Apply Critical Thinking with AI

Course description

AI can generate ideas, summarize information, analyze patterns, and produce recommendations in seconds. That speed can be useful, but a polished response is not automatically accurate, complete, fair, or appropriate for the situation at hand. Strong decisions still require people to question the output, check the evidence, and consider what could be missing. This practical course helps professionals use critical thinking when working with AI-generated content and recommendations. Learners examine why AI can produce confident but unreliable information, including unsupported claims, invented details, outdated information, and conclusions based on incomplete context. They also explore two common sources of bias: limitations in AI outputs and confirmation bias in the person reviewing them. Using a workplace staffing scenario, learners practice framing questions that surface multiple options, assumptions, risks, trade-offs, and possible failure points rather than pushing AI toward one preferred answer. They learn how to evaluate an AI-supported recommendation against trusted evidence, operational constraints, stakeholder impact, and the consequences of being wrong. The course also introduces the Ladder of Evidence, a practical questioning method leaders can use to help team members examine claims, evidence, assumptions, missing information, and alternative explanations. The result is a more thoughtful approach to AI use. Learners leave better prepared to treat AI as a useful input, not the final authority, and to build team habits that keep human judgment and accountability at the center of decision-making.

Course outline