AI outputs can be fluent, authoritative, and wrong, sometimes all at once.
This workshop equips learners with a practical verification mindset and a set of transferable habits for evaluating AI-generated content before acting on it.
Participants will work through "spot the error" exercises, developing pattern recognition for the specific ways AI tends to fail. The session will also address the 'verification gap' - the documented tendency for fluent, well-formatted AI outputs to reduce users' felt need to question them - and teach practical counter-habits.
Workshop participants will leave with a personal verification checklist they can apply immediately in their workflows.