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).

To identify trends, as well as gaps, in our understanding of the AI opinion landscape.

The plan is 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.

Database of AI-related survey questions from academia, think tanks, and polling firms to study the landscape of evolving public, elite, and expert attitudes on AI

Checking on the current analysis in Artificial Intelligence in order to further goals considering questions in AI.

An ambitious project focused on reducing carbon footprint through innovative recycling methods.

To find out about AI is to fathom AI.

The vision here is to perceive Artificial Intelligence in many ways and understand, in the base level, the survey regarding the field of AI.

AI related perceptions are the target of this project.

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Team Members

Faculty:

Graduate researchers: Chloe Ahn, Indira Patil, Anjali Bhati, Yunzhe "Leo" Liu, Maheshwari "Maahi" Das, Maxwell Kowalski, Kunal Rustagi

Undergraduate researchers:

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For Prospective Team Members:

This project is ideal for students who want to build expertise in survey design, survey experiments, and public opinion research. Students will contribute to large-scale meta-analysis and develop technical skills in synthesizing cross-national datasets for policy-relevant questions.