Computing Power and the Governance of Artificial Intelligence
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Abstract (arXiv)
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.
Key facts. Cited by 38 papers in the map (data through 7 Oct 2026). First posted on arXiv 13 Feb 2024.
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Citing papers per year: 2024: 10; 2025: 13; 2026: 15.
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- 2024Knowledge Mechanisms in Large Language Models: A Survey and Perspectivecited by 50
- 2024Immunization against harmful fine-tuning attackscited by 33
- 2024Training Compute Thresholds: Features and Functions in AI Regulationcited by 13
- 2024Responsible Reporting for Frontier AI Developmentcited by 10
- 2024Societal Adaptation to Advanced AIcited by 10
- 2024Trust AI Regulation? Discerning users are vital to build trust and effective AI regulationcited by 9
- 2024Verification methods for international AI agreementscited by 9
- 2025The Singapore Consensus on Global AI Safety Research Prioritiescited by 9
- 2026Path-conditioned training: a principled way to rescale ReLU neural networkscited by 6
- 2024Panacea: Novel DNN Accelerator using Accuracy-Preserving Asymmetric Quantization and Energy-Saving Bit-Slice Sparsitycited by 5
- 2025A Theory of Inference Compute Scaling: Reasoning through Directed Stochastic Skill Searchcited by 5
- 2026Self-Improvement of Large Language Models: A Technical Overview and Future Outlookcited by 5
26 more
- 2025The Jumping Reasoning Curve? Tracking the Evolution of Reasoning Performance in GPT-[n] and o-[n] Models on Multimodal Puzzlescited by 4
- 2025Trends in AI Supercomputerscited by 4
- 2024Towards Data Governance of Frontier AI Modelscited by 3
- 2025International Agreements on AI Safety: Review and Recommendations for a Conditional AI Safety Treatycited by 3
- 2025Distinguishing Task-Specific and General-Purpose AI in Regulationcited by 3
- 2025Agentic Inequalitycited by 3
- 2026Detecting Hidden ML Training With Zero-Overhead Telemetrycited by 3
- 2025Practical Principles for AI Cost and Compute Accountingcited by 2
- 2025Position: Neglecting the Sustainability of AI is Fuelling a Global AI Arms Racecited by 2
- 2025Distributed and Decentralised Training: Technical Governance Challenges in a Shifting AI Landscapecited by 2
- 2025Technical Requirements for Halting Dangerous AI Activitiescited by 2
- 2024Countering Autonomous Cyber Threatscited by 1
- 2025Trends in Frontier AI Model Count: A Forecast to 2028cited by 1
- 2025Compute Requirements for Algorithmic Innovation in Frontier AI Modelscited by 1
- 2026Comprehensive AI governance requires addressing non-model gainscited by 1
- 2026LLM-Enabled Multi-Agent Systems: Empirical Evaluation and Insights into Emerging Design Patterns & Paradigmscited by 0
- 2026The Economics of AI Supply Chain Regulationcited by 0
- 2026Precautionary Governance of Autonomous AI: Legal Personhood as Functional Instrumentcited by 0
- 2026Is Decentralized AI Governable? From Regulative Policy to Constitutive Protocolcited by 0
- 2026AI Researchers Must Help Lead Arms Control to Mitigate Military AI Riskscited by 0
- 2026Decentralised AI Training and Inference with BlockTraincited by 0
- 2026Hardware Mechanisms to Dynamically Throttle AI Performancecited by 0
- 2026The Closing Window: How Governments Could Lose Their Ability to Restrain Advanced AIcited by 0
- 2026Resourced Authority A Mechanism-Design Model for Participatory Governance of Deployed AI Agentscited by 0
- 2026GPS-Bench: A Governance Policy Benchmark for Automating Policy Analysiscited by 0
- 2026The End of AI Exponentiation: Fluttering Inside and Outside AI Bubblecited by 0
- 2026The End of AI Exponentiation: Fluttering Inside and Outside AI Bubble5 Sep 2026
- 2026GPS-Bench: A Governance Policy Benchmark for Automating Policy Analysis3 Sep 2026
- 2026Resourced Authority A Mechanism-Design Model for Participatory Governance of Deployed AI Agents6 Aug 2026
- 2026Hardware Mechanisms to Dynamically Throttle AI Performance20 Jul 2026
- 2026The Closing Window: How Governments Could Lose Their Ability to Restrain Advanced AI26 Jun 2026
- 2026Decentralised AI Training and Inference with BlockTrain23 Jun 2026
- 2026Detecting Hidden ML Training With Zero-Overhead Telemetry17 Jun 2026
- 2026AI Researchers Must Help Lead Arms Control to Mitigate Military AI Risks10 Jun 2026
- 2026Is Decentralized AI Governable? From Regulative Policy to Constitutive Protocol23 May 2026
- 2026Comprehensive AI governance requires addressing non-model gains1 May 2026
- 2026Self-Improvement of Large Language Models: A Technical Overview and Future Outlook26 Mar 2026
- 2026Precautionary Governance of Autonomous AI: Legal Personhood as Functional Instrument14 Mar 2026
26 more
- 2026The Economics of AI Supply Chain Regulation13 Mar 2026
- 2026Path-conditioned training: a principled way to rescale ReLU neural networks23 Feb 2026
- 2026LLM-Enabled Multi-Agent Systems: Empirical Evaluation and Insights into Emerging Design Patterns & Paradigms6 Jan 2026
- 2025Agentic Inequality19 Oct 2025
- 2025Compute Requirements for Algorithmic Innovation in Frontier AI Models13 Jul 2025
- 2025Technical Requirements for Halting Dangerous AI Activities13 Jul 2025
- 2025Distributed and Decentralised Training: Technical Governance Challenges in a Shifting AI Landscape10 Jul 2025
- 2025The Singapore Consensus on Global AI Safety Research Priorities25 Jun 2025
- 2025Distinguishing Task-Specific and General-Purpose AI in Regulation19 Jun 2025
- 2025A Theory of Inference Compute Scaling: Reasoning through Directed Stochastic Skill Search10 Jun 2025
- 2025Trends in AI Supercomputers22 Apr 2025
- 2025Trends in Frontier AI Model Count: A Forecast to 202821 Apr 2025
- 2025International Agreements on AI Safety: Review and Recommendations for a Conditional AI Safety Treaty18 Mar 2025
- 2025Position: Neglecting the Sustainability of AI is Fuelling a Global AI Arms Race27 Feb 2025
- 2025Practical Principles for AI Cost and Compute Accounting21 Feb 2025
- 2025The Jumping Reasoning Curve? Tracking the Evolution of Reasoning Performance in GPT-[n] and o-[n] Models on Multimodal Puzzles3 Feb 2025
- 2024Panacea: Novel DNN Accelerator using Accuracy-Preserving Asymmetric Quantization and Energy-Saving Bit-Slice Sparsity13 Dec 2024
- 2024Towards Data Governance of Frontier AI Models5 Dec 2024
- 2024Countering Autonomous Cyber Threats23 Oct 2024
- 2024Verification methods for international AI agreements28 Aug 2024
- 2024Knowledge Mechanisms in Large Language Models: A Survey and Perspective22 Jul 2024
- 2024Training Compute Thresholds: Features and Functions in AI Regulation17 May 2024
- 2024Societal Adaptation to Advanced AI16 May 2024
- 2024Responsible Reporting for Frontier AI Development3 Apr 2024
- 2024Trust AI Regulation? Discerning users are vital to build trust and effective AI regulation14 Mar 2024
- 2024Immunization against harmful fine-tuning attacks26 Feb 2024
- 2024Knowledge Mechanisms in Large Language Models: A Survey and Perspectivecited by 50
- 2024Immunization against harmful fine-tuning attackscited by 33
- 2024Training Compute Thresholds: Features and Functions in AI Regulationcited by 13
- 2024Responsible Reporting for Frontier AI Developmentcited by 10
- 2024Societal Adaptation to Advanced AIcited by 10
- 2024Trust AI Regulation? Discerning users are vital to build trust and effective AI regulationcited by 9
- 2024Verification methods for international AI agreementscited by 9
- 2025The Singapore Consensus on Global AI Safety Research Prioritiescited by 9
- 2026Path-conditioned training: a principled way to rescale ReLU neural networkscited by 6
- 2024Panacea: Novel DNN Accelerator using Accuracy-Preserving Asymmetric Quantization and Energy-Saving Bit-Slice Sparsitycited by 5
- 2025Trends in AI Supercomputerscited by 4
- 2024Towards Data Governance of Frontier AI Modelscited by 3
12 most cited of 33 All 33 (JSON)
- 2026The End of AI Exponentiation: Fluttering Inside and Outside AI Bubble5 Sep 2026
- 2026GPS-Bench: A Governance Policy Benchmark for Automating Policy Analysis3 Sep 2026
- 2026Resourced Authority A Mechanism-Design Model for Participatory Governance of Deployed AI Agents6 Aug 2026
- 2026Hardware Mechanisms to Dynamically Throttle AI Performance20 Jul 2026
- 2026The Closing Window: How Governments Could Lose Their Ability to Restrain Advanced AI26 Jun 2026
- 2026Decentralised AI Training and Inference with BlockTrain23 Jun 2026
- 2026Detecting Hidden ML Training With Zero-Overhead Telemetry17 Jun 2026
- 2026AI Researchers Must Help Lead Arms Control to Mitigate Military AI Risks10 Jun 2026
- 2026Is Decentralized AI Governable? From Regulative Policy to Constitutive Protocol23 May 2026
- 2026Comprehensive AI governance requires addressing non-model gains1 May 2026
- 2026Precautionary Governance of Autonomous AI: Legal Personhood as Functional Instrument14 Mar 2026
- 2026The Economics of AI Supply Chain Regulation13 Mar 2026
12 newest of 33 All 33 (JSON)