US Policy Communication Playbook for an AI Crisis

The problem:
At the time of a major AI-related incident, like an AI-enabled cyber attack, an AI-assisted biological incident or a loss-of-control event, it's likely that the U.S. government will take fast action under pressure.
Due to the rapid progress of AI, it's likely that AI safety policies will need to be implemented in crisis conditions, but the policy literature is severely lacking in understanding how best to advocate for certain policies during these fast-moving crisis windows.
Understanding how crisis policymaking works could be critical for implementing AI safety solutions that address X risk. We need to know who to build relationships with, through which channels, with what type of messaging, and on what timelines. I have found no resources that discuss this topic as it refers to U.S. domestic policy making on AI. This project will fill the gap.

What I will do:

• Analyze five historical windows when the U.S. government implemented new policy to deal with a fast-moving crisis. For each case study, I will extract takeaways about what actions and structures had the strongest effects on which policies got put in place.

• Interview experienced AI policy advocates and congressional staff to surface the tacit knowledge of how this actually works, and where organizations feel underprepared.

Concrete output:
A written policy communication strategy playbook that contains:

1. Short breakdowns of each historical case study I looked at along with actionable takeaways

2. An guide suitable for low-capacity organizations who want to improve their policy positioning

3. A more aspirational capacity-building section that's aimed at funders and org builders to know where it might be good to put resources for policy impact at the time of crisis

4. Action plans that can be triggered at the time of crisis to make use of pre-positioning and networks

Each section will have a quick reference card containing the key insights.

I plan to publish through an established institution to increase credibility and reach.

As I work, I will be releasing a series of blog posts to stress test the arguments and quickly show progress.

Who:
I am the primary person doing this work, but I'm actively recruiting collaborators. I have a bachelor's degree in science communication. I've completed the AGI Strategy course and the Frontier AI Governance course from Bluedot Impact, as well as the Aspen Policy Academy's Getting Through to Government course. I've done over 700 hours of active study on AI safety and AI policy. I also co-lead the Community Engagement Group in Utah's Responsible AI Community Consortium.
I'm a strong fit for this project because of my experience in both communication strategy as well as AI safety policy. This project is also building a base of quality outputs needed to secure other AI safety policy roles in the future.

AI is moving quickly, and the time between emerging publicly visible risks and the end of our window to prevent catastrophic harms might be short. Often, policy making has years or even decades to implement solutions. AI safety might have to move quicker, and there is very little literature on how to influence policy outcomes on short timelines in the midst of a crisis. AI safety policy advocates need to know how this process works to have the best possible chance of making AI governance go well.

This project applies examples of past crisis policymaking directly to AI governance to improve the strategies used by AI safety policy organizations.

Theory map:

Assumptions:

• An AI related crisis is possible

• AI safety policy might be implemented in crisis conditions.

• If I build this guide, policy advocates will change their strategies

Generally understood to be true:

• Crisis policy making functions differently than standard policy making.

• There is insufficient research on crisis policymaking

Chain of effect:

1. Improve understanding of crisis policy making in conditions similar to an AI crisis

2. AI safety advocates change their strategies based on my findings

3. Good X-risk relevant policies are more likely to be implemented at the time of a crisis

4. X-risk is reduced

Validation I have already received

• A staff member at BlueDot Impact said the project "sounds like it could be highly impactful" and that "most people in the field acknowledge [it] matters (to at least some degree) but nobody has really done the work to systematize this."

• Staff at a leading AI safety advocacy organization said: "If it was genuinely detailed and well researched I think we would genuinely reference it in a crisis," adding that they had had the same thought themselves but lacked the time, and that they don't think the other larger AI safety advocacy groups "have a fleshed out plan like this either."

• A congressional staffer said "the most valuable stuff would probably be the case studies," and that framing "hey here is the actual bill that should be passed or the 3-pager that should be the basis for it" would be valuable.

• Staff at the AI governance organization whose report prompted this project said: "I think this is a valuable project ... what's most needed is past examples of influence and how it happened, but mostly the playbook that AI experts should have to be ready by the time of the crisis + the immediate aftermath."

• An independent AI policy practitioner called it "an exciting project" and offered to suggest further contacts once the draft matures.

The people I have spoken with are consistently most excited about the case studies, which suggests the historical analysis is the component with the clearest, most immediate demand.

Minimum that makes the project happen: $20,150

• Labor: Salary: $19,500 (3 months of DC median income)
• Tools: Claude Max: $300 (3 months × $100)
• Flight to DC: $350

Ideal (fully funds the best 6 month version): $41,500

• Labor: Salary: $39,000 (6 months of DC median income)
• Tools: Claude Max: $600 (6 months × $100)
• Flight to DC: $350
• SF conference
  • Round-trip flight: $500
  • Housing (with friend): $0
  • Registration: $600
  • Meals + ground transport: $450
  • SF subtotal: $1,550

How the money is spent

I do not currently have the financial runway to relocate to DC, but my work would be much more effective while living in D.C. I have a cheap group-house opportunity in DC that makes this feasible if funded.