title: Computing Power and the Governance of Artificial Intelligence
summary: Computing power, or "compute," is crucial for the development and deployment
  of artificial intelligence (AI) capabilities. As a result, governments and
  companies have started to leverage compute as a means to govern AI. For
  example, governments are investing in domestic compute capacity, controlling
  the flow of compute to competing countries, and subsidizing compute access to
  certain sectors. However, these efforts only scratch the surface of how compute
  can be used to govern AI development and deployment. Relative to other key
  inputs to AI (data and algorithms), AI-relevant compute is a particularly
  effective point of intervention: it is detectable, excludable, and
  quantifiable, and is produced via an extremely concentrated supply chain. These
  characteristics, alongside the singular importance of compute for cutting-edge
  AI models, suggest that governing compute can contribute to achieving common
  policy objectives, such as ensuring the safety and beneficial use of AI. More
  precisely, policymakers could use compute to facilitate regulatory visibility
  of AI, allocate resources to promote beneficial outcomes, and enforce
  restrictions against irresponsible or malicious AI development and usage.
  However, while compute-based policies and technologies have the potential to
  assist in these areas, there is significant variation in their readiness for
  implementation. Some ideas are currently being piloted, while others are
  hindered by the need for fundamental research. Furthermore, naive or poorly
  scoped approaches to compute governance carry significant risks in areas like
  privacy, economic impacts, and centralization of power. We end by suggesting
  guardrails to minimize these risks from compute governance.
paper_authors._id: 65cda3264c7d24132a3a38e1
paper_authors.name: Girish Sastry
paper_authors._id: 65cda3264c7d24132a3a38e2
paper_authors.name: Lennart Heim
paper_authors._id: 65cda3264c7d24132a3a38e3
paper_authors.name: Haydn Belfield
paper_authors._id: 65cda3264c7d24132a3a38e4
paper_authors.name: Markus Anderljung
paper_authors._id: 65cda3264c7d24132a3a38e5
paper_authors.name: Miles Brundage
paper_authors._id: 65cda3264c7d24132a3a38e6
paper_authors.name: Julian Hazell
paper_authors._id: 65cda3264c7d24132a3a38e7
paper_authors.name: Cullen O'Keefe
paper_authors._id: 65cda3264c7d24132a3a38e8
paper_authors.name: Gillian K. Hadfield
paper_authors._id: 65cda3264c7d24132a3a38e9
paper_authors.name: Richard Ngo
paper_authors._id: 65cda3264c7d24132a3a38ea
paper_authors.name: Konstantin Pilz
paper_authors._id: 65cda3264c7d24132a3a38eb
paper_authors.name: George Gor
paper_authors._id: 65cda3264c7d24132a3a38ec
paper_authors.name: Emma Bluemke
paper_authors._id: 65cda3264c7d24132a3a38ed
paper_authors.name: Sarah Shoker
paper_authors._id: 65cda3264c7d24132a3a38ee
paper_authors.name: Janet Egan
paper_authors._id: 65cda3264c7d24132a3a38ef
paper_authors.name: Robert F. Trager
paper_authors._id: 65cda3264c7d24132a3a38f0
paper_authors.name: Shahar Avin
paper_authors._id: 65cda3264c7d24132a3a38f1
paper_authors.name: Adrian Weller
paper_authors._id: 65cda3264c7d24132a3a38f2
paper_authors.name: Yoshua Bengio
paper_authors._id: 65cda3264c7d24132a3a38f3
paper_authors.name: Diane Coyle
paper_title: Computing Power and the Governance of Artificial Intelligence
paper_summary: Computing power, or "compute," is crucial for the development and deployment
  of artificial intelligence (AI) capabilities. As a result, governments and
  companies have started to leverage compute as a means to govern AI. For
  example, governments are investing in domestic compute capacity, controlling
  the flow of compute to competing countries, and subsidizing compute access to
  certain sectors. However, these efforts only scratch the surface of how compute
  can be used to govern AI development and deployment. Relative to other key
  inputs to AI (data and algorithms), AI-relevant compute is a particularly
  effective point of intervention: it is detectable, excludable, and
  quantifiable, and is produced via an extremely concentrated supply chain. These
  characteristics, alongside the singular importance of compute for cutting-edge
  AI models, suggest that governing compute can contribute to achieving common
  policy objectives, such as ensuring the safety and beneficial use of AI. More
  precisely, policymakers could use compute to facilitate regulatory visibility
  of AI, allocate resources to promote beneficial outcomes, and enforce
  restrictions against irresponsible or malicious AI development and usage.
  However, while compute-based policies and technologies have the potential to
  assist in these areas, there is significant variation in their readiness for
  implementation. Some ideas are currently being piloted, while others are
  hindered by the need for fundamental research. Furthermore, naive or poorly
  scoped approaches to compute governance carry significant risks in areas like
  privacy, economic impacts, and centralization of power. We end by suggesting
  guardrails to minimize these risks from compute governance.