Data (Re)Makes the World

127 Wall Street,New Haven CT 06511

31 March, 2023

Description

Artificial intelligence, data science, and algorithmic approaches to decision making often assume we can better describe and predict social phenomena through the collection, imputation, and manipulation of data. But the problems and issues of how to measure, how to count, and what counts in counting, have a long history that predates the digital revolution. Quantifying social life shapes not only what we know but how we know. It simultaneously describes, imposes perspectives, and presupposes values. New forms of quantification and data analysis displace earlier ways of understanding. They may transform and threaten existing practices and professions, and, in the process, create social conflict and breed distrust. Using machine learning systems to augment or replace human decision making may conflict with existing social norms, political values, and legal interpretations. The rise and spread of machine learning systems, and of algorithmic decision making more generally, have spurred calls for legal and social reform. But these technologies may also change people’s existing values, lead to new political and cultural norms, and novel conceptions (and measures) of community, justice, and equality. We seek paper submissions that investigate the ways our quantification practices are informing and reshaping our values and our communities—including the effects on democratic representation, civil rights, civil liberties, civil and criminal justice, and the promotion of sound public policy. We are particularly interested in papers discussing artificial intelligence, machine learning, and algorithmic decision-making, but also welcome papers that explore quantification practices across different times, places, and cultures. We hope to bring together an interdisciplinary group of scholars, technologists, and policy activists working in and outside of the academy, including but not limited to those working in and across the disciplines of history, public health, philosophy, anthropology, sociology, computer science, statistics, mathematics, economics, cultural studies, medicine, and law.