In the case of a Middle Power Frontier AI coalition, what would be the most effective routes to sufficiently large compute buildout? How quickly could middle powers acquire and operationalise substantial compute? Which constraints determine their progress?
About the project
Brief: Governments increasingly treat domestic access to AI compute as a source of economic and strategic autonomy. Existing research has classified national AI strategies, catalogued sovereign-compute projects and examined the budget and capacity required for a successful buildout. However, there is little research on the best routes to operationalising such a project. This project would theorise and collate the optimal paths a middle power coalition could take to complete a sufficient large buildout as quickly as possible. The analysis would examine the time between announcement, financing, construction, energisation and actual operation across several and also seek to understand common failure modes (such as why projects are delayed).
Outputs: A comparative research paper looking at previous compute buildouts, and a policy memo on optimal routes for middle-power compute expansion.
Theory of change
This projects seeks to assess whether a number of AI strategy scenarios (fast-follower, global AI coalition, etc.) are possible on certain timelines, and if so, how this might be achieved. Whether middle powers can build frontier compute capacity, quickly enough, will shape proliferation timelines, influence multilateral coalitions as a counterweight to bipolar racing, and leverage available for access agreements. There is significant commentary on sovereign compute but little work on buildout routes and constraints. The goal is to ground this empirically and help policymakers identify credible pathways.
Your role
Mentees will lead on desk research, writing/drafting, and expert interviews where appropriate. Mentees will have substantial autonomy to pursue additional research directions within the project's scope. We'll hold a weekly meeting covering drafts, research taste, and mentee development (career planning, network building), with brief async updates between meetings.
My aim is to facilitate a project and devision of labour similar to what you may experience in an AI Safety fellowship such as Pivotal, LASR, or ERA.
Prerequisites
I expect to be interested in mentees from a wide-variety of backgrounds.
Required:
- Strong analytical writing
- Comfortable with self-directed desk research
- Able to commit ~10 hours/week for the full programme period, including a ~weekly call.
- Broad familiarity with AI governance, with strong insights into why compute is a governance lever
Ideal:
- Experience with comparative case-study research or structured analysis (e.g. has written a literature review, policy analysis, or thesis chapter using multiple cases).
- Strong familiarity with at least one of: datacentre/energy infrastructure, semiconductor supply chains, industrial policy, or project finance.
- Quantitative literacy: comfortable building timelines and cost/capacity estimates in a spreadsheet.
Application question(s)
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Provide a link to one or more writing samples, ideally on AI safety or governance. This may include a paper, blog post, or coursework. If it was co-authored or heavily edited, state your contribution. (No word limit; link only)
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Should a potential Middle Power AI coalition pursue a frontier-level compute buildout? Why, and why not? What implications might this have for global AI safety? (200 words max)
About the mentor
Research Manager @ Pivotal Research, focusing on AI Governance.
Projects I manage mostly focus on compute governance, power concentration, middle power AI policy. I have managed over a dozen research fellows across a wide swath of AI governance topics, with outputs including policy memos, blog posts, and conference and workshop papers.
I have an academic background in engineering and social research, with experience in policy contexts in Brussels, London, and Dublin.