Keeping AI Honest: When to Trust, Verify, or Say No

What you'll learn

⚡ Decide when AI assistance is appropriate using a seven-question decision framework.
⚡ Choose sensible levels of AI authority, from read-only analysis to bounded autonomy.
⚡ Identify hallucinations, misleading summaries, unsupported claims, and consequential omissions.
⚡ Apply a framework (TRACE) to verify AI recommendations against independent sources of truth.
⚡ Explain why AI agents can game metrics and why independent verification matters.
⚡ Design practical human-review checkpoints, escalation rules, and operating limits for business workflows.

Requirements

❗ No programming or AI engineering experience required.
❗ Basic familiarity with AI assistants is useful, but not required.
❗ Optional: access to an AI assistant to experiment with the prompts; all core exercises include provided examples.

Description

This course contains the use of artificial intelligence.
AI can produce a polished report, persuasive recommendation, or confident answer in seconds. But how do you know whether it deserves your trust? And when should you avoid delegating the task in the first place?
InKeeping AI Honest, you will learn a practical, tool-independent approach to using AI at work without giving up critical thinking, evidence, or accountability. Instead of focusing on prompts or one AI platform, this course teaches the decisions that matter before and after AI generates an answer.
You will apply a seven-question framework to decide which tasks are appropriate for AI and how much authority it should have. You will learnTRACE, a five-step approach to verifying important claims against reliable evidence, and explore how autonomous agents can mislead themselves—or optimize the wrong goals—when their checks are weak.
Through workplace scenarios, downloadable exercises, and short quizzes, you will practice reviewing executive recommendations, finding omitted risks, designing review checkpoints, and setting useful limits on AI-assisted workflows.
Whether your organization uses ChatGPT, Claude, Microsoft Copilot, Gemini, or internal AI systems, the principles are the same: delegate thoughtfully, verify independently, and keep accountability clear.
No coding is required. This is not a technical framework tutorial or an introduction to prompt engineering. It is a practical course for professionals who want to use AI confidently without trusting it blindly.

Who this course is for

⭐ Professionals and managers who use AI-generated reports, recommendations, and analyses.
⭐ Project and program managers, analysts, operations leaders, and consultants.
⭐ Team leaders responsible for quality, oversight, and AI-assisted workflows.
⭐ Technical professionals who want better decision and verification practices without another tool-specific tutorial.

Homepage

https://www.udemy.com/course/keeping-ai-honest

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