SRI releases new white paper on trust in human–AI interaction
AI is everywhere. But can we trust it? A new SRI white paper led by Beth Coleman reframes trust in AI as a multidisciplinary challenge—not just a technical one—and charts a path forward.
What does it mean to trust AI—and what does it take for that trust to be earned?
A new white paper from the Schwartz Reisman Institute for Technology and Society (SRI), led by Research Lead Beth Coleman, reframes trust as a challenge at the center of responsible 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, the paper brings together perspectives from computer science, engineering, psychology, sociology, law, public policy, history, and philosophy to examine how trust is conceptualized and applied in human–AI interaction.
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. The authors argue that functional reliability alone isn't enough. AI systems must also align with social values to earn justified confidence.
Adoption moves at the speed of trust
The report arrives at a pivotal moment in Canada’s AI policy landscape, where trust is emerging as a central challenge for adoption, governance, and public confidence. In its new National Artificial Intelligence Strategy, the federal government observes, “For Canada to thrive in the era of AI, Canadians need to trust in its promise. [...] Trust is the north star of this strategy.” As Evan Solomon, Canada’s minister of artificial intelligence and digital innovation, noted in a recent talk, “Technology moves at the speed of innovation, but adoption moves at the speed of trust.”
That tension is increasingly visible in Canada’s national AI strategy discussions. A recent federal consultation, drawing more than 64,000 responses, found Canadians are almost evenly split between excitement about AI’s economic potential and concern about its risks, highlighting trust as a defining factor in whether and how AI systems are adopted.
The report also intersects with growing discussions about technological sovereignty in Canada. As policymakers emphasize the need for domestic AI capacity and governance, trustworthiness becomes foundational—not only for public adoption, but for maintaining control over how these systems are developed and deployed.
In this context, trustworthiness is not just a theoretical concern. As deployment accelerates, understanding how trust forms, and how trustworthiness is demonstrated, has become a policy and governance priority.
SRI Research Lead Beth Coleman
A shift from “trust in AI” to “trustworthy AI”
“Trust in AI is often framed as a user attitude or interface challenge, our analysis shows that trust must be grounded in demonstrated system performance, clear governance, and institutional responsibility,” said Coleman, a full professor of data and cities at the University of Toronto’s Institute of Communication, Culture, Information and Technology and Faculty of Information. “In other words, AI systems should not simply seek trust—they must be designed and governed to earn it.”
“Trust in AI is not a single property, but a relationship between systems, users, and institutions.”
The paper findings reinforce a key unifying theme: trust in AI is not a single property, but a dynamic relation between systems, users, and institutions.
From white paper to ongoing research agenda
As governments and organizations move from experimentation to real-world deployment, the need for shared frameworks of trust is becoming more urgent.
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."
Stay tuned for the 2026 AI & Trust Working Group Report and the call for next year's cohort.
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