If there was a theme to my week in browsing the internet, it would be arguments over ontology warping people’s thinking. I think it’s a legitimate subject for discourse, I guess, but the more I see it lead people astray the less useful it seems. Somehow intelligent, thoughtful people seem to think crazy things when they start worrying about what is “really real”, especially regarding morality. This is not a new debate of course, but it was reignited by the publication of Sam Harris’ book The Moral Landscape, which argued that morals are “true” in some sense and could be determined scientifically. On the off-chance I haven’t posted this before, I was sympathetic to this argument before I discovered a PhD thesis from Joshua Greene entitled The Terrible, Horrible, No Good, Very Bad Truth about Morality and What to Do About it. Here’s a link to all 250+ pages of it (worth reading at least some of it), but you might just want to read this shorter article. The basic idea is quite simple: morality is a property of minds, not the natural world, and therefore is not “true” in some universal way. That doesn’t mean you should go out and kill your neighbor or rob a bank, but even if it did, the facts about morality would be the same. There is the Truth about morality, and, separately, What to Do About it. That’s the most frustrating objection I’ve heard to moral anti-realism, so I thought I’d get it out of the way before continuing.
This weeks troubles started with a post on Cosmic Variance about another moral realist, and why he was wrong. Good on Sean for setting the record straight, but I was surprised to see the moral realist he was arguing with was none other than Richard Carrier, who so spectacularly and elegantly defined naturalism as “no ontologically basic mental entities”. Naturalism is perhaps a discussion for another post, but I think I may have brought it up before. If not, here’s the link. If he was advocating moral realism, perhaps I should at least consider his view. After reading his argument, I was surprised by the subtle missteps in reasoning he made. I suspect it is due mainly to Carrier’s desire to recover what he sees as “beneficial” aspects of Christian doctrine such as an absolute moral force, as well as goodness, kindness, and other things I really would call unmitigated goods.
Carrier manages to agree with me on almost every philosophical fact, and yet calls his view realism, whereas I call myself an anti-realist. Situations such as these suggest that at least one of us is failing to make our beliefs pay rent in anticipated experience. I think Carrier’s desire to find a naturalistic source for the good bits of Christianity gives him the motive, but luckily I don’t have to speculate on exactly where he went wrong, since he provides an explicit discussion of his reasoning in his post on moral ontology. He uses a number of examples in his post, but I think the first is sufficient to explain his logic:
Take, for instance, the scariness of an enraged bear: a bear is scary to a person (because of the horrible harm it can do) but not scary to Superman, even though it’s the very same bear, and thus none of its intrinsic properties have changed. Thus the bear’s scariness is relative, but still real. It is not a product of anyone’s opinions, it is not a cultural construct, but a physical fact about bears and people. Thus the scariness of an enraged bear is not a property of the bear alone but a property of the entire bear-person system.
Certainly you cannot observe bear-scariness under a microscope or pick it up with a radio antenna, but, he claims, it’s not solely a mental phenomenon. Therefore, assuming we aren’t superman, we ought to believe bears are scary. Given this definition of ought, its only a few (completely valid) philosophical jumps to oughts for values. Given that we have certain goals, goals like happiness and fulfillment that are common to almost all intelligent agents, there are certain instrumental values we ought to have, like the rule of law, free expression, etc. Thus, he concludes, as there are values grounded in real life that we should hold, regardless of any other rational belief, morality is real. I don’t deeply disagree with this, although I feel it’s slightly misleading based on what moral realists usually believe.
But, as I said, I think the real problem comes when you try to use these beliefs about morality to constrain your expectations of the world. Although this is absolutely essential to the pursuit of rationalism, I think Carrier can be forgiven for not including it in his article since he usefully covered so much philosophical ground. I will also save this for my next post, but in case you’re reading this before I’ve posted it, ask yourself this; if a highly intelligent (and therefore not irrationally amoral) alien/robot suddenly came to our planet, what “morals” would you expect it to have by Carrier’s definition, assuming you have no previous information about its beliefs and goals?
A lot of my idle thinking relates to computers, what exactly they are in the broadest meaningful sense, and how they relate to the intelligent processes in our brains. Although I’m heading generally toward becoming an economist at the moment, computer science is a hobby and possible secondary specialty of mine. So I read this article in Scientific American with interest. The first paragraph summarizes it pretty well:
What kind of discipline is computer science? I thought it was a science when I received my BS. I believed its subdiscipline software engineering was engineering when I received my PhD. I’d heard, and would continue to hear, “This isn’t any kind of science/engineering I know!” from physicists and electrical engineers. I tried for years to prove them wrong. But now I think they’re right.
Essentially the author thinks computer science belongs in the realm of philosophy, and is not very amenable to normal scientific inquiry. I’ve thought quite a bit about this sort of claim, but more in the context of economics. Although I haven’t quite formulated my argument for why economics is a science, I’m pretty sure of how I feel about the subject. While its calm tone may help (by avoiding my metacontrarian reflex), the Scientific American article was more thought-provoking than what I’m used to reading, and I’m less certain of my feelings on its conclusion.
The core of the argument is computer scientists’ inability to formulate predictive hypotheses about the world, and the notion that computers somehow inhabit an abstract “virtual” reality divorced from our own. While it’s hard for me to really grasp the concepts involved here, I think both claims are most likely false. The first makes me think of the way Stephen Wolfram approaches the idea of computation in his February 2010 TED talk. He was also quoted saying something similar in the July 2008 edition of Philosophy of Computing and Information:
4. What do you consider the most neglected topics and/or contributions in late 20th century studies of computation and/or information?
Computer and information science have tended to define themselves in a rather engineering-based way–concentrating on creating and studying systems that perform particular specified tasks.
But there’s a whole different approach that’s much closer to natural science: to just investigate the computational universe of possible programs, and see what’s out there.
One might have thought that most programs that one would encounter this way would not do anything very interesting. But the discovery that launched what I’ve done for the past quarter century is that that’s not the case. Even remarkably simple programs–that one would quickly encounter in sampling programs from the computational universe–can show immensely rich and complex behavior.
There’s a whole new kind of science that can be done by studying those programs.
The idea that computation is something we can sample just like a vernal pool ecosystem or a statistical representation of demographics is fascinating, and I can’t see anything wrong with it on face. I must admit to being attracted to the idea of mapping concepts into spaces (eg “mind design space“, or the original concept of “phase space“), so I might be a bit biased, but if Wolfram is correct then Computer Science really is a naturalistic science in some ways, even more so than mathematics or logic.
Of course the idea that computation space can be sampled suggests that computation really is a property of the universe, which gets into the second main claim made in Steve Wartik’s article, that computing is more like philosophy; necessarily separate from the everyday world we inhabit. This is a way complicated topic, far too complicated for me to address with my limited knowledge of the field, but I’ll try to say a little about how I feel and delve deeper into it another time.
Although my grasp of computation theory is tenuous at best, here’s my understanding of the situation: in the late 1930’s, many mathematicians and logicians were scrambling in the wake of Gödel’s Incompleteness Theorems. While those still tie my head in knots, I understand that they did more than just destroyed once and for all the idea that mathematics (or any system) can be provably complete and consistent; they advanced our understanding of the limits of formal systems in general, and in doing so gave mathematicians more direction in their studies of such system. Around this time, Alonzo Church, Alan Turing, and two other mathematicians/logicians were working on systems to define functions and the methods of calculating them. Church’s was called lambda calculus, Turing’s the Turing machine, and a third developed by JB Rosser and Stephen Kleene was known as recursion functions. In 1939, Rosser claimed that the 3 systems were equivalent; all were different representations of the same underlying set of rules. This lead to the concept of a universal Turing machine, which would theoretically be able to run any calculation that any other programmable computer could run. This is the Thesis, that in some way all (turing-complete) computers are equivalent systems. This, again, points to computation being some deep and underlying property of the universe.
But where the whole line of inquiry gets really interesting is in the so called “strong” version of the Church-Turing thesis; that the universe itself is Turing computable. While this has not been formally proven, the fact that all known laws of physics have effects that are computable by approximation on a digital computer is evidence for it, and for the corresponding interpretation of physics as “digital“. This is a rich vein of interesting stuff I would like to explore further, but suffice to say if the strong version of the Church-Turing thesis were true, it would mean that the universe is a property of computation, instead of the other way around, and thus the study of computation is one of the most valid pursuits of the ultimate truth of reality. It could be simulated on the most powerful computer imaginable, on my laptop, or even on a billiard ball computer given enough time, memory, and energy, and it would make no difference. This gets into highly metaphysical territory very quickly, and lends some credence to Stephen Landsburg’s claims about the reality of mathematical objects. All of my explanations gloss over so much for the sake of some semblance of brevity, even without considering how little I know about the computation theory. But if the universe really is a giant computer, I think it’s safe to say that the study of the process behind that computer is as scientific a discipline as any.
A lot of what we call “fun” seems to be based on fairly simple principles. Ok, so there’s still a fair bit of complexity there. But after I read this interview with AI designer Jurgen Schmidhuber and watched his excellent presentation at this year’s singularity summit I’ve started to view a surprising number of things I do through a different lens. There’s all sorts of deep and strange ideas in that interview, but the one that stuck with me the longest is the notion that much of what we consider deeply and fundamentally human is reducible to our brains rewarding us for gathering and efficiently compressing information.
I’ve been aware for a while that many video games I play, particularly RPGs, are little more than cheap hacks of the dopamine system my brain has evolved to encourage me to do things. It’s just gambling without the high monetary cost, or cigarettes without the lung cancer.
But Schmidhuber is making an even more bizarre claim, and making it in a very compelling way.Essentialy, he’s saying that many of our drives are based simply on gathering and compressing information. Compression here means something a little different from what your computer does when it compresses a .zip or .rar file, but its the same basic idea; removing unnecessary information to make a given thing fit in a smaller box. Computers do it by finding redundant sequences of bits and representing them in more efficient ways, and humans do it by making connections and forming “understanding”. There’s a diverse array of examples of this discussed in the interview. Music is appealing to us because we can recognize novel patterns that are somewhat, but not too familiar to us, and music that is either too formulaic or too discordant is unappealing. Art is interesting because we can find compressible visual or cultural themes. Dancing is much the same as music; repetitive yet novel sequences that initially seem bizarre and random but show deep patterns. We laugh at jokes because we make interesting and surprising connections between various semantic pieces. The list goes on, and Schmidhuber makes the case for the truth of this better than I can so if you don’t understand, go check out that video. You can find exceptions and complications that culture and emotions have introduced to all of these things, but it really is remarkable how often that basic principle of novel compression shows up.
Schmidhubers theory has interesting implications for what it means to be the complex biological robots we call homo sapiens. What is the first objection people raise when the question of machines being “conscious” or “intelligent” comes up? It’s usually something along the lines of “Well they might be fancy calculators, but they’ll never [be creative, appreciate beauty, laugh at our jokes, etc]”. There’s all sorts of things wrong with that argument, which I’ll probably have to write a separate post on sometime. Suffice to say even if you believe those things are deeply weird and complicated, you have no reason to doubt a sufficiently powerful and well programmed computer would be able to do them (unless you believe the brain runs on magic). If, however, many of those precious deeply complex human characteristics are really fairly simple processes, what does it imply about us? As sympathetic as I am to the notion that we are just complicated computers of one type or another, I was somewhat skeptical at first. But ever since I read through that interview, I’m noticing more and more often how true it is.
I’ll leave this as an exercise to the reader; now that you’ve been exposed to this idea, start looking at your daily activities through the lens of information compression. I think you’ll be surprised at how often it fits. Not so high and mighty now eh Mr deeply mysterious human?