An emerging concern in algorithmic fairness is the tension with privacy interests. Data minimization can restrict access to protected attributes, such as race and ethnicity, for bias assessment and mitigation. This paper examines how this “privacy-bias tradeoff” has become an important battleground for fairness assessments in the U.S. government and provides rich lessons for resolving these tradeoffs.
ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT)
This guidebook offers an introduction to the risks of discrimination when using automated decision-making systems. This report also includes helpful definitions related to automation.
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.
This MOA outlines Hawai'i's legal data sharing agreement between the Women, Infants and Children Services Branch of the Department of Health (DOH/WIC), and the Benefit, Employment and Support Services Division of the Department of Human Services (DHS/BESSD) to exchange SNAP and WIC data.
This quarterly research update aims to highlight key learnings related to improving unemployment insurance (UI) systems in the areas of equity, timeliness, and fraud, and monitor for model UI legislation and policy related specifically to technology. Subscribe to receive future editions.
This video shows you how to get started with using Generative AI tools, including Bard, Bing, and ChatGPT, in your work as public sector professionals.
The Better Government Lab at the McCourt School of Public Policy at Georgetown University has developed a new scale for measuring the experience of burden when accessing public benefits. They offer both a three-item scale and a single-item scale, which can be utilized for any public benefit program. The shorter scales provide a less burdensome way to measure by requiring less information from users.
