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White Papers

HAI’s white papers take a deeper dive into AI/ML research. Driven by faculty, researchers, students, and staff, these white papers aim to inform policymakers on cutting-edge research related to emerging technologies.


Enhancing International Cooperation in AI Research: The Case for a Multilateral AI Research InstituteWhite Paper

May 2022
Developing responsible, human-centered AI is a complex and resource-intensive task. As governments around the world race to meet the opportunities and challenges of developing AI, there remains an absence of deep, technical international cooperation that allows like-minded countries to leverage one another’s resources and competitive advantages to facilitate cutting-edge AI research in a manner that upholds and promotes democratic values. In its final report, the National Security Commission on Artificial Intelligence (NSCAI) recommended that the United States work closely with key allies and partners to establish a MAIRI and called for congressional authorization and funding to allow the National Science Foundation (NSF) to lead the effort. Built upon these recommendations, this white paper outlines a blueprint for an AI research institute that can champion human-centered approaches to conducting AI research, promote multi-stakeholder international R&D cooperation to unleash innovation and economic prosperity, and cultivate AI talent.

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Recommendations on Updating the National Artificial Intelligence Research and Development Strategic PlanWhite Paper

March 2022
Stanford HAI submitted this response in March 2022 to support the work of the White House Office of Science and Technology Policy to update the National Artificial Intelligence Research and Development Strategic Plan. We offered a set of recommendations for eight strategies, including boosting non-defense AI R&D budgets, particularly on AI-related infrastructure, to support long-term investments; increasing support for interdisciplinary and multidisciplinary AI research on human-AI collaboration that expands beyond exclusively technical research; strengthening partnerships with academic institutions and build a framework for a public-university-industry AI R&D ecosystem to drive AI development forward; and more. This response was co-led by Daniel E. Ho, Jennifer King, Russell Wald, and Daniel Zhang.

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Advancing a More Productive Tech EconomyWhite Paper

February 2022
Stanford HAI and the Stanford Digital Economy Lab submitted this response in January 2022 to support the work of the National Institute of Standards and Technology (NIST) to advance a more productive technology economy. NIST’s work in this area is more essential than ever as remote work, artificial intelligence (AI), and other new technologies change the job landscape and the future of the economy. In this submission, we discuss why productivity has not been sufficiently understood or measured, especially from AI; how AI is still emerging and may help workers and economic growth; and the need for immigration reform to attract and retain top talent. This response was co-led by Erik Brynjolfsson and Georgios Petropoulos.

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Stanford HAI Artificial Intelligence Bill of RightsWhite Paper

January 2022
Stanford HAI submitted this response in January 2022 to support the work of the White House Office of Science and Technology to develop an AI Bill of Rights that safeguards the American public against powerful technologies. We recommend six principles to guide the public and private uses of biometric and broader artificial intelligence technologies, including ensuring those technologies support fundamental democratic values, safeguarding fairness and rights to nondiscrimination, ensuring transparency and explainability, strengthening the participation of civil society organizations, embedding accountability measures into the system design, and enhancing citizen education concerning AI and its impacts. This response was co-led by HAI associate directors, Michele Elam and Rob Reich.

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Building a National AI Research ResourceWhite Paper

October 2021
In late 2019, Stanford HAI co-directors Fei-Fei Li and John Etchemendy were one of the first to issue a call for the U.S. government to create a National Research Cloud (NRC). They envisioned the NRC would be a close partnership between academia, government, industry, and civil society to provide researchers equitable access to high-end computational resources, large-scale government datasets in a secure cloud environment, and necessary expertise to benefit from a NRC. Stanford HAI led efforts with 22 top computer science universities and a bipartisan, bicameral group of lawmakers proposing legislation to bring the NRC to fruition. On January 1, 2021, the U.S. Congress authorized the National AI Research Resource Task Force Act as part of the National Defense Authorization Act for Fiscal Year 2021.

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Evaluating Facial Recognition Technology: A Protocol for Performance Assessment in New DomainsPolicy Resources

November 2020
Facial recognition technology has proliferated throughout society – today it helps us unlock smartphones, access our bank accounts, and receive targeted advertising. FRT is also used in high-stakes situations where the output of the software can lead to substantial effects on a person’s life. This has led to a loud call to understand and regulate the technology. We support the call for rigorous reflection of its use and its accuracy. In this white paper, we look to provide a common understanding of the capabilities and limitations of the technology in order to properly assess its risks and benefits.

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