Social Skill Training with Large Language Models
Diyi Yang, Caleb Ziems, William Held, Omar Shaikh, Michael S., Bernstein, John Mitchell

TL;DR
This paper proposes a novel framework using large language models to make social skill training more accessible, realistic, and personalized, aiming to improve communication skills across diverse populations.
Contribution
It introduces the AI Partner, AI Mentor framework that combines experiential learning, realistic practice, and tailored feedback for social skill development.
Findings
Framework enables realistic social skill practice
Personalized feedback enhances learning outcomes
Potential to improve social skill accessibility
Abstract
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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Taxonomy
TopicsTopic Modeling
