Job Description

Gillian K. Hadfield is an AI researcher focused on the technical and policy challenge of ensuring that AI is built in safe and aligned ways that promote human well-being across the globe.

She has recently joined Johns Hopkins University, where she is the Bloomberg Distinguished Professor of AI Alignment and Governance in the School of Government and Policy and of the Department of Computer Science at the Whiting School of Engineering. Hadfield is also a Canada CIFAR AI Chair at the Vector Institute for Artificial Intelligence and a Schmidt Sciences AI2050 Senior Fellow. Hadfield’s research is focused on innovative design for legal and regulatory systems for AI and other complex global technologies; computational models of human normative systems; and working with machine learning researchers to build ML systems that understand and respond to human norms. She is known globally for her work on AI alignment, governance and safety and serves as a founding trustee of the Cooperative AI Foundation, a member of the founding Steering Committee for the International Association for Safe and Ethical AI, and an advisor to and participant in the International Dialogues on AI Safety.



Professor Hadfield is seeking a dynamic and knowledgeable AI Policy Researcher to support the ongoing work she is undertaking in the fields of AI safety and governance through knowledge translation, policy research and analysis, and stakeholder outreach.



This role will involve conducting in-depth research on AI technologies' legal and social implications, with a strong emphasis on producing high-quality research reports, policy recommendations, and white papers that inform and shape effective governance frameworks. The successful candidate will work closely with Professor Hadfield and her collaborators to explore innovative regulatory frameworks and governance models.



Applicants should include a cover letter addressing your interest in Professor Hadfield’s AI safety and governance work and your experience distilling information from technical sources into communications products.



The AI Policy Researcher may work from either Baltimore or Washington, DC offices.



Specific Duties & Responsibilities

Research & Analysis

Lead and support research initiatives that analyze the impact of AI technologies on social systems and design innovative methods for adapting economic and social governance to AI development. A special focus will be on translating technical research into policy proposals and collaborating with technical researchers on policy implementation.
Prepare comprehensive research reports, policy briefs, and white papers that articulate findings and present actionable recommendations for policymakers and stakeholders.
Design, conduct, and analyze empirical studies related to AI policy, governance frameworks, and regulatory needs.
Translate complex technical research findings into accessible and actionable policy proposals for diverse audiences, including policymakers, industry stakeholders, and academics.
Policy Development & Advocacy

Prepare and publish policy briefs, research reports, and white papers with a focus on recommendations for improving AI governance and safety.
Evaluate and critique existing policies, identify regulatory gaps, and propose innovative frameworks to address the challenges of AI alignment and ethics.
Advocate for AI governance best practices through collaborative engagement with industry leaders, academic researchers, and government bodies, representing Professor Hadfield’s work in public and professional settings.


Project & Stakeholder Management

Serve as a liaison between Professor Hadfield’s lab and external collaborators, coordinating interdisciplinary research efforts in law, social sciences, and technology.
Organize and lead presentations, workshops, and public forums to disseminate research findings and foster dialogue on AI governance.
Manage multiple projects simultaneously, ensuring timelines are met and resources are effectively allocated.


Collaboration & Knowledge Exchange

Collaborate with policymakers, industry leaders, and an interdisciplinary group of academic researchers, including computer science, law, and policy experts, to advocate for best practices in AI governance and safety, ensuring that research is effectively communicated.
Facilitate knowledge sharing within Professor Hadfield’s team and with external partners to enhance the impact of research on policy outcomes.
Engage with various audiences through presentations, workshops, and public forums to disseminate research findings and promote dialogue on AI governance issues.


Special Knowledge, Skills & Abilities

Familiarity with current AI technologies, ethical implications, and governance frameworks, including knowledge of algorithmic accountability and transparency.
Experience with both qualitative and quantitative research methods, and proficiency in data analysis tools (e.g., Python, R, SPSS).
Proven track record of conducting research in AI safety, governance, or related areas, with publications in peer-reviewed journals or policy reports.
Familiarity with current AI technologies, ethical implications, and governance frameworks, including knowledge of algorithmic accountability and transparency.
Strong organizational and project management skills, with the ability to manage multiple projects simultaneously and meet deadlines.
Excellent written and verbal communication skills, capable of engaging diverse audiences, including academic, policy, and public sectors.
Ability to work effectively in interdisciplinary teams, fostering collaboration and knowledge sharing.


Minimum Qualifications
Bachelor's Degree in related discipline.
Five years related experience, including demonstrated supervisory or lead responsibilities.
Demonstrated experience in AI safety or governance research, with a history of publication in peer-reviewed journals or policy reports.


Preferred Qualifications
Related Master's or J.D. preferred.
Direct experience in policy advocacy, with engagement or partnerships with governmental or regulatory bodies.
Familiarity with interdisciplinary approaches to AI research, especially collaboration between technology and social sciences.
Demonstrated expertise in AI alignment challenges, governance frameworks, or machine learning interpretability.
Experience in policy advocacy or engagement with governmental and regulatory bodies is a plus.