How the mind works

In a conversation about religion and science on Joi Ito’s blog, John Jensen recommended Steven Pinker’s How the Mind Works for a scientific perspective on the origin of culture and religion. The book fails at that mission, but is interesting in a more limited scope.
The parts of the book backed up by experimental research are fascinating. In readable prose, Pinker summarizes research about how the mind processes visual images, logic, and math. The experimental evidence supports a coherent theory that intelligence is composed of modular components.
The parts of the book about emotions, altruism, and values have much less experimental content. Pinker uses evolution as myth — canonical stories about hunter-gatherer cultures and primate ethology are used to draw broad lessons about human nature. One of Pinker’s “insights” — humans have evolved to assess the trustworthiness of others, and also to deceive themselves and others. Another: addictions to food and sex derive from biological desires for pleasure. Another: human cultural achievements are driven by desire for status.
Damasio’s based analysis of emotion and consciousness based on clinical neurological research and Terrence Deacon’s analysis of the neuroanatomy of the brain are more empirically based, and have more compelling insights about the relationships between emotions, language, and consciousness. When Deacon strays off the empirical farm and does evidence-free, evolution-based mythic speculation, he gets shallow too.
Pinker’s use of evolution as a myth doesn’t lead to more insight than traditional explanations of human complexity (desire leads to suffering in the Buddhist tradition; the “good inclination/evil inclination” framework in the Jewish tradition). These traditional sources don’t have evolutionary science as their base, yet they perceive the conflicts in human nature, and can reach wise insights about how to handle the conflicts.
A good part of the argument in “How the Mind Works” is polemic against foolish politically-correct academic conventional wisdom that humans don’t have natural tendencies toward selfishness, deceit and violence.
But in arguing against “culturist” extremism, Pinker misses the point about culture. Pinker ties himself into knots trying to explain why people would engage in behavior that contradicted a basic evolutionary program — why a successful scientist would focus on career and marry late, why a family would adopt a child.
He doesn’t understand that cultural rewards like prestige and social experiences like nurturing can extend underlying biological programming. It’s not enough for Pinker to reverse-engineer the biological roots of behavior, he needs to explain the higher-level behavior in terms of the lower-level behavior. This is like explaining the plot of a video game in terms of assembly language, or even the game’s object model.
In summary, Pinker does fine as a scientist, but he hasn’t successfully made the transition to moral philosopher. And he certainly hasn’t made the case that scientific research has made moral philosophy obsolete.

“hypertext cycles” and decision-making

Peter Merholz writes about a pattern he observed, back when he was in Epinions, about the way people decided what digital camera to buy.

We assumed that, given the task of finding an appropriate digital camera, people would whittle down the attributes such as price, megapixel count, and brand, and arrive at the few options best suited to them. If they had questions along the way, they could read helpful guides that would define terms, suggest comparison strategies, etc.
Again and again in our observations, that didn’t happen. People who knew little about digital cameras made no attempt to bone up. Instead they’d barrel through the taxonomy, usually beginning with a familiar brand, and get to a product page as quick as possible. It was only then, when looking at a specific item, and seeing what it’s basic specifications were, did they pause, sit back, and think, “Hmmm. This has 2 megapixels. I wonder how many I want?” Some would look for glossaries or guides, others would read reviews, and some just guessed by comparing the various products.
They would go through this cycle — looking at a product, reflect on their needs, understand concepts, look at another product, reflect again, etc. — a few times. Todd and I came up with a conceptual model, where the user is something like a bouncing ball, falling straight onto a product, then bouncing up, getting a lay of the land, falling onto another product, bouncing up again, but not as high since they’re starting to figure it out, falling onto another product, and repeating until they’ve found the right one.

Makes total sense. People need concrete examples in order to start to understand the conceptual space of digital camera features.
More good decision-making references in the comments to peterme’s post.

Is society a small-world network

Mr. Barabasi believes the human social network is scale-free with the expected smattering of richly connected hubs. Mr. Watts disagrees. “If you asked people to list the number of people they recognize, that could be scale-free, everyone recognizes Michael Jordan,” he said. “But if you said, `Who would you trust to look after your kids?’ That’s not scale-free. As you start to ratchet up the requirements for what it means to know someone, connections diminish.”

Computers won’t be reading Plato any time soon, Part 2

Thanks to Ed Nixon for a link to an interesting article by philosopher
John Searle, arguing against Ray Kurzweil’s contention that computers
will soon be smarter than people.
The strong part of Searle’s article is the argument that “syntax is not
semantics” — a computer that can calculate chess moves based on
pre-defined algorithms does not actually understand chess. Searle argues
successfully that Deep Blue is unintelligent in the same way that a
pocket calculator is unintelligent; it is simply manipulating symbols,
just as a human who speaks Chinese phrases using a transliteration is
manipulating symbols but does not understand Chinese.
Searle is right that Deep Blue is very far from being conscious. The
fact that a computer can beat a human at chess means about as much as
the fact that an automobile can move faster than a runner. Humans
designed the automobile; and human programmers chose the heuristics that
drive Deep Blue’s decisions.
Searle is less successful with the argument that a computer cannot have
intelligence, since a computer contains a mere model of intelligent
processes; and models are different from the physical things that they
Searle acknowledges that human intelligence is an emergent property of
neurons firing in the brain. This means, though, that intelligence is
based on circuitry, a pattern of information. Similarly, scientists are
gradually deciphering the informational patterns of genes and gene
expression. The lines between information and reality are not so clear
cut; it may be possible to develop living, even intelligent patterns in
some other medium.
Human intelligence probably has subtle dependencies on the biochemical
nature of the brain and the organism. Tom Ray makes this point
beautifully. But it does not follow that the only possible kind of
intelligence requires a body; it certainly does not follow that theonly
kind of intelligence requires this sort of body.
It may be theoretically possible for intelligence to develop in some
other medium. But despite Kurzweil’s optimism, there is little evidence
that we have any idea how to do this. Searle is right that just because
we can program computers to play chess does not mean we are anywhere
near creating computers with conscious minds.

The Origin of Animal Body

The Origin of Animal Body Plans by Wallace Arthur

This is a test of the BookPost feature written by Paul Bauch. BookPost is a web service that lets you post book reviews while browsing the book on Amazon. Bookpost uses a JavaScript bookmarklet that calls an ASP script that uses the Amazon API to pull in the book’s title, author, and URL; and the Blogger API to automatically post to your weblog.
Unfortunately, the Amazon API does not seem to cover reviews; I would love to be able to cross-post reviews to Amazon and the weblog!
This book looks nontrivial but fascinating. Into the to-read queue it goes. So many books, so little time.