Monthly Archives: November 2007

Artificial Addition

By Eliezer Yudkowsky · November 20, 2007 2:58 am · Comments (41)

Followup to:  The Simple Truth

Suppose that human beings had absolutely no idea how they performed arithmetic.  Imagine that human beings had evolved, rather than having learned, the ability to count sheep and add sheep.  People using this built-in ability have no idea how it worked, the way Aristotle had no idea how his visual cortex supported his ability to see things.  Peano Arithmetic as we know it has not been invented.  There are philosophers working to formalize numerical intuitions, but they employ notations such as

Plus-Of(Seven, Six) = Thirteen

to formalize the intuitively obvious fact that when you add "seven" plus "six", of course you get "thirteen".

In this world, pocket calculators work by storing a giant lookup table of arithmetical facts, entered manually by a team of expert Artificial Arithmeticians, for starting values that range between zero and one hundred.  While these calculators may be helpful in a pragmatic sense, many philosophers argue that they’re only simulating addition, rather than really adding.  No machine can really count – that’s why humans have to count thirteen sheep before typing "thirteen" into the calculator.  Calculators can recite back stored facts, but they can never know what the statements mean – if you type in "two hundred plus two hundred" the calculator says "Error: Outrange", when it’s intuitively obvious, if you know what the words mean, that the answer is "four hundred".

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Publication Bias and the Death Penalty

By Justin Wolfers · November 19, 2007 9:07 am · Comments (9)

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The front page of Sunday’s New York Times contained an interesting article reviewing research linking  the death penalty to homicide trends.  Adam Liptak attempts to provide a balanced account of the debate, noting first one set of findings:

According to roughly a dozen recent studies, executions save lives. For each inmate put to death, the studies say, 3 to 18 murders are prevented.

And then my own research:

The death penalty “is applied so rarely that the number of homicides it can plausibly have caused or deterred cannot reliably be disentangled from the large year-to-year changes in the homicide rate caused by other factors,” John J. Donohue III, a law professor at Yale with a doctorate in economics, and Justin Wolfers, an economist at the University of Pennsylvania, wrote in the Stanford Law Review in 2005. “The existing evidence for deterrence,” they concluded, “is surprisingly fragile.”

Surely a dozen studies is itself evidence of robustness.  Why then is then is it that we find these results are fragile?  Two words: Publication bias (also known as the file drawer problem).  Our research revealed that alternative approaches to testing the execution-homicide link can yield a huge array of possible results (positive and negative).  But if only strong pro-deterrent results are reported (and the others remain in the file drawer), this could look misleadingly like there is a pro-deterrent consensus.

It turns out that there are some rather simple tests for publication bias.  Our friends in medicine provide a useful intuition.  Imagine that there are many separate drug trials being considered – some with large samples, some with small samples.  If all results are being reported, then smaller samples should, on average, yield similar estimates to larger samples, albeit with a bit more noise (in both directions).  So the standard error of an estimate should be uncorrelated with the coefficient.  But if researchers only report statistically significant estimates, then they will only report results with t-statistics>2, yielding a strong correlation between standard errors and coefficient estimates.

You can probably guess what we find.

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Development Futures

By Robin Hanson · November 19, 2007 6:00 am · Comments (21)

Over the last month I’ve sketched how decision markets might inform choices in marriage, college, college admissions, and medical treatment.  Today I consider development, i.e., advising governments and non-profits trying to improve "developing" nations and societies.  Rick Davies, Michael Strong (here and here), and Robert Hahn and Paul Tetlock have written already about this to varying degrees, but let me say it my way. 

Decision markets are markets where speculators set prices that estimate the consequences of a decision. The big win here would be decision markets estimating envisioned outcomes of proposed development projects.  Imagine that before the World Bank, IMF, or Gates Foundation approved a particular development project, we could learn of the discrete alternatives being considered, and of the measurable outcomes they planned to publish and use to evaluate success or failure.   

For example, there might be several Malaria-reduction projects being proposed, each of which will be evaluated later by the actual rate of Malaria in some area.  AIDS projects might be evaluated via later rates of infection.  Education projects might be evaluated later by literacy rates, while national investment or loan projects might be evaluated on growth rates of GDP.

Development futures could directly evaluate expected outcomes both given that a project was approved, and given that the project was not approved.  The difference between these numbers is the expected effect of the project.  Development futures could tell everyone that the Gates Foundation’s malaria project is not expected to change malaria rates, or that a World Bank loan to Mongolia would dramatically improve growth rates there. 

The cooperation of the Gates Foundation or the World Bank would not be required (beyond revealing projects considered and evaluation criteria).  Any other interested organization could create markets allowing anyone they approved to trade.  Ideally someone would subsidize cash markets where anyone could trade. 

Once development futures had built up a track record of unprecedented accuracy, they could cut through poisonous biases on both sides – to expose both wasteful projects built on wishful thinking, and insincere skepticism used as an excuse to do nothing.  Let’s find out what really works, and then let’s really do it. 

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Conjuring An Evolution To Serve You

By Eliezer Yudkowsky · November 19, 2007 12:55 am · Comments (17)

GreyThumb.blog offers an interesting analogue between research on animal breeding and the fall of Enron.  Before 1995, the way animal breeding worked was that you would take the top individual performers in each generation and breed from them, or their parents.  A cockerel doesn’t lay eggs, so you have to observe daughter hens to determine which cockerels to breed.  Sounds logical, right?  If you take the hens who lay the most eggs in each generation, and breed from them, you should get hens who lay more and more eggs.

Behold the awesome power of making evolution work for you!  The power that made butterflies – now constrained to your own purposes!  And it worked, too.  Per-cow milk output in the US doubled between 1905 and 1965, and has doubled again since then.

Yet conjuring Azathoth oft has unintended consequences, as some researchers realized in the 1990s.  In the real world, sometimes you have more than animal per farm.  You see the problem, right?  If you don’t, you should probably think twice before trying to conjure an evolution to serve you – magic is not for the unparanoid.

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US South Had 42% Chance

By Robin Hanson · November 18, 2007 1:00 pm · Comments (3)

Hindsight bias tricks us into thinking familiar war outcomes were inevitable.  So it is good to remind ourselves how easily things could have been different.  Marc Weidenmier and Kim Oosterlinck argue that "European investors gave the Confederacy approximately a 42 percent chance of victory prior to the battle of Gettysburg/Vicksburg":

Historians have long wondered whether the Southern Confederacy had a realistic chance at winning the American Civil War. We provide some quantitative evidence on this question by introducing a new methodology for estimating the probability of winning a civil war or revolution based on decisions in financial markets. Using a unique dataset of Confederate gold bonds in Amsterdam, we apply this methodology to estimate the probability of a Southern victory from the summer of 1863 until the end of the war. Our results suggest that European investors gave the Confederacy approximately a 42 percent chance of victory prior to the battle of Gettysburg/Vicksburg. News of the severity of the two rebel defeats led to a sell-off in Confederate bonds. By the end of 1863, the probability of a Southern victory fell to about 15 percent. Confederate victory prospects generally decreased for the remainder of the war. The analysis also suggests that McClellan’s possible election as U.S. President on a peace party platform as well as Confederate military victories in 1864 did little to reverse the market’s assessment that the South would probably lose the Civil War.

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Towards a typology of bias

By Nick Bostrom · November 18, 2007 12:40 pm · Comments (17)

It seems to me that we have reached a stage in our discussions on this blog, and in the field of bias studies more generally, where it would be useful to begin to develop a more systematic typology.  There are so many different alleged biases that without some unifying framework it is easy to get lost in the details.  Finding the right categories would also help us theorize better about bias.

To this end, let me tentatively propose a classification scheme, organized around the sources of bias:

Type-I biases arise from the fact that our beliefs sometimes serve functions – such as social signaling – that can conflict with their navigational (truth-tracking) function.  For example, our tendency to overestimate our own positive attributes may be an example of a Type I bias.

Type-II biases arise from the shortcomings and flaws of our minds.  We are subject to various kinds of processing constraints, and even aside from these hard limitations we weren’t very successfully optimized for efficiency in abstract rationality even in contexts where no adaptive function interferes with the navigational function of our beliefs.  Type II biases can result from fast-and-frugal heuristics that compromise accuracy for speed and ease of use, or from various idiosyncratic features of our brains and psyches.  We can distinguish subtype-II(a) biases deriving from shortcomings general to the human psyche (availability bias?), and subtype-II(b) biases deriving from shortcomings specific to some individual or group (beliefs about being danger among the paranoid?)

Type-III biases arise from our avoidable ignorance of facts or lack of insights, the possession of which would have improved our epistemic accuracy across a broad domain.  (Many of Eliezer’s recent postings appear to aim to overcome Type III bias, for example by explaining important facts about evolution, which would help us form more accurate belief about many specific issues that are illuminated by evolutionary biology.)  We distinguish subtype-III(a) resulting from lack of (procedural) insights about methodology, logic, or reasoning principles (e.g. anthropic bias), and subtype-III(b) resulting from lack of (substantial) knowledge about theoretical or concrete facts (e.g. errors resulting from ignorance about the basic findings of evolutionary psychology).

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The Simple Math of Everything

By Eliezer Yudkowsky · November 17, 2007 5:42 pm · Comments (38)

I am not a professional evolutionary biologist.  I only know a few equations, very simple ones by comparison to what can be found in any textbook on evolutionary theory with math, and on one memorable occasion I used one incorrectly.  For me to publish an article in a highly technical ev-bio journal would be as impossible as corporations evolving.  And yet when I’m dealing with almost anyone who’s not a professional evolutionary biologist…

It seems to me that there’s a substantial advantage in knowing the drop-dead basic fundamental embarrassingly simple mathematics in as many different subjects as you can manage.  Not, necessarily, the high-falutin’ complicated damn math that appears in the latest journal articles.  Not unless you plan to become a professional in the field.  But for people who can read calculus, and sometimes just plain algebra, the drop-dead basic mathematics of a field may not take that long to learn.  And it’s likely to change your outlook on life more than the math-free popularizations or the highly technical math.

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My Guatemala Interviews

By Robin Hanson · November 17, 2007 6:00 am · Comments (3)

Last month I visited Universidad Francisco Marroquín in Guatemala and gave a series of talks and interviews.  The two interviews are available, in high definition video:

  • An 11 minute interview with Luis Figueroa, on medicine.
  • A 70 minute interview with Carlisle Johnson, on everything.

This second interview is by far the most far ranging interview I’ve ever had or likely will ever have, out of 200 media mentions.  Quite a credit to Mr. Johnson. 

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No Evolutions for Corporations or Nanodevices

By Eliezer Yudkowsky · November 16, 2007 9:24 pm · Comments (20)

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        “The laws of physics and the rules of math don’t cease to apply. That leads me to believe that evolution doesn’t stop. That further leads me to believe that nature — bloody in tooth and claw, as some have termed it — will simply be taken to the next level…
        “[Getting rid of Darwinian evolution is] like trying to get rid of gravitation.  So long as there are limited resources and multiple competing actors capable of passing on characteristics, you have selection pressure.”
       — Perry Metzger, predicting that the reign of natural selection would continue into the indefinite future.

In evolutionary biology, as in many other fields, it is important to think quantitatively rather than qualitatively.  Does a beneficial mutation “sometimes spread, but not always”?  Well, a psychic power would be a beneficial mutation, so you’d expect it to spread, right?  Yet this is qualitative reasoning, not quantitative – if X is true, then Y is true; if psychic powers are beneficial, they may spread.  In Evolutions Are Stupid, I described the equations for a beneficial mutation’s probability of fixation, roughly twice the fitness advantage (6% for a 3% advantage).  Only this kind of numerical thinking is likely to make us realize that mutations which are only rarely useful are extremely unlikely to spread, and that it is practically impossible for complex adaptations to arise without constant use.  If psychic powers really existed, we should expect to see everyone using them all the time – not just because they would be so amazingly useful, but because otherwise they couldn’t have evolved in the first place.

“So long as there are limited resources and multiple competing actors capable of passing on characteristics, you have selection pressure.”  This is qualitative reasoning.  How much selection pressure?

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Nature Endorses Human Extinction

By Robin Hanson · November 16, 2007 6:00 am · Comments (55)

In the latest Nature, Chris Thomas says:

This year the baiji river dolphin (Lipotes vexillifer), a victim of the pollution and boat traffic of China’s Yangtze river, was added to the list of creatures on the verge of extinction. Is this part of the sixth mass extinction in 450 million years, or does the recent spate of losses caused by humans represent a blip in the history of life on Earth? Michael Novacek’s Terra takes stock of the situation and provides an opportunity to learn from the past.  … 

Of course, we shall solve some of these issues with technological fixes. Yet if we maintain 9 billion avaricious people on Earth for the next millennium, a sixth extinction event seems inevitable.  The geological perspective of Terra is bizarrely reassuring. Humans will presumably be gone within a few million years, perhaps sooner. If the past that Novacek describes is a guide to the future, global ecosystem processes will be restored some tens of thousands to a million years after our demise, and new forms of life over the ensuing millions of years will exploit the denuded planet we leave behind. Thirty million years on, things will be back to normal, albeit a very different `normal’ from before. It is good to be optimistic. The problem is living here in the meantime.

Thomas is "optimistic" that humans and any descendants with a remotely similar population or resource-intensive technology will be extinct in a million years.   Yet if a plague, for example, were to produce this outcome within the next ten years, I’m pretty sure most everyone would see this as a catastrophe of the highest possible order.  So how does this become a good thing if it happens in the next million years?

Added 21Nov:  I emailed Chris Thomas the day of this post, and today he commented that I was "over-interpreting a few tongue-in-cheek comments."  I responded.

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