Debates about the societal influence of data and automation cannot meaningfully happen without an evidence base, drawn from empirical research, that challenges the hype and fear surrounding sociotechnical systems. At Data & Society, we pursue frame-breaking research questions informed by the realities of those who may be adversely affected by the integration and implementation of these technologies.
Research
Research Tracks
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Labor Futures
We interrogate how technology is disrupting, destabilizing, and transforming many aspects of work and employment.
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AI on the Ground
We use social science to develop robust analyses of AI systems; effectively assess the impact of AI systems; and inform future design, use, and governance.
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Trustworthy Infrastructures
We explore how diverse sets of communities shape their collective responses to top-down technological solutions.
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Climate, Technology, and Justice
With a focus on people and communities, our research explores the full spectrum of environmental concerns connected to technology.
Cross-Cutting Themes
Featured Reports
Report
Establishing Vigilant Care: Data Infrastructures and the Black Birthing Experience
Joan Mukogosi
Book
Keywords of the Datafied State
Jenna Burrell, Ranjit Singh, Patrick Davison, et al.
Report
Blooming in Muddy Waters: DEI at AI Ethics Conferences
Emnet Tafesse, Meg Young, Jacob Metcalf, Ranjit Singh
Report
A Primer on AI in/from the Majority World
Sareeta Amrute, Ranjit Singh, Rigoberto Lara Guzmán
Our Approach to Research
Fellowship Highlights
Capstone Conversations: 2022-23 Race & Technology Fellows
Lindsey Cameron, Christina Harrington, Sareeta Amrute
In Fellowship: Capstone Conversation
Chaz Arnett, Tamara K. Nopper, Tiara Roxanne, Murali Shanmugavelan, Sareeta Amrute
Race, Surveillance, Resistance
Tamara K. Nopper, Alyx Goodwin, Raúl Carrillo, Chaz Arnett
Black Lives Monitored
Chaz Arnett
Latest Academic Publishing
Proverbial Economies of STS
Read in Social Studies of Science
Null Compliance: NYC Local Law 144 and the Challenges of Algorithm Accountability
Read in ACM FAccT
Auditing Work: Exploring the New York City algorithmic bias audit regime
Read in ACM FAccT
Carbon Emissions in the Tailpipe of Generative AI
Read in Harvard Data Science Review
A Collective Work Agenda for the Digital Economy
Read in Friedrich Ebert Stiftung
Participatory versus Scale: Tensions in the Practical Demands on Participatory AI
Read in First Monday
Introduction for the special issue of “Ideologies of AI and the consolidation of power”: Naming power
Read in First Monday
'Scaling Up Mischief: Red-Teaming AI and Distributing Governance
Read in Harvard Data Science Review