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on these inputs that generates an output. In the case of rational choice theory, for example, the “parameters and conditions” might be captured by the utility function, and the “operation” would be some optimization procedure; but one could imagine other conditions and operations as well, including heuristics, habits, and other nonrational approaches to problem solving. The point is that no matter what kind of computation one tries to write down, one must start from some set of assumptions about what is relevant, and that decision is not one that can be resolved in the same (i.e., local) manner. If one tried to resolve it, for example, by starting with some independent set of assumptions about what is relevant to the computation itself, one would simply end up with a different version of the same problem (what is relevant to that computation?), just one step removed. Of course, one could keep iterating this process and hope that it terminates at some well-defined point. In fact, one can always do this trivially by exhaustively including every item and concept in the known universe in the basket of potentially relevant factors, thereby making what at first seems to be a global problem local by definition. Unfortunately, this approach succeeds only at the expense of rendering the computational procedure intractable.

18. For an introduction to machine learning, see Bishop (2006). See Thompson (2010) for a story about the Jeopardy-playing computer.

19. For a compelling discussion of the many ways in which our brains misrepresent both our memories of past events and our anticipated experience of future events, see Gilbert (2006). As Becker (1998, p. 14) has noted, even social scientists are prone to this error, filling in the motivations, perspectives, and intentions of their subjects whenever they have no direct evidence of them. For related work on memory, see Schacter (2001) and Marcus (2008). See Bernard et al. (1984) for many examples of errors in survey respondents’ recollections of their own past behavior and experience. See Ariely (2008) for additional examples of individuals overestimating their anticipated happiness or, alternatively, underestimating their anticipated unhappiness, regarding future events. For the results on online dating, see Norton, Frost, and Ariely (2007).

20. For discussions of performance-based pay, see Hall and Liebman (1997) and Murphy (1998).

21. Mechanical Turk is named for a ninteenth-century chess-playing automaton that was famous for having beaten Napoleon. The original Turk, of course, was a hoax—in reality there was a human inside making all the moves—and that’s exactly the point. The tasks that one typically finds on Mechanical Turk are there because they are relatively easy for humans to solve, but difficult for computers—a phenomenon that Amazon founder Jeff Bezos calls “artificial, artificial intelligence. See Howe (2006) for an early report on Amazon’s Mechanical Turk, and Pontin (2007) for Bezos’s coinage of “artificial, artificial intelligence.” See http://behind-the-enemy-lines.blogspot.com for additional information on Mechanical Turk.

22. See Mason and Watts (2009) for details on the financial incentives experiment.

23. Overall, women in fact earn only about 75 percent as much as men, but much of this “pay gap” can be accounted for in terms of different choices that women make—for example, to work in lower-paying professions, or to take time off from work to raise a family, and so on. Accounting for all this variability, and comparing only men and women who work in comparable jobs under comparable conditions, roughly a 9 percent gap remains. See Bernard (2010) and http://www.iwpr.org/pdf/C350.pdf for more details.

24. See Prendergast (1999), Holmstrom and Milgrom (1991), and Baker (1992) for studies of “multitasking.” See Gneezy et al. (2009) for a study of the “choking” effect. See Herzberg (1987), Kohn (1993), and Pink (2009) for general critiques of financial rewards.

25. Levitt and Dubner (2005, p. 20)

26. For details on the unintended consequences of the No Child