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Historical analogues that can inform AI governance / Michael J.D. Vermeer.
- Format:
- Book
- Author/Creator:
- Vermeer, Michael J. D.
- Language:
- English
- Subjects (All):
- Artificial intelligence--Law and legislation--United States.
- Public-private sector cooperation.
- Internet--Law and legislation--United States.
- Genetic engineering--Law and legislation--United States.
- Data encryption (Computer science)--Law and legislation--United States.
- Deterrence (Strategy).
- Nuclear weapons--Law and legislation--United States.
- Artificial intelligence.
- Internet.
- Data encryption (Computer science).
- Nuclear weapons.
- Artificial Intelligence.
- Corporate Governance.
- Genetics.
- The Internet.
- Nuclear Deterrence.
- Public Sector Governance.
- Signals Intelligence.
- artificial intelligence.
- Local Subjects:
- Artificial Intelligence.
- Corporate Governance.
- Genetics.
- The Internet.
- Nuclear Deterrence.
- Public Sector Governance.
- Signals Intelligence.
- Place of Publication:
- RAND Corporation 2024
- Summary:
- The increasing capabilities of artificial intelligence (AI) have raised questions about how to maximize its benefits while minimizing the risks that it may pose. Similar questions regarding governance have arisen for four technologies in recent decades: nuclear technology, the Internet, encryption products, and genetic engineering. The histories of their governance illustrate three themes: the need for consensus on norms for the technology, important differences in the governance of physical and nonphysical assets, and the role of partnerships between the public and private sectors in governance. These technologies vary in terms of the resources they require to compete in their development, whether their uses are primarily in the public or private sector, the security risks they pose, consensus on these risks, their physical assets that can be controlled, whether they can foster a community of shared interests for governance, and whether public or private governance is best suited for minimizing risks and maximizing benefits.
- Contents:
- CHAPTER 1: The Urgency of Governance for Artificial Intelligence
- CHAPTER 2: Historical Analogues for AI Governance
- CHAPTER 3: Lessons for AI Governance
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