Researcher - MIT AI Risk Initiative (Technical Associate)

Position overview

As AI capabilities rapidly advance, we face critical information gaps in effective AI risk management:

• What are the risks from AI, which are most important, and what are the critical gaps in response?
• What are the mitigations for AI risks, and which are the highest priority to implement?
• Which AI risks and mitigations are relevant to which actors and sectors?
• Which mitigations are being implemented, and which are neglected?
• How is the above changing over time?

Within MIT FutureTech, the MIT AI Risk Initiative aims to provide credible, timely, and decision-relevant answers to these questions. Our core outputs include the AI Risk Repository, Incident Tracker, Mitigations Database, and Governance Map.

We are hiring a Technical Associate to support the MIT AI Risk Initiative's applied research, data analysis, and project delivery.

This is an early-career research staff role. The primary function is to contribute to research projects that help decision-makers understand AI risks, mitigations, organizational responses, and gaps in practice. The role involves reviewing and synthesizing evidence, collecting and analyzing data, producing research outputs, and supporting engagement with external collaborators.

The ideal candidate will have strong analytical skills, attention to detail, intellectual curiosity, and an interest in producing rigorous research with practical applications. They should be comfortable working with both qualitative and quantitative information, learning new methods, and contributing to collaborative projects.

We welcome applications from recent graduates, early-career researchers, and candidates seeking to develop their research skills. Previous experience in AI risk or AI governance is beneficial but not essential.

What you'll do

Evidence synthesis and measurement

• Conduct literature searches, evidence reviews, and structured assessments of AI risks, mitigations, and organizational responses.
• Support systematic reviews through searching, screening, data extraction, coding, and quality assurance.
• Collect, clean, classify, and analyze qualitative and quantitative data.
• Help develop and maintain research protocols, codebooks, datasets, and documentation to ensure results are reproducible and updateable over time.
• Identify patterns, gaps, and emerging findings in research evidence.

Surveys and expert input

• Support the design, administration, and analysis of surveys involving experts, practitioners, and organizations.
• Assist with identifying and recruiting participants, managing survey data, and conducting follow-ups.
• Summarize and analyze survey results, interviews, and other forms of expert input.

Research outputs and decision support

• Contribute to research papers, reports, briefs, presentations, and other publications.
• Prepare clear summaries of research findings for academic, policy, and practitioner audiences.
• Help maintain and improve structured datasets, taxonomies, and decision-support tools.
• Support the preparation of tables, figures, visualizations, and other materials that communicate research findings.

Stakeholder engagement

• Support engagement with researchers, policymakers, industry representatives, and other stakeholders.
• Help prepare materials for external meetings, briefings, workshops, and presentations.
• Assist with gathering and synthesizing stakeholder feedback to improve the relevance and usability of research outputs.
• Communicate research findings to collaborators and external audiences where appropriate.

Project delivery and operations

• Manage assigned research tasks and contribute to project milestones and deliverables.
• Maintain accurate records, organize research materials, and document methods and decisions.
• Support project coordination, including tracking progress, preparing updates, and coordinating inputs from contributors.
• Identify and communicate research challenges, uncertainties, and opportunities for improvement.

Lab participation

• Participate actively in the MIT FutureTech research community by attending lab meetings, sharing updates, and contributing feedback on related projects.
• Collaborate with other researchers across the lab to improve research quality and develop new ideas.
• Develop research skills through mentorship, feedback, and participation in collaborative projects.

Supervision Received

• Reports to Neil Thompson, with day-to-day supervision and project guidance from Peter Slattery and other members of the team as appropriate.
• Works under regular guidance, with increasing independence as experience and capabilities develop.

Supervision Exercised

• No formal supervisory responsibilities are expected.

Qualifications & Skills

Minimum Required Education and Experience

• Bachelor's degree in an applied social science (e.g., economics, psychology, behavioral science), public policy, computer science, or another relevant field, or equivalent research experience.
• Some experience conducting research, which may include university coursework, a thesis, research assistantships, internships, or professional projects.
• Familiarity with research methods, including literature reviews, data collection, and qualitative or quantitative analysis.
• Ability to work with structured data using tools such as Excel, Google Sheets, or statistical software.
• Strong analytical and critical thinking skills, including the ability to assess evidence, identify patterns, and draw well-supported conclusions.
• Clear written communication skills and the ability to summarize complex information accurately and concisely.
• Strong attention to detail, organizational skills, and a commitment to research quality.
• Ability to manage assigned tasks, meet deadlines, and work effectively in a collaborative research environment.
• Willingness to learn new methods, tools, and subject matter.

Preferred Education

• Honours or master's degree in an applied social science, public policy, computer science, or another relevant field.

Preferred Experience

• Experience conducting systematic or structured literature reviews, including screening, extraction, or coding.
• Experience designing, administering, or analyzing surveys or interviews.
• Experience working with qualitative or quantitative datasets, including data cleaning, classification, analysis, or visualization.
• Familiarity with research software and programming tools such as R, Python, or statistical analysis packages.
• Experience contributing to academic publications, research reports, policy briefs, or other research outputs.
• Interest in or knowledge of AI risks, AI governance, AI safety, or the social and economic impacts of AI.
• Experience working in a research, academic, consulting, policy, or technology-oriented environment.

We recognize that early-career applicants may have developed relevant skills through academic projects, independent research, internships, or other activities. We encourage candidates to apply even if they do not meet every preferred qualification.

Other information

• One-year term based on research grant funding, with the possibility of renewal subject to funding and project needs.
• Salary: $55,000 per year (full-time equivalent), prorated for part-time appointments.
• This is an on-site role based at MIT in Cambridge, MA.
• We have a slight preference for candidates who can work hours that overlap with Australia (later afternoon and evening).
• Full-time is preferred, but part-time commitments will also be considered.

Selection process

• Short test task
• Interviews
• Potential paid work trial

About MIT FutureTech 

MIT FutureTech is an interdisciplinary group of  economists, computer scientists, and engineerswho study the foundations and economic implications of progress in computing and Artificial Intelligence.  Economic and social change is underpinned by advances in computing: for instance, improvements in the miniaturization of integrated circuits, the discovery and refinement of algorithms, and the development and diffusion of better software systems and processes. We aim to identify and understand the trends in computing that create opportunities or risks and help leaders in computing, scientific funding bodies, and government to respond appropriately. 

Our research therefore helps to answer important questions including: Will AI progress accelerate or decline – and should it? What are the implications for economic growth and for the labor markets? What are the bottlenecks to growth from AI, and how can they be solved? What are the risks from AI, and how can we mitigate them? 

To support our research, we run seminars and conferences to better connect the field of computer scientists, economists, and innovation scholars to build a thriving global research community. 

To disseminate it, we advise governments, nonprofits and industry, including via National Academies panels on transformational technologies and scientific reliability, the Council on Competitiveness’ National Commission on Innovation and Competitiveness Frontiers, and the National Science Foundation’s National Network for Critical Technology Assessment. 

Our work has been funded by Open Philanthropy, the National Science Foundation, Microsoft, Accenture, IBM, the MIT-Air Force AI accelerator, and the MIT Lincoln Laboratory. 

Some of our recent outputs:  

• ‍The AI Risk Repository: A Comprehensive Meta-Review, Database, and Taxonomy of Risks from Artificial Intelligence 
• Beyond AI Exposure: Which Tasks are Cost-Effective to Automate with Computer Vision? 
• How industry is dominating AI research   
• The Quantum Tortoise and the Classical Hare: A simple framework for understanding which problems quantum computing will accelerate (and which it will not)  
• A workshop on AI scaling and its implications for AI development, automation, and more  
• The Great Inflection? A Debate About AI and Explosive Growth   
• There’s plenty of room at the Top: What will drive computer performance after Moore’s law?   
• Deep Learning's Diminishing Returns: The Cost of Improvement is Becoming Unsustainable  
• America’s lead in advanced computing is almost gone  
• The Decline of Computers as a General Purpose Technology: Why Deep Learning and the End of Moore’s Law are Fragmenting Computing  
• How Fast Do Algorithms Improve?  

Some recent articles about our research: 

• Techcrunch: MIT researchers release a repository of AI risks 
• CNN: AI and the labor market: MIT study findings 
• TIME: AI job replacement fears and the MIT study 
• Boston Globe: AI's impact on jobs according to MIT 

You will be working with Dr. Neil Thompson, the Director of MIT FutureTech. Prior to starting FutureTech, Dr. Thompson was a professor of Innovation and Strategy at the MIT Sloan School of Management.  His PhD is in Business & Public Policy from Berkeley.  He also holds Master’s degrees in: Computer Science (Berkeley), Economics (London School of Economics), and Statistics (Berkeley).  Prior to joining academia, Dr. Thompson was a management consultant with Bain & Company, and worked for the Canadian Government and the United Nations.

‍About the MIT Computer Science and Artificial Intelligence Lab (CSAIL) 

CSAIL is one of the world’s top research centers for computer science and artificial intelligence (currently ranked #1).  It has hosted 9 Turing awards winners (the “Nobel Prize of Computing”) and has pioneered many of the technologies that underpin computing.

How to apply

Please use this form to register interest in this role or to submit a general expression of interest.

Selected candidates will be first interviewed via Zoom. We are recruiting on a rolling basis and may close applications early if we find a suitable candidate, so please apply as soon as possible to maximize your chances.

** To comply with regulations by the American with Disabilities Act (ADA), the principal duties in position descriptions must be essential to the job. To identify essential functions, focus on the purpose and the result of the duties rather than the manner in which they are performed. The following definition applies: a job function is essential if removal of that function would fundamentally change the job.

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