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SRI Seminar Series: Jon Kleinberg, “The challenge of understanding what users want: Inconsistent preferences and engagement optimization”

Our weekly SRI Seminar Series welcomes Jon Kleinberg, a professor of computer science at Cornell University. Kleinberg’s research focuses on issues at the interface of networks and information, with an emphasis on the social and information networks that underpin the web and other online media. He is a member of the National Academy of Sciences, the National Academy of Engineering, and the American Academy of Arts and Sciences, and serves on the Computer and Information Science and Engineering (CISE) Advisory Committee of the National Science Foundation, and the Computer Science and Telecommunications Board (CSTB) of the National Research Council.

In this talk, Kleinberg proposes a revised method for online platforms to optimize user experience, based on an insight that users have inconsistent preferences and their activity does not always reflect their preferences. Using a framework guided by two conflicting sets of user preferences—one that operates impulsively in the moment, and one that makes plans over longer time scales—Kleinberg will explore new insights regarding interactions between design, behavioral science, and social media.

Talk title:

“The challenge of understanding what users want: Inconsistent preferences and engagement optimization”

Abstract:

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, behaviours that feel entirely familiar on online platforms. 

In this work, we develop a model of media consumption where users have inconsistent preferences. We consider what happens when a platform that simply wants to maximize user utility is only able to observe behavioral data in the form of user engagement. Our framework is based on a stochastic model of user behaviour, in which users are guided by two conflicting sets of preferences—one that operates impulsively in the moment, and the other of which makes plans over longer time-scales. By linking the behaviour of this model to abstractions of platform design choices, we can develop a theoretical framework and vocabulary in which to explore interactions between design, behavioral science, and social media. 

This talk is based on joint work with Sendhil Mullainathan and Manish Raghavan.


Recommended readings:

Kleinberg, Jon, Sendhil Mullainathan, and Manish Raghavan. “The challenge of understanding what users want: Inconsistent preferences and engagement optimization.” Management Science (2023).


About Jon Kleinberg

Jon Kleinberg is the Tisch University Professor in the Departments of Computer Science and Information Science at Cornell University. His research focuses on the interaction of algorithms and networks, the roles they play in large-scale social and information systems, and their broader societal implications. He is the author of the textbooks Algorithm Design (with Éva Tardos, Pearson/Addison-Wesley, 2006) and Networks, Crowds, and Markets (with David Easley, Cambridge University Press, 2009). He is a member of the US National Academies of Sciences and Engineering and serves on the US National AI Advisory Committee. He has received MacArthur, Packard, Simons, Sloan, and Vannevar Bush research fellowships, as well as awards including the Nevanlinna Prize, the Allen Newell Award, and the ACM Prize in Computing. 


About the SRI Seminar Series

The SRI Seminar Series brings together the Schwartz Reisman community and beyond for a robust exchange of ideas that advance scholarship at the intersection of technology and society. Seminars are led by a leading or emerging scholar and feature extensive discussion.

Each week, a featured speaker will present for 45 minutes, followed by an open discussion. Registered attendees will be emailed a Zoom link before the event begins. The event will be recorded and posted online.

Jon Kleinberg

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February 28

SRI Seminar Series: Vincent Conitzer, “Social choice and game theory for AI alignment”