Assessing Taiwan’s Global Position for Transformative AI

Background Almost any scenario in which AI proves transformative would be shaped by decisions made in Taiwan – producer of ~90% of the AI supply chain's most advanced logic chips and the center of the US-China technology conflict. There's a small but growing AI safety community (e.g. NTU AI Safety), and some relevant research by institutions like DSET and the Singapore AI Safety Hub. However, Taiwan's readiness for a scenario of transformative AI remains badly underexplored. Decisions taken in Taiwan – on energy, export policy, chip governance, participation in any verification regime – shape the global compute landscape whether or not they're framed that way, and hardware-verification proposals run physically through Taiwanese fabs. This project produces the first baseline assessment, and with it begins a research pipeline in a strategically critical, underserved jurisdiction.

Structure Each mentee owns one of four modules end to end, working from a shared analytical template: current posture and key actors, what that posture implicitly assumes about the pace and scale of AI, how it holds up if significantly more capable AI arrives faster than planned, and the concrete gaps and levers that follow.

• Policy situation: Institutions, initiatives, and funding (MoDA, NSTC, the AI Evaluation Center, TAIDE, the AI Basic Act, DSET).
• Defense and cognitive security: Information operations and how more capable AI reshapes the cross-strait threat model.
• Compute and verification: Infrastructure, energy constraints, and Taiwan's potential role in hardware-enabled verification.
• Elite discourse mapping: Who in Taiwan speaks about advanced AI and what they say, via legislative statements, documents, and media (Mandarin heavily favored).

Deliverables & logistics

• A two-page executive summary (Traditional Chinese and English) written directly for policymakers
• An ~8,000-word public report with the research underneath
• [Optional] Serialized publication on Substack or the EA Forum.

Expect 8-12hrs/week, flexible.

Timeline

• Weeks 1-3: orientation and scoping.
• Weeks 4-8: drafting and peer-review pairs.
• Weeks 9-12: revision, comparative synthesis, the executive summary, and Demo Day materials.

Taiwan is often described as a chokepoint, bottleneck, and one of the most consequential jurisdictions in the AI supply chain. Its dynamics with China and the United States are among the largest geopolitical wildcards in how transformative AI unfolds. Currently, Taiwan has a fledgling, but lagging, indigenous capacity focused on transformative AI-strategy. Its AI policy apparatus is built for incremental AI and the international preparedness conversation figures Taiwan as a bystander at best, or a footnote at worst.

That gap itself is a global risk, and the project addresses this in three ways. First, a baseline assessment gives international researchers and policy conveners something to build on when Taiwan enters transformative-AI conversations. Today there is no document that specifically addresses this issue. Second, hardware-enabled verification proposals run physically through Taiwanese fabs; whether Taiwan can engage with them depends on local policy capacity that does not currently exist, and a Taiwan able to participate expands the option space for global coordination on AI. Third, field-building: the project is designed to recruit and train Taiwan-based or Taiwan-interested researchers, growing a pipeline in a strategically critical, badly underserved jurisdiction.

The Traditional Chinese executive summary extends this from analysis to outreach by creating a document Taiwanese policymakers and researchers can act on and cite.

Each mentee owns one of the four modules end to end: building the source inventory, conducting the desk research (plus potential expert interviews where feasible, mentors can help facilitate these), drafting, and revising toward a publishable module.

Mentee 1 – Policy situation Mentee 2 – Defense and cognitive security Mentee 3 – Compute and verification Mentee 4 – Elite discourse mapping

Mentors provide the analytical template, source network, weekly direction, and written feedback on drafts, and write the comparative synthesis that ties the modules together. This is a high-autonomy project: it suits people who can run with a template and a reading list between check-ins, flag blockers early, and hold themselves to deadlines. It is a poor fit for anyone wanting close supervision or coaching on basic research skills.

All mentees also participate in mutual peer-review pairs, contribute to the drafting of the shared research, and condense their module into the final executive summary. Mentees are credited as authors of their modules and present at Demo Day. To our knowledge no baseline document of this kind exists, so mentees are not filling in a well-mapped literature but producing genuinely first-pass analysis on a novel question, which means real ownership and unusually high scope for original contribution.

Essential (all modules):

• Strong analytical writing in English: able to turn research into clear, structured prose. A writing sample is required; a class paper, blog post, policy memo, or research write-up is all fine.
• Ability to work independently from a shared template and reading list, holding yourself to deadlines between weekly check-ins. This is a high-autonomy project.
• Genuine engagement with transformative AI: you don't need to hold any particular timeline view, but you should take the possibility of rapidly more capable AI seriously and be able to reason about what it means for Taiwan.
• Basic familiarity with the AI governance landscape: you should roughly know what export controls, compute governance, and frontier-model evaluations are. Module-specific depth is not expected at the start.

Essential for some modules:

• Traditional Chinese reading ability and Mandarin skills: required for the elite-discourse module and strongly preferred for the policy module. The compute/verification and defense modules have substantial English-language literatures, so non-Mandarin readers are welcome there.

Nice to have:

• Technical background or working understanding of the semiconductor industry (compute/verification module).
• Prior experience conducting literature reviews or desk research.
• Prior research experience in AI governance or a related policy field.
• Clear strategic thinking about transformative AI and being able to trace second-order consequences of a scenario, not just describe it.
• Background in public policy, international relations, political science, East Asian studies, or security studies, or demonstrated equivalent, such as a completed AI-governance course (e.g. BlueDot courses) or prior governance research.

Some working time overlap with Taiwan (UTC +8) is a plus, as is familiarity with the Taiwanese policy landscape and AI discussions, though neither is a strict requirement.