Beyond accuracy and transparency: the real product factors driving human-AI trust

UX wants transparency features, and engineers want 99% accuracy - but neither guarantees safe AI adoption. Real product trust relies on how predictable your errors are, whether users can easily override flawed outputs, and how well the system signals its own limits. Learn how to design AI tools that encourage calibrated reliance without creating safety hazards.