As AI adoption accelerates, new SRI report examines what makes AI trustworthy

As governments, companies, and public institutions move from experimenting with AI to deploying it in the real world, one question is becoming increasingly urgent:

What does it mean to trust AI? And what does it take for that trust to be earned?

A new white paper published by the Schwartz Reisman Institute for Technology and Society (SRI) at the University of Toronto reframes trust as a multidisciplinary, institutional challenge at the center of AI adoption and governance.

The report, Trust in human–artificial intelligence interactions: A multidisciplinary approach, offers a comprehensive framework for understanding and building trust in artificial intelligence (AI) systems.

Developed by a working group of graduate and postdoctoral researchers convened by SRI, and led by Research Lead Beth Coleman, the publication arrives at a critical juncture in Canadian AI policy. It provides policymakers, developers, and researchers with an actionable, six-part interdisciplinary framework to ensure AI systems are designed and governed to be genuinely trustworthy rather than merely trusted.

The paper identifies six principles that shape how trust is built, maintained, and broken: reliability and competence; contextual awareness; transparency, accountability, and legitimacy; fairness and integrity; resilience; and relational dynamics.

"Trust in AI is often framed as a user attitude or interface challenge, but our analysis shows that trust must be grounded in demonstrated system performance, clear governance, and institutional responsibility," says Beth Coleman, lead author of the report and professor at the University of Toronto. "AI systems should not simply seek trust—they must be designed and governed to earn it."

The report brings together perspectives from computer science, engineering, psychology, sociology, law, public policy, history, and philosophy. The work was developed through an interdisciplinary working group of graduate and postdoctoral researchers convened by SRI.

The white paper marks an important step in SRI’s continuing work on AI and society through Coleman’s AI & Trust Working Group, which brings together over 70 international researchers, policymakers, industry leaders, and civil society actors. The group works across geopolitical sectors to develop robust, applicable frameworks for AI and trust, support international policy engagement, and produce public-facing guidance for practitioners and decision-makers.

"I created this group because the need for international, interdisciplinary work on AI and trust seemed clear," says Coleman. "The response was incredible, with interest spanning three continents and multiple time zones."

The release comes amid growing international discussions about AI governance, public confidence, and technological sovereignty. In Canada, trust has emerged as a central theme in the federal government's new National Artificial Intelligence Strategy, which identifies trust as essential to responsible AI adoption and deployment.

The report further argues that policymakers, researchers, and organizations should shift focus away from increasing public trust in AI and toward developing AI systems that are demonstrably trustworthy.

ABOUT THE SCHWARTZ REISMAN INSTITUTE FOR TECHNOLOGY AND SOCIETY

The Schwartz Reisman Institute for Technology and Society (SRI) at the University of Toronto is an interdisciplinary research hub that examines the social impacts of advanced technologies like artificial intelligence. SRI integrates research across a wide range of disciplines to foster insights towards safe and responsible AI innovation, developing policy-oriented solutions to better align powerful technologies with human values and harness their potential to improve life—for everyone.