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.
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.
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
Artificial intelligence promises exciting new opportunities for the government to make policy, deliver services and engage with residents. But government procurement practices need to adapt if we are to ensure that rapidly-evolving AI tools meet intended purposes, avoid bias, and minimize risks to people, organizations, and communities. This report lays out five distinct challenges related to procuring AI in government.
This reporting explores how algorithms used to screen prospective tenants, including those waiting for public housing, can block renters from housing based on faulty information.
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.
This panel discussion from the Academy's 2025 Policy Summit explores the intersection of artificial intelligence (AI) and public benefits, examining how technological advancements are influencing policy decisions and the delivery of social services.
Sarah Bargal provides an overview of AI, machine learning, and deep learning, illustrating their potential for both positive and negative applications, including authentication, adversarial attacks, deepfakes, generative models, personalization, and ethical concerns.
