Deciding by Default
Impersonal default rules, chosen by private or public institutions, establish settings and starting points for countless goods and activities—cell phones, rental car agreements, computers, savings plans, health insurance, websites, privacy, and much more. Some of these rules do a great deal of good, but others might be poorly chosen, perhaps because the choice architects who select them are insufficiently informed, perhaps because they are self-interested, perhaps because one size does not fit all. The existence of heterogeneity argues against impersonal default rules. The obvious alternative to impersonal default rules, of particular interest when individual situations are diverse, is active choosing, by which people are asked or required to make decisions on their own. The choice between impersonal default rules and active choosing depends largely on the costs of decisions and the costs of errors. If active choosing were required in all contexts, people would quickly be overwhelmed; default rules save a great deal of time, making it possible to make other choices and in that sense promoting autonomy. Especially in complex and unfamiliar areas, impersonal default rules have significant advantages. But where people prefer to choose, and where learning is both feasible and important, active choosing may be best, especially if people’s situations are relevantly dissimilar. At the same time, it is increasingly possible for private and public institutions to produce highly personalized default rules, which reduce the problems with one-size-fits-all defaults. In principle, personalized default rules could be designed for every individual in the relevant population. Collection of the information that would allow accurate personalization might be burdensome and expensive, and might also raise serious questions about privacy. But at least when choice architects can be trusted, personalized default rules offer most (not all) of the advantages of active choosing without the disadvantages.
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Allison Orr Larsen