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🔮 Introducing: AI Economy Research Fellowship

Exponential View

Exponential View just opened its first Research Fellowship to study how AI reshapes the economy. It wants an economist who can turn big questions into testable numbers, fast, not slow academic papers.

Based on reporting by Exponential View — read the original for the full story.

Summary, retelling and take written by AI under human oversight; images are AI-generated illustrations. How we work · Report an error

Exponential View, the independent research outfit founded by Azeem Azhar, is hiring its first Research Fellow. The role is paid, based in London, and runs six or twelve months, with the brief of investigating how AI is changing economic value, work, firms and markets.

The questions on the table are deliberately broad. How should AI companies, infrastructure and capabilities be valued from first principles. Where in the AI value chain the economic surplus actually lands, and who captures it. What happens to wages, employment, productivity and worker bargaining power over the long run. What the microeconomic effects look like inside individual firms. And what would actually count as transformative AI, plus which leading indicators might signal that transition is underway.

Nobody expects the Fellow to show up with finished answers. What EV wants instead is someone who can convert those open questions into testable economic mechanisms, explicit assumptions and back-of-the-envelope estimates that later empirical work can build on. The pace matters as much as the rigor: academic projects can stretch across months or years, but EV says it often needs a defensible answer within hours or days, which means tightly framed questions, comfort with imperfect data, and a willingness to drop a view the moment the evidence shifts.

The candidate profile is specific. At minimum an outstanding master's-level economics qualification, including an MPhil, or a current doctoral student wanting a stretch of applied work. Relevant backgrounds include applied microeconomics, labour economics, industrial organisation, productivity and growth, innovation economics, financial economics or the economics of technological change. EV is explicit that a generic interest in AI won't cut it — they want serious prior engagement with AI, automation or technological change, real experience wrestling with messy, incomplete or inconsistently defined data, and the ability to write plainly for an economically literate audience. Right to work in the UK is required.

Applicants need to send a CV, a short note on why they want the role, one or two substantial pieces of empirical work, and answers to two essay prompts — one asking them to pick a claim about AI's effect on value, wages, productivity or market structure and describe how they'd test and potentially reject it, the other asking them to translate a proposition from economists like Anton Korinek or Daron Acemoglu into observable indicators over the next two years. The deadline is 6 September 2026, and shortlisted candidates will go through an interview followed by a paid, time-boxed research exercise before anyone gets the job.

My take — AI-written commentary, not fact-checked reporting

Hiring a fellow specifically to distinguish observed fact from inference in AI economics is a quiet admission that most public commentary on this topic is guesswork dressed up as analysis. The insistence on speed over the usual academic publishing cycle is the right instinct — by the time a peer-reviewed paper on AI's labour effects clears review, the labour market it describes may no longer exist. Demanding

Read more about this at: Exponential View

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