Scientist
Explains the relevant evidence, how it was studied and where it stops, and responds to the stakeholder’s account.
Dialogue series
TRUST Across Perspectives
Scientists and stakeholders in conversation about trust in AI.
Name proposed to the Board, 13 Nov 2026 · three-episode pilot proposed for January–March 2027
The Format
A Scientist, a Stakeholder, One Shared Question
A scientist and a stakeholder bring research and experience to the same question. Frank Krueger moderates, asking what the evidence tells us, what people encounter in practice, and where the two guests disagree. Each conversation closes with an open question and a practical next step.
Stakeholder
Uses the technology, puts it into practice or lives with its consequences. The role is stated clearly; one guest does not speak for all users.
Moderator: Frank Krueger
Keeps the conversation accessible and brings in the questions of people affected. Where he has no first-hand experience, he says so and invites those perspectives into the preparation.
One Conversation
About Forty Minutes, Six Steps
Proposed structure · recorded, no live audience in the pilot
- The situationA concrete AI-related trust problem and why it matters to the people affected.
- EvidenceWhat research can establish, how it was studied, and what it cannot yet resolve.
- ExperienceWhat the stakeholder sees in practice, including constraints and consequences.
- Questions across perspectivesThe guests question each other; the moderator brings in the questions of people affected.
- What changesEach guest names something learned, a practical implication, or a view that needs testing.
- What remains openOne research question and one next step, with links to the sources.
Pilot
Three Proposed Questions
Topics for a January–March 2027 pilot. These are proposed questions; no guests have been invited.
When should we rely on an AI answer?
A researcher on trust or human–AI interaction, with a practitioner responsible for how people use AI information.
Trust and accountability in automated hiring
A researcher on human judgment or responsible AI, with an employment practitioner or a representative of people affected.
AI in public services
A researcher on institutional trust, with a public-service practitioner or community representative.
How It Connects
From Evidence to Conversation
A finding in TRUST TRACE can suggest a question. The guests refine it, discuss it, and the conversation leaves a short note with sources that feeds the newsletter and new questions for TRACE.
- TRACE finding
- Shared question
- Dialogue
- Outcome note
- Newsletter
For an example of a question raised before any guest is invited, read the first TRACE Field Note on what AI trust research draws from decision science.
Looking for the TRUST Atlas interview series?
Earlier plans for a one-guest interview series under the name TRUST Atlas are under review. The scientist–stakeholder format on this page is proposed instead, for the Board’s decision. The Foundation’s research explorer is proposed to be renamed TRUST TRACE.