Machine Learning and the Social Sciences

Two Workshops Co-organized by the
School of Mathematics
and the
School of Social Science

Sanjeev Arora, Princeton University/Institute for Advanced Study
Didier Fassin, Institute for Advanced Study
Jacob Foster, University of California, Los Angeles
Marion Fourcade, University of California, Berkeley/Institute for Advanced Study

First Workshop: Workshop on Social and Ethical Challenges in Machine Learning
Date: November 6, 2019
Location: Institute for Advanced Study, Princeton

This invitation-only workshop will bring together experts in machine learning and social scientists in an effort to reflect on the social and ethical challenges of producing machine learning and using it "in the wild."  Possible topics include the social and ethical issues related to: the global digital labor market that supports many practical applications of ML;  the impact of AI advances on work and occupations; unchartered territories for the application of new learning methods; public attitudes toward (and understandings of) artificial intelligence; deep fakes, democracy and the transformation of civic discourses; possible biases and discrimination embedded in predictive analytics (e.g. from search to policing and sentencing, from HR to dating, from social services to marketing); human sense making, opacity and machine learning outcomes; the promises and pitfalls of using AI to manage and control individuals and  populations (e.g. via the generalized surveillance and scoring of individuals, as in the social credit system); the AI-induced reconfiguration of emotions, desires, and cognition; and cross-national differences in the implementation and regulation of machine learning.

Workshop Schedule
Public Event

Second Workshop: Title TBA
Date: March 4-5, 2020
Location: Institute for Advanced Study, Princeton

Workshop description TBA

Workshop Website