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Mitigating economic impacts of the COVID-19 pandemic and preserving U.S. strategic competitiveness in artificial intelligence / National Security Commission on Artificial Intelligence Commissioners Chris Darby, Gilman Louie, and Dr. Jason Matheny.
- Format:
- Book
- Government document
- Author/Creator:
- Darby, Chris (Investment executive), author.
- Louie, Gilman, author.
- Matheny, Jason, author.
- Series:
- White paper series on pandemic response and preparedness ; No. 2
- Language:
- English
- Subjects (All):
- COVID-19 (Disease)--Economic aspects.
- COVID-19 (Disease).
- Artificial intelligence--Government policy--United States.
- Artificial intelligence.
- Artificial intelligence--Economic aspects--United States.
- Technology and state--United States.
- Technology and state.
- Artificial intelligence--Government policy.
- Artificial intelligence--Economic aspects.
- United States.
- Physical Description:
- 1 online resource (18 pages)
- Place of Publication:
- [Washington, D.C.] : National Security Commission on Artificial Intelligence, [2020?]
- System Details:
- text file
- Summary:
- This paper offers several steps policymakers could take to utilize and protect U.S. capabilities in AI and associated technologies during the current crisis and beyond. AI presents opportunities to help safely reopen and grow the U.S. economic while minimizing the risk of future outbreaks of the virus, but the AI ecosystem itself is one of the most critical sectors in need of assistance and protection from foreign competitors as it weathers the brutal economic crisis. At the same time, policymakers must be circumspect about AI's ability to solve all of the problems created by the pandemic, especially in areas where there is not enough data to fuel machine learning applications.
- Notes:
- In scope of the U.S. Government Publishing Office Cataloging and Indexing Program (C&I) and Federal Depository Library Program (FDLP).
- Includes bibliographical references.
- Description based on online resource; title from PDF title screen (NASCI, viewed on June 8, 2023).
- OCLC:
- 1155624103
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