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Small Alberta company making waves with what is shaping up to be the largest gaming convention in Western Canada

Dalit Student s Suicide Points to Well-Known – But Ignored – Caste Discrimination in IITs

CITP Distinguished Lecture Series: Jon Kleinberg, The Challenge of Understanding What Users Want: Inconsistent Preferences and Engagement Optimization

Please register here to attend in person. 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

Reactions: Princeton faculty discuss ChatGPT in the classroom

Princeton faculty members Arvind Narayanan, Sarah Case, Steven Kelts, and Matt Weinberg discuss the utility (and futility) of using ChatGPT in the classroom and on assignments — and what ChatGPT reveals about the value of education.

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