Lesson 893 of 1550
AI Recommender Radicalization Audits: Trajectory Testing
Recommender systems can drift users toward harmful content — design trajectory audits that test journeys, not just individual recommendations.
Lesson map
What this lesson covers
Learning path
The main moves in order
- 1The premise
- 2recommendation trajectory
- 3rabbit hole
- 4synthetic persona
Concept cluster
Terms to connect while reading
Section 1
The premise
AI can simulate user trajectories through your recommender and flag harmful drift, but harm thresholds need policy ownership.
What AI does well here
- Generate synthetic-persona watch sessions across diverse starting points.
- Cluster trajectory endpoints against a harm taxonomy.
What AI cannot do
- Decide what level of drift constitutes a policy violation.
- Replace a multidisciplinary harm review.
Key terms in this lesson
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