This report analyzes lawsuits that have been filed within the past 10 years arising from the use of algorithm-driven systems to assess people’s eligibility for, or the distribution of, public benefits. It identifies key insights from the various cases into what went wrong and analyzes the legal arguments that plaintiffs have used to challenge those systems in court.
The article discusses the phenomenon of model multiplicity in machine learning, arguing that developers should be legally obligated to search for less discriminatory algorithms (LDAs) to reduce disparities in algorithmic decision-making.
Executed on September 24, 2024, a memorandum for the heads of executive departments and agencies on advancing the responsible acquisition of artificial intelligence in government.
This course is designed to help public professionals accelerate the process of finding and implementing urgently-needed evidence-based solutions to public problems.
This paper introduces the problem of semi-automatically building decision models from eligibility policies for social services, and presents an initial emerging approach to shorten the route from policy documents to executable, interpretable and standardised decision models using AI, NLP and Knowledge Graphs. There is enormous potential of AI to assist government agencies and policy experts in scaling the production of both human-readable and machine executable policy rules, while improving transparency, interpretability, traceability and accountability of the decision making.
In this interview, Code for America staff members share how client success, data science, and qualitative research teams work together to consider the responsible deployment of artificial intelligence (AI) in responding to clients who seek assistance with three products.
The Center for Democracy and Technology's brief clarifies misconceptions about artificial intelligence (AI) in government services, emphasizing the need for precise definitions, awareness of AI's limitations, recognition of inherent biases, and acknowledgment of the significant resources required for effective implementation.
This policy supports the appropriate development, deployment, and use of generative artificial intelligence (GenAI) systems, products, services, tools, and content within consolidated state agencies in Colorado.
Colorado Governor's Office of Information Technology (OIT)
The Digital Benefit Network's Digital Identity Community of Practice held a session to hear considerations from civil rights technologists and human-centered design practitioners on ways to ensure program security while simultaneously promoting equity, enabling accessibility, and minimizing bias.
The team developed an AI-powered explanation feature that effectively translates complex, multi-program policy calculations into clear and accessible explanations, enabling users to explore "what-if" scenarios and understand key factors influencing benefit amounts and eligibility thresholds.
Webinar that shares Nava’s partnership with the Gates Foundation and the Benefits Data Trust that seeks to answer if generative and predictive AI can be used ethically to help reduce administrative burdens for benefits navigators.
