Module 11 Summary: Privacy, Safety, Bias, and Human Boundaries

Module ID: AIT-M11 Status: Source package created; public shell pending

What learners should remember

Learners can identify information that should not be shared, spot bias and unfair assumptions, define human review boundaries, and keep records for important AI-assisted work.

The module is practical. The learner should leave with a small piece of reusable work, not only an idea.

Evidence produced

• Privacy checklist.
• Bias review note.
• Human review boundary.
• AI-use record.
• Knowledge check score.

Ready for the next module when

The learner can:

• some information should not be pasted into general tools.;
• different roles create different duties of care.;
• ai output can repeat unfair patterns or invent reasons about people.;
• some outputs need human or expert review before use.;
• important ai-assisted work may need a simple record.;
• safety improves when it becomes a checklist, not a feeling.;
• explain what they will verify, edit, ask again, or reject.

Next module

Module 12 is the capstone everyday AI workflow.