Archive for December, 2009

Moral Machines

Sunday, December 27th, 2009

Book review: Moral Machines: Teaching Robots Right from Wrong by Wendell Wallach and Collin Allen.

This book combines the ideas of leading commentators on ethics, methods of implementing AI, and the risks of AI, into a set of ideas on how machines ought to achieve ethical behavior.

The book mostly provides an accurate survey of what those commentators agree and disagree about. But there’s enough disagreement that we need some insights into which views are correct (especially about theories of ethics) in order to produce useful advice to AI designers, and the authors don’t have those kinds of insights.

The book focuses more on near term risks of software that is much less intelligent than humans, and is complacent about the risks of superhuman AI.

The implications of superhuman AIs for theories of ethics ought to illuminate flaws in them that aren’t obvious when considering purely human-level intelligence. For example, they mention an argument that any AI would value humans for their diversity of ideas, which would help AIs to search the space of possible ideas. This seems to have serious problems, such as what stops an AI from fiddling with human minds to increase their diversity? Yet the authors are too focused on human-like minds to imagine an intelligence which would do that.

Their discussion of the advocates friendly AI seems a bit confused. The authors wonder if those advocates are trying to quell apprehension about AI risks, when I’ve observed pretty consistent efforts by those advocates to create apprehension among AI researchers.

The Value of Cute Kittens

Wednesday, December 23rd, 2009

This research suggests you should look at pictures of cute kittens before starting tasks that require a lot of dexterity, and possibly a broader set of tasks that require caution.

What Intelligence Tests Miss

Saturday, December 12th, 2009

Book review: What Intelligence Tests Miss – The Psychology of Rational Thought by Keith E. Stanovich.

Stanovich presents extensive evidence that rationality is very different from what IQ tests measure, and the two are only weakly related. He describes good reasons why society would be better if people became more rational.

He is too optimistic that becoming more rational will help most people who accomplish it. Overconfidence provides widespread benefits to people who use it in job interviews, political discussions, etc.

He gives some advice on how to be more rational, such as thinking the opposite of each new hypothesis you are about to start believing. But will training yourself to do that on test problems cause you to do it when it matters? I don’t see signs that Stanovich practiced it much while writing the book. The most important implication he wants us to draw from the book is that we should develop and use Rationality Quotient (RQ) tests for at least as many purposes as IQ tests are used. But he doesn’t mention any doubts that I’d expect him to have if he thought about how rewarding high RQ scores might affect the validity of those scores.

He reports that high IQ people can avoid some framing effects and overconfidence, but do so only when told to do so. Also, the sunk cost bias test looks easy to learn how to score well on, even when it’s hard to practice the right behavior – the Bruine de Bruin, Parker and Fischhoff paper than Stanovich implies is the best attempt so far to produce an RQ test lists a sample question for the sunk costs bias that involves abandoning food when you’re too full at a restaurant. It’s obvious what answer produces a higher RQ score, but that doesn’t say much about how I’d behave when the food is in front of me.

He sometimes writes as if rationality were as close to being a single mental ability as IQ is, but at other times he implies it isn’t. I needed to read the Bruine de Bruin, Parker and Fischhoff paper to get real evidence. Their path independence component looks unrelated to the others. The remaining components have enough correlation with each other that there may be connections between them, but those correlations are lower than the correlations between the overall rationality score and IQ tests. So it’s far from clear whether a single RQ score is better than using the components as independent tests.

Given the importance he attaches to testing for and rewarding rationality, it’s disappointing that he devotes so little attention to how to do that.

He has some good explanations of why evolution would have produced minds with the irrational features we observe. He’s much less impressive when he describes how we should classify various biases.

I was occasionally annoyed that he treats disrespect for scientific authority as if it were equivalent to irrationality. The evidence for Big Foot or extraterrestrial visitors may be too flimsy to belong in scientific papers, but when he says there’s “not a shred of evidence” for them, he’s either using a meaning of “evidence” that’s inappropriate when discussing the rationality of people who may be sensibly lazy about gathering relevant data, or he’s simply wrong.

Finding Alpha

Tuesday, December 1st, 2009

Book review: Finding Alpha: The Search for Alpha When Risk and Return Break Down by Eric Falkenstein.

This book presents mostly convincing arguments that refute the basic principle of CAPM that riskier investments are rewarded with higher returns, and the relation between risk and returns is better explained by modeling investors as wanting high returns relative to other investors rather than high absolute returns. But the quality of the arguments is quite variable. Much of the book assumes a good understanding of finance theory. If you don’t understand the importance of a Sharpe ratio, you’re not in his target audience.

I was not convinced by his most heavily emphasized empirical claim, that returns on equities are unrelated to beta because controlling for size eliminates the apparent relation. There’s enough connection between size and risk that this raises many questions he doesn’t answer (e.g. JB Berk, A critique of size-related anomalies). But later on he devotes a chapter to a wide variety of evidence that overcomes these concerns, and somewhat supports his claim that for riskier investments, the correlation between risk and return is negative (for the safest investments, it’s positive). And the authoritative Fama and French paper has more convincing evidence about beta – even without controlling for size, the correlation between beta and returns vanished during the 1963 to 1990 period.

He claims that the equity risk premium is effectively zero for a typical investor. His attempt to add up the different adjustments is confusing. He concludes with a table showing size adjustments to that standard estimate that add up to a mind-boggling 15 percent, which would result in a “premium” of -9 percent or so. But adding them is clearly wrong – the tax adjustment assumes the absence of some of the other adjustments. Still, the arguments he assembles from other researchers imply a good chance that the sign of the equity risk premium varies with the time period over which it’s measured.

He suggests some strategies to invest more wisely as a result of the ideas he presents, which he aptly summarizes as “selling hope relative to the market” (i.e. treating volatile stocks as overpriced due to a hope premium). But claiming this produces “superior returns, with less risk however measured” is too strong. Financial risk is not the only relevant measure of risk. Following his advice has social risks that he hints at elsewhere. Being invested in boring stocks in a bubble impairs your ability to engage in some interesting conversations, and you won’t make up for that by mentioning how you outperform the market in times when other want to avoid remembering their investments. Is it possible to minimize both kinds of risks by investing token amounts in ways that trendy folks are talking about, and investing most of your money to maximize your Sharpe ratio? Or does that require too much cognitive dissonance?

The book encourages pessimism, especially about the effects of people wanting relative wealth, and makes disturbing claims such as “Envy is necessary for compassion”.

He provides a number of other good ideas about investing, such as the possibility that the internet bubble adds a big anomaly to many data sets used for backtesting.