March 28, 2024
To Govern AI, We Must Govern Compute
Computing power—compute, for short—is a key driver of artificial intelligence (AI) progress. Over the past 13 years, the amount of compute used to train leading AI systems has increased by a factor of 350 million. This has enabled the major AI advances that have recently gained global attention. However, compute is important not only for the progress of AI but also for its governance. Governments have taken notice. As we argue in a recent paper, they are increasingly engaged in compute governance: using compute as a lever to pursue AI policy goals, such as limiting misuse risks, supporting domestic industries, or engaging in geopolitical competition.
The Biden administration introduced export controls on advanced semiconductor manufacturing equipment and the most high-end AI-relevant chips, aimed at undercutting Chinese access to leading-edge AI applications. In October 2023, the administration’s executive order “On the Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence” introduced reporting requirements on models trained using more compute (1026 operations) than any that have been trained to date. Overseas, the EU’s AI Act will place additional requirements on foundation models trained using more than 1025 operations, currently covering three or four existing systems (GPT-4, Gemini Ultra, Claude 3, and Inflection 2).
Just because compute can be used as a tool to govern AI doesn’t mean it should be used in all cases.
The Biden administration introduced export controls on advanced semiconductor manufacturing equipment and the most high-end AI-relevant chips, aimed at undercutting Chinese access to leading-edge AI applications. In October 2023, the administration’s executive order “On the Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence” introduced reporting requirements on models trained using more compute (1026 operations) than any that have been trained to date. Overseas, the EU’s AI Act will place additional requirements on foundation models trained using more than 1025 operations, currently covering three or four existing systems (GPT-4, Gemini Ultra, Claude 3, and Inflection 2).
States understand the importance of compute. The U.S. and the EU are both investing $50 billion in subsidies through their Chips Acts. Companies understand its importance, too. Almost all start-ups working on advanced AI have entered into “compute partnerships” with U.S. Big Tech compute providers. This includes most recently the French company Mistral, even though it had branded itself as a French-European national champion. Microsoft is reportedly investing $50 billion into expanding its Azure data centers worldwide, one of the biggest corporate infrastructure investments ever. NVIDIA has rocketed up to having the third biggest market capitalization in the world. And to boost compute production, Sam Altman is reportedly trying to raise $7 trillion.
Read the full story and more from Lawfare.
More from CNAS
-
Beyond DeepSeek: How China’s AI Ecosystem Fuels Breakthroughs
Commentary
While the United States should not mimic China’s state-backed funding model, it also can’t leave AI’s future to the market alone....
By Ruby Scanlon
-
Averting AI Armageddon
Reports
In recent years, the previous bipolar nuclear order led by the United States and Russia has given way to a more volatile tripolar one, as China has quantitatively and qualitat...
By Jacob Stokes, Colin H. Kahl, Andrea Kendall-Taylor & Nicholas Lokker
-
France Pursues an AI “Third Way”
Commentary
This AI third way is not AI sovereignty in a traditional sense, which at a high level is a nation’s policy of placing the development, deployment, and control of AI models, in...
By Pablo Chavez
-
How Can We Develop AI That Helps, Rather Than Harms, People?
Commentary
In every technological revolution, we face a choice: build for freedom or watch as others build for control. With AI the stakes couldn’t be higher. It already mediates 20 per ...
By Brendan McCord
