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Begin with complexity. Behavioral scientists often divide what we do on the job or learn in school into two categories: “algorithmic” and “heuristic.” An algorithmic task is one in which you follow a set of established instructions down a single pathway to one conclusion. That is, there’s an algorithm for solving it. A heuristic task is the opposite. Precisely because no algorithm exists for it, you have to experiment with possibilities and devise a novel solution.
Experts can tell the voters what is likely to happen, but voters must engage those issues and decide what they value most, and therefore what they want done. Letting Boston slide into the harbor is not my preferred outcome, but it is not a failure of expertise if people ignore the experts and let it happen anyway: it is instead a failure of civic engagement. If Boston is to become Venice, it should be by choice, not by accident. When voters remain utterly unwilling to understand important issues because they are too difficult or discomfiting, it is unsurprising that experts will give up talking to them and instead rely on their positions in the policy world to advocate for their own solutions.
The Death of Expertise
Tom Nichols
Try to encourage a kid to learn math by paying her for each workbook page she completes—and she’ll almost certainly become more diligent in the short term and lose interest in math in the long term. Take an industrial designer who loves his work and try to get him to do better by making his pay contingent on a hit product—and he’ll almost certainly work like a maniac in the short term, but become less interested in his job in the long term. As one leading behavioral science textbook puts it, “People use rewards expecting to gain the benefit of increasing another person’s motivation and behavior, but in so doing, they often incur the unintentional and hidden cost of undermining that person’s intrinsic motivation toward the activity.”
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