Responsible AI at Work

Course contents (12 parts)

1. 1

   Pre-course assessment

   Check your starting knowledge before learning

2. 2

   Our approach to responsible AI

   Lesson video

3. 3

   Start with benefits and affected people

   Ask who benefits, who could be harmed, and why AI is being considered.

4. 4

   Map risks before a trial

   Consider data, impact, context, and reversibility.

5. 5

   Give human reviewers real authority

   Define review points, accountable people, and ways to correct outcomes.

6. 6

   Communicate limitations and protect data

   Explain to users what AI does and how data is handled.

7. 7

   Monitor outcomes and stop when needed

   Set measures, check differences between groups, and review when context changes.

8. 8

   Applied case study and evidence review

   Define meaningful review and stop authority for complaint summarization

9. 9
   Document0 points1 min

   Course study guide

   A practical guide to the course lessons, with Thai and English editions.

10. 10
    Document0 points1 min

    Practical workbook

    Course-based exercises for review and planning a small real-world trial.

11. 11
    Document0 points1 min

    Quick reference

    A concise reference to course topics and review points for use while working.

12. 12

    Post-course assessment

    Review key ideas and apply them to practical situations.