Although the use of artificial intelligence (AI) chatbots in public organizations has increased in recent years, crucial gaps remain unresolved, and this paper explores adoption and implementation of chatbots in state government contexts.
This paper describes the policy choices, business practices, and technology innovations that the State of New Jersey is employing to ensure that the right people get benefits — accurately and on time.
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.
The Digital Benefits Wishlist collects on tools, resources, or policy changes needed to improve benefits delivery. Originally created as part of BenCon2023, a conference hosted by the Digital Benefits Network, it continues to grow and accept new wishes.
This article theorizes the wait list as an underexamined vehicle of administrative burden. Focusing on the example of subsidized chidl care, the article's findings suggest wait lists as understudied but consequential sites of opaque policymaking that shape access to critical social services and the legibility of unmet need.
Lightning talks on innovative ideas, approaches, and pilots to understand and improve benefits delivery. This video was recorded at the Digital Benefits Conference (BenCon) at Georgetown University on June 14, 2023.
This study investigates how administrative burdens influence differential receipt of income transfers after a family member loses a job, looking at Unemployment Insurance, Temporary Assistance for Needy Families, and the Supplemental Nutrition Assistance Program.
This study examines how individuals assess administrative burdens and how these views change over time within the context of the Special Supplemental Nutrition Assistance Program for Women, Infants, and Children (WIC).
In May 2020, Stanford's HAI hosted a workshop to discuss the performance of facial recognition technologies that included leading computer scientists, legal scholars, and representatives from industry, government, and civil society. The white paper this workshop produced seeks to answer key questions in improving understandings of this rapidly changing space.
This policy brief offers recommendations to policymakers relating to the computational and human sides of facial recognition technologies based on a May 2020 workshop with leading computer scientists, legal scholars, and representatives from industry, government, and civil society
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
