Hiring nowAI economics, labour and social research

AI Social Impact Researcher

Also called AI Society Researcher

An AI Social Impact Researcher studies how AI products and policies affect communities, workers and institutions. They give the company evidence it can defend, so product and policy decisions rest on more than instinct or opinion.

What they do

They design and run studies on how AI changes work and community outcomes. That means choosing the question, the comparison group and the method. They run surveys, interview workers and managers, and map tasks to see what is shifting. They analyse the data with econometric tools and check whether the effect is causal or just correlated. They bring in the people affected, not just those who answer a survey. Then they write up findings with clear limits and tie every claim back to its evidence. They also brief product, policy and leadership teams on what the findings mean.

What a strong hire delivers

In the first months, a strong hire turns a vague worry about AI's social effects into a scoped, answerable research question. They deliver a first mixed-methods impact study with a clear method and honest limits. They set up a way to hear from affected workers and communities. They give leadership a short set of policy implications, each traceable to evidence, that the company can act on or publish.

How you can tell they are good

Ask for a past study and have them walk through it. Strong candidates explain why they chose the design, what could have biased it, and who was missing from the sample. They separate what the data showed from what they inferred. Ask what they would do if the results were inconvenient. Be wary of anyone who offers only headline findings, or who cannot say how a claim links to its source.

Why it is hard to fill

Few people combine causal rigour, qualitative fieldwork and a working grasp of AI systems. Most come from academia or evaluation consultancies and rarely have AI company experience. Titles vary widely, so searching on the job title misses many of them. Candidates often lean either quantitative or qualitative, and a true mixed-methods researcher is rarer. Many also want publishing freedom, which needs settling early.

Where to find them

Look in labour economics, sociology, public policy and evaluation science. Strong candidates often hold titles such as research fellow, policy researcher, impact evaluator or labour market analyst. They work in universities, think tanks, public bodies, development research groups and non-profits. Some sit inside technology firms in responsible AI, economics or policy research teams. Researchers who have run field studies with workers or communities are especially worth approaching.

Indicative pay

Not enough published evidence yet to give a fair range for this role, which is common for work this new. We benchmark it for you as part of a search.

Interview questions for an AI Social Impact Researcher

  1. Tell us about a study where you measured the effect of a technology or policy on people. What design did you choose and why?

    A strong answer names the question, comparison group, data sources and trade-offs behind the design. They admit limits plainly. Worry if they describe only results, or cannot explain why they picked one method over another.

  2. How would you tell whether a change in workers' outcomes was caused by an AI tool rather than something else?

    Good answers cover comparison groups, timing, confounders and natural experiments or trials where possible. They also say when causal claims are not justified. Worry about anyone who treats correlation as enough.

4 more questions, with what a strong answer covers, are in the Role Kit.

Job description you can post

We are hiring an AI Social Impact Researcher to study how our technology, and AI more broadly, affects workers, communities and institutions. You will design rigorous studies, work directly with affected people and give our teams evidence they can act on and defend.

What you will do

  • Design and run mixed-methods studies on the social and economic effects of AI
  • Apply causal inference and experimental design to impact questions
  • Run surveys, interviews and task analysis with workers and communities
  • Build ways for affected people to take part in the research
  • Analyse data with econometric tools and document limits clearly
  • Write impact studies with policy implications traceable to evidence
  • Brief product, policy and leadership teams on findings

What you will bring

  • Published or shared impact studies that show sound design and honest limits
  • Demonstrated use of causal inference methods on real data
  • Experience running qualitative fieldwork such as interviews or participatory research
  • Working knowledge of public policy and labour economics
  • Clear writing for both specialist and non-specialist readers
  • Ability to explain how each claim traces back to evidence

Nice to have

  • Experience studying AI or automation in workplaces
  • Experience running field experiments or evaluations
  • Familiarity with how AI systems are built and deployed

Free to use and adapt. If it saves you time, a link back to this page is appreciated.

Skills that matter

  • Public policy and economicsAdvancedAnalyse institutional choices and distributional effects
  • Causal inferenceAdvancedSeparate causal claims from predictive associations
  • Experimental designWorkingChoose comparisons that identify credible effects
  • Worker and community participationWorkingInclude affected workers and communities in decisions

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How we wrote this

Role definitions are our own editorial work, checked against occupational classifications, standards, research and employer pages. Titles vary by company, and this is a description of the work, not a job advert.

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