Generative AI at Work / Unit 9 GAI 220 review, 2 to 3 minutes
The Whole Pattern
The idea
The final capstone draws the course into one pattern, built on the principle it started with: AI proposes, humans decide.
In practice
The pattern has eight parts, one for each unit before this one. First, know what the tool is: a generator of fluent, derived text whose confidence is not evidence, and which confabulates as a matter of design. Second, name the risks, using NIST's twelve and its seven marks of trustworthiness, and scan each use before adopting it. Third, prompt deliberately: instruction, context, input and format, tested against criteria, and changed one thing at a time. Fourth, use safe patterns: use only what is given, invent nothing, ask instead of guessing, mark uncertainty, and never paste what you would not publish. Fifth, verify claim by claim, number by number, against the real source, with experts where the stakes need them, and record what you checked. Sixth, keep humans in the loop by design: a feature gate, a clear line between what AI suggests and what the system decides, review matched to the stakes, and a log of overrides. Seventh, govern the tools: governed services for sensitive work, vendors checked like any other supplier, and short team rules people actually read. Eighth, document the AI and the work it touches, with model cards read critically, data questioned, and reference packs owned, versioned and kept current. Through all eight runs the method's working line: draft, check, decide.
Where people slip
None of the eight makes the tool more accurate. Together they make its errors visible, its use accountable, and its benefits safe to keep. The method's own conclusion fits the whole course: AI can speed the mechanics of good work enormously, and it is no substitute for the judgment of the people doing it.
Your place on the trail
Every lesson rests on earlier ones and opens later ones. Tap any to jump.
Builds on
Unlocks
- Nothing yet depends on this.
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