All else being equal, not many people would prefer to destroy the world. Even faceless corporations, meddling governments, reckless scientists, and other agents of doom, require a world in which to achieve their goals of profit, order, tenure, or other villainies. If our extinction proceeds slowly enough to allow a moment of horrified realization, the doers of the deed will likely be quite taken aback on realizing that they have actually destroyed the world. Therefore I suggest that if the Earth is destroyed, it will probably be by mistake.
The systematic experimental study of reproducible errors of human reasoning, and what these errors reveal about underlying mental processes, is known as the heuristics and biases programme in cognitive psychology. This programme has made discoveries highly relevant to assessors of global catastrophic risks. Suppose you are worried about the risk of Substance P, an explosive of planet-wrecking potency which will detonate if exposed to a strong radio signal. Luckily there is a famous expert who discovered Substance P, spent the last 30 years working with it, and knows it better than anyone else in the world. You call up the expert and ask how strong the radio signal has to be. The expert replies that the critical threshold is probably around 4000 terawatts. 'Probably?' you query. 'Can you give me a 98% confidence interval?' 'Sure', replies the expert. 'I'm 99% confident that the critical threshold is above 500 terawatts, and 99% confident that the threshold is below 80,000 terawatts.' 'What about 10 terawatts?' you ask. 'Impossible', replies the expert.
The above methodology for expert elicitation looks perfectly reasonable, the sort of thing any competent practitioner might do when faced with such a problem. Indeed, this methodology was used in the Reactor Safety Study (Rasmussen, 1975), now widely regarded as the first major attempt at probabilistic risk assessment. But the student of heuristics and biases will recognize at least two major mistakes in the method - not logical flaws, but conditions extremely susceptible to human error. I shall return to this example in the discussion of anchoring and adjustments biases (Section 5.7)
I thank Michael Roy Ames, Nick Bostrom, Milan Cirkovic, Olie Lamb, Tamas Martinec, Robin Lee Powell, Christian Rovner, and Michael Wilson for their comments, suggestions, and criticisms. Needless to say, any remaining errors in this paper are my own.
The heuristics and biases program has uncovered results that may startle and dismay the unaccustomed scholar. Some readers, first encountering the experimental results cited here, may sit up and say: "Is that really an experimental result? Are people really such poor guessers? Maybe the experiment was poorly designed, and the result would go away with such-and-such manipulation." Lacking the space for exposition, I can only plead with the reader to consult the primary literature. The obvious manipulations have already been tried, and the results found to be robust.
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