How Does Differential Privacy Affect Social Bias in LLMs? A Systematic Evaluation

This research systematically evaluates the relationship between differential privacy (DP) and social bias in large language models (LLMs). It compares a DP-trained LLM against non-DP baselines across various tasks, finding that DP reduces bias in sentence scoring but not universally, and reveals a discrepancy between logit-level and output-level bias.