their own best interests tend, on the whole, to lead to good solutions for the entire system of all humans together. Humans decide for themselves what ends they pursue in the market according to some personal “objective function”: an assessment of the values they have and goals they seek in relation to the transactions they can make in the market. Whereas warehouse robots might have an objective function that values moving closer to needed objects and avoiding collisions, humans might have an objective function that values obtaining food, shelter, sex, status, power, etc.<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">The development of this decentralized economic approach is incredibly important in human history. Again, this is not a history lesson, but earlier kinds of solutions to PHEA did not so crisply and directly enable individual human actors to make their own, personal, best decisions. Instead of being forced to act in the best interests of, say, their lord, their guild, or their town, people’s natural desire for self-betterment (which Gordon Gekko might call greed) turns from vice to virtue. By enshrining a free market where private property could be openly exchanged, capitalism created a machine that channeled individual people’s natural desire to better themselves with the betterment of society at large.<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">However, also incredibly important, PHEA is a hard problem! I have not studied it formally enough, nor do I know of any such studies, to say something like “PHEA is NP-complete,” but I can say it is like, really, really hard. Even harder than coordinating 1000 robots in a warehouse. Setting aside the human factors like answering questions like “is it OK to make one person suffer so ten others may live?” or “is private property/taxation/your-least-favorite-thing theft?”, trying to come up with an efficient solution to optimize some kind of objective function for a bunch of people is quite challenging. What’s more, unlike warehouse robots, not everyone will have the same objective function, and people’s objective functions may change over time. Given these aspects, it is reasonable to assume PHEA is a hard problem because no efficient solution for it is known.<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">Because capitalism is a greedy algorithm, and PHEA is a hard problem, then capitalism is not guaranteed to generate an optimal solution to PHEA. By this, we mean there may exist some other means of commodifying needs and desires that would be even better than the results capitalism generates. We don’t necessarily know what such a solution would look like, or even if one exists for sure, but it’s possible there is a better solution.<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">Why does any of this matter? For two reasons: first, the context for why capitalism has done so well, and second, what might a better solution look like.<o:p></o:p></p><h2 style="text-align: left;">What Capitalism Does Well</h2><h1 style="break-after: avoid; color: #2f5496; font-family: "Calibri Light", sans-serif; font-size: 16pt; font-weight: normal; margin: 12pt 0in 0in;"><o:p></o:p></h1><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">Capitalism has been a successful solution to PHEA because, firstly, it’s usually possible to craft a good greedy algorithm to solve any hard problem. But the form of capitalism we have today is not just the basic greedy algorithm version. That version of capitalism would have little beyond a clear-cut statement about private property rights, a public ledger recording free market transactions, and some simple rules to enforce the system (“<a href="https://youtu.be/YLjwEodCmT4" style="color: #954f72;">bust a deal, face the wheel!</a>”). Today’s Western capitalism has numerous modifications beyond a basic greedy algorithm which establish additional norms and rules that, based on observation, seem to (usually) improve the quality of the solution.<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">For starters, the market is not totally free. If you want to tell someone you can sell them a drug that will cure their cancer (and you are in the US for example), you need to get approval from the Food & Drug Administration <a href="https://www.justice.gov/civil/false-claims-act" style="color: #954f72;">before you can claim that</a>. If you want to buy or sell a stock, you cannot do so based on insider information, or else the Securities & Exchange Commission will <a href="https://www.investor.gov/introduction-investing/investing-basics/glossary/insider-trading" style="color: #954f72;">take all your profits and throw you in jail</a>. More broadly, you cannot lie in an effort to get someone to enter into a transaction with you, or else you’ll be <a href="https://www.law.cornell.edu/wex/fraudulent_misrepresentation" style="color: #954f72;">prosecuted for fraud</a>. All these rules prohibit transactions that, while they might be extremely rewarding to one individual within the population, are considered so detrimental to the population as a whole that they are not permitted. It is not only that these things may be considered morally wrong. It is that, if we allow individual agents (people) do perform these transactions on the free market, they will be pulling us away from a more optimum overall solution.<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">American capitalism also does things to change people’s objective functions in an effort to change the decisions they make. The federal government provides subsidies to farmers to encourage them to grow certain crops, <a href="https://farm.ewg.org/progdetail.php?fips=00000&progcode=corn" style="color: #954f72;">like corn</a>. It also provides people tax incentives to perform certain transactions, such as to <a href="https://www.nerdwallet.com/blog/mortgage-interest-deduction/" style="color: #954f72;">take out a mortgage</a> or to <a href="https://www.investopedia.com/terms/1/401kplan.asp" style="color: #954f72;">save for retirement</a>. The <a href="https://www.investopedia.com/articles/investing/010616/impact-fed-interest-rate-hike.asp" style="color: #954f72;">Federal Reserve adjusts interest rates</a> to encourage investment, manage inflation, or reduce unemployment. These kinds of policies modify the incentives people have to make certain decisions because, absent these modifications, an individual would find the decision suboptimal. In other words, the government influences people’s objective functions (“puts their thumb on the scale” is sometimes used to describe this kind of action) to cause them to make decisions that lead to a better overall solution to PHEA.<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">Modern capitalism allows people to choose to form groups and act together economically. This is the essence of unions, trade groups, partnerships, and even political parties to some extent (side note: democracy is just a greedy algorithm for solving the problem of human governance, instead of PHEA). Forming groups reduces the complexity of PHEA because there are fewer agents making decisions within the population. To the extent these groups more effectively advocate for their members than the members themselves (case in point: <a href="https://www.epi.org/publication/why-unions-are-good-for-workers-especially-in-a-crisis-like-covid-19-12-policies-that-would-boost-worker-rights-safety-and-wages/" style="color: #954f72;">unions get better healthcare cheaper</a> for their members than individuals do), these groups help their members achieve more favorable results than they would be able to individually.<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">Clearly, all these modifications to a basic, naïve form of capitalism seem to be helpful, or at the very least ubiquitous. But the degree to which modifications have been applied has varied from country to country and era to era. Modern Western notions of capitalism contain a spectrum of configurations depending on how a society wants to prioritize components of the solution. <a href="https://www.cato.org/commentary/key-concepts-libertarianism" style="color: #954f72;">Mainstream libertarians</a>, for example, prioritize the economic agency of individual people within the society above all else. Anything that reduces a person’s control over their private property, or that restricts their ability to enter into whatever transactions they see fit in the free market, is considered abusive. Meanwhile, <a href="https://www.dsausa.org/about-us/what-is-democratic-socialism/" style="color: #954f72;">democratic-socialists</a> consider negative side effects experienced by uninvolved parties in property rights or free-market transactions abusive, to the extent they emphasize collective ownership. And, of course, there are many varieties of positions about these kinds of topics to suit one’s taste. But regardless of where one falls on this spectrum, all of these ideologies are tolerated within broader capitalist thought, and they all seek to improve the greedy algorithm represented by it.<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">All that said, perhaps capitalism’s chief advantage over other economic systems is one simple trick: it requires almost no central planning (gasp! Someone said <a href="https://link.springer.com/chapter/10.1007%2F978-1-349-20863-0_5" style="color: #954f72;">central planning</a>!). In capitalism, aside from setting up the laws, structures, and a few core policies (e.g., norms, incentives), no one has to make any actual smart economic decisions on behalf anyone else. Save for a handful of rules or programs, everyone is personally responsible for their own economic health. Capitalism relies on its individual agents, acting in their own self-interest, to make personal decisions that, more or less, are good ones overall for the whole of society.<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">By way of example, let’s examine the question “how many loaves of bread should we bake next week?” In a capitalist society, this question is answered by summing together the individual decisions of individual bakers. Each baker looks at the orders on their books, how long their lines are, seasonal bread eating patterns, and whatever other information they care to look at to make a personal decision about how many loaves of bread to bake. If they do a good job, they profit. If they do a bad job, they lose money. If they keep doing a bad job, one way or another, they will be removed from the bread loaf decision making process. All of these individual decisions accrue to some society-wide prediction of how much bread will be eaten next week. Usually, these predictions at a society-wide level are pretty accurate, even though no one ever considered that problem directly.<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">In a society with a stronger central authority, some central person or body actually does need to answer this question, for everyone, and with enough nuance to know which bakers can make and distribute the right amount of bread among a variety of other complexities. It’s quite a challenging problem. Just deciding how to distribute bread efficiently, for example, smacks of an NP-complete problem all on its own! The stakes are higher too. If the central planner is right, everybody eats, and maybe it was even a little bit more efficient than the capitalist solution to the bread-forecasting problem. But if the central planner is wrong, the effects could be disastrous. Instead of one bad-decision-making baker running himself out of business, a bad central planner could cause a famine for the entire country. With a relatively small upside and a much bigger downside to the capitalist solution, it seems hard to expect a centrally planned solution to be worth using. With the possible exception of China, who are in the midst of showing us <a href="https://asia.nikkei.com/Spotlight/Comment/China-can-use-tech-to-prove-planned-economies-work" style="color: #954f72;">how competent they are at central planning</a> (for now), previous large economies that were managed with a strong central hand have not fared well over time. From the <a href="https://www.historylearningsite.co.uk/spain-under-phillip-ii/the-economic-problems-of-spain/" style="color: #954f72;">kings of old</a> to <a href="https://www.investopedia.com/articles/investing/021716/why-ussr-collapsed-economically.asp" style="color: #954f72;">the Soviets</a>, it seems to be very hard to centrally plan an economy well for long. It’s just a really, really hard thing to get right, and inevitably, <a href="https://youtu.be/WPMMNvYTEyI" style="color: #954f72;">we just aren’t that smart</a>.<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">Nonetheless, as we have shown above, us not being smart enough to find some kind of solution better than a greedy algorithm doesn’t mean there isn’t one. It just means we might not have been smart enough yet to do it. Could there be something better?<o:p></o:p></p><h2 style="text-align: left;">What Better Looks Like</h2><h1 style="break-after: avoid; color: #2f5496; font-family: "Calibri Light", sans-serif; font-size: 16pt; font-weight: normal; margin: 12pt 0in 0in;"><o:p></o:p></h1><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">Just by continuing to modify rules and incentives, it is simple to imagine the kinds of proposals that could be made within the context of capitalism’s greedy algorithm that might improve its solution to PHEA (though, of course, one can agree or disagree with the proposals). Should we <a href="https://www.investopedia.com/ask/answers/040915/why-do-mbs-mortgagebacked-securities-still-exist-if-they-created-so-much-trouble-2008.asp" style="color: #954f72;">prohibit mortgage-backed securities</a>? Should we <a href="https://taxfoundation.org/benefits-of-a-corporate-tax-cut/" style="color: #954f72;">lower the corporate tax rate</a> to incentivize people to build businesses in America (or wherever)? Should we <a href="https://www.sanders.senate.gov/press-releases/news-sanders-jayapal-and-colleagues-introduce-legislation-to-make-college-tuition-free-and-debt-free-for-working-families/" style="color: #954f72;">spend public dollars to subsidize college education</a> and encourage people to gain advanced skills?<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">We can imagine almost endless ideas that work within the overall greedy solution of capitalism to solve PHEA better, whether by modifying the rules governing the free market, the incentives used to manipulate people’s decisions, or anything else. Indeed, basically all mainstream economic discussion centers on these kinds of things because it is easy to talk about incremental changes to the solution we already have.<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">Nothing will change, however, the fact that capitalism is still a greedy solution to PHEA. Can we envision qualities an alternative, potentially better solution might have? Well, me being me and this blog being this blog, we can draw inspiration from computer science. In computer science, when faced with a hard problem, we either need to simplify the problem, or we need to be smarter.</p><h3 style="text-align: left;">Simplifying PHEA: Reduced Economic Scope</h3><h2 style="break-after: avoid; color: #2f5496; font-family: "Calibri Light", sans-serif; font-size: 13pt; font-weight: normal; margin: 2pt 0in 0in;"><o:p></o:p></h2><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">One of the first things one can do when faced with a hard problem in computer science is to try and simplify the problem. Maybe the salesman is happy if he only finds the optimal travel itinerary some of the time, or if the itinerary is within 10% of optimum. Or, maybe he’s comfortable skipping a city if it would cause the itinerary to be too crazy. Depending on the situation, in the real world, we often don’t need a perfect solution. Just a good enough one.<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">One way to simplify PHEA is to not attempt to have a single system that solves for all economic activity at once. American capitalism attempts to lay out economic rules for all kinds of private property and free market transactions within an ultimately holistic, consistent system. Whether you are buying a tank of gas, an oil field, or shares of Exxon, you will use dollars and follow the associated rules, and these rules won’t contradict each other based on what you are trying to buy. This attempt at economic completeness is part of what makes PHEA so difficult to solve. However, there are ways to break it down into smaller problems that are indeed easier to solve.<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">Just using our previous example, why must it be the case that we buy tanks of gas, oil fields, and Exxon shares in essentially the same system? Sure, there are some minor differences in how different kinds of property are traded, but why do I buy each of them following the same rules of private property, or the same accounting rules for how I bought them, or the same body of contract law to enforce the transaction? Why do we even use dollars for all of them?<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">Let’s examine that last bit, about not basing our economy on the single currency of dollars, some more. “That’s crazy,” you might be saying to yourself right now, “how would that even work! We need a single unit of economic exchange for the economy to hold together, and that’s the dollar.” And you’re right, that does sound crazy, because it’s so different from what we are used to. It’s hard to even imagine what it would look like if, fundamentally, we did not even use the same units to measure value in gas, oil fields, or oil companies. It might help, then, if we look at an appropriately techbuzzy example of how something like that might work: asset-specific cryptos.<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">Suppose I was a rich oil company and created three new kinds of cryptos: GasCoinX, FieldCoinX, and ShareCoinX. I accept GasCoinX for tanks of gas, FieldCoinX if you want to buy one of my oil fields, and ShareCoinX if you want to buy shares in my company from me. To get the coins out there, we do an ICO, and after the ICO sells out, new coins slowly enter the system from mining. Importantly, though, we don’t buy or sell these coins for dollars after the ICO.<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">What happens? What did we just do? Well, essentially, we have created three independent currencies for these three different kinds of property. They are monetarily decoupled from each other: changes to the value of one crypto do not <i>directly</i> influence the others. It might be the case that the value of my oil fields going up increases the value of my shares, of course, but if that happens, it’s not because of <i>monetary</i> connections between them. It’s because the underlying business connects the oil fields to the company’s shares.<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">In perhaps a clearer example, there is no <i>direct</i> connection between the dollar and the number of GasCoinX’s I will sell someone a tank of gas for. If the dollar tanks, GasCoinX might go up in value <i>relative to the dollar</i>, but not relative to a tank of gas, or relative to FieldCoinX or ShareCoinX. GasCoinX behaves essentially as a foreign currency relative to the dollar. Sure, they might be correlated a lot of the time, but they aren’t locked together, and their economies can be solved for independently, using independent rules and mechanisms. (Incidentally, proposals around creating a <a href="http://www.c2es.org/content/cap-and-trade-basics/" style="color: #954f72;">cap-and-trade carbon system</a> to address climate change are essentially this idea: create a separate sub-economy where a greedy algorithm can try to solve a simpler, targeted problem.)<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">This example is still an oversimplification of what a system like this would need to look like to be anything more than just “dollars by another name.” Certainly, it would require more than just one oil company to break down correlations between oil prices and the dollar, and the same ideas would have to be applied across all economic sectors. But laying out some sort of brilliant, buttoned up, perfect alternate vision of the economy is not the point of this piece.<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">All we are trying to do here is envision a simpler, plausible version of PHEA, so that it is easier to solve. In this example, we see inklings of doing that. We are trying to take related but largely separate kinds of property and place them into separate problem statements. Instead of looking for a solution to PHEA, we are only looking for a solution to the problem of gasoline tank economics, or oil field economics, or oil stock economics. Smaller, more focused, decoupled portions of the overall PHEA which can more easily be solved with a more narrowly focused capitalist greedy algorithm, or possible a different algorithm in some cases. This approach does create a new problem—coordinating activity between these decoupled units—and it’s not guaranteed that combining more optimum solutions to these sub-problems always yields a more optimum solution to PHEA (in fact, it’s probably true that PHEA does not have <a href="https://en.wikipedia.org/wiki/Optimal_substructure" style="color: #954f72;">optimal substructure</a>). However, it’s often the case that this type of simplification does yield improvements to the broader problem, while also reducing the total complexity of the overall solution.</p><h3 style="text-align: left;">Simplifying PHEA: Solving for Smaller Groups</h3><h2 style="break-after: avoid; color: #2f5496; font-family: "Calibri Light", sans-serif; font-size: 13pt; font-weight: normal; margin: 2pt 0in 0in;"><o:p></o:p></h2><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">Another form of simplification is to make the problem smaller. Instead of trying to solve PHEA for all of humanity, solve just for a smaller group. To some extent, we already do this at a country level, and even state and municipal levels to a degree. However, it would also be possible to optimize for small, explicitly formed groups of people. <a href="https://www.touristisrael.com/what-is-a-kibbutz/6053/" style="color: #954f72;">Kibbutz’s</a> and <a href="https://libcom.org/library/idea-commune-anarchist-practice" style="color: #954f72;">anarcho-communes</a> (even <a href="https://youtu.be/KN9c2TAWMlg" style="color: #954f72;">anarcho-syndicalist communes</a>) do this to some extent: a group of like-minded individuals agrees to adopt a system that lets them solve their economic problems together. They commodify their needs and desires at the community level, making decisions to optimize for the overall community.<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">Within a country like America, this kind of system would place a much heavier emphasis on local decision making. While the <a href="https://www.ushistory.org/gov/3a.asp" style="color: #954f72;">Founders may have envisioned</a> an ever-shrinking domain of authority moving along the continuum from local to state to national politics, in modern America, we often find the opposite to be the case. With all economic activity quantified by the dollar at the end of the day, and the federal government given explicit domain over interstate commerce (not to mention the various ways they regulate economic activity in general), PHEA in America is set up to use solutions that apply more or less nationwide.<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">If we were to enable PHEA to be solved for smaller groups of people, instead of by broad, single-source federal means, smaller groups would need to be defined. These smaller groups could then operate their own solutions for the commodification of their needs and desires. The natural way to define these groups is based on geography, with each state, county, and/or town having its own approach. In fact, at various points in history, this was how things were: small, local regions came up with their own currencies and economic systems. However, whether we look at <a href="https://www.worldhistory.org/article/638/trade-in-the-roman-world/" style="color: #954f72;">Rome’s spread through Europe</a>, at the <a href="https://www.federalreservehistory.org/essays/first-bank-of-the-us" style="color: #954f72;">early US’s adoption of a national currency and bank</a>, or at the <a href="https://www.theatlantic.com/magazine/archive/1896/09/the-problem-of-the-west/525699/" style="color: #954f72;">taming of the Wild West’s frontier economies</a>, it seems, for whatever reason, small, geographically based economies tend to get subsumed by larger national ones over time.<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">What we draw from that history, then, should <i>only</i> be healthy skepticism that letting people solve PHEA in small geographic groups is less likely to lead to an enduring economic solution than solving PHEA in larger geographic groups. It’s not necessarily the case that the centralized solution for all the population was <i>better</i>than the fragmented version for geographic subgroups; only that the centralized solution conquered the smaller solutions. And, importantly, geography isn’t the only way of dividing people into subgroups for PHEA solutions. They could be divided by industry of employment, or education level, or political philosophy, or any number of factors (also bearing in mind these kinds of divided societies can be rather dystopian if done poorly). What would it look like to solve PHEA independently for college-educated people and non-college-educated people? Or people working in the service industry vs. people working in agriculture vs. people working in manufacturing? I’m not entirely sure, but it seems there should be configurations like this that don’t devolve into <a href="https://en.wikipedia.org/wiki/Fictional_world_of_The_Hunger_Games#The_Districts_of_Panem" style="color: #954f72;">Hunger Games</a>.</p><h3 style="text-align: left;">Simplifying PHEA: Separating Needs and Desires</h3><h2 style="break-after: avoid; color: #2f5496; font-family: "Calibri Light", sans-serif; font-size: 13pt; font-weight: normal; margin: 2pt 0in 0in;"><o:p></o:p></h2><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">A final kind of simplification goes back to an earlier point, in which capitalism simplified PHEA by choosing to treat needs and desires the same. For a greedy algorithm, this is helpful because it makes objective functions more consistent and predictable. By enabling one solution for commodifying needs and a different one for commodifying desires, we create more degrees of freedom that, intuitively, should make it easier to approximate the optimum economic solution.<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">This setup would be pretty obvious: society at large decides a set of things that are considered needs, and everything else is a desire. Needs would perhaps include things like food, shelter, clothing, voting, education, freedom from fear, protection of private property, basic rights, or whatever collection of objectives floats society’s boat. Everything else would be classified as a desire, though it would be important to allow definitions of needs and desires to change over time (for example, 100 years ago, electricity was a desire, but now it is a need). Separate economic solutions would then be used to govern needs vs. desires.<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">An algorithm that presents a good solution for handling economic activity associated with needs might be different from one that solves for desires, and we could prioritize which solution takes precedence in the case of a conflict. For example, we might bias towards the needs solution until all people’s needs are satisfied, before allowing economic activity associated with desires to take place. “That’s communist!” you might object (and <a href="https://www.investopedia.com/ask/answers/100214/what-difference-between-communism-and-socialism.asp" style="color: #954f72;">it’s not communist, it’s socialist</a>), but all this requires is trying to make “needs” independently solvable from “desires.” <a href="https://www.usa.gov/benefits" style="color: #954f72;">Programs like welfare, social security, and Medicaid</a> attempt to do this. As does something like <a href="https://www.investopedia.com/terms/b/basic-income.asp" style="color: #954f72;">universal basic income</a>, which seeks to ensure people have enough money to at least satisfy their needs. All of these approaches fail to break correlation with the dollar, of course, so they aren’t truly separating needs from desires. But fundamentally, that is what they are trying to do: pose sub-problems of PHEA aimed at turning hunger, homelessness, or other basic needs into individually solvable problems.</p><h3 style="text-align: left;">Get Smarter: An AI Assist</h3><h2 style="break-after: avoid; color: #2f5496; font-family: "Calibri Light", sans-serif; font-size: 13pt; font-weight: normal; margin: 2pt 0in 0in;"><o:p></o:p></h2><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">Now, suppose all of the above sounds like hogwash, and keeping the full, society-wide, pan-economic PHEA as our main problem is the “right” way to address economics (it very well may be that breaking it into subproblems creates damning inefficiencies anyway). What else might we imagine a better solution than a greedy algorithm to look like?<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">Based on the historical challenges central planning, we can assume humans aren’t smart enough to pull it off. If you’ve read anything else on this blog, my next proposal won’t shock you: artificial intelligence. AI has shown itself to be quite adept at solving hard problems, especially narrow ones. In fact, AI is already gaining traction for complex, high-stakes, real-world <a href="https://www.globalrailwayreview.com/article/78709/ai-hype-reality-transform-technology/" style="color: #954f72;">problems like train scheduling</a>, which is known to be an <a href="https://en.wikipedia.org/wiki/NP-hardness" style="color: #954f72;">NP-hard</a> problem (i.e., it’s at least as hard as NP-complete problems). While we might be a long way from having a super-AI smart enough to control the whole economy, thinkers such as <a href="https://www.britannica.com/topic/I-Robot" style="color: #954f72;">Asimov have imagined</a> what that might be like. And even if we look at today’s AI capabilities, <a href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3489259" style="color: #954f72;">we see some promise</a> it might be able to help centrally plan pieces of a larger solution.<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">In one of our earlier examples, we looked at the problem of deciding how many loaves of bread to bake. Humans have historically been bad at predicting this at scale, so we rely on capitalism’s greedy algorithm to solve it. Instead, though, one could easily imagine and AI that would predict the future supply of bread that needed to be baked based on examining vast amounts of historical data about bread consumption. AI systems like this often outperform humans, sometimes <a href="https://www.pnas.org/content/117/48/30033" style="color: #954f72;">making shocking predictions</a> that turn out correct. In fact, it would be surprising if large bread manufacturers like <a href="https://www.grupobimbo.com/en/our-brands" style="color: #954f72;">Grupo Bimbo</a> and <a href="https://www.flowersfoods.com/brands" style="color: #954f72;">Flowers Foods</a> are not already exploring this problem as part of their <a href="https://www.bakeryandsnacks.com/Article/2019/11/25/Next-gen-AI-equipment-will-future-proof-the-baked-goods-market" style="color: #954f72;">AI adoption efforts</a>, for they already have to answer this question for their own massive operations.<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">One limitation of currently available AI technologies is that they are often narrowly focused, great at performing one specific task but nothing else. These specialist AIs, called <a href="https://deepai.org/machine-learning-glossary-and-terms/narrow-ai" style="color: #954f72;">narrow AIs</a>, can be combined into what are called “<a href="https://en.wikipedia.org/wiki/Multi-agent_system" style="color: #954f72;">multi-agent systems</a>.” These systems rely on individual narrow AIs to make their specialized predictions, then combine the specialized predictions into broader predictions or statements. The act of combining predictions can even itself be the job of another narrow AI, which is trained to accurately generate meta-predictions from lower level specialized predictions. Such a system could, for example, predict the total amount of all foodstuffs needed by a population, and therefore the amount of agricultural products needed, and therefore the amount of farmland needed for a given amount of agricultural products needed, and therefore the amount of water needed for agriculture, and so on. This system would be massive, complex, and likely inscrutable. But it is extremely plausible using only extant AI technology.<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">Viewed in another way, this is actually almost what capitalism is doing! Each baker is a specialist, capable of predicting the amount of bread they need to make. Each farmer is a specialist, capable of predicting the amount of food they need to grow and resources they need to do it. However, capitalism lacks an explicit entity to synthesize these projections into a meta-prediction, so instead it relies on the free market to more or less figure it out with its “invisible hand.” It may be that something smarter than us, or at least more adept at specializing in this kind of analysis, can fulfill these ends better.</p><h3 style="text-align: left;">Better Objective Functions with Brain-Machine Interfaces</h3><h2 style="break-after: avoid; color: #2f5496; font-family: "Calibri Light", sans-serif; font-size: 13pt; font-weight: normal; margin: 2pt 0in 0in;"><o:p></o:p></h2><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">Another futuristic approach to solving PHEA would seek to change people’s objective functions to better approximate global utility rather than individual utility, without departing much from the capitalist greedy algorithm. Today, people often make economic decisions that favor them <a href="https://www.frontiersin.org/articles/10.3389/fpsyg.2019.00372/full" style="color: #954f72;">despite their impact on others</a>; sometimes, even, they make decisions <a href="https://www.wired.com/2011/04/shocking-experiment-money/" style="color: #954f72;">knowing full well that they are negatively impacting others</a>. Using <a href="https://en.wikipedia.org/wiki/Brain%E2%80%93computer_interface" style="color: #954f72;">brain-machine interfaces</a> (BMIs), it might be possible to cause people to truly feel and understand the impact of their choices on others, and thus use improved objective functions when assessing their choices.<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">For example, suppose BMIs would allow the full-fidelity capture of a person’s experience, and then allow that experience to be delivered at full-fidelity to another person. It would be possible to record and save the actual, first-person experience of homelessness, or being swindled, or having to watch your child try to go to sleep hungry for the third day in a row. And then, that experience could be delivered to others, such that they actually, truly received that experience as if it were their own. You know, like in <a href="https://youtu.be/JYRVMeAwVKk" style="color: #954f72;">Total Recall</a>. Would people still choose to make decisions that benefitted themselves at real cost to others, if they knew they were going to have to experience those costs first-hand? If they knew other people could also to experience those exact costs, and know exactly who it was who imposed those costs? Likely not. This kind of forced empathy, though possibly ethically dubious, would nonetheless likely have positive socioeconomic effect.<o:p></o:p></p><h2 style="text-align: left;">Conclusion</h2><h1 style="break-after: avoid; color: #2f5496; font-family: "Calibri Light", sans-serif; font-size: 16pt; font-weight: normal; margin: 12pt 0in 0in;"><o:p></o:p></h1><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">Whew! This is a long post, so let’s review. We started off by defining capitalism in relation to the problem it purports to solve: the commodification of needs and desires, aka PHEA, the problem of human economic activity. Next, we looked at complexity theory in computer science and what problems that are really, really hard to solve look like. We defined greedy algorithms as solutions which try to solve hard problems by making short-term optimal decisions, and that greedy approaches often yield good but not optimal solutions.<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">Armed with that background, we looked at capitalism as a greedy algorithm attempting to solve PHEA. We saw how it has had many successes in this regard, especially relative to its competitors that employ central planning. We also saw how modern capitalism has deftly adjusted the rules governing the free market and objective functions used by people to make their decisions, all in an effort to make its greedy algorithm more closely approximate the overall optimum solution. Then, we thought about ways we might generate a better solution than modern capitalism. We thought through subdividing PHEA for smaller groups of people, for smaller domains of economic activity, or by separating needs from desires. Finally, we considered how artificial intelligence might make us better at central planning, and how brain-machine interfaces might help people have objective functions which help them evaluate decisions for overall rather than personal optimality.<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><br /></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;">That’s a lot of different stuff. Even after writing over 8000 words about it, I am still left with more questions than answers about what kinds of things might really, truly improve capitalism’s ability to facilitate good economic outcomes for society at large. Capitalism has done really well, and greedy algorithms are very attractive when it comes to really complex problems. There might be more changes to market mechanisms or incentives to drive significant (but incremental) improvements without straying from capitalism’s greedy algorithm. Or, perhaps these are simply the only kinds of changes we can make with any degree of confidence because the problem is so complex. Yet it could also be (and I hope it is) true that, by leveraging technology to make us smarter and more empathetic, we will be able to craft a new, better system. In any case, however, it is useful to think of capitalism not as some kind of all-consuming devil, nor as some kind of sacred savior, but simply as one of the ways we are trying to solve a really, really hard problem. It’s been a decent solution, by and large, but it’s by no means guaranteed to be optimal. With a pragmatist’s problem-solving mind, we just might be able to engineer a better solution, if we can finally start asking ourselves what it truly is that we actually want our economic system to <i>do </i>for us.<o:p></o:p></p><p class="MsoNormal" style="font-family: Calibri, sans-serif; margin: 0in;"><o:p> </o:p></p>Shawnhttp://www.blogger.com/profile/06311618271709855605noreply@blogger.com0tag:blogger.com,1999:blog-2034578472218454150.post-27597453706258266502019-12-16T15:55:00.002-08:002021-06-15T11:58:42.546-07:00How Many Stars Are *Really* In The Universe?<h2>
How Many Stars Are *Really* In The Universe?</h2>
<div>
<br />
Over the weekend, I heard a song playing in the background at the <a href="https://www.pacificsciencecenter.org/">Pacific Science Center</a> that was ostensibly a piece of pleasant science-themed audio scenery. Its chorus repeatedly posed a pretty simple question: "how many stars do you think are in the universe?" (PS - I can't find this song online for the life of me, but if you know it, let me know!)</div>
<div>
<br /></div>
<div>
It's had me thinking ever since. Of course, there are some answers to that question that are commonly accepted in science. Answers (<a href="https://www.esa.int/Science_Exploration/Space_Science/Herschel/How_many_stars_are_there_in_the_Universe">1</a>, <a href="https://scienceline.ucsb.edu/getkey.php?key=3775">2</a>, <a href="https://www.space.com/26078-how-many-stars-are-there.html">3</a>, <a href="https://helios.gsfc.nasa.gov/qa_star.html#howmany">4</a>) seem to range between 10^21 and 10^24. But those answers are only estimates based largely on the assumptions being made about the universe, and we've been <a href="https://www.nasa.gov/feature/goddard/2016/hubble-reveals-observable-universe-contains-10-times-more-galaxies-than-previously-thought">wrong about these assumptions before</a>. I've been wondering what the true answer to that question might be.</div>
<div>
<br /></div>
<h3>
We'll Never Know The Answer</h3>
<div>
It's actually physically impossible to count the number of stars in the universe. It's not a figurative "physically impossible," as in the number is so big we can't count that high in practical terms. It's genuinely physically impossible, as in the laws of physics say we cannot know the answer to that question.</div>
<div>
<br /></div>
<div>
Under general relatively, we know two things: nothing can travel faster than the speed of light, and the universe is expanding. Together, these facts limit our ability to gather information to the <a href="https://en.wikipedia.org/wiki/Observable_universe">observable universe</a> (side note: I'm still not fully convinced we don't <a href="http://seereason.blogspot.com/2016/06/do-we-live-in-personal-universes.html">live in our own separate observable universes</a>). It turns out because the rate of expansion of the universe is increasing (<a href="https://www.space.com/39815-hubble-suggests-universe-expanding-faster-study.html">1</a>, <a href="https://www.space.com/universe-expanding-fast-new-physics.html">2</a>, <a href="https://en.wikipedia.org/wiki/Accelerating_expansion_of_the_universe">3</a>), there are things we can see in the universe today that, eventually (like, millions or billions of years from now), our descendants will not be able to see anymore because they will have moved too far away, with our last possible glimpses of them redshifted below the visible spectrum. We also know that because the laws of physics are time invariant, there are things that used to be a part of the observable universe which are no longer part of the observable universe for us today.</div>
<div>
<br /></div>
<div>
Additionally, because light has a finite speed, the deeper we look into space, the farther back into time we look. This means the light we see from stars billions of years away may very well be from stars which have long since gone supernova or otherwise advanced into another phase of the <a href="https://en.wikipedia.org/wiki/Stellar_evolution">stellar lifecycle</a>. In fact, this concept is a key outcome of special relativity: that there is no such thing as <a href="https://en.wikipedia.org/wiki/Relativity_of_simultaneity">simultaneity</a>. A question like "how many stars in the universe are there right now?" has no specific meaning, because there is no such thing as an absolute "right now."</div>
<div>
<br /></div>
<div>
Taken together, these factors mean there is actually no way to observe all the stars that might exist in the universe. The laws of physics prevent us from doing so. This is also not something outside the common understanding of science, but it is the background behind the main thing I've been wondering.</div>
<div>
<br /></div>
<h3>
Is There Actually An Answer To This Question?</h3>
<div>
If the laws of physics mean we can never know the answer to this question, are we sure there is an answer to the question at all?</div>
<div>
<br /></div>
<div>
A problem people sometimes relate to counting the stars in the universe is counting the number of grains of sand on a beach. While that would be extremely cumbersome, there is nothing in the laws of physics which forbids us from designing a fancy machine or just grabbing a few thousand of our closest friends and eventually counting up all the grains of sand in any volume we have on Earth. So we are sure that, even if it's hard to get, there is an answer to the question "how many grains of sand are there on Beach X" or even "how many grains of sand are there on Earth."</div>
<div>
<br /></div>
<div>
We do not have the same assurances about the number of stars in the universe. Neither us nor any entity we could conceive of, all of us being bound by the same laws of physics, can ever see all the stars in the universe, whether relative to our frame of reference or in some sort of absolute manner. </div>
<div>
<br /></div>
<div>
This is what I've been hung up on: if the laws of physics say we cannot answer a question, does that question <b>actually have</b> an answer?</div>
<div>
<br /></div>
<h3>
A Finite Or Infinite Universe, And What We Can Know About It</h3>
<div>
Relatedly, there is <a href="https://phys.org/news/2015-03-universe-finite-infinite.html">some debate</a> (well, <a href="https://medium.com/starts-with-a-bang/ask-ethan-is-the-universe-infinite-or-finite-ec032624dd61">maybe a lot</a>) about whether the universe is finite or infinite. If the universe is infinite, it's possible it could contain infinite stars, which means there really is no answer to this question (besides "infinity"), and all the estimates of the number of stars are bunk. On the other hand, if the universe is finite, or if it is infinite but contains a finite number of stars, then there must be some integer number of stars that are in the universe, even if we can't see them all.</div>
<div>
<br /></div>
<div>
The lack of an answer to this question if the universe is infinite and contains infinite stars is easier to digest than the other one, where the universe contains a finite number of stars. If the universe contains infinite stars, the question lacks an answer directly because there are infinite stars. There isn't some number that enumerates the stars in the universe. This conclusion is straightforward. In practice, we are used to the idea that something can be "infinite," and thus it's not something we can really count to completion. But if the universe is finite, or otherwise contains finite stars, it's harder to say what a good answer to the question "how many stars are in the universe " might be. In fact, it might be that such a question has no answer at all.</div>
<div>
<br /></div>
<div>
A similar question on the opposite end of the size spectrum is Heisenberg's famous <a href="https://en.wikipedia.org/wiki/Uncertainty_principle">uncertainty principle.</a> While original (and often still mistakenly) described in terms of the <a href="https://en.wikipedia.org/wiki/Observer_effect_(physics)">observer effect</a>, what we have come to learn is that it is actually a fundamental property of subatomic particles that, for example, the precision with which one <b>can know </b>related quantities, like the position and momentum of a particle, are inversely related. I emphasize "can know" because it really means "how much the laws of physics allow to be known," not simply something related to our ability to measure or observe the particles.</div>
<div>
<br /></div>
<div>
In part, the uncertainty principle is a reflection of the imperfection of modeling subatomic particles as particles. It's well-known that at the quantum scale, particles sometimes are better described as particles, and sometimes they are better described as waves. It turns out that the position and momentum of a particle are better described as waves. Even so, modeling them both as particles or waves are abstractions we make in order to try and describe our observations. All abstractions have limitations or eventually break down when certain fundamental assumption they require are violated.</div>
<div>
<br /></div>
<div>
So, the uncertainty principle tells us something we know we can't know: we know there is no possible way we can know both the position and momentum of a subatomic particle to an arbitrary precision, because those concepts don't map to the quantum domain in the same way they do for larger objects. The inability to know these things is not a failing of humans or our technology; it is a property of the universe that these quanties cannot be known to arbitrary position simultaneously. In the same way asking "what color is something that is white and black at the same time" is nonsensical, asking "what's the exact position and momentum of this electron" is also nonsensical. Those words don't mean what we think they mean.</div>
<div>
<br /></div>
<h3>
Can We Reasonably Ask How Many Stars Are In The Universe?</h3>
<div>
If the universe contains infinite stars, then of course there is no numerical answer to the question of how many stars there are. But if the universe is finite or otherwise contains a finite number of stars, then is asking the question "how many stars are in the universe?" nonsensical?<br />
<br />
We can never know the answer to that question because the laws of physics do not allow it. But if the universe is finite, it must contain finite stars, so there must be some number that is correct, right?</div>
<div>
<br /></div>
<div>
I have come to think that in fact there is no such number. In the same way that we can't know the position and momentum of an electron (in part because <b>such concepts are abstractions </b>for electrons, which are more nuanced than macroscopic objects), we can't know the number of stars in the universe.<br />
<br />
In such cases where the laws of physics prevent an answer from being known, I would argue that the answer does not exist at all. Not because we are too stupid or inept to answer the question, but rather because the laws of physics mandate that there is no possible answer to that question. The answer doesn't exist because of practical purposes or limitations on us imposed by the laws of physics, not merely our technical shortcomings finding an answer. The answer doesn't exist because it's a nonsensical question, a question which arises because of the <b>flaws in our abstractions</b> about the universe lead to contradictory or undefinable answers.</div>
<div>
<br /></div>
<div>
For the uncertainty principle, it's a faulty premise to suppose that subatomic particles are tiny little bits of matter that have position, momentum, and otherwise behave like really tiny billiard balls. If you map the principles in your abstraction of billiard balls down to subatomic particles, you can start asking a bunch of irrelevant, nonsensical questions, or drawing a bunch of incorrect conclusions. The story of twentieth century physics, in fact, was the realization of this fact and the development of new models which better fit observations, even when those models contradicted our observations at everyday scale.</div>
<div>
<br /></div>
<div>
If it's nonsensical to ask "how many stars are in the universe," then, what are the pieces of our everyday abstraction we are mapping to the universe at large that lead to the bad question? Well, assuming we <a href="http://seereason.blogspot.com/2008/06/quantum-mechanics-cures-my-fear-of.html">suppose the universe really exists</a>, one is certainly the concept of simultaneity. Part of the reason this question is nonsensical is there is no definition of "right now," so defining a specific time in which to count all the stars is impossible.</div>
<div>
<br /></div>
<div>
However, even if we restrict ourselves to how many stars there are in the universe from our current frame of reference, thus eliminating the problem of simultaneity, we still have a problem. There are stars outside the observable universe we cannot and will not ever know about. In our every day lives, we are used to expecting that anything we can count a little bit, we can count all the way. Some people with deeper mathematical knowledge are used to the idea that there are "<a href="https://en.wikipedia.org/wiki/Countable_set">countable infinities</a>," like the set of even numbers or the set of combinations of letters in the alphabet. But our flaw related to asking how many stars are in the universe is different than these. It's a finite number we can't count -- an "uncountable finity" -- at least in the physics sense if not the mathematical sense (set theory <a href="http://math.uga.edu/~pete/settheorypart1.pdf">only allows for</a> finite, countably infinite, and uncountably infinite sets).</div>
<div>
<br /></div>
<h3>
Conclusion: There Is No Answer To The Question Because It Is Nonsensical</h3>
<div>
I haven't gotten much farther with this issue than that, probably because I lack the mathematical tools to try and be more formal about it. I also don't mean to suggest a problem in set theory, because I don't know set theory well enough to find a problem in it. But, in terms of the question of how many stars are in the universe, that language expresses the closest thing I have come up with to describe why it is flawed to map our everyday understanding of counting and finiteness to the universe at large.</div>
<div>
<br /></div>
<div>
By way of trying to summarize: on one hand, if the universe is infinite and contains infinite stars, the question is nonsensical on its face. On the other hand, if the universe is finite, or infinite with finite stars, the question is nonsensical because it maps everyday abstractions into an inappropriate physical context. Counting and finiteness work as concepts when applied solely to objects wholly contained within the observable universe, but stop functioning for anything larger than the observable universe because the laws of physics do not allow information from outside the observable universe in. Counting is fundamentally a process of accumulating information, so it only applies when a counter can access 100% of the information about that which they would count. Whenever they have less than 100% of the information required to count the objects, the objects being counted are an "uncountable finity."</div>
<div>
<br /></div>
<div>
Thus, there is no answer to the question "how many stars are in the universe," because such a question is nonsensical. Of course, if you modify the question slightly and make a song about "how many stars do you think are in the universe," we can answer that question, because we are entitled to think whatever we want even if we are wrong.</div>
Shawnhttp://www.blogger.com/profile/06311618271709855605noreply@blogger.com0tag:blogger.com,1999:blog-2034578472218454150.post-79844187393425041182016-07-01T02:12:00.000-07:002016-12-10T02:34:09.827-08:00Who are the "fittest?"<h2>
I'm Doing Darwin a Disservice</h2>
Most of my days are spent at work programming. As 50% of the entire workforce and the sole programmer (though not for long - we welcome our first developer hire July 5!), I have a lot of work to do. When I program, I usually listen to punk and metal on Pandora, and today while watching a new data analysis process I was debugging cranking along in AWS, a lyric from the NOFX song "<a href="https://www.youtube.com/watch?v=3kqLVeP7iHA">The Idiots are Taking Over</a>" struck me:<br />
<br />
<blockquote class="tr_bq">
<span style="background-color: white;"><span style="font-family: "verdana" , "arial"; font-size: 13px; text-align: center;">Darwin's rollin over in his coffin</span><br style="box-sizing: border-box; font-family: Verdana, Arial; font-size: 13px; text-align: center;" /><span style="font-family: "verdana" , "arial"; font-size: 13px; text-align: center;">the fittest are surviving much less often</span></span></blockquote>
<br />
I've listened to this song a million times, and it's always good for a whipping up a little anti-conservative, anti-religious-establishment furor in me. NOFX really nails that in some of their songs (see also <a href="https://www.youtube.com/watch?v=9v8oDqN76Mc">Leaving Jesusland</a>), but that one line hit me in a new way today.<br />
<br />
I'm not very evolutionarily fit.<br />
<h2>
What Do We Mean by "Fitness?"</h2>
Somewhat subconsciously, I've always considered myself extremely fit (I'm just going to say "fit" from here on out when I mean "evolutionarily fit" - my physical fitness level is a whole other topic, and you won't confuse me with a triathlete). I am smart, at least reasonably good at pretty much everything I try, and able to learn very quickly and develop mastery over pretty much any domain given enough time. I also think I'm socially competent, funny, a good speaker and leader, and not terrible looking, and someone who will do a great job raising kids. There isn't a good way to write this that doesn't sound vain, but I think, like I imagine most people do, that I'm a pretty good catch overall.<br />
<br />
But that has nothing to do with evolutionary fitness. Evolutionary fitness is solely about your ability to survive and pass on your genes by reproduction. I didn't have kids until 32, when I had twins, and I probably won't have any more kids. Meanwhile, I know people who grew up with me in Alabama and have 3, 4, 5, even more kids. They are reproducing at a much higher rate than me and are far more successful from an evolutionary standpoint.<br />
<br />
I am not unique in my experience. <a href="http://www.reuters.com/article/us-children-later-idUSTRE6454PF20100506">Many people are waiting</a> until later in life to have kids and are having fewer kids, and society is creating new support mechanisms to enable this behavior, such as <a href="http://money.cnn.com/2014/10/14/news/companies/facebook-apple-egg-freeze/index.html">Apple and Facebook's offers</a> to pay for its female employees to freeze eggs and have children later in life, after they have given the abundant energy of their 20's to the company to lay the foundation for a career.<br />
<br />
While the number of children someone has might be an obvious sign of this trend, the age at which they have them is the more important factor. Because population growth is more or less exponential, generation time has a much larger impact on the number of individuals born to a given lineage than the number of children in a particular generation.<br />
<h2>
A Fitness Example</h2>
As an example, suppose we were to look at the progeny of two families starting from today for the next hundred years. One family tends to have people who are focused on achieving "high success" as defined by conventional values (for whatever reason - nature vs. nurture are interestingly not interesting for this kind of family tendency), such as obtaining a solid education with potential graduate degrees followed by demanding careers in fields like medicine, law, finance, or engineering. The other family tends to seek more "normal success" in conventional terms, with an education including some college education or a bachelor's from an average school, a job that keeps the family out of financial danger but offers little luxury, and emphasis on other non-career measures of fulfillment such as volunteering, community/church participation, or family time.<br />
<br />
(Aside: it's not useful to try and decide whether one family is "wrong" about how they live their lives and the other is "right." Such discussions are fundamentally subjective and nothing can be proved. Avoid spending cycles on these kinds of thought trains. The only important thing in real life is whether the individuals feel fulfilled by their lives. The only important thing in this post is that the two families hypothetically exist.)<br />
<br />
In the first family, the average generation time is 33 and they tend to have 2 children. In the second family, the average generation time is 25 and they tend to have 3 children. That may not seem like a huge difference, but over the course of 100 years, the first family will produce 14 children: 2 children in 33 years, 4 grandchildren after 66 years, and 8 great-grandchildren after 99 years. The second family will produce a whopping <i>120 </i>children, nearly 10 times as many: 3 children in 25 years, 9 grandchildren in 50 years, 27 great-grandchildren in 75 years, and 81 children in 100 years. Exponential growth is a powerful thing.<br />
<br />
So which family is more fit?<br />
<br />
Well, fitness is generally related to the "ability to survive and reproduce." Because we're dealing with hypotheticals and averages, we can assume there is little difference in the ability of the two families to survive - at least inasmuch as survival would inhibit reproduction. Similarly, we can assume there are no issues affecting ability to reproduce. The key difference postulated is that the <i>choices </i>about reproduction are different between the two families. If we want to define fitness as something concrete regarding the ability to reproduce, those choices are the key difference in fitness between the two families.<br />
<h2>
How Does Intelligence Relate to Fitness?</h2>
NOFX's lyric is a catchy turn of a familiar phrase, but the problem is not that the fittest people are not surviving. It's that many people who think they are very fit because they are intelligent, successful people are actually not very evolutionarily fit at all if they don't have children.<br />
<br />
Or, perhaps worded more in alignment with other definitions in evolutionary theory but ultimately amounting to the same thing, despite these intelligent, successful people being very fit in terms of ability to survive, they are not reproducing at a rate commensurate with their success surviving. They are effectively behaving like they were less fit to survive and reproduce, or even as if they died if they choose not to reproduce. One could even view whatever qualities they possess that make them successful and intelligent as evolutionary negatives. Even though they might personally be doing quite well, the fact that they are reproducing less often is actually an evolutionary weakness, destined to be bred out of the population.<br />
<br />
None of these are original observations. Satoshi Kanazawa wrote a <a href="http://www.economist.com/blogs/prospero/2012/06/quick-study-satoshi-kanazawa-intelligence">great article</a> pointing out the ways in which intelligence is actually an evolutionary disadvantage. Mike Judge's <a href="https://www.youtube.com/watch?v=CsJFNQd62Wk&feature=youtu.be">Idiocracy</a> basically takes this premise that intelligent people are being bred out and turns it into a movie. Richard Dawkins' <a href="https://en.wikipedia.org/wiki/The_Selfish_Gene">The Selfish Gene</a> explores some of this territory, including coining the original meaning of meme to describe social and cultural elements that essentially undergo an evolutionary process in our collective minds.<br />
<br />
These make good arguments that there might be something to the idea that intelligence is an evolutionary disadvantage at this point in our species history (even putting aside the fact that our intelligence has grown sufficiently for us to create existential threats like nuclear holocaust and catastrophic climate change). So is there something to it?<br />
<h2>
Memes are Important lol</h2>
The meme connection is also interesting and relevant here. Memes are basically little cultural nuggets that compete for survival in culture at large. Dawkins explained them with an analogy to his claim that evolution operates at the gene level, with the propagation of useful genes being the process underlying evolution. Memes can be grouped into ideologies, which are an analogy to entire organism genomes: collections of genes that form a larger coherent entity better able to spread all of the genes together than any one gene would be on its own.<br />
<br />
Memes that correlate with or encourage increased reproduction, such as anti-contraceptive/anti-abortion messages, ending one's education sooner, agrarian lifestyles, and general "be fruitful and multiply" religious beliefs, tend to have an evolutionary advantage because they speed up generation times and/or increase the average number of children per generation. Over time, one would expect these kinds of memes to dominate society and push out competing or incompatible ideas. Indeed, many of the worlds leading religions have been around for thousands of years and, among other moral principles, espouse having many children as primary goals.<br />
<br />
I love my kids and think parenthood is the most rewarding thing you can do in life, so my point is not to suggest there is something wrong with memes that encourage you to have many kids. I get why someone would like having many kids, although it's not for me. My point is that these memes are expected to win and push rival ideologies to the side. Over time, ideologies that feature memes emphasizing having many children should increase their prominence in society to the point of domination.<br />
<br />
Yet that is not what we observe. If it were possible for strong memes about bountiful reproduction to propel the ideologies that contain them to dominate society, we would never have left the Dark Ages. So something else must be going on.<br />
<h2>
Memes Evolve</h2>
Certainly part of the reason ideologies with hyper-reproductive memes aren't totally dominant is that ideologies are not monolithic or static. People are free to adopt parts of an ideology and reject others, or even adopt parts of multiple ideologies, and the memes constituting an ideology can and do change over time. Today, most religious people accept that the Earth revolves around the Sun, even though 1000 years ago such a belief was a great way to get the Church to burn you at the stake.<br />
<br />
Most modern religions do not reject science, and while I personally think there is no way to truly accept science and believe in a religion, I recognize many people do and I am happy for them as long as they don't impose those beliefs on others (although I am stricter about that than many religious people are probably comfortable with - things like being against LGBTQ equality are an obvious no-no with me, but so are little things like the "Under God" in the Pledge of Allegiance).<br />
<br />
But another important role science has played has been to increase the overall ability of our species to survive and reproduce. <a href="https://en.wikipedia.org/wiki/Homo_sapiens">Humans and our ancestors</a> have gone from learning to stand up to dominating every aspect of life on this planet in only 4 million years, or 0.09% of the lifetime of Earth. Homo sapiens have gone from achieving <a href="https://en.wikipedia.org/wiki/Behavioral_modernity#Great_leap_forward">rudimentary modern behaviors</a> like being able to plan and think abstractly to figuring out how to land on the moon, create the Internet, and feed a population that has been growing exponentially without limit in only 50,000 years - 0.001% of the lifetime of Earth. These are incredible achievements, not to be overlooked as possible contributors to resolving <a href="https://en.wikipedia.org/wiki/Fermi_paradox">the Fermi paradox</a>.<br />
<h2>
Science is an Ideology, but *Inherently* Not One That Can Survive Independently</h2>
<div>
It pains me to the core of my soul, but I don't think a science-first society like the United Federation of Planets can ever exist.</div>
<div>
<br /></div>
Science is a symbiotic ideology composed of symbiotic memes. On its own, science will tend to be overwhelmed by other ideologies and memes that encourage more, faster reproduction, which works against allowing people to spend more time engaged in learning, thinking, experimenting, and inventing. Science by itself is unlikely to become a dominant ideology on evolutionary timescales as long as biological reproduction is necessary for the growth of a population.<br />
<br />
But there is a bright side to science's symbiosis. Any ideology which rejects science loses access to the powerful technologies and other benefits it generates, which ultimately makes that ideology weaker than its competitors. If an ideology abandons science or randomly comes to prominence with anti-science memes, other ideologies that do permit science will rise up to replace the science-rejecting ideologies over time due in part to the power science brings them.<br />
<br />
This is why the mainstream belief systems of major religions tend to have some sort of love/hate relationship with science. They accept as much science as they can, while leaving room for their deepest beliefs in order to encourage the application of science within their ideologies wherever doing so doesn't threaten the ideas they most want to preserve. Where there are direct tensions, over time (perhaps generations), the religion will let go of certain specific memes in order to maintain a connection to science and not prevent it from being applied fully by it. Hence the Sun-revolves-around-Earth flip flop.<br />
<h2>
But We Still Need to Make New Science People</h2>
To ensure a supply of new scientists and other science-minded people in the face of memes which push for more reproduction and thus less science, successful ideologies often incorporate other memes which reward a handful of individuals who do put aside reproduction and take up science. They may earn significant financial rewards, and they may earn respect from others and prestigious recognition. Some even achieve popular fame simply for being smart.<br />
<br />
But the ideologies also constrain the number of those who can pursue these scientific goals in order to maintain the primacy of the reproductive memes. Only a few people can become tenured professors or be admitted to medical school. Only a few people can work at Google or get their startup funded. Even before those achievements, only a few people can be top of their class students or earn all A's.<br />
<br />
One could argue that is natural because not everyone is equally capable. But if one doesn't let that sentiment stop one from continuing to think, one could also argue that the efforts to limit the number of people who go into scientific fields are baked into the way we teach our children from the very beginning, in what behaviors we reward vs. punish, how we teach science and math, and even how we pass on our own apprehensions (unwittingly or not) about science and math to our children. Only a few people can learn to read or go to school, or have enough to eat.<br />
<br />
By constraining the ability of people to become engaged in scientific careers, and by glorifying those who obtain such careers at least in some circles, we create a limited opportunity for a few ambitious people to compete to fulfill the expectations of the special-purpose memes of science. These memes are poorly suited to survival on their own, but in the context of the larger ideology and society in which they exist, they contribute immensely to the survival of all.<br />
<h2>
Humans Win Because They Make Fitness About Ideologies and Memes</h2>
Ideologies that survive are complex webs of memes, pushing people to hold certain beliefs and perform certain actions, which make the overall population of people believing that ideology more numerous. Sometimes, the motives of different individuals holding an ideology seem to run counter to each other. Sometimes the motives in an individual even seem to contradict.<br />
<br />
While I'm personally not perhaps as fit as someone else who has 6 children before 30, the fact that I have invested in my intelligence and education and am pursuing a technical career means I am creating means to support the people who do invest their effort in reproduction, almost as if they were my children. That seems like a good thing overall for whatever pieces of ideology we share, even though it's likely that we would hold very different beliefs and memes on other points and maybe not even like each other. But for our society as a whole, our ability to support each other even indirectly is a good thing.<br />
<br />
And that perhaps is the most important trait humans have developed which have allowed us to take over the world: we have mastered the means by which a group of individuals with disagreements can become a cohesive meta-organism, with the individuals contributing to the fitness of the overall meta-organism even if they are not personally reproducing in great numbers.<br />
<br />
So, the next time you meet someone who says or does or believes things you disagree with, realize they are more important to you than you might think. Your beliefs and actions can either support each other or work against each other, and you can choose to increase or decrease the support. You can choose to focus on your differences or on your similarities. But know that the evolutionary trend is toward support because that increases the fitness of your ideology, and you fight evolutionary trends at your own peril.<br />
<br />
Of course, all of this <a href="http://seereason.blogspot.com/2008/06/quantum-mechanics-cures-my-fear-of.html">assumes other people exist</a>, and it's also likely that soon <a href="http://seereason.blogspot.com/2016/06/eight-years-went-by-fast-better-late.html">human intelligence won't matter</a>, so yeah, there's that :)Shawnhttp://www.blogger.com/profile/06311618271709855605noreply@blogger.com0tag:blogger.com,1999:blog-2034578472218454150.post-65064299407989783442016-06-03T23:22:00.002-07:002016-12-10T01:46:36.052-08:00Do We Live In Personal Universes?It's generally useful to behave as if we all live in the same universe. Even if one agrees with quantum solipsism - the idea that <a href="http://seereason.blogspot.com/2008/06/quantum-mechanics-cures-my-fear-of.html">one is the only person one knows exists and that the existence of the entire universe depends on you continuing to exist</a> - walking around acting that way makes you look crazy and you're sure to piss off everyone around you if they do in fact also exist. Life is a lot easier to live if one accepts the postulate that other people really do exist even if it can't be proven - and even if they don't exist, behaving as if they do keeps your experience of reality consistent with the expectations your mind has built up over years of experience before you started questioning the reality of other people.<br />
<br />
If one puts aside quantum solipsism, there is still a problem in knowing whether or not other people exist in the same universe as you or not. It turns out that one can only prove that other people's universe is consistent with your universe, and not that they are in the same universe.<br />
<h2>
The Observable Universe</h2>
<div>
Scientists sometimes mention the <a href="https://en.wikipedia.org/wiki/Observable_universe">observable universe</a>. The observable universe is basically the subset of the universe that we could possibly observe or otherwise be affected by. Because <a href="https://en.wikipedia.org/wiki/Speed_of_light#Upper_limit_on_speeds">nothing can travel faster than the speed of light</a> under relativity, it's not the case that some object in the universe an arbitrary distance away from Earth can affect Earth (although there are phenomena that do seem to violate the universal speed limit, they are either <a href="https://en.wikipedia.org/wiki/Tachyon">purely theoretical</a> or <a href="https://en.wikipedia.org/wiki/Quantum_entanglement">confined to the quantum scale</a>, so we will ignore them here).</div>
<div>
<br /></div>
<div>
Only objects that are no farther away than the speed of light times the age of the universe can have affected Earth, so one might guess that the observable universe is a sphere with Earth at the origin and a radius of about 13.8 billion light-years - the speed of light times age of the universe. However, the universe is also expanding, so 13 billion years ago many objects were much closer to us when they emitted light that we observe today. Taking the expansion rate of the universe into account, the actual radius of the observable universe is about 46.5 billion light-years. Also because of the expansion of the universe, there are a set of objects which will never enter the observable universe - they are becoming more distant fast enough that the light they emit will never reach us. In fact, because the universe expands exponentially but the rate of expansion of the universe is constant, <a href="http://physics.stackexchange.com/questions/5320/maximum-size-of-the-observable-universe">objects in the observable universe slowly leave it</a>!</div>
<div>
<br /></div>
<div>
Side note - because light takes time to travel to Earth, it's also the case that looking out into space is looking back in time. When we look out to the edge of the observable universe, we are seeing things as they were billions of years ago. If you go back far enough, the elemental composition of the universe was different, with heavy elements not yet having been <a href="https://en.wikipedia.org/wiki/Supernova_nucleosynthesis">synthesized in supernovas</a>. In these conditions, stars and galaxies themselves often took different forms than they do today. Distant galaxies are <a href="http://curious.astro.cornell.edu/about-us/97-the-universe/galaxies/cosmology/533-how-do-distant-galaxies-differ-from-those-nearby-advanced">usually bluer and more metal-poor</a> because of their youth, for example.</div>
<div>
<br /></div>
<div>
The observable universe is relative to the point from which one looks out into the galaxy. Because its radius is so huge, the observable universe on Mars is very nearly identical to that on Earth - at its most distant, Mars is about 401 million km from Earth, or 0.0000423 light-years, or 0.0000000000000912% (9.12 e-14%) the radius of the observable universe. That is insignificant enough to consider the observable universe of Mars as the same as the observable universe of Earth for most purposes - any information that reaches Mars at the speed of light reaches Earth no more than about 24 minutes later, and vice versa. Compare to the age of the universe, that is nearly instantaneous.</div>
<div>
<br /></div>
<div>
<b style="font-style: italic;">But the difference is not zero.</b> There is a slight difference between the observable universe of Mars and that of Earth, and while it's unlikely ever to matter, it's still not zero. It's still different.</div>
<h2>
Our Own Observable Universes</h2>
<div>
Earth is not a point in space, so similar to the difference between the observable universes of Mars and Earth, different locations on the Earth's surface have ever so slight differences in their observable universes. The differences are four orders of magnitude less than the greatest difference between Earth and Mars - the Earth's diameter is only about 12,742 km on average - but the difference is still not zero.</div>
<div>
<br /></div>
<div>
People are not points in space either, but because our observation and understanding of the universe arise from of the abstract viewpoint of our brains, we perceive the universe as if we were points in space. Because we are made of <a href="https://en.wikipedia.org/wiki/Fermion">fermions</a>, no two people can <a href="https://en.wikipedia.org/wiki/Pauli_exclusion_principle">occupy the same point in space</a>, so no two people can observe the universe from the same point. Thus, like Mars and Earth, we each have our own observable universes too. If we're having a conversation we might only be a meter apart - 9 orders of magnitude closer than the Earth and Mars at their most distant - but we are still a non-zero distance apart and we have different observable universes.</div>
<div>
<br /></div>
<div>
Being in different observable universes doesn't mean we are in different actual universes, however. As long as our observations of the universe are consistent, it only means we observe things at slightly different times - only if we observed a contradiction, like me observing a coin come up heads and you observing it come up tails, or me observing a distant supernova and you observing a star happily chugging along, would being in different observable universes show that we are in different actual universes.</div>
<div>
<br /></div>
<div>
But it also means that we can't <i style="font-weight: bold;">prove </i>that we are in the same actual universe. It only means that we can check our past observations against each other and determine whether or not they are consistent with the hypothesis that we are in the same actual universe.</div>
<div>
<br /></div>
<div>
There is a similar thought process some have explored regarding the fact that it takes time for light to enter your eye, cause chemical reactions in your retina, travel up your optic nerve, and be processed into information by your brain. This process means we are always observing the past, and the present ever eludes us. This is a valid observation, but different from the observable universe argument in that it speaks about our limits making observations, not about the content of the universe we are able to observe.</div>
<div>
<br /></div>
<div>
So, does it matter if we can't prove that we are in the same actual universe? Certainly, all our experience has been consistent with that hypothesis. And like quantum solipsism, running around saying that no one else is in the same universe as you is a great way to alienate friends and get committed.</div>
<div>
<br /></div>
<div>
But that's not the point. The point is to use things we can <i style="font-weight: bold;">know </i>to reason about the world and form a logical understanding of reality. And the fact that you and I are in different observable universes (assuming you exist :) ) means that neither I nor you can <i style="font-weight: bold;">know</i> that the other is also in the same universe. It means we either accept the loneliness that implies, or adopt some additional postulates into our worldview.</div>
<div>
<br /></div>
<div>
Personally, I find it more practical to accept the postulates and carry on with the assumption that other people are in the same actual universe as I. But it's good to know what beliefs you hold that are postulates, both because being logically explicit is mentally healthy and calling out your assumptions enables you to reason and understand other things more effectively. Plus, you never know when you'll see a coin come up heads that I see come up tails, and we'll suddenly realize we aren't in the same universe after all.</div>
Shawnhttp://www.blogger.com/profile/06311618271709855605noreply@blogger.com0tag:blogger.com,1999:blog-2034578472218454150.post-9313945363339138352016-06-02T22:44:00.002-07:002016-06-03T13:49:49.612-07:00Preparing for the Singularity<div class="MsoNormal">
Eight years went by fast! Better late than never picking
back up a blog I suppose.<o:p></o:p></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
Since I last wrote (in addition to everyone driving home
getting “Internet phones” to provide them real-time traffic data which should
hypothetically lead to more efficient travel times) I’ve largely maintained
most of the beliefs from my posts and developed my thinking along several
lines. Today, I’m going to talk about something that’s been on my mind a lot
recently: what will happen to society leading into and after the singularity?<o:p></o:p></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
On one hand, the definition of the singularity is that we
cannot see what the world will be like beyond its horizon, because we cannot
predict what the presence of one or more intelligences far superior to our own
would do with the world. However, we can project some of the current aspects of
our society forward to the singularity and make some educated guesses about
what will happen to them after the singularity as well.<o:p></o:p></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
I’m going to first talk through the DMV as a case study in
technological advancement, and then describe the two critical developments we
need to focus on making now as a society to avoid the worst sociological
effects of the singularity. Also, it should be noted that I continue to take
the arrival of the singularity as a given – it’s important to prepare for it
because there is no way it doesn’t happen.<o:p></o:p></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
I should also say this post began from an outline for a book
on this topic, which would provide more examples, flesh out ideas further, and
try to offer some more concrete suggestions. It also would have more citations, which I ordinarily would include in a blog post but have omitted now because of my purpose for sharing this. I’m posting this as a
blog to get ideas down and see what others think of them. </div>
<h2>
<b style="mso-bidi-font-weight: normal;"><span style="font-size: large;">Why Do We Still Have The
DMV?</span></b></h2>
<div class="MsoNormal">
The Department of Motor Vehicles (DMV – note that other
states have different names for the same function, but DMV is most common) is
the bureaucratic hell most of us have to experience every few years to replace
our licenses. You go, get a number, wait, then talk to a person who does some
work on the computer and prints some things out. A few weeks later, a new
license arrives in the mail.<o:p></o:p></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
The DMV could be replaced almost <i style="mso-bidi-font-style: normal;">entirely </i>by a website. In fact, one day it almost certainly will
be. A website could instantly field requests, handle routine activity totally
automatically, and make complex decisions with little to no human involvement.
A website could provide you an instant temporary license to print at home, and have
a new license show up in your mail box within a few business days.<o:p></o:p></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
Some states have replaced portions of their DMV process with
websites or call centers, but none have gone all the way (comment if you know
of some!). There is indeed little effort to create all-software replacements for the current DMV process, and certainly
any effort to do so would be encountered by tremendous resistance from the
government and likely many other organizations. The DMV process is established
and many public and private sector jobs depend on it. It would be easy for
those organizations to stymie efforts to fully automate the licensing process
by drudging up fear of terrorists, illegal immigrants, and reckless drunk
drivers being given licenses by soulless computers.<o:p></o:p></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
Yet for the customers of the DMV, a totally web-based system
would be a far superior experience. No lines, the ability to renew your license
outside business hours or whenever is convenient for you, maybe even the
ability to choose your license picture. Nonetheless, there is no real effort
being made to turn the DMV experience into a website.<o:p></o:p></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
Why? Certainly part of the answer is that as a government
organization, the DMV doesn’t really need to compete for customers. But many
DMVs have private partners who do face competition, and the tendency of the government’s use of
technology is to adopt it slowly rather than never. So why would there be
resistance to creating software to make it easier for an organization to
deliver better service to those it would serve? If people prefer a given piece
of software to provide them a service instead of a human-based alternative, why
is it hard to make that happen?<o:p></o:p></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
The answer is jobs. Putting software in charge of tasks
humans currently perform eliminates the need for those humans to be employed to
perform those tasks. Our current economic system is based on the premise that
people acquire wealth by being employed in jobs, whether they work for others
or themselves, so preservation of jobs is an important subconscious facet of almost all economic decisions. Without competition, the DMV doesn’t need to become more efficient
or better satisfy its customers, so it faces no real pressure to
change. Without that kind of pressure, the people within the DMV are not
likely to start replacing their coworkers with software.<o:p></o:p></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
Using a public sector bureaucracy as an example enables us to really
highlight a blatant existing inefficiency, whereas a private sector example would likely
highlight a company that no longer exists. But this same broad theme is true in
many areas: transportation, bartending, outdoor guiding, tailoring, piloting,
accounting, investing, governing. Software could perform a great many functions
for people, even better than people, and yet in many areas we see little to no
application of software to truly improving them to that extent. Where there has
been progress, with software like Uber, Spotify, or Amazon, numerous challenges
have presented themselves from displaced interests.<o:p></o:p></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
Now, I don’t mean to celebrate this trend. Only clearly
point out its existence. It’s not necessarily always a good thing to just start
eliminating jobs with software (even though that’s what we’ve been doing since
the ‘70’s – also, note that the local impact of this is very similar to jobs
being exported overseas instead of given to computers). Like anything else
there are pros and cons, and we need to recognize the cons in order to mitigate
them.<o:p></o:p></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
Ultimately, the major con in this trend is that many people
are losing their ability to acquire the resources they need to live. By having
their jobs replaced, they stop making money, and they face the prospect of not
being able to afford to live as they had been.<o:p></o:p></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
So, we need to mitigate the downside impact of people losing
jobs to software. We’ll come back to that. But first, we need to understand the
scope of jobs that are threatened by software.</div>
<h2>
<b style="mso-bidi-font-weight: normal;"><span style="font-size: large;">The Singularity Means A
Computer Will Be Bettter At Your Job Than You - ALL Of You</span></b></h2>
<div class="MsoNormal">
For many people, especially those who I’d expect to be
reading my blog, jobs being replaced by machines or computers has always been
something that happened to “someone else.” Manufacturing, labor, paper pushing,
delivery, basic math, editing… the kinds of jobs that are highly repetitive
and/or mainly involve executing a series of rule-based decisions. Not the white
collar, intellectual, creative jobs of someone with a college education.<o:p></o:p></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
After the singularity, this will no longer be true. The
singularity is the culmination of a larger software revolution in which, as
Marc Andreessen says, “software will eat the world.”<o:p></o:p></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
It can be tempting to argue that the software revolution,
like all technological revolutions of the past, on the balance will actually
create jobs. For example, while the invention of the mechanized loom
drastically shrunk demand for human weavers, it created other, higher-level
jobs that could assume the availability of cheap fabric as given and create
larger net productivity. Although it’s true that many weavers who lost their
jobs could not transition to new roles and suffered as a result, society as a
whole benefitted.<o:p></o:p></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
What is different about the software revolution is that it
results in technology which supersedes <i style="mso-bidi-font-style: normal;">essentially
all </i>human capabilities. The technology of the singularity is by definition
of superior intelligence to humans – it is better than us at <i style="mso-bidi-font-style: normal;">any </i>mental task. When a stockbroker or
an aeronautical engineer or a lawyer is replaced by software (software more
effective than the humans, in fact!), there is <b style="mso-bidi-font-weight: normal;"><i style="mso-bidi-font-style: normal;">no longer a higher-level role </i></b>a
human can move into in order to fulfill some need better than another piece of software could (at least,
not in significant enough numbers to provide traditional jobs for all the
displaced). There may be a tiny number of jobs created to manage all these
pieces of software, but not enough for even 1% of the displaced. And even then,
these management jobs will likely be better performed by more software anyway.<o:p></o:p></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
The core economic disruption caused by the software
revolution is that it will <b style="mso-bidi-font-weight: normal;"><i style="mso-bidi-font-style: normal;">*never*</i></b> be economically correct to
hire a human to do a job over having a machine do it. There will not be jobs to
be had because those who might need some work done – owners, for lack of a
better term – will find computers a far more cost effective way to have the
work performed. Without a need for human labor, the only humans to whom wealth
accrues will be the owners.<o:p></o:p></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
This means that the people at the DMV, the taxi drivers, and
the baristas aren’t the only ones whose livelihoods are endangered by the
singularity. Unless you own some technology that will be part of the
transformation the singularity entails, you too are threatened.<o:p></o:p></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
So, with essentially everyone on the planet at risk of
economic disaster, how can we mitigate the downside of jobs lost to software? We'll have to deeply understand the problem first...</div>
<h2>
<b style="mso-bidi-font-weight: normal;"><span style="font-size: large;">The Core Problem: How We
Gain Wealth</span></b></h2>
<div class="MsoNormal">
The primary means by which most people acquire wealth is by having
a job. In a job, people sell the hours of their life to perform the tasks that job
is intended to achieve. If there are almost no tasks which a human is
better suited to perform than software, what happens to all the humans
displaced by software? And perhaps more importantly, what happens to the humans
who own that software?<o:p></o:p></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
The answer today is that the humans who hold the displaced
jobs are themselves displaced. They lose their ability to gain wealth and the
survival of both themselves and those who depend on them is endangered.
Meanwhile, those who own the software and related means that replace them gain
the wealth the displaced would have otherwise acquired.<o:p></o:p></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
This is not a sustainable arrangement as software becomes
more and more capable of performing complex tasks. It’s not the case that a
very small few can concentrate the wealth that the great many expected to
acquire without consequences. It is hard to predict specific consequences, but
these are the circumstances on which revolution is built. Left unchecked, one
of two things will happen: revolution, or a return to feudalism. Neither result
benefits the progress of humanity; a different result must be obtained.<o:p></o:p></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
The advance of technology cannot be stopped. The solution is
not to reject technology and attempt to preserve human roles in economic
functions. Such an effort may achieve temporary, local successes, but cannot
stop the tidal forces of technological advance. The solution is to change the
system by which technological advances are managed.<o:p></o:p></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
How do we change the system in such a way?<o:p></o:p></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
Basic capitalism is a good first order description of a
better system, but not the same capitalism that applies in a world where the
majority of work is performed by humans. Capitalism is based on the two premises
(1) that the application of owned capital is the basis for economic development,
and (2) that human labor is an essential function of applying capital. In a
world where software can replace the output of multitudes of humans, the second
premise breaks down.</div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
The only humans who win in this scenario are those who own
the software in question, because our economic system provides them with all
the benefits generated by the software. If a new X-ray analysis program
eliminates the need for radiologists (or more precisely, offers the same
services as radiologists at 10% the price and with 200% the effectiveness), the
entity which owns that program gets to assume the economic benefits of a tremendous
swath of formerly well-paid, useful humans who no longer have marketable skills.<o:p></o:p></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
Left unchecked, this trend will cause a return to feudal
society, with ownership of software rather than land as the core mechanic.
However, unlike feudal society where tiers of humans were necessary to
administer the land and humans occupying it, the need for intermediate tiers of
humans will be minimal to none. Instead of a king, dukes, earls, barons, and
serfs, we will only have kings and serfs.<o:p></o:p></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
The antidote to this problem is not simple. It requires
social, political, and economic advances on several fronts. But the critical
step is to redefine how wealth is accrued: most people cannot expect someone
else to pay them to perform work for them, and simultaneously most people
cannot expect to own some set of software that generates wealth for them.<o:p></o:p></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
Unfortunately, I don’t have a specific plan for a specific
system (yet?), but I do know the two critical characteristics a good plan must
have, and these characteristics are goals we can start heading towards now. </div>
<h2>
<b style="mso-bidi-font-weight: normal;"><span style="font-size: large;">Step 1: Eliminate Time As
The Core Wealth Generator</span></b></h2>
<div class="MsoNormal">
Firstly, we must stop thinking that selling the hours of our
life is how wealth is acquired. Whether you are a grocery checker, truck
driver, lawyer, doctor, stock broker, or even computer programmer, after and
even soon before the singularity, there will come a point where your employer
will find it in their economic interests to replace you with software under the
current economic paradigm. You cannot expect your time to remain a resource
others will want to purchase (and besides, they've been paying you to browse the internet and read blogs like this from your desk at least *some* of the time, right? :) ).<o:p></o:p></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
While broad changes are needed to resolve this at a macro
level, one can pursue this goal on one’s own, without any of macro changes, in
order to build a more robust livelihood in the face of larger trends. One can
prepare now and set oneself up to survive through the singularity even if one
is not one of the privileged few who will own the mechanisms of the
singularity.<o:p></o:p></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
The entrepreneur is a person doing this already: a person
starting their own small business, selling a product or service others will pay
for. One is still selling one’s hours under this model, but one is not selling
them to an employer who has a monopoly over them and decides what they are
worth. One is converting one’s hours into products or services which the market
values, and one can pursue increased value for one’s hours according to one’s
wishes. You are converting your hours into a marketable good which can be
priced according to the demand it satisfies. Becoming one’s own boss is not
just a luxury – it is a necessity to survive the software revolution. <o:p></o:p></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
A key concept to becoming this kind of entrepreneur is to
generate a marketable good whose marginal labor cost is trivial. The total
marginal cost can be non-trivial – for example, maybe you make a widget that
requires you purchase raw materials and manufacture something on an assembly
line – but it must not take a noticeable amount of human effort to produce a
unit. Like those sitting on top of the singularity, you need a product which
you can allow machines to largely create and deliver for you.<o:p></o:p></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
Also note that “entrepreneur” is meant in the classic sense
of someone starting their own business, to generate income for themselves. The
shiny Silicon Valley “entrepreneur” is not necessarily this person, for many
Silicon Valley entrepreneurs are still ultimately selling a product with
non-trivial marginal labor costs or with significant outside ownership. Someone
who is attempting to create a business that existing capital holders (rich companies or people) will
purchase for large amounts of money, but with a majority of the return on their
effort being diverted to other existing capital holders (venture capitalists
and their investors) is not the right kind of entrepreneur to strive to be.<o:p></o:p></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
While the shiny Silicon Valley approach can be a valid short-term strategy for
generating wealth to sustain oneself through before we get too close to the
singularity, it’s important to recognize this form of entrepreneurship is not
going to remain effective for the entrepreneur as the singularity approaches.
Perhaps worse, it is improving the financial situation for a small number of
people by contributing to the overall problem of capital accumulating in fewer
and fewer hands. Those involved in this activity aren’t inherently bad, but
they are taking the efforts of intelligent people and applying them towards the
furthering of the problem of capital consolidation, which is not the best use of
their abilities.<o:p></o:p></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
So, to take steps towards preparing for the singularity
economy, one should look for ways to create a high-demand product with
negligible marginal labor costs. Examples include designing a product that can
be manufactured and delivered mostly by machines, writing a book or blog,
making music or movies, lecturing online, or making software.<span style="mso-spacerun: yes;"> </span>Unfortunately, it’s not obvious there is
enough demand for these kinds of products for everyone to find profit making them (although my ability to come up with examples of these products is limited to my own capabilities - others who can identify new kinds of products can profit greatly). But there is enough
demand for many to find a good living at such pursuits. Starting now is a great
way to try and find a niche before nearly everyone is trying to do the same
thing. </div>
<h2>
<b style="mso-bidi-font-weight: normal;"><span style="font-size: large;">Step 2: Make
Ownership Less Important</span></b></h2>
<div class="MsoNormal">
Secondly, we must stop treating owners as more important
than doers. A man who owns a business deserves no more credit for the success
of that business than those who work in it. He deserves some – providing
capital to the business is usually essential to its success – but ascribing
most of the benefits of success to an individual simply because they put in
money instead of time overemphasizes the role of capital in achieving success.
Further, because benefits of success accrue to owners rather than doers, the
problem of capital consolidation grows worse when we use ownership to allocate benefits,
because owners gain even more capital to benefit from over time. “The rich
become richer.”<o:p></o:p></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
However, it’s also not the case that Marxian distribution of
the benefits of success to doers is correct. Communism is not the answer to
this problem because communism runs counter to human nature at a macro scale.
Both owners and doers deserve a share of benefits. But it’s hard to know how to
distribute benefits effectively.<o:p></o:p></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
It’s important to allocate benefits to those whose actions
contributed to success, but to do so one must measure their contributions. Just
as capital spent is not a good metric for assigning benefits, time spent to
create is also not a good metric. Nor are metrics which measure volume of
output, such as units made or lines of code written. Any such metrics can be
gamed and organizing the distribution of benefits based on them will only
result in activity that optimizes those metrics at the expense of greater
success.<o:p></o:p></div>
<div class="MsoNormal">
<br />
Without an obvious way to measure contribution to success, it's best that the profits of success be distributed in a manner agreeable to everyone involved in making success happen. Success comes from a combination of capital and labor that is different for every business, so it seems best for each business to decide how to allocate profits among owners and employees on their own as part of a profit sharing program.<br />
<br /></div>
<div class="MsoNormal">
Today, we already have examples of companies who practice
profit sharing. In these models, some of the total return of the company is
distributed to those who generated that return. Employee ownership models offer
similar incentives, as do typical sales or money management jobs where a
commission is paid. The key component in these kinds of businesses is that the
compensation due to everyone involved <i style="mso-bidi-font-style: normal;">scales
with the success</i>. Everyone involved earns a percentage, rather than a fixed
sum.<o:p></o:p></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
However, most jobs are not like this, and many people – not
to mention entities like lending organizations – are uncomfortable with jobs
whose compensation has little to no floor. And in many of these jobs, the
profits shared are a relative pittance compared to the total profit. For
example, an employer who shared 5% of profits with employees would be
exceptionally generous.<o:p></o:p></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
I am not sure how to cause macro changes to our economic
system in this vein, but I can see ways for individuals to align themselves
more in that direction. The step you can take today is to try and find jobs
which include some percentage-based share of profits to their employees. The
higher the percentage, the better, even if the actual numbers are less than a
different job you could get.<o:p></o:p></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
Further, try and encourage your employer to increase profit
sharing. It’s still the case that most employers need their employees to do
their work today, so leverage that need to gain for yourself while you still can. Try to get profit sharing as a permanent component of your employment contract, and encourage your
co-workers to do the same. If you can, organize – unions have always been the
friend of the worker (how capital holders have managed to convince workers to
hate unions is a tragic coup for another discussion).<o:p></o:p></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
The key is to distribute the benefits of ownership away from
actual owners and into more hands. If possession of capital remains the primary
determinant of how wealth is accrued, capital will continue to concentrate into
fewer and fewer hands because the ability to leverage capital becomes nearly
infinite post-singularity. Even if you are a millionaire today earning 7 or 8
figures at your job, be aware that the 10 figure owner of your company will be
happy to replace you with software as soon as possible.</div>
<h2>
<b style="mso-bidi-font-weight: normal;"><span style="font-size: large;">Possible Bonus Step 3: Other
Transformational Technology*</span></b></h2>
<div class="MsoNormal">
There is a possible third way to resolve the problem of
economic inequality post-singularity. Whether through the means in which the singularity
is achieved or simply through technological advances on other fronts, new
technology could disrupt the current economic paradigm in such a way that
capital concentration is no longer a problem. Sufficient benefits for every human
being might be available no matter how the benefits of success are ascribed.<o:p></o:p></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
For the benefits of success not to be ascribed based on
capital invested or work performed, benefits must be distributed based on some
basis orthogonal to the success itself. This may seem to imply the creation of
some sort of magical charity state, where people invest lots of capital and do
lots of work for no reason, but there is an incorrect assumption in that
implication which provides a different answer: that the supply of benefits is
finite.<o:p></o:p></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
It’s not the case that everyone in the world can have a
mansion, 68’ yacht, and steak dinners every night. But it is the case that
everyone in the world can have a comfortable house large enough for their
family, access to wonderful recreation, and enough good food to eat. With the
reduction of the need for human labor to achieve goals through the software
revolution, enough value can be created without significant capital or labor
investment to provide significant benefits to every human on the planet as long
as so many benefits are available that they cannot accrue in the hands of a few
kings.<o:p></o:p></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
One way to achieve this is simple to state and hard to achieve:
the software revolution must be for all. It must be embodied by freely available,
open-source software, with contributions from the greatest minds available (at
least, until the greatest minds are themselves open-source software). Today,
it’s the case that these minds are generally employed by would-be kings –
Google, Amazon, Facebook, Microsoft, even places like Stanford and MIT. But
there is no reason that this must be so, and no reason that must remain so once
momentum is built towards a different way. If fantastic productivity is
available via free, ubiquitous software, there is no reason every single human
cannot live what one would call a comfortable upper-middle-class life because
all their needs are met by free software and machines. Some may even still live
extraordinarily comfortable upper-class lives, but that does not mean others
must suffer for it or that the extraordinarily comfortable need oppose this
development (for if one has a wonderful life, what does it matter if another
has more?).<o:p></o:p></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
Another possible development is significant advances in
energy, food, and other forms of production such that the availability of the
resources needed for a comfortable life is practically infinite. Even if there
are kings, if there is so much available that they could not possibly possess
it all, then it doesn’t matter if they possess arbitrarily large amounts. And
over time, if possessing more does not matter, the drive some feel to acquire
more and more may subside – if owning things and acquiring more wealth has
little to no bearing on how you live your life, why own more?<o:p></o:p></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
This essentially attacks the problem of ownership and greed
on the supply side, instead of the demand side.<o:p></o:p></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
An example of such a change could be practical fusion
energy. In theory, fusion power could provide orders of magnitude more
electrical energy than produced by all the world today, and primarily consume
water as its power source. Energy costs would go so low as to approach zero,
and suddenly wealth would not be required to obtain nearly any amount of
energy. Were this to be true, power could be treated as a basic human right,
enabling many to improve their lives significantly – even if other people still
have more than them.<o:p></o:p></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
An analogy can be drawn right out of Adam Smith’s original
thinking on capitalism. For him, it was important that people engaging in capitalism
not take ownership of so much as to leave others unable to survive and
participate economically. Suppose there were an island with 10 people on it,
and the primary food source on that island were banana trees producing 1000
bananas a day. A person needs to eat 10 bananas a day to survive, and perhaps
another 10 to have some surplus to feel comfortable.<o:p></o:p></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
Under Smith’s vision for capitalism, it’s OK for 1 person to
own a banana harvesting business and gain 820 bananas a day, with the
other 9 as his employees earning 20 bananas each. It might even be OK for the 1
owner to gain 910 bananas and leave the other 9 only 10 each – they can still
survive, so it’s an ethical question whether it’s acceptable for the owner to
deprive the other 9 a feeling of comfort because he owns the business. But it’s
not acceptable to go any farther than that.<o:p></o:p></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
But what if the supply of bananas were infinite? Well, then
the 1 owner can take as many bananas as he likes, because the 9 employees can
still get their 20. In fact, the owner can let the employees take as many
bananas as they like, because it doesn’t prevent him from having as many
bananas as he likes. It’s even possible the owner will stop even caring or
noticing that he owns the banana harvesting business, and it will become a
mundane property of just living on the island, same as having air to breathe
and a sun in the sky.<o:p></o:p></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
Because it requires a either the singularity to be achieved
in a specific way or significant technological breakthroughs on other fronts, it’s
not a given that a solution like this will present itself, so one should not
bank on this over the first two steps. But it’s a good low-probability
get-out-of-jail-free card, and if you happen to be someone in a position to
push in these kinds of directions, doing so would be a great service to
humanity. </div>
<h2>
<b style="mso-bidi-font-weight: normal;"><span style="font-size: large;">Summary</span></b></h2>
<div class="MsoNormal">
So what was that all about? Well, briefly:</div>
<div class="MsoNormal">
</div>
<ul>
<li><span style="text-indent: -0.25in;">Most people today get money by being paid for
their time at a job</span></li>
<li><span style="text-indent: -0.25in;">Organizations (like the DMV) are made of people,
who resist the elimination of jobs</span></li>
<li><span style="text-indent: -0.25in;">Nonetheless, eventually software will eliminate
all jobs</span></li>
<li><span style="text-indent: -0.25in;">Significant social change is necessary to truly
prepare for a world without jobs</span></li>
<li><span style="text-indent: -0.25in;">Whether or not significant change will happen,
one can personally prepare for a world without jobs by</span></li>
<ul>
<li><span style="text-indent: -0.25in;">Finding ways to earn money besides selling one’s
time</span></li>
<li><span style="text-indent: -0.25in;">Finding jobs that include significant profit
sharing that scales with profits</span></li>
</ul>
<li><span style="text-indent: -0.25in;">There is a chance that through either being
purposeful about making the singularity work for all or by dramatically
improving production on other fronts that people will end up living comfortable
lives despite the problems the current trajectory to the singularity imply</span></li>
</ul>
<br />
<div class="MsoNormal">
Hopefully this post gives you some things to think about in
how you live your life. For me, these realizations have caused me to become a
lot more entrepreneurial and look for multiple passive income streams I can
implement in my life. After all, the alternative is to wait around until
software eats me, and I would prefer to be immortal and comfortable because of
the singularity rather than chewed up by it.<o:p></o:p></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<br /></div>
<div class="MsoNormal">
<br /></div>
<!--[if gte mso 9]><xml>
<o:OfficeDocumentSettings>
<o:AllowPNG/>
</o:OfficeDocumentSettings>
</xml><![endif]-->
<!--[if gte mso 9]><xml>
<w:WordDocument>
<w:View>Normal</w:View>
<w:Zoom>0</w:Zoom>
<w:TrackMoves/>
<w:TrackFormatting/>
<w:PunctuationKerning/>
<w:ValidateAgainstSchemas/>
<w:SaveIfXMLInvalid>false</w:SaveIfXMLInvalid>
<w:IgnoreMixedContent>false</w:IgnoreMixedContent>
<w:AlwaysShowPlaceholderText>false</w:AlwaysShowPlaceholderText>
<w:DoNotPromoteQF/>
<w:LidThemeOther>EN-US</w:LidThemeOther>
<w:LidThemeAsian>JA</w:LidThemeAsian>
<w:LidThemeComplexScript>X-NONE</w:LidThemeComplexScript>
<w:Compatibility>
<w:BreakWrappedTables/>
<w:SnapToGridInCell/>
<w:WrapTextWithPunct/>
<w:UseAsianBreakRules/>
<w:DontGrowAutofit/>
<w:SplitPgBreakAndParaMark/>
<w:EnableOpenTypeKerning/>
<w:DontFlipMirrorIndents/>
<w:OverrideTableStyleHps/>
<w:UseFELayout/>
</w:Compatibility>
<m:mathPr>
<m:mathFont m:val="Cambria Math"/>
<m:brkBin m:val="before"/>
<m:brkBinSub m:val="--"/>
<m:smallFrac m:val="off"/>
<m:dispDef/>
<m:lMargin m:val="0"/>
<m:rMargin m:val="0"/>
<m:defJc m:val="centerGroup"/>
<m:wrapIndent m:val="1440"/>
<m:intLim m:val="subSup"/>
<m:naryLim m:val="undOvr"/>
</m:mathPr></w:WordDocument>
</xml><![endif]--><!--[if gte mso 9]><xml>
<w:LatentStyles DefLockedState="false" DefUnhideWhenUsed="true"
DefSemiHidden="true" DefQFormat="false" DefPriority="99"
LatentStyleCount="276">
<w:LsdException Locked="false" Priority="0" SemiHidden="false"
UnhideWhenUsed="false" QFormat="true" Name="Normal"/>
<w:LsdException Locked="false" Priority="9" SemiHidden="false"
UnhideWhenUsed="false" QFormat="true" Name="heading 1"/>
<w:LsdException Locked="false" Priority="9" QFormat="true" Name="heading 2"/>
<w:LsdException Locked="false" Priority="9" QFormat="true" Name="heading 3"/>
<w:LsdException Locked="false" Priority="9" QFormat="true" Name="heading 4"/>
<w:LsdException Locked="false" Priority="9" QFormat="true" Name="heading 5"/>
<w:LsdException Locked="false" Priority="9" QFormat="true" Name="heading 6"/>
<w:LsdException Locked="false" Priority="9" QFormat="true" Name="heading 7"/>
<w:LsdException Locked="false" Priority="9" QFormat="true" Name="heading 8"/>
<w:LsdException Locked="false" Priority="9" QFormat="true" Name="heading 9"/>
<w:LsdException Locked="false" Priority="39" Name="toc 1"/>
<w:LsdException Locked="false" Priority="39" Name="toc 2"/>
<w:LsdException Locked="false" Priority="39" Name="toc 3"/>
<w:LsdException Locked="false" Priority="39" Name="toc 4"/>
<w:LsdException Locked="false" Priority="39" Name="toc 5"/>
<w:LsdException Locked="false" Priority="39" Name="toc 6"/>
<w:LsdException Locked="false" Priority="39" Name="toc 7"/>
<w:LsdException Locked="false" Priority="39" Name="toc 8"/>
<w:LsdException Locked="false" Priority="39" Name="toc 9"/>
<w:LsdException Locked="false" Priority="35" QFormat="true" Name="caption"/>
<w:LsdException Locked="false" Priority="10" SemiHidden="false"
UnhideWhenUsed="false" QFormat="true" Name="Title"/>
<w:LsdException Locked="false" Priority="1" Name="Default Paragraph Font"/>
<w:LsdException Locked="false" Priority="11" SemiHidden="false"
UnhideWhenUsed="false" QFormat="true" Name="Subtitle"/>
<w:LsdException Locked="false" Priority="22" SemiHidden="false"
UnhideWhenUsed="false" QFormat="true" Name="Strong"/>
<w:LsdException Locked="false" Priority="20" SemiHidden="false"
UnhideWhenUsed="false" QFormat="true" Name="Emphasis"/>
<w:LsdException Locked="false" Priority="59" SemiHidden="false"
UnhideWhenUsed="false" Name="Table Grid"/>
<w:LsdException Locked="false" UnhideWhenUsed="false" Name="Placeholder Text"/>
<w:LsdException Locked="false" Priority="1" SemiHidden="false"
UnhideWhenUsed="false" QFormat="true" Name="No Spacing"/>
<w:LsdException Locked="false" Priority="60" SemiHidden="false"
UnhideWhenUsed="false" Name="Light Shading"/>
<w:LsdException Locked="false" Priority="61" SemiHidden="false"
UnhideWhenUsed="false" Name="Light List"/>
<w:LsdException Locked="false" Priority="62" SemiHidden="false"
UnhideWhenUsed="false" Name="Light Grid"/>
<w:LsdException Locked="false" Priority="63" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Shading 1"/>
<w:LsdException Locked="false" Priority="64" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Shading 2"/>
<w:LsdException Locked="false" Priority="65" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium List 1"/>
<w:LsdException Locked="false" Priority="66" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium List 2"/>
<w:LsdException Locked="false" Priority="67" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 1"/>
<w:LsdException Locked="false" Priority="68" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 2"/>
<w:LsdException Locked="false" Priority="69" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 3"/>
<w:LsdException Locked="false" Priority="70" SemiHidden="false"
UnhideWhenUsed="false" Name="Dark List"/>
<w:LsdException Locked="false" Priority="71" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful Shading"/>
<w:LsdException Locked="false" Priority="72" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful List"/>
<w:LsdException Locked="false" Priority="73" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful Grid"/>
<w:LsdException Locked="false" Priority="60" SemiHidden="false"
UnhideWhenUsed="false" Name="Light Shading Accent 1"/>
<w:LsdException Locked="false" Priority="61" SemiHidden="false"
UnhideWhenUsed="false" Name="Light List Accent 1"/>
<w:LsdException Locked="false" Priority="62" SemiHidden="false"
UnhideWhenUsed="false" Name="Light Grid Accent 1"/>
<w:LsdException Locked="false" Priority="63" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Shading 1 Accent 1"/>
<w:LsdException Locked="false" Priority="64" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Shading 2 Accent 1"/>
<w:LsdException Locked="false" Priority="65" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium List 1 Accent 1"/>
<w:LsdException Locked="false" UnhideWhenUsed="false" Name="Revision"/>
<w:LsdException Locked="false" Priority="34" SemiHidden="false"
UnhideWhenUsed="false" QFormat="true" Name="List Paragraph"/>
<w:LsdException Locked="false" Priority="29" SemiHidden="false"
UnhideWhenUsed="false" QFormat="true" Name="Quote"/>
<w:LsdException Locked="false" Priority="30" SemiHidden="false"
UnhideWhenUsed="false" QFormat="true" Name="Intense Quote"/>
<w:LsdException Locked="false" Priority="66" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium List 2 Accent 1"/>
<w:LsdException Locked="false" Priority="67" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 1 Accent 1"/>
<w:LsdException Locked="false" Priority="68" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 2 Accent 1"/>
<w:LsdException Locked="false" Priority="69" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 3 Accent 1"/>
<w:LsdException Locked="false" Priority="70" SemiHidden="false"
UnhideWhenUsed="false" Name="Dark List Accent 1"/>
<w:LsdException Locked="false" Priority="71" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful Shading Accent 1"/>
<w:LsdException Locked="false" Priority="72" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful List Accent 1"/>
<w:LsdException Locked="false" Priority="73" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful Grid Accent 1"/>
<w:LsdException Locked="false" Priority="60" SemiHidden="false"
UnhideWhenUsed="false" Name="Light Shading Accent 2"/>
<w:LsdException Locked="false" Priority="61" SemiHidden="false"
UnhideWhenUsed="false" Name="Light List Accent 2"/>
<w:LsdException Locked="false" Priority="62" SemiHidden="false"
UnhideWhenUsed="false" Name="Light Grid Accent 2"/>
<w:LsdException Locked="false" Priority="63" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Shading 1 Accent 2"/>
<w:LsdException Locked="false" Priority="64" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Shading 2 Accent 2"/>
<w:LsdException Locked="false" Priority="65" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium List 1 Accent 2"/>
<w:LsdException Locked="false" Priority="66" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium List 2 Accent 2"/>
<w:LsdException Locked="false" Priority="67" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 1 Accent 2"/>
<w:LsdException Locked="false" Priority="68" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 2 Accent 2"/>
<w:LsdException Locked="false" Priority="69" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 3 Accent 2"/>
<w:LsdException Locked="false" Priority="70" SemiHidden="false"
UnhideWhenUsed="false" Name="Dark List Accent 2"/>
<w:LsdException Locked="false" Priority="71" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful Shading Accent 2"/>
<w:LsdException Locked="false" Priority="72" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful List Accent 2"/>
<w:LsdException Locked="false" Priority="73" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful Grid Accent 2"/>
<w:LsdException Locked="false" Priority="60" SemiHidden="false"
UnhideWhenUsed="false" Name="Light Shading Accent 3"/>
<w:LsdException Locked="false" Priority="61" SemiHidden="false"
UnhideWhenUsed="false" Name="Light List Accent 3"/>
<w:LsdException Locked="false" Priority="62" SemiHidden="false"
UnhideWhenUsed="false" Name="Light Grid Accent 3"/>
<w:LsdException Locked="false" Priority="63" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Shading 1 Accent 3"/>
<w:LsdException Locked="false" Priority="64" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Shading 2 Accent 3"/>
<w:LsdException Locked="false" Priority="65" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium List 1 Accent 3"/>
<w:LsdException Locked="false" Priority="66" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium List 2 Accent 3"/>
<w:LsdException Locked="false" Priority="67" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 1 Accent 3"/>
<w:LsdException Locked="false" Priority="68" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 2 Accent 3"/>
<w:LsdException Locked="false" Priority="69" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 3 Accent 3"/>
<w:LsdException Locked="false" Priority="70" SemiHidden="false"
UnhideWhenUsed="false" Name="Dark List Accent 3"/>
<w:LsdException Locked="false" Priority="71" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful Shading Accent 3"/>
<w:LsdException Locked="false" Priority="72" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful List Accent 3"/>
<w:LsdException Locked="false" Priority="73" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful Grid Accent 3"/>
<w:LsdException Locked="false" Priority="60" SemiHidden="false"
UnhideWhenUsed="false" Name="Light Shading Accent 4"/>
<w:LsdException Locked="false" Priority="61" SemiHidden="false"
UnhideWhenUsed="false" Name="Light List Accent 4"/>
<w:LsdException Locked="false" Priority="62" SemiHidden="false"
UnhideWhenUsed="false" Name="Light Grid Accent 4"/>
<w:LsdException Locked="false" Priority="63" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Shading 1 Accent 4"/>
<w:LsdException Locked="false" Priority="64" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Shading 2 Accent 4"/>
<w:LsdException Locked="false" Priority="65" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium List 1 Accent 4"/>
<w:LsdException Locked="false" Priority="66" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium List 2 Accent 4"/>
<w:LsdException Locked="false" Priority="67" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 1 Accent 4"/>
<w:LsdException Locked="false" Priority="68" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 2 Accent 4"/>
<w:LsdException Locked="false" Priority="69" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 3 Accent 4"/>
<w:LsdException Locked="false" Priority="70" SemiHidden="false"
UnhideWhenUsed="false" Name="Dark List Accent 4"/>
<w:LsdException Locked="false" Priority="71" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful Shading Accent 4"/>
<w:LsdException Locked="false" Priority="72" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful List Accent 4"/>
<w:LsdException Locked="false" Priority="73" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful Grid Accent 4"/>
<w:LsdException Locked="false" Priority="60" SemiHidden="false"
UnhideWhenUsed="false" Name="Light Shading Accent 5"/>
<w:LsdException Locked="false" Priority="61" SemiHidden="false"
UnhideWhenUsed="false" Name="Light List Accent 5"/>
<w:LsdException Locked="false" Priority="62" SemiHidden="false"
UnhideWhenUsed="false" Name="Light Grid Accent 5"/>
<w:LsdException Locked="false" Priority="63" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Shading 1 Accent 5"/>
<w:LsdException Locked="false" Priority="64" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Shading 2 Accent 5"/>
<w:LsdException Locked="false" Priority="65" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium List 1 Accent 5"/>
<w:LsdException Locked="false" Priority="66" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium List 2 Accent 5"/>
<w:LsdException Locked="false" Priority="67" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 1 Accent 5"/>
<w:LsdException Locked="false" Priority="68" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 2 Accent 5"/>
<w:LsdException Locked="false" Priority="69" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 3 Accent 5"/>
<w:LsdException Locked="false" Priority="70" SemiHidden="false"
UnhideWhenUsed="false" Name="Dark List Accent 5"/>
<w:LsdException Locked="false" Priority="71" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful Shading Accent 5"/>
<w:LsdException Locked="false" Priority="72" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful List Accent 5"/>
<w:LsdException Locked="false" Priority="73" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful Grid Accent 5"/>
<w:LsdException Locked="false" Priority="60" SemiHidden="false"
UnhideWhenUsed="false" Name="Light Shading Accent 6"/>
<w:LsdException Locked="false" Priority="61" SemiHidden="false"
UnhideWhenUsed="false" Name="Light List Accent 6"/>
<w:LsdException Locked="false" Priority="62" SemiHidden="false"
UnhideWhenUsed="false" Name="Light Grid Accent 6"/>
<w:LsdException Locked="false" Priority="63" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Shading 1 Accent 6"/>
<w:LsdException Locked="false" Priority="64" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Shading 2 Accent 6"/>
<w:LsdException Locked="false" Priority="65" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium List 1 Accent 6"/>
<w:LsdException Locked="false" Priority="66" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium List 2 Accent 6"/>
<w:LsdException Locked="false" Priority="67" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 1 Accent 6"/>
<w:LsdException Locked="false" Priority="68" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 2 Accent 6"/>
<w:LsdException Locked="false" Priority="69" SemiHidden="false"
UnhideWhenUsed="false" Name="Medium Grid 3 Accent 6"/>
<w:LsdException Locked="false" Priority="70" SemiHidden="false"
UnhideWhenUsed="false" Name="Dark List Accent 6"/>
<w:LsdException Locked="false" Priority="71" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful Shading Accent 6"/>
<w:LsdException Locked="false" Priority="72" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful List Accent 6"/>
<w:LsdException Locked="false" Priority="73" SemiHidden="false"
UnhideWhenUsed="false" Name="Colorful Grid Accent 6"/>
<w:LsdException Locked="false" Priority="19" SemiHidden="false"
UnhideWhenUsed="false" QFormat="true" Name="Subtle Emphasis"/>
<w:LsdException Locked="false" Priority="21" SemiHidden="false"
UnhideWhenUsed="false" QFormat="true" Name="Intense Emphasis"/>
<w:LsdException Locked="false" Priority="31" SemiHidden="false"
UnhideWhenUsed="false" QFormat="true" Name="Subtle Reference"/>
<w:LsdException Locked="false" Priority="32" SemiHidden="false"
UnhideWhenUsed="false" QFormat="true" Name="Intense Reference"/>
<w:LsdException Locked="false" Priority="33" SemiHidden="false"
UnhideWhenUsed="false" QFormat="true" Name="Book Title"/>
<w:LsdException Locked="false" Priority="37" Name="Bibliography"/>
<w:LsdException Locked="false" Priority="39" QFormat="true" Name="TOC Heading"/>
</w:LatentStyles>
</xml><![endif]-->
<!--[if gte mso 10]>
<style>
/* Style Definitions */
table.MsoNormalTable
{mso-style-name:"Table Normal";
mso-tstyle-rowband-size:0;
mso-tstyle-colband-size:0;
mso-style-noshow:yes;
mso-style-priority:99;
mso-style-parent:"";
mso-padding-alt:0in 5.4pt 0in 5.4pt;
mso-para-margin:0in;
mso-para-margin-bottom:.0001pt;
mso-pagination:widow-orphan;
font-size:12.0pt;
font-family:Cambria;
mso-ascii-font-family:Cambria;
mso-ascii-theme-font:minor-latin;
mso-hansi-font-family:Cambria;
mso-hansi-theme-font:minor-latin;}
</style>
<![endif]-->
<!--StartFragment-->
<!--EndFragment--><br />
<div class="MsoNormal">
* - much credit for the step 3 section goes to Ryan Flynn, who
first told me about his thoughts around fusion and infinite energy and inspired me to
think about addressing the capital concentration problem from the supply side.<o:p></o:p></div>
Shawnhttp://www.blogger.com/profile/06311618271709855605noreply@blogger.com0tag:blogger.com,1999:blog-2034578472218454150.post-22597362366403117332008-07-06T18:05:00.000-07:002008-07-06T23:25:16.854-07:00The Singularity and MeI'm trying to write about whatever I'm currently thinking about on this blog, but with the holiday, I've been mostly thinking about how relaxing it is to have some vacation. And, this Wednesday, I leave for San Francisco to visit Sanna's family (she's my girlfriend) and some friends. So, I want to make a post before I go, so that you don't think I've given up on this whole blog thing. Rather than talk about hanging out on the fourth, or politics or libertarianism or something else that's just gonna get me fired up and ruin the end of the weekend, I'm going to talk about what might be the most important thing in the world to me, outside of people: the singularity.<br /><br /><a href="http://en.wikipedia.org/wiki/Technological_singularity">The singularity</a> is the name given to a broad collection of theories concerning the future development of technology and refers to the idea of a critical mass of technology beyond which lies an explosion in human intelligence and technological capabilities. The term was coined about 25 years ago by scientist/science fiction author Vernon Vinge to describe a startling trend in computer science: more and more, computers were performing basic tasks in place of humans, including circuit design and compiling executable code. Humans had to know and do less basic tasks as computers became able to do them. So, Vinge asked, what if this trend continues until all human thought is basic enough that computers can be made to do it?<br /><br />Before I get too deep here, I'd also like to point my influences in this area for context. I first encountered the singularity reading <a href="http://en.wikipedia.org/wiki/Ray_Kurzweil">Ray Kurzweil</a>'s <a href="http://www.amazon.com/Age-Spiritual-Machines-Computers-Intelligence/dp/0140282025">The Age of Spiritual Machines</a> in college. He's probably the most optimistic singulatarian, and while I think his projected timeline may be a bit ambitious, he does serve as a deep inspiration to me. I also had the fortune to study under <a href="http://en.wikipedia.org/wiki/Marvin_Minsky">Marvin Minsky</a> while in graduate school at the Media Lab, including taking his class on cognition and computation (for which I received an A+ :)). From a technical and philosophical standpoint, I identify closely with him, and feel his work on cognition and AI is the most significant relative to the singularity. I highly recommend his books <a href="http://www.amazon.com/Society-Mind-Marvin-Minsky/dp/0671657135">The Society of Mind</a> and <a href="http://www.amazon.com/Emotion-Machine-Commonsense-Artificial-Intelligence/dp/B000WPPYGS/ref=pd_bxgy_b_text_b">The Emotion Machine</a> for a lay (but rigorous) examination of consciousness, its origins, and how one might go about implementing a system to possess it. I'll also note that, in poor form and against Marvin's recommendations, I'm going to use the term consciousness because it's easy. Really, it's a dangerously overloaded term and shouldn't be used in scientific context. Just know that when I refer to consciousness, I'm speaking exactly to cognition and personality, not being awake, or anything religious or classical psychologists mean.<br /><br />There are many possible answers to the question of the extent to which computers can replicate or replace human thought, and of course you have to accept it's premise is valid to get started. If you believe in some sort of soul or other mystical force that makes humans somehow totally unique and outside the physical basis of the universe, you probably disagree with most singulatarians, and many of the things I'll say on this blog. But, if only to better understand your enemy, you can follow my thinking by knowing the two postulates about humans and cognition to which I subscribe:<br /><br />(1) The brain is a finite system subject to the same physical laws as all other matter in the universe<br />(2) Everything that composes what we think of as a person's character or consciousness or whatever you want to call it arises solely from the brain<br /><br />(NOTE- I'm going to use the word "brain" a lot without loss of generality. It may be that other parts of the central nervous system or body matter for consciousness, but we don't know for sure yet. In the end, adding a few more body parts to these postulates does not affect the validity of the argument. So, I'm going to keep it simple and just say brain.)<br /><br />Postulate 2 implies there is no soul or animating force beyond biology. That may not sit well with you, especially if you're religious/spiritual/whatever, but I think it only increases my wonderment at existence. It's too easy to just invent all these mystical, infinite, unknowable things like spirits and grand designs and gods to explain things. Such simplifications detract from the stunning processes that actually govern the universe in verifiable manners. But I'm not here to convert you to atheism or defend it. I'm here to explain the singularity, which doesn't even need to imply anything religious in some interpretations. I'm just trying to show you where I'm coming from so you can understand my thinking.<br /><br />So, from those postulates, we can begin making some projections about how far computers can go in helping humans perform tasks. If the brain is finite, we can model it. And if the sum of a person's consciousness is their brain, then we can model a person.<br /><br />If you're reading this, you already use technology to do a lot of basic tasks for you. You're accessing my words without having to go pick up a letter at the post office, or if we're even more primitive, walking to my apartment to listen to me talk. Language itself is a form of technology, one that took 4.5 billion years less a few tens of thousands of years to evolve on Earth with modern linguistic characteristics.<br /><br />You probably also don't do much arithmetic anymore, using calculators and spreadsheets to do math. You probably don't write by hand as much either, instead typing everything on a computer. All of these things are examples of technology we have created to replace basic, repetitive work we didn't want to do.<br /><br />So, then, why should we stop applying technology more and more to help us? Are we going to wake up someday and decide we have enough convenience, enough tools to help us improve out life? I don't think so. Are we going to run into some barrier or insurmountable problem we'll never be able to solve? Maybe, but I think it's unlikely. Humans have shown an incredible ability to think our way past seemingly insurmountable hurdles. So if we're at least going to try and continue to improve life with technology, what would that look like?<br /><br />Here's the basic plot for the singularity: through a combination of hardware capabilities, software implementation, and further understanding of the biological and chemical basis for human intelligence, we are able to create a computer program which is as smart as a human. That's the fundamental characteristic of all singularity theories. How this happens and what else it enables is a vast field of speculation that forms a lot of the talk about the singularity now.<br /><br />There are lots of ways we might get there. It could be on purpose, through groups like the <a href="http://singinst.org/">Singularity Institute</a> who are expressly dedicated to doing it. It could happen so gradually we don't even notice it, as people more and more begin incorporating technology into their lives and even bodies (you can already get highly-effective artificial <a href="http://www.nidcd.nih.gov/health/hearing/coch.asp">cochlear implants</a> implanted in your brain if you are deaf). Or it could be an unguided machine like <a href="http://www.googleguide.com/google_works.html">Google's web crawler</a> developing so many connections and having so much information that intelligent behavior spontaneously arises. No one knows. Not everyone even believes it's possible. But, if we accept that the brain is a finite system, there is a strong possibility we can model it and emulate the intelligence of a human.<br /><br />The implications of doing so are too many to address in a blog, but I'll note some. First, a computer as smart as a human will inevitably become smarter than a human, because it will be able to program itself as well as any computer scientist could. This is the concept of <a href="http://en.wikipedia.org/wiki/Seed_AI">Seed AI</a>, which shows how rapidly intelligence will grow once we reach that basic level.<br /><br />Second is the idea of <a href="http://en.wikipedia.org/wiki/Mind_transfer">uploading </a>and virtual immortality. If we can completely model a human brain in a computer, and we can scan a biological human brain well enough to input it into this model, then we can load a copy of an individual human into a computer. You can imagine this as effectively a prosthetic brain. As you age and your biological brain's physical medium begins to break down, you can replace it with a more stable technological medium, much as you might replace a lost limb or lost sense of hearing today. A radical idea, but one I accept as possible and the ultimate goal of the singularity.<br /><br />There are all sorts of moral implications to uploading. Do you still have the same rights as a biological human brain? Are you the same person? To help answer them, let me summarize an arugment by Kurzweil.<br /><br />Suppose you were in an accident and lost your hearing. You get cochlear implants in your nervous system to restore it. You're still the same person, even though you have some technology wired into your brain, right? Then suppose in you lose your vision and replace that with a set of cameras wired into your brain. Still the same person, right? 15 years later, you begin developing Alzheimer's, and get a memory prosthesis implanted in your brain. Now your memories are stored on a chip. But they're still <span style="font-style: italic;">your</span> memories, and you're still the same person. Then, you get a math processor implanted in your brain to help you do basic calculations. Still the same person, except you can use the calculator in your brain without having to tell your fingers to push buttons, right? This continues, until biology accounts for very little or none of your actual brain. Are you still the same person? I'd say yes, but if you say no, then tell me, when did you stop being you? And if you have a soul that somehow prevents that technology from actually being you, when did your soul leave?<br /><br />Tough questions to answer, especially if you're coming from a religious or anti-singularity point of view. Personally, I accept the simple solution that you are still the same person, and should be afforded all rights given to purely biological people. But, I'm sure that won't stop outcry from various religious or conservative humanist groups. I wouldn't even be surprised to see war or terrorism about it. But fundamentally, I think there is no difference between biological or technological people, and I don't doubt that we will have both in the future.<br /><br />Another question about the singularity is when will it happen. Estimates vary wildly, from Kurweil, who thinks less than 30 years, to others who think centuries or millennia from now, or even never. And of course all of this supposes we are mature enough as a species not to kill our selves off on the way there. This post is long enough, so I won't get into details, but I'll mention that Kurzweil makes compelling arguments related to the strong exponential trend in technological advances, even going as far as showing how technology is really just an extension of evolution. <a href="http://en.wikipedia.org/wiki/Moore%27s_law">Moore's Law</a> is an illustration of this exponential advance in computing power, and <a href="http://markii.wordpress.com/2008/02/08/kurzweils-singularity-time-line/">Kurzweil's full timeline</a> demonstrates how it dovetails nicely with the evolution of the universe. Personally, I think that the singularity will occur in my lifetime, and likely in no more than 30-50 years (I wouldn't be surprised if medical advances would extend my life expectancy to 100 years or more independent of the singularity. Potentially much more than 100 years).<br /><br />I could go on about the singularity a lot more, from any number of technical and philosophical tangents, to what I'm actually working on to try to help. Ask me sometime about it if you like. I'll also probably write more posts about various aspects of it in the future. But I've summarized it here, at least as I see it, and it is very important to me. It's not the Matrix or science fiction, but a legitimate area of research involving hundreds or thousands of well-respected scientists. It's not a religion, and I don't need any faith to accept it, but it might be as important to me as religion is to other people. It's what got me interested in AI, set me on the path to a lifetime of learning about AI and cognition, and gives me hope for the future of the human race.<a href="http://en.wikipedia.org/wiki/Seed_AI"><br /></a><br />For more information on the singularity, I recommend Wikipedia surfing from the <a href="http://en.wikipedia.org/wiki/Technological_singularity">singularity entry</a>, and the <a href="http://www.spectrum.ieee.org/singularity">IEEE site for the singularity</a>.Shawnhttp://www.blogger.com/profile/06311618271709855605noreply@blogger.com2tag:blogger.com,1999:blog-2034578472218454150.post-87589470346831538522008-06-28T11:53:00.000-07:002008-06-28T12:53:28.664-07:00Quantum mechanics cures my fear of flyingMaybe 3 or 4 years ago, I started developing a fear of flying. I never had a problem before then, but for some reason I started getting scared, especially when there's <span class="blsp-spelling-corrected" id="SPELLING_ERROR_0">turbulence</span>. My mother says it's because I became an atheist, but I don't buy that, because I've been a closet atheist for a while, well before my fear of flying. I know that flying is extremely safe, safer than driving, but that doesn't comfort me. I think my fear comes from the fact that if there is a crash, I have about a 0% chance of survival. At least in a car crash, I have a shot at survival. On a plane, there is nothing I can do. You just go down, and that's it.<br /><br />But I have to fly, because it's the only practical way to travel long distances. I don't believe in any supernatural protectors, so I can't pray for safety or anything. So I need a way to get over my fear. It helps to have a couple drinks before getting on the plane, and sometimes that's enough, but usually, I get too in my head about it. It's too easy to imagine, when the plane hits a little <span class="blsp-spelling-corrected" id="SPELLING_ERROR_1">turbulence</span>, it just going down and not stopping. I know it's irrational, and I know that airplanes are incredibly well-engineered, designed to handle stresses well beyond those actually experienced during flight.<br /><br />So, when I really need to console myself, I turn to an idea that comes from quantum mechanics (and pushes into philosophy a bit): <a href="http://en.wikipedia.org/wiki/Anthropic_principle">the anthropic principle</a>. It's a <span class="blsp-spelling-corrected" id="SPELLING_ERROR_2">controversial</span> idea that has several variations and different interpretations, but I'm mainly concerned with comforting myself on a plane, not fundamental scientific and philosophical issues.<br /><br />Basically, the anthropic principle states that humans (or some observer) are the forcing factor that causes the universe to exist. In quantum mechanics, all possible outcomes of any situation coexist simultaneously, until something observes them and forces a single one to be chosen, according to a probability distribution. <a href="http://en.wikipedia.org/wiki/Schrodinger%27s_cat"><span class="blsp-spelling-error" id="SPELLING_ERROR_3">Schrodinger's</span> cat </a>is the classic macro analogy. The anthropic principle applies this theory on a universal scale (a source of controversy), and claims that the universe must exist in a state that allows something to observe it. Any possible universes which do not support some sort of observer within that universe cannot be observed, and therefore do not exist.<br /><br />It's sort of like the proverbial tree falling in the forest, except I don't like Zen. Zen embraces contradiction and illogicality, which is great if it works for you, but all it does for me is piss me off. If a universe big bangs into existence and no one sees it, does it exist? The anthropic principle says no.<br /><br />So, if no one is around to observe the universe, it doesn't exist. How does this help me on airplanes?<br /><br />Well, I take another idea from philosophy to complete the picture. A fundamental question since ancient Greece has been "how do I know anything exists." It's an impossible question, one that requires some sort of assumption or leap of faith at some point (such as <a href="http://en.wikipedia.org/wiki/Ren%C3%A9_Descartes">Descartes' </a>famous "<a href="http://en.wikipedia.org/wiki/Cogito_ergo_sum"><span class="blsp-spelling-error" id="SPELLING_ERROR_4">cogito</span> ergo sum</a>"). But at the end, I have no idea what <em>truly</em> exists. I don't <em>know</em> whether everything I observe, including other people, is real, or a figment of my imagination (I disagree with <a href="http://en.wikipedia.org/wiki/Existentialism">existentialism</a> here... I'll buy that existence is fundamental for me, but can't see that it therefore must be so for everything else I observe). As far as I can tell, other people very well may not be real. I certainly have no way of proving that they are not.<br /><br />So, I can suppose that I am the only real person in the universe. I am at least by far the most provably existing person in the universe. Under the anthropic principle, therefore, the universe exists because <em>I</em> am here to <span class="blsp-spelling-corrected" id="SPELLING_ERROR_5">observe</span> it. Not humanity in general, but me specifically, because I have no idea whether or not anyone else really exists. If I don't exist, neither does the universe, because I can't observe the universe.<br /><br />Thus, if the plane goes down and crashes and I die, I will no longer be here to observe the universe, and it will not exist anymore. Poof! Gone. That would be quite an <span class="blsp-spelling-corrected" id="SPELLING_ERROR_6">abrupt</span> end to the universe. I comfort myself thinking how unlikely and catastrophic that would be. It would be a shame for all the wonderful complexities and amazing processes of the universe to just halt all of the sudden. I comfort myself knowing all this, and it gets me through flights.<br /><br />It may sound conceited or vain or something, but from a purely scientific standpoint, factoring in what information I can truly <em>know</em> (that I exist), it is 100% correct (given that you accept the theories outlined above). I don't go around acting like I'm the center of the universe or anything. I just know in the back of my mind, that whenever I think I might die, that would mean the end of the universe (at least to me) because I won't be around to observe it anymore. I use that to help me not feel so scared, because <span class="blsp-spelling-error" id="SPELLING_ERROR_7">the</span> end of the universe is a big deal, big enough that I can convince myself I will be OK.<br /><br />That's why I need to live an arbitrarily long time. To keep the universe going. That's where the <a href="http://en.wikipedia.org/wiki/Technological_singularity">singularity </a>comes in, but that's another post.Shawnhttp://www.blogger.com/profile/06311618271709855605noreply@blogger.com2tag:blogger.com,1999:blog-2034578472218454150.post-60977564988996954032008-06-23T18:59:00.001-07:002008-06-23T21:09:22.314-07:00Traffic, game theory, and efficient marketsOne of the perks of working for Microsoft and living in Seattle is getting to sit in traffic for a couple hours a day (I'm working on something greener, honest). So, I have a lot of time to think. Often, my thoughts turn to why exactly there is so much traffic. (There is a lot of scholarly work on traffic, and you can write code to model different things, but I'm speaking from a more theoretical perspective).<br /><br />I take State Route 520 to and from work. There are no traffic lights, so on the surface, I thought traffic couldn't get too bad. I don't see much reason why the ratio of total trip time to the number of cars on the road shouldn't remain fairly constant or at least scale gracefully. But, it does not. At some point, there is enough traffic that you spend most of the time stopped, and getting home takes an hour plus, instead of 15 minutes.<br /><br />So, there must be other factors affecting traffic patterns besides the road itself. There are two important other factors: surrounding road topology, and people. Traffic is worst coming home (Westbound), and it's bad from about 4-7 every day. That's what I'm going to look at here.<br /><br />520 runs through Redmond, to a bridge across Lake Washington, and ends at I-5 in Seattle. During rush hour, there's traffic along the whole way. The strange thing is, it's not uniform. Not even close. It tends to be wide open until you hit the I-405 intersection, and then be solid all the way to the lake, where it opens up until it ends at I-5. The area of interest is <a href="http://maps.live.com/default.aspx?v=2&FORM=LMLTCC&cp=47.634569~-122.199383&style=r&lvl=13&tilt=-90&dir=0&alt=-1000&scene=3730080&phx=0&phy=0&phscl=1&encType=1">this map</a>.<br /><br />In terms of topology, the road is two normal westbound lanes, with a carpool lane on the right. The carpool lane ends right before the bridge across Lake Washington, and two lanes go west across the bridge. There are 3 entrances to 520 that are near the traffic: I-405, 108<span class="blsp-spelling-error" id="SPELLING_ERROR_0">th</span> Ave, and 84<span class="blsp-spelling-error" id="SPELLING_ERROR_1">th</span> Ave (see map above). You can get on or off 520 there, and some people use them as shortcuts to skip 520 traffic.<br /><br />People getting on at these shortcuts cause a large delay due to merging. At each intersection, you are effectively merging another lane or two of cars into 520's two lanes. On top of that, merging occurs through the carpool lane, slowing it greatly. Merging forms the primary source of delay because it is essentially a funnel for cars. In total, with the 3 entrances, and additional 5 lanes (plus the carpool lane) of cars have to be merged into 520's 2 lanes to go across the bridge.<br /><br />That got me thinking, <strong>why doesn't everyone just not take shortcuts</strong>? I am almost positive the average time to get across 520 would be greatly reduced.<br /><br />The answer comes from game theory. Unfortunately, this is a classic example of the <a href="http://en.wikipedia.org/wiki/Prisoners">Prisoner's Dilemma</a>. Suppose that I did convince everyone not to take the shortcuts for a day. Then, one unscrupulous (or logical) person could bypass all the remaining traffic by taking a shortcut. From a game <span class="blsp-spelling-corrected" id="SPELLING_ERROR_2">theoretical</span> perspective, that person is doing the correct action if his goal is to maximize his own happiness (a fundamental tenet of economies and societies... true selflessness is so rare as to almost always have no impact on their courses). Game theory and the Prisoner's Dilemma make it clear why there will always be people trying to take these shortcuts to skip 520 traffic: everyone wants to maximize his or her own personal utility. In this particular case, this <a href="http://en.wikipedia.org/wiki/Greedy_algorithm">greedy algorithm</a> creates a global suboptimal solution relative to the better solution of no shortcuts, as measured by average trip time. It is extremely unlikely that this will change without topological changes to the road system.<br /><br />Once I arrived at this conclusion in late 2007, I was satisfied in my analysis of the patterns and decided to just sit in the traffic in the left lane to minimize my impact and involvement in negative traffic behaviors. Then, about a month ago, I was in a rush and had to run an errand near one of the shortcut entrances. So, I tried a shortcut for the first time. I discovered it took just as long as simply sitting in the traffic.<br /><br />This seemed strange to me. I mean, I knew that game theory projected there would always be people taking the shortcuts, and that at <span class="blsp-spelling-corrected" id="SPELLING_ERROR_3">equilibrium</span> all the routes would take around the same time, but it got me thinking about the decision process behind those people who choose to take the shortcuts, especially those who did it all the time. What did they think they were getting, and why are they choosing a particular route?<br /><br />This led me to the efficient market hypothesis. Sure, there are psychological factors to it related specifically to driving, like preferring moving along a longer route vs. sitting still on a shorter one, but I saw another parallel to economics.<br /><br />The (controversial) <a href="http://en.wikipedia.org/wiki/Efficient_market_hypothesis">efficient market hypothesis</a> (<span class="blsp-spelling-error" id="SPELLING_ERROR_4">EMH</span>) says that at all times, the prices of objects in the market (stocks, bonds, commodities, etc.) reflect an accurate value incorporating the sum of all public information about that object. These fair market prices arise naturally out of buying and selling those objects on the open market, and are kept in check globally and across all markets by <a href="http://en.wikipedia.org/wiki/Arbitrage">arbitrage</a>.<br /><br />For example, suppose there were 100 tons of gold that we knew about and had mined from the earth, and that gold was $1000 an ounce. Then, suppose I get lucky and find a 2 ton vein in my back yard. The <span class="blsp-spelling-error" id="SPELLING_ERROR_5">EMH</span> says that, as soon as my find is public knowledge, and given that the demand for gold is fixed, that the value of an amount of golf will drop 1.96% to make an ounce of gold worth $980.39. Arbitrageurs make sure that prices of gold across the planet, in all currencies, are the same by exploiting small differences for profit until the difference disappears.<br /><br />So, what does this mean to traffic? It's more of a leap to <span class="blsp-spelling-error" id="SPELLING_ERROR_6">EMH</span> than Prisoners Dilemma, but <span class="blsp-spelling-error" id="SPELLING_ERROR_7">EMH</span> can be applied to traffic in some ways, only with time instead of money as the "gold".<br /><br />There are 4 ways to get onto the bridge on 520: sitting in traffic, or taking one of three shortcuts. All of these routes are public knowledge, and everyone who does this commute knows about them. Everyone can also look up traffic data on the Internet, providing an approximation of how long it will take to get to the bridge. So, the <span class="blsp-spelling-error" id="SPELLING_ERROR_8">EMH</span> s says all routes should take about the same amount of time. If any particular route did let one "beat the traffic," more and more people would take it as the information became public, until it no longer beat the traffic.<br /><br />In practice, the times on all the shortcuts are fairly close. But, the differences in the times highlight some of the problems with applying the <span class="blsp-spelling-error" id="SPELLING_ERROR_9">EMH</span> to traffic (and the market in general, in my opinion). First, the <span class="blsp-spelling-error" id="SPELLING_ERROR_10">EMH</span> depends on the market having <a href="http://en.wikipedia.org/wiki/Perfect_information">perfect information</a>. Inaccurate, incomplete traffic data, people who don't know about the shortcuts, and other factors cause the information in this system to be imperfect. Second, once you're in your car, by and large you won't get any more information (unless you have something like GPS or Internet phone that can get it for you). Finally, you can't change routes at will. In the market, you can buy or sell almost anything at any time (if the market is open). In traffic, you only have a few chances to change, namely by finding some intersection between one of the 4 paths and changing routes. There are only a handful of times in your journey home you can make this decision. The application of EMH therefore isn't entirely correct, but it still provides some insight.<br /><br />So, there is a small amount of <span class="blsp-spelling-corrected" id="SPELLING_ERROR_11">inefficiency</span> in the traffic system. There's a chance that you could get home faster by taking one route over the others. This chance is what people on shortcuts are chasing. Sometimes they make it, sometimes they don't. But, they are always acting as a sort of arbitrageur (except they, unlike a good arbitrageur, <em>can</em> lose). They are providing stability to the system by decreasing the impact of random events (like accidents), and decrease the variance of my trip time. For that, I decided, I am thankful. I'd rather spend an hour in traffic everyday, that 3 hours every once in a while.<br /><br />The moral of the story: as long as there are shortcuts, people will take them, even if they don't help (which they shouldn't in the aggregate). And while you're yelling at them for skipping traffic in front of you, remember that they aren't getting there any faster in the long run, but they are helping you get there more consistently.<br /><br />A better moral: take the bus. You'll get to spend time thinking about things other than traffic.Shawnhttp://www.blogger.com/profile/06311618271709855605noreply@blogger.com1tag:blogger.com,1999:blog-2034578472218454150.post-40296471059012337442008-06-21T18:58:00.000-07:002008-06-21T20:42:58.056-07:00The impetus for all this...So, now that I've told you what this blog is, here's why I decided "yes, today is the day I join the <span class="blsp-spelling-error" id="SPELLING_ERROR_0">blogosphere</span>:" I just finished writing an email in response to one a relative sent that basically tried to say the Democrats made oil $130+ a barrel and gas $4+ a gallon by not letting us drill our land. I don't very much like Democrats, Republicans, or politicians in general, but I can't abide unproductive, unwarranted blaming of all our problems on any single <span class="blsp-spelling-corrected" id="SPELLING_ERROR_1">villain</span>. After reading an article on the great <a href="http://seekingalpha.com/">http://seekingalpha.com/</a>, I was inspired enough to write my response, which I thought was good enough I wanted to make it public in case some day someone else might read it and start thinking more rationally.<br /><br />Preface: I am convinced by the <a href="http://en.wikipedia.org/wiki/Image:Instrumental_Temperature_Record.png">evidence </a>of <a href="http://en.wikipedia.org/wiki/Global_warming">global warming</a> (there is so much out there... do a <a href="http://scholar.google.com/scholar?q=global+warming&hl=en&lr=">Google scholar search </a>if you don't like <span class="blsp-spelling-error" id="SPELLING_ERROR_2">Wikipedia</span> and aren't convinced), and do think we need to start reducing our impact on the environment. However, I also recognize the need to keep our society moving, which includes having a plan to get all this great energy that brings these words to you. That puts me in a tough position if I want to remain logically consistent with myself. Below, I try to do so.<br /><br />This is long enough an outline will help. By paragraphs:<br /><ol><li><a href="http://seereason.blogspot.com/2008/06/impetus-for-all-this.html#1"><span class="blsp-spelling-error" id="SPELLING_ERROR_3">Shoutout</span> to the <span class="blsp-spelling-error" id="SPELLING_ERROR_4">SeekingAlpha</span> article</a></li><li><a href="http://seereason.blogspot.com/2008/06/impetus-for-all-this.html#2">Money, power, and oil, and political accountability</a></li><li><a href="http://seereason.blogspot.com/2008/06/impetus-for-all-this.html#3">It's easier to blame people for our problems than fix them; oil is a political tool</a></li><li><a href="http://seereason.blogspot.com/2008/06/impetus-for-all-this.html#4">Problems with oil the US can't control</a></li><li><a href="http://seereason.blogspot.com/2008/06/impetus-for-all-this.html#5">Economies are cyclic and fighting that is dangerous; why I like recessions</a></li><li><a href="http://seereason.blogspot.com/2008/06/impetus-for-all-this.html#6">There is no simple solution to oil; chaos theory and the economy</a></li><li><a href="http://seereason.blogspot.com/2008/06/impetus-for-all-this.html#7"><span class="blsp-spelling-error" id="SPELLING_ERROR_5">Subprime</span> crisis as an example of why you can't regulate your way to economic bliss in a chaotic system</a></li><li><a href="http://seereason.blogspot.com/2008/06/impetus-for-all-this.html#8">Conclusion: I'm a libertarian</a></li></ol><br />Here is my email (plus a few more cites for those of you more critical of quality of thinking than my family):<br /><br /><a name="#1"></a><span style="font-family:arial;">I found a great article about this topic on an investment site I read: </span><a href="http://seekingalpha.com/article/82127-oil-prices-and-political-energy?source=yahoo" target="_blank"><span style="font-family:arial;">http://seekingalpha.com/article/82127-oil-prices-and-political-energy?source=yahoo</span></a><span style="font-family:arial;">. It says some of the exact things I wanted to say in response to this email in a way I couldn't put together. It also helped me get some of my own thoughts down.<br /><br /><a name="#2"></a>It's not Democrats or Republicans maliciously trying to run up oil prices or being ignorant... it's about money and power, as usual. Oil producers and companies have made a lot of money on oil. They use this money to buy government influence and make more money. Politicians in turn use the oil crisis as a political football to get votes. Unfortunately, unlike other election-year hot topics like abortion or gay marriage, oil and energy policy has an extraordinary ability to do significant damage to American and global society. It's a shame that our leaders get away with inaction in this important area 3 out of every 4 years.<br /><br /><a name="#3"></a>But it's a lot easier to yell and scream and blame people about a problem then do the hard work it takes to fix it. Current leaders from <a href="http://en.wikipedia.org/wiki/An_Inconvenient_Truth#Media">Al Gore </a>to <a href="http://www.cnn.com/2008/POLITICS/06/18/bush.offshore/index.html?iref=newssearch">George W. Bush </a>are all guilty of trying to blame instead of fix to some extent. To fix this, we need a combination of reduced consumption, increasing energy supply (whether by alternative energy or expanded domestic oil production or both), creating sensible, practical regulations, and knowing that almost everything coming out of Washington, especially in an election year, is a smokescreen. Politicians survive by manipulating emotions, not being logical and solving problems. Emotions (and money) are how they get reelected.<br /><br /><a name="#4"></a>So much in the oil game is out of our control... <a href="http://www.reuters.com/article/reutersEdge/idUSBNG12910820080604?sp=true">foreign subsidies</a>, <a href="http://en.wikipedia.org/wiki/Opec">cartel action</a>, <a href="http://online.barrons.com/article/SB120293863029666285.html?mod=djemBF"><span class="blsp-spelling-error" id="SPELLING_ERROR_6">overextension</span> of the dollar internationally</a>, <a href="http://money.cnn.com/2008/06/10/news/international/iea_forecast.ap/index.htm">global demand </a>, even <a href="http://www.bloggingstocks.com/2008/01/17/study-says-new-oil-field-production-offsetting-existing-declines/">how much oil gets sucked out of the ground</a>... I don't have enough fingers to point menacingly at "those people" who made this happen. No one person or group put $4 on the gas pump (or $4.38 if you're in Seattle like me :( ).<br /><br /><a name="#5"></a>Economies are cyclic; sometimes they grow, sometimes they shrink. The real problem is trying to make them grow when it's just not meant to be (like Greenspan's dubious <a href="http://mutualfunds.about.com/library/weekly/aa100201a.htm">market-must-grow rate cuts</a>). The economy wants to go down a little bit frequently, but if we don't let it, then we get these infrequent huge drops. "Recession" is not a bad word; it's a good thing, because it keeps prices rational, and when everyone panics and prices get too low, "recession"="clearance sale." It may seem callous now while the economy is falling down and people are worried, but I feel lucky to have the opportunity to get into the market when it is so low. Long term, this recession will help anyone who remains calm and realizes they can profit by looking for undervalued investments. The real danger is depression... we get there by blindly assuming the economy will keep going up and up and up until we all live in gold palaces, and then trying to force it to happen. Don't fight economic tides; surf them.<br /><br /><a name="#6"></a>Democrats and Republicans have exaggerated their positions on oil and are just saying the same things over and over until you think they're true. It's not guaranteed that more drilling will cause vast environmental damage, or that more drilling will bring gas prices down. The environment and the economy are too complex to jump to such conclusions. These types of things have an enormous number of variables; you can't just change one or two and fix everything. If we'd been drilling in <a href="http://en.wikipedia.org/wiki/ANWR"><span class="blsp-spelling-error" id="SPELLING_ERROR_7">ANWR</span></a> for the last 30 years and oil was that much cheaper ever since, do you think we'd have the same demand for oil we do today? Do you think that without the oil problem, everything in the economy would be great forever? These are </span><a href="http://en.wikipedia.org/wiki/Chaos_theory" target="_blank"><span style="font-family:arial;">chaotic systems</span></a><span style="font-family:arial;">, like the butterfly that flaps its wings in China and makes a hurricane in Florida. Governing them with inflexible, top-down rules, no matter how well-intentioned and well thought out, will never be as effective as allowing a market-derived solution.<br /><br /><a name="#7"></a>Another example of how hard it is to govern a chaotic system is the <a href="http://en.wikipedia.org/wiki/Subprime_Crisis"><span class="blsp-spelling-error" id="SPELLING_ERROR_8">subprime</span> mortgage collapse</a>. It was enabled by <a href="https://research.stlouisfed.org/publications/review/06/01/ChomPennCross.pdf">a series of laws </a>in the 80's (<a href="http://en.wikipedia.org/wiki/Depository_Institutions_Deregulation_and_Monetary_Control_Act"><span class="blsp-spelling-error" id="SPELLING_ERROR_9">DIDMCA</span></a>, <a href="http://www.wimba.org/displaycommon.cfm?an=1&subarticlenbr=16">Alternative Mortgage Transaction Parity Act</a>, and <a href="http://en.wikipedia.org/wiki/Tax_Reform_Act_of_1986#Tax_incentives"><span class="blsp-spelling-error" id="SPELLING_ERROR_10">TRA</span> of 1986</a>) designed to encourage home ownership across society. These laws combined with macroeconomic trends to create a shiny veneer on otherwise dangerous debt practices, and when <a href="http://en.wikipedia.org/wiki/Dot_com_bubble#Aftermath">macroeconomic growth slowed after the .com bubble</a> (<a href="http://en.wikipedia.org/wiki/Image:Change_in_US_household_wealth_1946-2007.gif">chart</a>), the rickety credit structure imploded. If regulations enforced basic good practices, like making a <a href="http://en.wikipedia.org/wiki/Mortgage_loan#Loan_to_value_and_downpayments">reasonable down payment</a>, <a href="http://www.sfgate.com/cgi-bin/article.cgi?f=/chronicle/archive/2005/07/31/REGIVDVN461.DTL">not lying about income level</a>, and <a href="http://en.wikipedia.org/wiki/Negative_amortization">actually paying off the loan</a>, instead of enabling mortgage interest tax deductions, usurious interest rates, and preposterous loan structures, we might not be in this mess because the market would have imposed the reasonable loan practices it had for decades. (But might is the key word - it's not the case we could say whether or not doing anything different would have prevented the crisis. There are so many other variables and other things that can go wrong just by, say, never having mortgage interest deductions you really can't say).<br /><br /><a name="#8"></a>The problem is our leaders haven't done a good job. We need better government. But to some extent, it's not their fault that they can't do a job which very well may be impossible. In lieu of a brilliant, benevolent leader who can make everything OK, I prefer to follow a quote variously attributed to <a href="http://en.wikipedia.org/wiki/Thomas_paine">Thomas Paine</a>, <a href="http://en.wikipedia.org/wiki/Thomas_jefferson">Thomas Jefferson</a>, or <a href="http://en.wikipedia.org/wiki/Ralph_Waldo_Emerson">Ralph Waldo Emerson </a>(all of whom I respect immensely): "That government is best which governs least."</span>Shawnhttp://www.blogger.com/profile/06311618271709855605noreply@blogger.com0tag:blogger.com,1999:blog-2034578472218454150.post-2130335461892347702008-06-21T18:42:00.000-07:002008-06-21T20:22:20.235-07:00ANOTHER BLOG? WHY!!!!!I'm not much for blogging as of now... I read a few (<a href="http://withleather.com/">http://withleather.com/</a>, <a href="http://filmdrunk.com/">http://filmdrunk.com/</a>, <a href="http://wwtdd.com/">http://wwtdd.com/</a>, <a href="http://consumerist.com/">http://consumerist.com/</a>), but that's about it. So, why am I doing this? Well, mostly as a way of talking to myself. I like to organize my thinking by writing, so why not let other people read my thoughts if they like?<br /><br />This blog will therefore be about whatever I'm thinking about. I tend to view the world through science and reason, and that is my fundamental approach to doing pretty much everything, for better or worse. If you want to disagree with me and convince me of something, you'd best approach me with reason.<br /><br />Science-y topics to expect include artificial intelligence, cognitive science, computer science, economics, and mathematics. Outside those, I'll probably be talking about my relationships, job, life, books, movies, sports, my fantasy football team, and anything else I feel like. It is my blog after all. If you don't like it, piss off.<br /><br />About me:<br />I'm 25, living in Seattle and working for Microsoft as a Program Manager. I went to MIT for undergrad in Computer Science and grad school at the Media Lab. I was born in Southern California and raised in Birmingham, Alabama. I'm a libertarian and an atheist. Don't hate me for any of this; I'm also a person trying to live and be happy and help those around me as best I can, especially my girlfriend and our dog, William. And, my 10th grade English teacher Mrs. Bice said I was a natural writer. We'll see.Shawnhttp://www.blogger.com/profile/06311618271709855605noreply@blogger.com1