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Social Skill Training with Large Language Models

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arxiv 2404.04204 v1 pith:GGTZQJNR submitted 2024-04-05 cs.CL cs.HC

classification cs.CLcs.HC
keywords socialskilltrainingframeworklanguagelargemodelspeople
verification ladder T0 review T1 audit T2 compute T3 formal
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People rely on social skills like conflict resolution to communicate effectively and to thrive in both work and personal life. However, practice environments for social skills are typically out of reach for most people. How can we make social skill training more available, accessible, and inviting? Drawing upon interdisciplinary research from communication and psychology, this perspective paper identifies social skill barriers to enter specialized fields. Then we present a solution that leverages large language models for social skill training via a generic framework. Our AI Partner, AI Mentor framework merges experiential learning with realistic practice and tailored feedback. This work ultimately calls for cross-disciplinary innovation to address the broader implications for workforce development and social equality.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. OpenAlex reports about 5 citations worldwide. Full citation record

  1. Practicing with Language Models Cultivates Human Empathic Communication

    cs.CL 2026-03 conditional novelty 6.5 of 10

    Personalized LLM feedback after practice conversations with AI partners significantly improves human empathic communication on six preregistered dimensions without homogenizing responses, while trait empathy fails to ...

  2. FaciliTrain: Practicing Facilitation Skills through AI-Simulated Group Dialogue

    cs.HC 2026-07 conditional novelty 6.0 of 10

    A voice-based multi-participant AI simulation trains five facilitation techniques; a small controlled pilot shows comparable accuracy across feedback conditions, a comfort trade-off, and strong preference for AI feedback.

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