Generative AI Foundations – Diffusion, Attention, and Creative Systems
Lesson 4: Sampling, Evaluation, and Responsible Creative Use
Lesson Objectives
By the end of this lesson, students should be able to:
- Compare generated options using a review rubric.
- Recognize when a generated output should be rejected.
- Build a responsible-use checklist for creative AI.
Lesson Content
Sampling means exploring possible outputs. In practice, a student may generate several versions, compare them, revise the prompt, and choose the best candidate. The danger is choosing the prettiest output instead of the most appropriate output.
A strong review rubric includes fit to prompt, readability, factual honesty, accessibility, brand fit, privacy, rights, and audience impact. For course marketing, the output should invite trust without pretending the course is officially certified by an outside provider unless that is true.
Generated media should be rejected when it distorts people, fabricates credentials, uses private material, copies protected identity, misrepresents a product, or makes a claim that cannot be supported.
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