Memory tests appear to exhibit a Flynn Effect.
Science and Technology
The most interesting talk at the Singularity Summit 2010 was Shane Legg‘s description of an Algorithmic Intelligence Quotient (AIQ) test that measures something intelligence-like automatically in a way that can test AI programs (or at least the Monte-Carlo AIXI that he uses) on 1000+ environments.
He had a mathematical formula which he thinks rigorously defines intelligence. But he didn’t specify what he meant by the set of possible environments, saying that would be a 50 page paper (he said a good deal of the work on the test had been done last week, so presumably he’s still working on the project). He also included a term that applies Occam’s razor which I didn’t completely understand, but it seems likely that that should have a fairly non-controversial effect.
The environments sound like they imitate individual questions on an IQ test, but with a much wider range of difficulties. We need a more complete description of the set of environments he uses in order to evaluate whether they’re heavily biased toward what Monte-Carlo AIXI does well or whether they closely resemble the environments an AI will find in the real world. He described two reasons for having some confidence in his set of environments: different subsets provided roughly similar results, and a human taking a small subset of the test found some environments easy, some very challenging, and some too hard to understand.
It sounds like with a few more months worth of effort, he could generate a series of results that show a trend in the AIQ of the best AI program in any given year, and also the AIQ of some smart humans (although he implied it would take a long time for a human to complete a test). That would give us some idea of whether AI workers have been making steady progress, and if so when the trend is likely to cross human AIQ levels. An educated guess about when AI will have a major impact on the world should help a bit in preparing for it.
A more disturbing possibility is that this test will be used as a fitness function for genetic programming. Given sufficient computing power, that looks likely to generate superhuman intelligence that is almost certainly unfriendly to humans. I’m confident that sufficient computing power is not available yet, but my confidence will decline over time.
Brian Wang has a few more notes on this talk
Tyler Cowen has a good video describing why we shouldn’t be too influenced by stories. He exaggerates a bit when he says
There are only a few basic stories. If you think in stories, that means you are telling yourself the same thing over and over
but his point that stories allow storytellers to manipulate our minds deserves more emphasis. For me, one of the hardest parts of learning how to beat the stock market was to admit that I did poorly when I was influenced by stories, and did well mainly when I relied on numbers that are available and standardized for most companies, and on mechanical rules which varied little between companies (I sometimes use different rules for different industries, but beyond that I try to avoid adapting my approach to different circumstances).
For example, The stories I heard about Enron’s innovative management style gave me a gut feeling that it was a promising investment. But its numbers showed an uninteresting company, and persuaded me to postpone any investment.
But I’ve only told you a story here (it’s so much easier to do than provide rigorous evidence). If you really want good reasons, try testing for yourself story versus non-story approaches to something like the stock market.
(HT Patri).
Book review: Probability Theory: The Logic of Science, by E. T. Jaynes.
This book does an impressive job of replacing ad hoc rules of statistics with rigorous logic, but it is difficult enough to fully understand that most people will only use small parts of it.
He emphasizes that probability theory consists of logical reasoning about the imperfect information we have, and repeatedly rants against the belief that probabilities or randomness represent features of nature that exist independent of our knowledge. Even something seemingly simple such as a toss of an ordinary coin cannot have some objectively fixed frequency unless concepts such as “toss” are specified in unreasonable detail. What we think of as randomness is best thought of as a procedure for generating results of which we are ignorant.
He derives his methods from a few simple axioms which appear close to common sense, and don’t look much like they are specifically designed to produce statistical rules.
He is careful to advocate Bayesian methods for an idealized robot, and avoids addressing questions of whether fallible humans should sometimes do something else. In particular, his axiom that the robot should never ignore information is a goal that will probably reduce the quality of human reasoning in some cases where there’s too much information for humans to handle well.
I’m convinced that when his methods can be properly applied and produce different results than frequentist methods do, we should reject the frequentist results. But it’s not obvious how easy it is to apply his methods properly, nor is it obvious whether he has accurately represented the beliefs of frequentists (who I suspect often don’t think clearly enough about the issues he raises to be clearly pinned down).
He does a good job of clarifying the concept of “induction”, showing that we shouldn’t try to make it refer to some simple and clearly specified rule, but rather we should think of it as a large set of rules for logical reasoning, much like the concept of “science”.
Book review: Hierarchy in the Forest: The Evolution of Egalitarian Behavior, by Christopher Boehm.
This book makes a good argument that a major change from strongly hierarchical societies to fairly egalitarian societies happened to the human race sometime after it diverged from Chimpanzees and Bonobos. Not due to any changes in attitudes toward status, but because language enabled low-status individuals to cooperate more effectively to restrain high-status individuals, and because of he equalizing effects of weapons. Hunter-gatherer societies seem rather consistently egalitarian, and the partial reversion to hierarchy in modern times may be due to the ability to accumulate wealth or the larger size of our societies.
He provides a plausible hypothesis that this change enabled group selection to become more powerful than in a typical species, but that doesn’t imply that group selection became as important as within-group selection, and he doesn’t have a good way of figuring out how important the effect was.
He demonstrates that humans became more altruistic, using a narrow biological definition of altruism, but it’s important to note that this only means agreeing to follow altruistic rules. He isn’t able to say much about how well people follow those rules when nobody notices what they’re doing.
Much of the middle of the book recounting anthropological evidence can be skipped without much loss – the most important parts are chapters 8 and 9.
Book review: Breakdown of Will, by George Ainslie.
This book analyzes will, mainly problems connected with willpower, as a form of intertemporal bargaining between a current self that highly values immediate temptation and future selves who prefer that current choices be more far-sighted. He contrasts simple models of rational agents who exponentially discount future utility with his more sophisticated and complex model of people whose natural discount curve is hyperbolic. Hyperbolic discounting causes time-inconsistent preferences, resulting in problems such as addiction. Intertemporal bargains can generate rules which bundle rewards to produce behavior more closely approximating the more consistent exponential discount model.
He also discusses problems associated with habituation to rewards, and strategies that can be used to preserve an appetite for common rewards. For example, gambling might sometimes be rational if losing money that way restores an appetite for acquiring wealth.
Some interesting ideas mentioned are that timidity can be an addiction, and that pain involves some immediate short-lived reward (to draw attention) in addition to the more obvious negative effects.
For someone who already knows a fair amount about psychology, only small parts of the book will be surprising, but most parts will help you think a bit clearer about a broad range of problems.
Book Review: Simple Heuristics That Make Us Smart by Gerd Gigerenzer and Peter M. Todd.
This book presents serious arguments in favor of using simple rules to make most decisions. They present many examples where getting a quick answer by evaluating a minimal amount of data produces almost as accurate a result as highly sophisticated models. They point out that ignoring information can minimize some biases:
people seldom consider more than one or two factors at any one time, although they feel that they can take a host of factors into account
(Tetlock makes similar suggestions).
They appear to overstate the extent to which their evidence generalizes. They test their stock market heuristic on a mere six months worth of data. If they knew much about stock markets, they’d realize that there are a lot more bad heuristics which work for a few years at a time than there are good heuristics. I’ll bet that theirs will do worse than random in most decades.
The book’s conclusions can be understood by skimming small parts of the book. Most of the book is devoted to detailed discussions of the evidence. I suggest following the book’s advice when reading it – don’t try to evaluate all the evidence, just pick out a few pieces.
Book review: Happiness from the Inside Out: The Art and Science of Fulfillment by Robert Mack.
This easy to read book describes many of the approaches I’ve used to make myself happier. That makes me somewhat tempted to believe the rest of his advice, but he seems to exaggerate enough that I have some doubts.
Being less concerned about what others think of me is an important part of his advice. But it seems implausible that I can be completely unharmed by other peoples opinions of me. He seems to believe that it’s possible to have a romantic relationship without risking being disappointed by one’s partner. I can somewhat reduce my emotional reaction to a partner not acting as I expected, but complete detachment would seem to make it hard for me to sympathize with a partner when appropriate.
There’s plenty of peer pressure for people to claim to be less susceptible to peer pressure than they actually are, so many people will be unaware of how to reduce those influences. This book’s focus on optimism is likely to distract people from such unflattering insights. You should look elsewhere for awareness of your desires for status, and choose wisely which status hierarchies you want to care about.
His paints a misleadingly gloomy picture of long-term happiness trends in the U.S., by selective evidence such as rising teen suicide rates, but not the fact that overall suicide rates are lower than a few decades ago.
His discussion of the genetic influence on happiness is unnecessarily discouraging. He mentions height as a stereotypical trait influenced by genes. I suggest thinking about hair color – it’s probably more influenced by genes than happiness, yet people who decide their hair should be purple often succeed quickly.
His claim that “Happiness is a particularly personal journey and no amount of data or research can tell you what will bring you happiness” is somewhat misleading – see the book Stumbling on Happiness for a very different perspective.
My understanding of Aspergers/autism (AS) and ADHD suggests to me that they can’t coexist in one personality. I keep coming across reports of people having both, and I’ve been trying to research whether those reports result from mistaken diagnoses or whether I’m missing something. I haven’t found any insightful discussion that addresses this directly. I’ve done some research on ADHD recently which clarified my ideas on this subject.
Both produce social problems due to unusual ways in which their attention works, and both involve unusually focused attention, which produce a good deal of overlap in symptoms. But there are many other features for which the two seem opposites.
ADHD – shifts attention easily and quickly in response to new stimuli
AS – slow to shift attention in response to stimuli
ADHD – seeks adrenaline rush from stimulating/risky situations
AS – avoids being overwhelmed by stimulating/risky situations
ADHD – often pays attention to multiple tasks at once
AS – finds multitasking unusually hard
From answers.com:
ADHD – makes inappropriate comments due to being impulsive but realizes afterward it was inappropriate
AS – makes inappropriate comments due to not knowing better and not understanding social conventions
ADHD – forgets details of daily routines
AS – follows daily routines rigidly
From another source:
Children with ADHD frequently break rules they understand, but defy and dislike. Children with Asperger’s Syndrome like rules, and break the ones they don’t understand. They are ever alert to injustice and unfairness and, unfortunately, these are invariably understood from their own nonnegotiable perspective. Children with ADHD are often oppositional in the service of seeking attention. Children with Asperger’s disorder are oppositional in the service of avoiding something that makes them anxious
With all these traits, there are wide variations in the degree to which anyone has them. But most of what I know suggests that people on one side of the AS/ADHD spectrum with regard to one of these traits are almost always on the same side with respect to the others, or else too close to the middle to classify.
Since many of these traits are poorly observed by those who diagnose them (you don’t observe peoples’ daily routines in a doctor’s office), it’s easy to imagine that widespread mistakes in diagnoses create a false impression that AS and ADHD coexist. Does anyone know of a good analysis that disagrees with my conclusion?
[Update 2010-11-15: I’ve gotten some feedback from people with some ADHD traits who don’t clearly fit the pattern I’ve described. Maybe my analysis only works for one subtype of ADHD, or maybe things are too complex for any existing categories to work as well as I’d like.]
The Chimera Hypothesis: Homosexuality and Plural Pregnancy makes the surprising claim that:
at least 50-70% of healthy adults are chimeric to some extent.
The hypothesis can explain some homosexual and transgender tendencies, and suggests some reproductive advantages that offset those reproductive disadvantages:
Therefore, women prone to having more than one egg fertilized, but whose pregnancies only resulted in only one live birth, would have the optimum level of fertility. A side effect of this could be an increased incidence of chimerism in human children … even a relatively small increase in female fertility, which is really the limiting factor in human population growth, could outweigh the disadvantage of less fertility in a small number of male infants.
One observation that this hypothesis doesn’t explain is why there are many more homosexuals than transgenders. So my guess is that it explains only a modest fraction of the homosexuality that we observe, but might explain the observed frequency of transgenders fairly well.