AI-generated personas marketed as substitutes for real research participants. The pitch is faster and cheaper than recruitment; the reality is regression to training-data averages dressed up as user voices.
Definition: AI-generated personas marketed as substitutes for real research participants. The pitch is faster and cheaper than recruitment; the reality is regression to training-data averages dressed up as user voices.
AI-generated personas marketed as substitutes for real research participants. The pitch is faster and cheaper than recruitment. The reality is regression to training-data averages dressed up as user voices. Useful for pilot questionnaires or stimulus material; not a substitute for actual users, no matter how confident the demo looked. See AI-moderated interviews for related issues.
When an AI model generates plausible-sounding but factually incorrect or fabricated information. A natural consequence of how LLMs predict probable text rather than verify truth.
The verified, real-world data that a model or analysis is measured against. In UX research: actual behavior, actual interviews, actual outcomes, not what a model predicts.
A trained system that maps input to output through learned patterns. In research practice usually a large language model, but the term also covers image, audio, and multi-modal systems.