Political Economist, Rule of Law
About the role
Anthropic has done pioneering work examining the economic impacts of AI. The AI & Rule of Law team takes an analogous approach to a different question: how will AI affect our constitutional democratic institutions?
Increasingly powerful AI systems will put pressure on societal functions at every level — the courts, legislatures, electoral systems, oversight bodies, and the legal frameworks that hold democratic governance together. Our team exists to ask hard questions about those vulnerabilities, and to seek out strategies for protecting democratic freedoms — in the short and long term, through both technical and policy levers.
This is early, high-stakes research. The team is small, the problems are genuinely unsolved, and the work will matter.
We are looking for someone with deep expertise in both AI and at least one of: law, government, political science, or public policy. The ideal candidate understands the technical landscape well enough to reason about AI capabilities and risks, and understands democratic institutions well enough to see where those risks become structural threats.
Key responsibilities
Projects on this team are illustrative rather than fixed — we expect the research agenda to evolve as both AI capabilities and institutional pressures change. Current and expected focus areas include:
Making fundamental contributions to the development and expansion of our public data and research on how people use AI for politics, including regular reports and deep dives on elections and policy topics, and grow into leading this work over time
Designing and conduct empirical research on AI’s political effects, drawing on external data sources and the privacy-preserving measurement systems internally
Designing, running, and analyzing experiments on systems of many AI agents, testing whether and when tools from political economy (rules, monitoring, voting, dispute resolution) help agents govern themselves and stay under human oversight
Developing new methodological approaches for studying AI’s impact on:
Developing measurement and causal-inference tooling to help Anthropic evaluate the downstream political consequences of its own training, product, and policy decisions
Building and maintaining relationships with academic institutions, policy think tanks, and other research partners, and serve as the point of contact for outside researchers who use our data
Working cross-functionally with other technical teams to improve our measurement infrastructure and data collection
Translating research insights into actionable recommendations for model training, product decisions, and policy discussions
Amplifying external engagement through research publications, policy briefs, convenings, and presentations to diverse stakeholders
Minimum qualifications
A primary degree in law, political science, or a closely related field at the Ph.D. level
A computational research background in Political Science, Economics, or a related field
Demonstrated ability to produce rigorous, public-facing work — scholarship, policy analysis, government output, or a published body of writing
Preferred qualifications
Experience relevant to the study of AI’s impact on politics
Track record of empirical research, particularly studies combining novel data sources and game theory or those implementing frontier methods in causal inference
Comfort operating with significant autonomy in an environment where the problems are new and the playbook is still being written
At least five years of relevant experience in academia, industry, or government
Some Examples of Our Recent Work
Preparing for the 2026 US midterms
Measuring political bias in Claude
Clio: Privacy-preserving insights into AI use
Introducing The Anthropic Institute
The annual compensation range for this role is listed below.
For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
Annual Salary:
$295,000—$345,000 USD