This paper introduces a framework for algorithmic auditing that supports artificial intelligence system development end-to-end, to be applied throughout the internal organization development lifecycle.
ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT)
This policy brief offers recommendations to policymakers relating to the computational and human sides of facial recognition technologies based on a May 2020 workshop with leading computer scientists, legal scholars, and representatives from industry, government, and civil society
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.
An article examining how automation and AI are being used in welfare systems, arguing that digital benefits administration often reproduces longstanding patterns of surveillance, exclusion, and inequality.
This post introduces EPIC's exploration of actionable recommendations and points of agreement from leading A.I. frameworks, beginning with the National Institute of Standards and Technology's AI Risk Management Framework.
