Organization: Data & Society
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Automation + AI 
Democratizing AI: Principles for Meaningful Public Participation
In this policy brief and video, Michele Gilman summarizes evidence-based recommendations for better structuring public participation processes for AI, and underscores the urgency of enacting them.
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Automation + AI 
The Social Life of Algorithmic Harms
This series of essays seeks to expand our vocabulary of algorithmic harms to help protect against them.
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Automation + AI 
Assembling Accountability: Algorithmic Impact Assessment for the Public Interest
This project maps the challenges of constructing algorithmic impact assessments (AIAs) by analyzing impact assessments in other domains—from the environment to human rights to privacy and identifies ten needed components for a robust impact assessment.
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Automation + AI 
POVERTY LAWGORITHMS: A Poverty Lawyer’s Guide to Fighting Automated Decision-Making Harms on Low-Income Communities
This guide, directed at poverty lawyers, explains automated decision-making systems so lawyers and advocates can better identify the source of their clients' problems and advocate on their behalf. Relevant for practitioners, this report covers key questions around automated decision-making systems.
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Automation + AI
Algorithmic Accountability: A Primer
The primer–originally prepared for the Progressive Congressional Caucus’ Tech Algorithm Briefing–explores the trade-offs and debates about algorithms and accountability across several key ethical dimensions, including fairness and bias; opacity and transparency; and lack of standards for auditing.