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Join the Department of Philosophy and the Goergen Institute for Data Science for Evaluating AI Capabilities as Affordances: Implications for Decision Support and Redteaming, with Sina Fazelpour, Assistant Professor of Philosophy and Computer Science at Northeastern University, on May 3, 2024 from 3-5 pm in Dewey 2110-D.  This special colloquium is part of our ongoing series of philosophers working on AI ethics. 

Abstract: The rapid organizational uptake of generative AI models has focused research and regulatory attention on evaluating the capabilities and limitations of these tools. For example, the recent Presidential Executive Order has called upon the National Institute of Standards and Technology to create guidelines for evaluating and auditing AI capabilities and risks. Yet, standard approaches that focus on assessing static model properties on benchmark tasks and datasets are insufficient for achieving this task. In this talk, after highlighting some of the key assumptions and choices that underpin standard evaluations, I propose a complementary affordance-based approach in terms of the relational dynamics of technology, users, and environments. I apply the framework to the evaluation of predictive models used as decision support as well as to red-teaming evaluations of generative AI. I show how this perspective can offer a more functionally and ethically robust approach to AI evaluation, while highlighting the precise shortcomings of existing practices. 

Bio: Sina Fazelpour is an Assistant Professor of Philosophy and Computer Science at Northeastern University. He is also a visiting AI fellow at the National Institute of Standards and Technology (NIST), where he contributes to NIST’s efforts on extending and operationalizing its AI Risk Management Framework. He is part of the inaugural cohort of Schmidt Futures AI2050 Early Career Fellows, and the 2020-21 Council Fellow on the World Economic Forum’s Global Future Council on Data Policy. Sina is the co-founder and organizer of the IDEAS summer institute for undergraduate students, which aims to broaden participation in and advance a cross-disciplinary approach towards the field of responsible AI.

Event Details

  • Sylvia Francisco
  • Kristin Galvin-Burwick
  • Antonia Floratos
  • Kristen Love

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