Thinking With, Not Like, AI

Which aspects of judgment and wisdom are uniquely human and difficult for AI to replicate? How can domain experts use AI as a partner without surrendering their own responsibility or skepticism? What kinds of decisions should always remain under human control, even if AI could automate them? How can individuals cultivate intuition and ethical reflection alongside technical literacy?

What questions can you ask to uncover the assumptions and blind spots in an AI-generated answer? How can you cross-check AI outputs against multiple sources, perspectives, or tools? In what ways can language, framing, and default options in AI interfaces subtly shape user choices? How can organizations build cultures where challenging AI recommendations is expected rather than punished?

How can teams integrate AI into their workflows without silencing quieter voices or minority views? What roles (researcher, critic, explainer, simulator) can AI play in collective decision-making processes? How might communities use AI to explore scenarios, negotiate trade-offs, or surface overlooked options? What governance structures are needed when groups rely on AI for high-stakes or public-impact decisions?