Quantitative Assessment of Intersectional Empathetic Bias and Understanding
This work addresses the issue of poor dataset quality and evaluation reliability in empathy assessment for LLMs, particularly for languages like Slavonic ones, though it is incremental as it builds on existing metrics and methods.
The authors tackled the problem of evaluating empathy in LLMs by proposing a framework that operationalizes empathy close to its psychological origins, using controlled prompt generation to measure variance in responses, but found small variance and no convincing differences in empathetic understanding across social groups in initial tests.
A growing amount of literature critiques the current operationalizations of empathy based on loose definitions of the construct. Such definitions negatively affect dataset quality, model robustness, and evaluation reliability. We propose an empathy evaluation framework that operationalizes empathy close to its psychological origins. The framework measures the variance in responses of LLMs to prompts using existing metrics for empathy and emotional valence. The variance is introduced through the controlled generation of the prompts by varying social biases affecting context understanding, thus impacting empathetic understanding. The control over generation ensures high theoretical validity of the constructs in the prompt dataset. Also, it makes high-quality translation, especially into languages that currently have little-to-no way of evaluating empathy or bias, such as the Slavonic family, more manageable. Using chosen LLMs and various prompt types, we demonstrate the empathy evaluation with the framework, including multiple-choice answers and free generation. The variance in our initial evaluation sample is small and we were unable to measure convincing differences between the empathetic understanding in contexts given by different social groups. However, the results are promising because the models showed significant alterations their reasoning chains needed to capture the relatively subtle changes in the prompts. This provides the basis for future research into the construction of the evaluation sample and statistical methods for measuring the results.