Trust in AI systems is becoming more critical than raw performance, as users need to feel confident in the reliability and consistency of these systems.

The importance of trust in AI systems is growing, as users need assurance that these systems will behave reliably and consistently.

Trust in AI systems involves verifying their reliability and consistency, which is crucial for user acceptance and enterprise success.

We need to manage transparency and control while using AI, ensuring users can trust the AI's actions on their behalf.

The behavior of AI systems is not just about what they produce but also how they produce it, which can significantly impact user trust.

Incorporating AI into workflows presents challenges, particularly in building trust with users and ensuring that AI helps them progress rather than causing frustration.

The main issue preventing people from gaining value from AI systems isn't performance optimization; it's the ability to confidently trust these systems.

The current environment fosters distrust among humans, leading to a paradox where people may trust AI systems more than their fellow humans, despite the potential dangers of AI. We are accelerating technology at the cost of transparency and regulation, which are essential checks and balances we need right now.

As AI becomes more capable, we need to ensure that it aligns with human values and interests.