ai-expertise-interrogation-designer

An AI interrogation activity uses student domain knowledge to detect AI distortions by having learners challenge AI-generated claims and annotate errors. It turns existing student expertise into a practical AI literacy lesson.

To design an AI evaluation lesson, specify a student expertise domain and age level to generate structured interrogation prompts, distortion annotation methods, and discussion synthesis frameworks for classroom use.

Yes, AI interrogation activities apply to any specialist interest including sports, cultural traditions, and hobbies. Students use their deep personal knowledge to identify oversimplifications and false confidence in AI responses.

AI distortions students can identify include errors, missing nuance, cultural flattening, and false confidence. The Skill provides taxonomies and annotation methods to help students systematically detect and categorize these limitations.

No prior AI evaluation training is required. The Skill provides structured expertise activation protocols and calibrated prompts, allowing educators to facilitate AI distortion analysis using students' existing domain knowledge.

Avoid expertise-based AI interrogation when students lack sufficient domain knowledge to evaluate AI claims, as the activity relies on activating existing specialist understanding to detect AI distortions accurately.