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)
In this piece, the Digital Benefits Network shares several sources—from journalistic pieces, to reports and academic articles—we’ve found useful and interesting in our reading on automation and artificial intelligence.
While most data sharing and integration occurs within a legal and governance framework, an emphasis on racial equity, transparency, and community engagement is often peripheral. This report focuses on the importance of a racial equity lens in data integration.
In this piece, the Digital Benefits Network shares several sources—from journalistic pieces, to reports and academic articles—we’ve found useful and interesting in our reading on automation and artificial intelligence.
Hear perspectives on topics including centering beneficiaries and workers in new ways, digital service delivery, digital identity, and automation.This video was recorded at the Digital Benefits Conference (BenCon) on June 14, 2023.
This paper argues that a human rights framework could help orient the research on artificial intelligence away from machines and the risks of their biases, and towards humans and the risks to their rights, helping to center the conversation around who is harmed, what harms they face, and how those harms may be mitigated.
2022 ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization
Through a field scan, this paper identifies emerging best practices as well as methods and tools that are becoming commonplace, and enumerates common barriers to leveraging algorithmic audits as effective accountability mechanisms.
ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT)
