Designing and Evaluating Dialogue LLMs for Co-Creative Improvised Theatre

• URL: http://arxiv.org/abs/2405.07111v1
• Date: Sat, 11 May 2024 23:19:42 GMT
• Title: Designing and Evaluating Dialogue LLMs for Co-Creative Improvised Theatre
• Authors: Boyd Branch, Piotr Mirowski, Kory Mathewson, Sophia Ppali, Alexandra Covaci,
• Abstract summary: This study presents Large Language Models (LLMs) deployed in a month-long live show at the Edinburgh Festival Fringe. We explore the technical capabilities and constraints of on-the-spot multi-party dialogue. Our human-in-the-loop methodology underlines the challenges of these LLMs in generating context-relevant responses.
• Score: 48.19823828240628
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Social robotics researchers are increasingly interested in multi-party trained conversational agents. With a growing demand for real-world evaluations, our study presents Large Language Models (LLMs) deployed in a month-long live show at the Edinburgh Festival Fringe. This case study investigates human improvisers co-creating with conversational agents in a professional theatre setting. We explore the technical capabilities and constraints of on-the-spot multi-party dialogue, providing comprehensive insights from both audience and performer experiences with AI on stage. Our human-in-the-loop methodology underlines the challenges of these LLMs in generating context-relevant responses, stressing the user interface's crucial role. Audience feedback indicates an evolving interest for AI-driven live entertainment, direct human-AI interaction, and a diverse range of expectations about AI's conversational competence and utility as a creativity support tool. Human performers express immense enthusiasm, varied satisfaction, and the evolving public opinion highlights mixed emotions about AI's role in arts.

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