Uncovering Tone Bias in LLM-Powered UX: An Empirical Study

This ArXiv article highlights a critical concern: the potential for bias within the tone of Large Language Model (LLM)-driven User Experience (UX) systems. The empirical characterization offers insights into how such biases manifest and their potential impact on user interactions.

• •Identifies potential for bias in the tone of LLM-powered UX.
• •Employs empirical methods to characterize the nature of tone biases.
• •Raises awareness regarding fairness and potential user impact of biases.