Unveiling Bias in Fairness Evaluations of Large Language Models: A Critical Literature Review of Music and Movie Recommendation Systems

Understand

The rise of generative artificial intelligence, particularly Large Language Models (LLMs), has intensified the imperative to scrutinize fairness alongside accuracy.

• Recent studies have begun to investigate fairness evaluations for LLMs within domains such as recommendations.
• Given that personalization is an intrinsic aspect of recommendation systems, its incorporation into fairness assessments is paramount.
• Yet, the degree to which current fairness evaluation frameworks account for personalization remains unclear.