Study shows facts, not experience, shape AI governance
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- Prof. Yotam Margalit and Dr. Shir Raviv conducted a field experiment with over 1,500 workers to examine attitudes toward AI in public policy.
- The experiment assigned participants to receive orders from either a human manager or an algorithmic “AI boss,” affecting job satisfaction and performance but not policy views.
- Expert commentary on AI’s societal impacts caused significant shifts in participants’ support for AI in government, even when contradicting prior beliefs.
- Workers who initially doubted AI became more supportive after reading about benefits such as accuracy and consistency; those informed about risks like racial bias reduced support.
- The findings suggest public attitudes toward AI governance are fluid and can be shaped by factual information rather than direct experience.
- The study was published in the British Journal of Political Science (2026) and includes a DOI for reference.
Why it matters: Policymakers gain a lever to steer AI governance by disseminating clear, expert‑based information, while partisan groups lose the assumption that public opinion is entrenched. The study shows that factual messaging can quickly reshape support for AI policy, opening a window for education‑driven consensus.
