The Collective Intelligence Project surveyed residents across 70 countries and found that public trust in artificial intelligence exceeds trust in government and social media platforms. The organization, which focuses on directing AI development toward broad societal benefit, released findings showing a significant trust gap between AI systems and traditional institutions.

The study highlights a critical governance challenge. AI deployment decisions rest with a small group of technology leaders and researchers, yet the consequences affect billions globally. This concentration of power contrasts sharply with public expectations for broader participation in shaping AI systems.

Trust levels reflect public frustration with established institutions. Governments face declining confidence due to polarization and perceived ineffectiveness on urgent issues like climate change and inequality. Social media platforms have eroded trust through data misuse scandals, algorithmic manipulation, and amplification of misinformation. By comparison, many people view AI as more neutral and objective, particularly when presented as a tool for solving complex problems.

The survey's 70-country scope reveals this pattern transcends regional boundaries and political systems. Trust in AI appears robust even as regulatory frameworks remain fragmented and incomplete. This disconnect creates risk. People express confidence in AI systems whose decision-making processes remain opaque, whose training data contains biases, and whose environmental costs remain largely unquantified.

The Collective Intelligence Project's findings underscore the need for immediate governance reform. Current AI development occurs largely outside democratic processes. Major technology corporations set deployment standards with minimal public input. Governments struggle to develop coherent regulations while the pace of innovation accelerates.

Rebuilding institutional trust while establishing AI accountability requires transparency in AI system design, training, and deployment. Independent auditing of AI systems used in high-stakes decisions, from criminal justice to healthcare to climate modeling, remains limited. Public participation in AI governance decisions must expand beyond academic and corporate circles.

The study suggests people want AI to work better for them. That aspiration depends on moving