Sunday, July 31, 2005

searchin' for our friend, homo economicus

I must have seen a zillion draft versions of this study floating around online, but here's a terrific preprint: “Economic man” in cross-cultural perspective: Behavioral experiments in 15 small-scale societies (Henrich, Boyd, Bowles, Camerer, Fehr, Gintis, McElreath, Alvard, Barr, Ensminger, Henrich, Hill, Gil-White, Gurven, Marlowe, Patton, and Tracer 2005 (!)). So looks like we're now pretty sure, culture affects cooperation, you can see it in social practices. It's a really neat study. The writeup in this version is terrific, they talk about implications for culture-gene evolution and have great statistical analysis of cultural factors on ultimatum game performance.

balkanized USA

From the same site, this is fun.

war death statistics

What a project -- an impressively painstaking compilation of 20th century civilian and military casualties. Summary: lots of people were killed. Interesting are the comments on morality and how prejudgement leads to differing casualty estimations -- estimates vary wildly for controversial regimes, like Castro's Cuba (I've heard lots about), but are suspiciously round and agreed-upon for incidents that scholars seem to care less about, like the Congo Crisis of the 1960's (I've heard not so much about.)

Sunday, July 10, 2005

guns, germs, & steel pbs show?!

Looks like it's become a mini-series: Jared Diamond's Guns, Germs, and Steel has hit PBS! Great book, if repetitive and a little too ambitious -- he has a great environmental/technology explanation of the differences in societal development between Europe and the Americas, but he's pretty weak when trying to tackle Asia vs. Europe, or a number of other situations talked about near the end of the book. But anyway, it's fantastic social science.

Wish I had a TV around... it would be nice if the show made it onto the web. For some time, I remember hearing that all of Commanding Heights was available for free on the web, but it looks like they've taken it down. We shall see.

Saturday, July 09, 2005

the psychology of design as explanation

Since I posted the link to his blog, Baron just wrote about Cardinal Schönborn's anti-evolution Op-Ed piece. I agree absolutely that people should learn about the psychology of judgment and probability for these sorts of questions, where it's really hard to understand that random processes can generate things that seem not so random.

I'm still thinking about how the psychology of judgment plays in to the analysis below. I have a feeling that people's intuitions are usually too hospitable for explanations based on intention. E.g.: People are poor, therefore someone is trying to make them poor. Organizations (corportations, governments) do things, therefore someone (say, at the top) ordered them to do these things. Natural disasters happen, therefore someone is wishing them upon us. Etc., etc. I'm still not sure how a bayesian dissection of whether "looks intentful" implies "is intentful" shows us whether such an "intent-seeking" bias (hey, I have to call it something) is correct or erroneous. Hopefully more to come.

Also: there was an older posting by Tabarrok on MR arguing that theism makes ID quite reasonable, and atheism makes evolution quite reasonable. This would be the effect of the dominance of the P(H) prior, I believe.

another blog: cog psych and political/social stuff

By cognitive psychologist Jon Baron

When is it time to stop accruing links to yet more blogs? Blogging makes no sense whatsoever.

a bayesian analysis of intelligent design

UPDATE: just wrote a revision of this.

Pick an organism. Two propositions, H and E, each may be either true or false about it.

H: the organism was designed by an intelligent creator.
E: the organism looks like it was designed by an intelligent creator.

Most of what I know about ID is from seeing a talk by Michael Behe (may 2005). He had to major lines of argument: (1) it is implausible that an evolutionary process could produce life that looks as if it was intelligently designed. (2) Since it looks like it was intelligently designed, it was. He really emphasized the E component of the argument.

Justifications for E: Lots of organisms look like they were intelligently designed. They have complex and intricate mechanisms involving coordination among many components. Sometimes they look like things humans would design: for example, bacteria locomotion devices sometimes bear uncanny resemblance to human-designed motors or propellers.

Behe was really into showing all these quotes from pro-evolution authors like Dawkins who note this fact: many forms of life appear to us as if they were designed. Consider one of those organisms where E is true. This organism looks as if it was designed.

However, does that mean it actually was designed? That's a different proposition, the difference between H and E. Since I distrust human intuition on matters of intention ascription (we do it too often), I'd rather look towards a rational framework.

What is the plausibility that this ID-looking orgnanism actually was designed? That's asking to evaluate P(H|E). Bayes rule tells us how to find P(H|E): the plausibility of a hypothesis H, given the truth of a proposition E (evidence).

Bayes rule derived:

P(H|E) P(E) = P(E|H) P(H)

P(H|E) = P(E|H) P(H) = likelihood * prior
----------- --------------------
P(E) marginal likelihood

P(H|E): if the organism looks like it was ID'd, the plausibility it actually was. (the core ID argument)
P(E|H): if the organism was ID'd, the plausibility it looks ID'd.

P(E|H) at first seems odd: certainly, if a creator intelligently designed an organism, doesn't that mean we'd be able to tell? Well, not necessarily: what if a designer makes decisions we cannot understand, or we can't divine the intelligence in the design of an organism? If that is likely to be the case, then P(E|H) decreases, and H|E becomes less likely.

P(H) is a pretty nasty prior: forgetting the evidence of whether it looks designed, what's the chance an organism was intelligently designed? That question seems to hinge on prior beliefs in the existence and activity of a creator. It's not up to debate. If you are already certain God exists, it may be reasonable to entertain the notion that organisms were intelligently designed. If you are less certain God exists, you may believe P(H) to be lower.

P(E) denotes the likelihood to find an organism that looks like it was intelligently designed. Though P(H|E) denotes the plausibility H is true given E is true, to evaluate it we have to look at the probability E could be true independently. The standard way to do this is to expand P(E).

P(H|E) = P(E|H) P(H)
P(E|H) P(H) + P(E|~H) P(~H)

E|~H: if the organism was not ID'd (e.g. it evolved), the plausibility it looks ID'd.

Some evolutionary theorists argue P(E|~H) can be quite high. e.g. Dawkins' "Blind Watchmaker": Nature can create impressively complex and purposeful looking life through random chance and natural selection. Behe's presentation seemed to unfairly argue down E|~H by only considering gradualist Darwinist explanations of evolution. It seems implausible that one-at-a-time tiny mutations could produce big complex systems like the eye or the immune system. That is, it's too hard to get out of local minima. However, to examine E|~H you need to look at all alternatives to ID. Complexity theory explanations might note that great complexity and order can emerge out of randomness; thus, the formation of complex systems through evolution is more plausible than our intuitions might tell us. Or exaptation: old adaptations might be put to new uses.

And of course, there's the hard-to-debate prior P(~H) again.

For reference, here are all the propositions again:
H: the organism was designed by an intelligent creator
E: the organism looks like it was designed by an intelligent creator
E|H: if the organism was ID'd, the plausibility it looks ID'd.
E|~H: if the organism was not ID'd (e.g. it evolved), the plausibility it looks ID'd.

So, here's how things line up for and against ID:

belief pro-ID belief reasons anti-ID belief reasons
E|H high ID'd organisms will look ID'd to us low we may not understand a designer's designs; they may not look familiar or intelligent to us

E|~H low gradualist adaptationism is unlikely to explain complex systems high blind watchmaker, complexity theory, exaptation... an evolutionary process could lead to outcomes that look as if they were designed.

H high prior belief in a creator and that creator's likelihood to design life low prior disbelief in a creator and that creator's likelihood to design life

Caveat: I'm confused how to analyze a given organism versus picking one at random. Does that make a difference?

Also, I'm wondering how to determine how much priors matter. When should argumentation over evidence for evolution force you to revise your beliefs about God? Is there a rational way to do this belief revision? If there isn't, are we all condemned to stick to our prior beliefs?

Tuesday, July 05, 2005

amazing: a blog on statistical inference for social science. Can't get more hardcore than that. Well, a formal modelling (e.g. mathematical game theory) blog would be quite something too.

finding some decision science blogs

Decision Science News looks active & useful. The cognitive neuroscience of decision making is such a great topic -- I mean, there are studies of the neurobiology of sarcasm!

There are some terrific older posts on the naturally named "Neuroeconomics". Steve Saletti also has there a post on Bernheim & Rangel's cue-triggered addiction paper, which I wrote about earlier (while taking taking a neuroeconomics course co-taught by Rangel, so I guess I'm biased!)

Monday, July 04, 2005

Here's a fantastic discussion by Alex Tabarrok and Bryan Caplan on social economics research and rationality -- and full of great links to current reviews & research.

NB: just realized Tabarrok is one of the authors of Marginal Revolution (already listed on the Links list here), and Bryan Caplan is at the same place, GMU... maybe the world of creative social economists isn't all that big after all...

City crisis simulation (e.g. terrorist attack)

WP: Computers simulate terrorist extremes

Los Alamos scientists are running terrorist attack/response simulations. Well, the article title is misleading, they're not simulating terrorists (which would pose a whole set of interesting questions about scientific knowledge, social construction and security), but rather, the impact on telecomm, health, and infrastructure systems. They're using the standard justifications for systems simulation: these are big, highly complex, highly interdependent systems that are ill-understood and have had drastic domino-effect collapses before (like the northeast power blackout).

The article also talks about epidemiology simulations (smallpox in this case, following the terrorist scenario again) that take into account the interactions of individual people with each other -- very much along the lines of agent-based simulations, and satisfying complexity theory's arguments about tipping points and emergent effects. [The article doesn't seem to say whether they actually computed at the level of individual agents, or used statistical aggregate approximations.]

freakonomics blog

Here it is! Still need to read the book. I'm a little bothered by people proclaiming it to be the first application of economic principles to social questions -- hasn't social economics been around for decades? -- but the spirit and approach is right.

Sunday, July 03, 2005

Cool visualization of agreement levels among Supreme Court justices. I like how they're ordered so that the smallest amount of agreement ends up in the lower-left. Hopefully it's not deceptive for certain cases: I imagine that summarizing their tendencies to vote certain ways into a one dimensional spectrum would lose important information of other dimensions of agreement or coalitions.

Friday, July 01, 2005

The current subtitle is "where {political, social, economic} crosses {cognition, behavior, systems}". Amusingly enough, this syntax on a unix shell actually gets you the 9 combinations:

~% echo {political,social,economic}{cognition,behavior,systems}
politicalcognition politicalbehavior politicalsystems
socialcognition socialbehavior socialsystems economiccognition
economicbehavior economicsystems

Tossing together groups of words is a good thing, since unexpected phrases suggest unexpected meanings. For example: Scott McCloud's story machine, where the point is to force yourself to see randomly generated new ideas.