Davos Panel Explores Building Trust in the AI Age

Experts discuss the need for governance, verifiable security, accountable deployment, audits, and protocols to foster trust in AI systems.

Published on Mar. 2, 2026

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At the Imagination in Action conference at the Davos summit, a panel of experts from Fudan University, Boston University, Stanford, and MIT discussed the key elements required to build trust in AI as the technology becomes more ubiquitous. The panelists emphasized the importance of governance, verifiable security, accountable deployment, audits, and technical protocols to address concerns around data privacy, algorithm transparency, and the psychological impact of AI agents.

Why it matters

As AI systems become more prevalent in consumer-facing applications and digital environments, establishing trust in the technology is crucial. The panel's discussion highlights the multifaceted challenges in building trust, including the need for collaboration, global governance, and a deeper understanding of human psychology in relation to AI.

The details

The panelists addressed several key aspects of building trust in AI. Fudan University Professor Charles Cheng stressed the importance of finding solutions that lead to collaboration and global-level governance. Boston University Associate Provost Azer Bestavros emphasized the need to not only trust the AI system itself, but also the individuals and organizations deploying it. Stanford's Robert Mahari discussed the use of cryptography, contracts, and technical safeguards to verify the security and integrity of AI systems. MIT's Ramesh Raskar proposed the idea of a protocol for the web, similar to the browser-website model, to enable secure communication between AI agents.

  • The Imagination in Action conference took place at the Davos summit in 2026.

The players

Charles Cheng

A professor at Fudan University who discussed the need for global-level governance and collaboration to build trust in AI.

Azer Bestavros

The associate provost at Boston University who emphasized the importance of trusting not just the AI system, but also the individuals and organizations deploying it.

Robert Mahari

The associate director of the Codex Center at Stanford who proposed the use of cryptography, contracts, and technical safeguards to verify the security and integrity of AI systems.

Ramesh Raskar

A researcher at MIT who suggested the idea of a protocol for the web, similar to the browser-website model, to enable secure communication between AI agents.

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What they’re saying

“For me, the key trust piece, or at least one of the key trust pieces, is: how do we make sure that we can trust the providers of these large language models that are increasingly ubiquitous, to safeguard the data?”

— Robert Mahari, Associate Director, Codex Center at Stanford (Imagination in Action conference)

“It depends on who you work with. If you are the individual, perhaps, worried about your data, well, perhaps not just do I trust my data, but do you trust the algorithm? Do you trust the recommendations? Do you trust whoever deployed that AI? It's actually not just the AI that needs to be trusted. It's who is deploying it.”

— Azer Bestavros, Associate Provost, Boston University (Imagination in Action conference)

“You verify by measuring, by observing. A big focus here is, we'll deploy it, but we have the responsibility to develop the tools that allow those who are going to use AI to score it. So we have faculty who will work on scoring ethics. We have faculty working on auditing it.”

— Azer Bestavros, Associate Provost, Boston University (Imagination in Action conference)

The takeaway

Building trust in AI will require a multifaceted approach, including governance, verifiable security, accountable deployment, audits, and technical protocols. As AI becomes more ubiquitous, addressing concerns around data privacy, algorithm transparency, and the psychological impact of AI agents will be crucial to fostering trust and ensuring the responsible development of this transformative technology.