What AI Can and Cannot Do – A Practical Guide By the end of this lesson, students should be able to: The core decision framework – four questions. Question 1: Is this task language-intensive? AI's strengths are primarily language-based – writing, synthesis, explanation, code. If the task is primarily about judgment, physical action, interpersonal relationship, or real-time data, AI adds less value. If it is primarily language-based, proceed to question 2. Question 2: Does this task require current or highly specific factual information? If yes – current events, live data, highly specific technical specifications, regulatory details – the answer is either (a) supplement AI output with verified current sources, or (b) do not use AI for the factual core of this task. AI handles well-established, general information reliably; specific and current information requires verification. Question 3: How severe are the consequences of an error? Low-severity, easily-correctable tasks (internal drafts, brainstorming, first outlines) tolerate AI's error rate well. High-severity tasks (legal filings, medical guidance, financial disclosures, safety protocols) require more stringent verification or human expert input, even if AI is involved in drafting. Question 4: Does this task require a judgment call that belongs to a human professional? If the task output is a professional recommendation, advice, or decision that carries accountability – and where your expertise is what the client, employer, or audience is paying for – AI is an input tool, not a decision maker. Human professional judgment is the required output. Quick reference: high-value AI use. Quick reference: use with caution. Quick reference: exclude or use minimally. Enroll to continue this lesson. The preview above shows the lesson objectives and opening lesson content. Enroll to view the full lesson, complete the practice work, and take the lesson quiz.
Lesson 5: Choosing When to Use AI and When Not To
Lesson Objectives
Lesson Content
