Governance and Responsible AI Lab (GRAIL) Projects
2025-26
VIP Projects
"AI SHARE" - AI Survey Hub for Attitudes and Research Exchange
We are building a database that includes survey questions about AI attitudes, opinions, and policy preferences across polls and surveys run by academic institutions, think tanks, and news organizations. This will assist in understanding how AI attitudes vary over time, across countries, and across subgroups of the population (e.g., the public, experts, policymakers). We will identify trends, as well as gaps, in our understanding of the AI opinion landscape. We plan to use this information to conduct meta-analyses, to validate survey questions/instruments, to develop a public-facing tool (like the Roper iPoll) for accessing survey questions and associated data related to AI, and to develop an annual survey on AI attitudes.
Strong fit for students who want to build expertise in survey design, survey experiments, and public opinion research. Excellent for students who want to contribute to large-scale meta-analysis and develop technical skills in synthesizing cross-national datasets for policy-relevant questions.
Status:
Next steps/needs:
AGORA (The AI Governance and Regulatory Archive)
The AI Governance Regulatory Archive (AGORA): This database is a collaboration between GRAIL and the Center for Security and Emerging Technology (CSET) at Georgetown, with the purpose of compiling AI-related legislation into a single archive. The archive will initially include US federal and state AI legislation and will gradually expand to US local and international AI legislation. We are tracking information about the legislation, including the risks/harms addressed, the policy sectors implicated, and the policy instruments (sticks and carrots) involved. The goal is to provide a resource to scholars to investigate priorities in the developing AI policy agenda, but we expect that policymakers may also benefit from a resource summarizing AI policy development. Ideal for students who care about public policy and legislation, and who want to engage directly with real-world regulatory debates.
Students will gain experience in policy tracking, legal analysis, qualitative coding, and have opportunities to contribute public-facing blog posts that communicate emerging trends in AI governance.
Status:
Next steps/needs: A clear system for continuous recruitment of undergrad students, trainings on qualitative codings on Airtable
Political Deepfakes Incident Database (PDID)
This database includes deepfake images and videos about political actors, institutions, or events. We are compiling information about the political deepfakes such as whether the images/videos are presented as real/fake, whether there is external verification, who the targets are, what potential harms are depicted, any real-world evidence of harms, how they are spread on social media, and what framing/narratives they evoke. The idea is to provide a public resource to researchers, journalists, and the public, and to assist in identifying the impact of policy solutions rolled out to address deepfakes (such as labeling, watermarking, etc.).
Great fit for students interested in misinformation, media manipulation, and the societal risks of AI-generated content. Especially suitable for students who are comfortable engaging with social media platforms, analyzing digital media content, and contributing to public debates on emerging threats.
Police Technology and Accountability Project (PTAP)
This project will examine how police executives impact accountability practices and outcomes within law enforcement agencies. The research team will create comprehensive datasets on police chiefs, sheriffs, civilian review boards, and accountability mechanisms like body-worn cameras, AI systems, and other technologies for identifying misconduct. Analyses will evaluate the adoption and effects of these AI tools and other accountability proposals, shedding light on the key role of police executives in implementing reforms. The interdisciplinary team of experts in fields like criminology, technology, and policing will provide vital insights on improving accountability through policy and practice related to police leadership.
Strong fit for students interested in criminal justice, police reform, and how leadership shapes accountability outcomes. Ideal for those who want experience with applied policy research, real-world implementation challenges, and the intersection of technology, AI, and law enforcement oversight.
Forecasting AI Risks and Impacts on the Workforce (FAIRWORK)
The FAIRWORK project investigates how artificial intelligence is reshaping labor markets, job structures, and workforce policy. Through systematic review and qualitative coding of hundreds of academic studies, the project builds a structured database mapping key trends in AI-driven automation, job displacement, skill shifts, and worker well-being. The research also examines policy responses including regulation, education, and worker protections. Undergraduate researchers play a central role in the coding and analysis process, gaining training in empirical research design, content analysis, and interdisciplinary policy scholarship.
Good fit for students interested in empirical policy research who want to engage deeply with interdisciplinary literatures across economics, sociology, policy, and technology studies. Students will develop expertise in research design, systematic reviews, and qualitative coding while reading and analyzing complex academic work from diverse fields.
Small Projects
Impact of Generative AI on Political Communication
Faculty: Kaylyn, Daniel, Bryce
Support: None
Substantive area: LLMs, political communication
Methodological area: Survey experiment
Status: Research design
Next steps/needs: Drafted paper, need revisions
Comparing Public, Policymaker, and AI Expert Attitudes
Faculty: Daniel, Kaylyn
Support: Shreya (undergrad)
Substantive area: Public opinion
Methodological area: Survey analysis
Status: Pre-design
Next steps/needs: Recruitment
Impact of AI Ethics Signals on Consumer Trust
Faculty: Daniel, Kaylyn, Tyler
Support: Alex W. (grad)
Substantive area: AI ethics audits/certification
Methodological area: Conjoint survey experiment
Status: Prep/planning
Next steps/needs: Research design
Validating an AI Literacy Instrument in the US, UK, and Germany
Faculty: Daniel
Support: Arne (postdoc at TUM), Marie (grad at TUM), Renee (Google)
Substantive area: AI ethics
Methodological area: Survey analysis, psychometrics
Status: Research design and data collection
Next steps/needs: Finalize survey, determine sample/cost
The Emergence of the AI Ethics Auditing Ecosystem
Faculty: Daniel, Stephanie (Ivey), Javier (Comillas)
Support: Indira (PhD)
Substantive area: AI ethics
Methodological area: Interviews, qualitative coding
Status: 1st paper under review research design for second paper on AI ethics
Next steps/needs: Write industry report and second paper
Ethics of LLMs in Teaching and Learning
Faculty: Daniel, Luisa, JP?, Ale
Support:
Substantive area: AI ethics, ethics education
Methodological area: Interviews, syllabus review
Status: Pre-design
Next steps/needs: Recruit, identify research design
Ethical Considerations for AI in Human Resource Management
Faculty: Kaylyn, Daniel, Ian Adams (U. South Carolina), Josh McCrain (U. Utah)
Support:
Substantive area: HR, AI ethics, local government
Methodological area: Conjoint survey experiment
Status: Research design
Next steps/needs: Need to verify HR contact list
AI Ethics Education Systematic Literature Review
Faculty: Daniel Schiff, Ale Magana
Support: Lucas Wiese (grad), Indira Patil (grad)
Substantive area: AI ethics
Methodological area: Literature review, qualitative coding
Status: Complete and published https://doi.org/10.1016/j.caeai.2025.100405
AI Ethics and Governance Career Pathways
Faculty: Daniel Schiff
Support: Lucas Wiese (grad), Bryan DeWitt (grad), Matthias Oschinski (CSET), Sonali Rathinam (CSET)
Substantive area: AI ethics and governance careers and education
Methodological area: Job posting analysis, quantitative analysis
Status: One manuscript under review at IEEE TTS
Next steps/needs: Brainstorm future work, interviews, surveys
Open-ended Responses and Synthetic Samples for Experimental Design
Faculty: Daniel, Kaylyn, Natalia Bueno (Emory)
Support: Will Dinneen (UPenn grad)
Substantive area: Survey and experiment design
Methodological area: LLMs
Status: Prep/planning
Next steps/needs: Make plan for summer tasks