In collaboration with the Department of Computer Science and the Department of Electrical and Computer Engineering

Online platforms have a wealth of data, run countless experiments and use industrial-scale algorithms to optimize user experience. Despite this, many users seem to regret the time they spend on these platforms. One possible explanation is that incentives are misaligned: platforms are not optimizing for user happiness. We suggest the problem runs deeper, transcending the specific incentives of any particular platform, and instead stems from a mistaken foundational assumption. To understand what users want, platforms look at what users do. This is a kind of revealed-preference assumption that is ubiquitous in user models. Yet research has demonstrated, and personal experience affirms, that we often make choices in the moment that are inconsistent with what we actually want: we can choose mindlessly or myopically, behaviors that feel entirely familiar on online platforms.

Jon Kleinberg is the Tisch University Professor in the Departments of Computer Science and Information Science at Cornell University.

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