Anthropic just published their submission to the Request for Information for a new US AI Action Plan (OSTP RFI).
It’s 10 pages total and focuses on strengthening the US AISI (and broadly government capacity to test models), strengthening export controls (with some very concrete proposals), enhancing lab security through standards, scaling up energy infrastructure (asking for building infrastructure for 50 GW of power, or about 4% of the entire US grid capacity), accelerating AI adoption in government, and improving government sensemaking around economic impacts.
I recommend reading it. It’s quite insightful regarding the priorities of Anthropic’s policy team right now.
Here’s my summary of the recommendations:
National security testing
Develop robust government capabilities to evaluate AI models (foreign and domestic) for security risks
Once ASL-3 is reached, government should mandate pre-deployment testing
Preserve the AI Safety Institute in the Department of Commerce to advance third-party testing
Direct NIST to develop comprehensive national security evaluations in partnership with frontier AI developers
Build classified and unclassified computing infrastructure for testing powerful AI systems
Assemble interdisciplinary teams with both technical AI and national security expertise
Export Control Enhancement
Tighten semiconductor export restrictions to prevent adversaries from accessing critical AI infrastructure
Control H20 chips
Require government-to-government agreements for countries hosting large chip deployments
As a prerequisite for hosting data centers with more than 50,000 chips from U.S. companies, the U.S. should mandate that countries at high-risk for chip smuggling comply with a government-to-government agreement that 1) requires them to align their export control systems with the U.S., 2) takes security measures to address chip smuggling to China, and 3) stops their companies from working with the Chinese military. The “Diffusion Rule” already contains the possibility for such agreements, laying a foundation for further policy development.
Review and reduce the 1,700 H100 no-license required threshold for Tier 2 countries
Currently, the Diffusion Rule allows advanced chip orders from Tier 2 countries for less than 1,700 H100s —an approximately $40 million order—to proceed without review. These orders do not count against the Rule’s caps, regardless of the purchaser. While these thresholds address legitimate commercial purposes, we believe that they also pose smuggling risks. We recommend that the Administration consider reducing the number of H100s that Tier 2 countries can purchase without review to further mitigate smuggling risks.
Increase funding for Bureau of Industry and Security (BIS) for export enforcement
Lab Security Improvements
Establish classified and unclassified communication channels between AI labs and intelligence agencies for threat intelligence sharing, similar to Information Sharing and Analysis Centers used in critical infrastructure sectors
Create systematic collaboration between frontier AI companies and intelligence agencies, including Five Eyes partners
Elevate collection and analysis of adversarial AI development to a top intelligence priority, as to provide strategic warning and support export controls
Expedite security clearances for AI industry professionals
Direct NIST to develop next-generation security standards for AI training/inference clusters
Develop confidential computing technologies that protect model weights even during processing
Develop meaningful incentives for implementing enhanced security measures via procurement requirements for systems supporting federal government deployments.
Direct DOE/DNI to conduct a study on advanced security requirements that may become appropriate to ensure sufficient control over and security of highly agentic models
Energy Infrastructure Scaling
Set an ambitious national target: build 50 additional gigawatts of power dedicated to AI by 2027
Streamline permitting processes for energy projects by accelerating reviews and enforcing timelines
Expedite transmission line approvals to connect new energy sources to data centers
Work with state/local governments to reduce permitting burdens
Leverage federal real estate for co-locating power generation and next-gen data centers
Government AI Adoption
across the whole of government, the Administration should systematically identify every instance where federal employees process text, images, audio, or video data, and augment these workflows with appropriate AI systems.
Task OMB to address resource constraints and procurement limitations for AI adoption
Eliminate regulatory and procedural barriers to rapid AI deployment across agencies
Direct DoD and Intelligence Community to accelerate AI research, development and procurement
Target largest civilian programs for AI implementation (IRS tax processing, VA healthcare delivery, etc.)
Economic Impact Monitoring
Enhance data collection mechanisms to track AI adoption patterns and economic implications
The Census Bureau’s American Time Use Survey should incorporate specific questions about AI usage, distinguishing between personal and professional applications while gathering detailed information about task types and systems employed.
Update Census Bureau surveys to gather detailed information on AI usage and impacts
Collect more granular data on tasks performed by workers to create a baseline for monitoring changes
Track the relationship between AI computation investments and economic performance
Examine how AI adoption might reshape the tax base and cause structural economic shifts
Nowhere in their RFP do they place restrictions on what kinds of energy capacity they want built. They are asking for a 4% increase in U.S. energy capacity—this is a serious amount of additional CO2 emissions if that capacity isn’t built renewably. But that’s just what they’re asking for now; if they’re serious about building & scaling AGI, they would be asking for much bigger increases, without a strong precedent of carbon-neutrality to back it up. That seems really bad?
Also to pre-empt—the energy capacity has to come before you build an AI powerful enough to ‘solve climate change’. So if they fail to do that, the downside is that they make the problem significantly worse. I think the environmental downsides of attempting to build AGI should be a meaningful part of one’s calculus.
Object-level aside, I suspect they’re aware their audience is the hypersensitive-to-appearances Trump admin, and framing things accordingly. Even basic, common sense points regarding climate change could have a significant cost to the doc’s reception.
Is the assumption here that they would lobby behind the scenes for carbon-neutrality? Because this just sounds like capitulation without a strong line in the sand to me
I don’t know. My guess is that they give very slim odds to the Trump admin caring about carbon neutrality, and think that the benefit of including a mention in their submission to be close to zero (other than demonstrating resolve in their principles to others).
On the minus side, such a mention risks a reaction with significant cost to their AI safety/security asks. So overall, I can see them thinking that including a mention does not make sense for their strategy. I’m not endorsing that calculus, just conjecturing.
This is worth considering, but FWIW, 50 GW would be around 10% of US electricity if it runs continuously (the US consumes at a rate of about 500 GW if you divide total consumption by one year). If the new capacity is as clean as the overall electric grid that would be about 2.5% of US emissions (25% of US emissions come from electricity) and 0.35% of global emissions (US emissions are 1⁄7 of global emissions).
I’m not going to do this math now but I think if the new capacity is 100% natural gas then that’s about as carbon-intense as the US electric grid as a whole, or maybe somewhat worse (the US has a lot of clean energy, but it also has coal plants which are >2x more carbon intense than gas). 100% natural gas would be the worst case, because there is no scenario where the US builds new coal plants (edit: it’s not the worst case, because increased power demand could cause the delay of coal plant retirements, but I don’t think this changes the conclusion all that much)
Completely agree that climate analysis should be a huge part of the scaling AGI equation. I don’t buy the “But AGI might solve climate” argument. It might solve everything, but the uncertainty is so huge I don’t think we should account for that in any equation—I think we should calculate the “knowns:” and largely ignore the wildly unpredictable “unknowns” here.