This analysis examines the surge in U.S. state-level AI legislation in 2023, highlighting enacted laws, proposed bills, and emerging regulatory trends.
This report by EPIC investigates how automated decision-making (ADM) systems are used across Washington, D.C.’s public services and the resulting impacts on equity, privacy, and access to benefits.
This essay explains why the Center on Privacy & Technology has chosen to stop using terms like "artificial intelligence," "AI," and "machine learning," arguing that such language obscures human accountability and overstates the capabilities of these technologies.
This academic paper examines predictive optimization, a category of decision-making algorithms that use machine learning (ML) to predict future outcomes of interest about individuals. Through this examination, the authors explore how predictive optimization can raise concerns that make its use illegitimate and challenge claims about predictive optimization's accuracy, efficiency, and fairness.
In accordance with Executive Order 13960, Promoting the Use of Trustworthy Artificial Intelligence in the Federal Government, Federal agencies began publishing their first annual inventories of artificial intelligence (AI) use cases in June 2022.
A guide from the General Service Administration to help government decision makers clearly see what AI means for their agencies and how to invest and build AI capabilities.
