
The AI Accountability Review translates research to help bridge the gap between knowledge and practice for AI policymakers, practitioners, and researchers.
| Platform | Pricing | Only free issues | Publishes | Weekly | |
|---|---|---|---|---|---|
| Issues | 15 | Subscribers | Read | ai-accountability-review.com |
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A group of researchers with the EvalEval Coalition recently published a new paper on arXiv: “Who Evaluates AI’s Social Impacts? Mapping Coverage and Gaps in First and Third Party Evaluations” where they present an analysis of evaluations of...
Establishing norms and behavioral standards for AI systems is central to the AI Accountability Problem. Over the years, private companies, government agencies, non-profits, and other organizations have put forth a number of AI ethics princi...
One important way to understand standards and expectations for AI system use and behavior is to ask the public. This is critical especially for calls for accountability in social or media forums since they are most exposed to a plurality of...
AI incident monitoring databases like the OECD AI Incident Monitor and the AI Incident Database track cases where AI has created harm. But by sourcing incidents from public news articles they’re limited in the detail they include. So there’...
The writers behind this newsletter.
Professor at Northwestern University. I study Computational Journalism as well as AI, Ethics, and Society.
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