A National Program for Building Artificial Intelligence within Communities

Author: Fernando Delgado


Summary 

While the United States is a global leader in Artificial Intelligence (AI) research and development (R&D), there has been growing concern that this may not last in the coming decade. China’s massive, state-based tech-investment schemes have catapulted the country to the status of a true competitor over the development and export of AI technologies. In response, there have been repeated calls as well as actions by the Federal Government to step up its funding of fundamental and defense AI research. Yet, maintaining our status as a global leader in AI will require not only a focus on fundamental and defense research. As a matter of domestic policy, we must also attend to the growing chasm that increasingly separates advances in state-of-the-art AI techniques from effective and responsible adoption of AI across American society and economy.


To address this chasm, the Biden-Harris Administration should establish an applied AI research program within the National Institute of Standards and Technology (NIST) to help community-serving organizations tackle the technological and ethical challenges involved in developing AI systems. This new NIST program would fill a key domestic policy gap in our nation’s AI R&D strategy by addressing the growing obstacles and uncertainty confronting AI integration, while broadening the reach of AI as a tool for economic and social betterment nationwide. Program funding would be devoted to research projects co-led by AI researchers and community-based practitioners who would ultimately oversee and operate the AI technology. Research teams would be tasked with co-designing and evaluating an AI system in light of the specific challenges faced by community institutions. Specific areas poised to benefit from this unique multi-stakeholder and cross-sectoral approach development include healthcare, municipal government, and social services.


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About the Author

Fernando Delgado is a PhD candidate in Information Science at Cornell University. Prior to commencing his doctoral studies, Fernando worked at H5, a pioneering firm in the field of legal technology designing and deploying algorithmic systems for fact-finding in civil litigation. His current academic research focuses on elaborating and refining design, evaluation, and governance frameworks for automated decision systems in high-stakes domains. He draws on theory and methods from the social science of technology and law, as well as the computational fields of information retrieval and machine learning. His research is supported by the McNair Scholars Program, the MacArthur Foundation program on Technology in the Public Interest, and the Russell Sage Foundation initiative on Computational Social Science.