FILED Talks:

AI is moving into everyday work faster than organizations can decide how much to trust it. The risk runs both ways: Employees blindly accept confident, polished answers without double checking accuracy — or they lost trust and stop using the tools altogether. Getting the balance right starts with understanding how trust is built in the first place.

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RecordPoint Global Head of AI Governance and Practice Sophie Boucher has a conversation with Dr. Max Evans, Associate Professor and Graduate Program Director at the School of Information Studies at McGill University to unpack what it really means to trust a technology that can't explain its reasoning and rarely gives the same answer twice.

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Max offers a model of trust built on ability, integrity, and benevolence, how data quality and limiting AI inputs to your structured data create more reliable outputs, where subject matter experts belong in the human-in-the-loop process, and why "Claude did this" is a sign that accountability has gone missing.

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This is a thoughtful, practical conversation about calibrating AI trust across your organization, so people neither accept AI outputs blindly nor burn hours second-guessing every one.