This academic paper examines how federal privacy laws restrict data collection needed for assessing racial disparities, creating a tradeoff between protecting individual privacy and enabling algorithmic fairness in government programs.
ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT)
NYC's My File NYC and New Jersey's unemployment insurance system improvements demonstrate how successful digital innovations can be scaled across various programs, leveraging trust-building, open-source technology, and strategic partnerships.
Takeaways from a workshop focusing on applying human-centered design to government artificial intelligence (AI) projects, led by Elham Ali, Researcher from the Beeck Center for Social Impact and Innovation.
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.
The team conducted experiments to determine whether clients would be responsive to proactive support offered by a chatbot, and identify the ideal timing of the intervention.
Public procurement in state governments can be slow and inefficient, but artificial intelligence (AI) offers a solution by automating tasks, improving decision-making, and addressing workforce gaps, as highlighted in a joint brief by NASCIO and NASPO.
National Association of State Chief Information Officers (NASCIO)
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.
A training course on using artificial intelligence (AI) tools to de-jargonize government language, with a tutorial on turning a complex piece of government writing into simpler and easier-to-understand language for government employees and residents alike.
Little is known about how agencies are currently using AI systems, and little attention has been devoted to how agencies acquire such tools or oversee their use.
This report explores key questions that a focus on disability raises for the project of understanding the social implications of AI, and for ensuring that AI technologies don’t reproduce and extend histories of marginalization.
