AWS Certified AI Practitioner
Human-Centered Explainable AI
An explanation only counts if it reaches the right person in a usable form. This lesson covers designing for the audience, disclosing AI use, building feedback paths, and keeping human oversight on consequential decisions.
Intermediate 20 minutes 5 Learning Objectives
- Explain why the audience for an explanation is a design input rather than an afterthought
- Apply contrastive framing so an explanation answers the question the person is actually asking
- Describe AI decision transparency in practice, including disclosure, watermarking, and content provenance
- Design a user-feedback mechanism that changes the system rather than collecting sentiment
- Identify when human oversight is required and the failure modes that make it ineffective