LLMs and Emotional Intelligence: Evaluating Emotional Understanding Through Psychometric Tools
Year: 2025
Type: conference-paper
Abstract: This study investigates the Emotional Intelligence (EI) of LLMs by evaluating their ability to replicate human-like emotional reasoning and self-assessment using established psychometric tools.Prior research has utilized standardized tests to evaluate LLMs in unambiguous emotional reasoning contexts, where a single correct answer is expected.However, emotional situations are rarely simple, and subjective evaluation can often produce equally valid alternative interpretations.This preliminary study proposes to investigate LLM EI using psychometric tests developed for humans, where the emotional reasoning contexts are more complex, subject to multiple interpretations, and often subjective.Four mainstream LLMs (GPT-4o, Mixtral, Gemma-2, and Llama-3.1) are evaluated using two well-established EI assessments: the Trait Emotional Intelligence Questionnaire (TEIQUE) and the Situational Test of Emotional Understanding (STEU).TEIQUE assesses self-perceived emotional capabilities across the facets of well-being, self-control, emotionality, and sociability, while STEU evaluates situational emotional reasoning in real-world contexts.The experiments reveal distinctive self-awareness traits in LLMs, varying levels of safety alignment, and their ability to interpret emotional situations.A human study is conducted to evaluate the reasonableness of LLM emotional appraisals that deviate from expected responses.The results highlight the potential of LLMs to act as tools for emotional interpretation, transcending the deterministic outputs of traditional NLP systems.Finally, this study concludes by discussing the need for non-deterministic and more sophisticated EI assessments that better align with human EI.
Authors: Dhairya Dalal, Gaurav Negi, Davide Picca
Language: English
Topic: Emotion and Mood Recognition
Subfield: Experimental and Cognitive Psychology
Field: Psychology
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W4411279332