"Not Human, Funnier": How Machine Identity Shapes Humor Perception in Online AI Stand-up Comedy

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Authors: Xuehan Huang, Canwen Wang, Yifei Hao, Daijin Yang, Ray Lc
Cited by: 5
References: 104

Abstract

Chatbots are increasingly applied to domains previously reserved for human actors. One such domain is comedy, whereby both the general public working with ChatGPT and research-based LLM-systems have tried their hands on making humor. In formative interviews with professional comedians and video analyses of stand-up comedy in humans, we found that human performers often use their ethnic, gender, community, and demographic-based identity to enable joke-making. This suggests whether the identity of AI itself can empower AI humor generation for human audiences. We designed a machine-identity-based agent that uses its own status as AI to tell jokes in online performance format. Studies with human audiences (N=32) showed that machine-identity-based agents were seen as funnier than baseline-GPT agent. This work suggests the design of human-AI integrated systems that explicitly utilize AI as its own unique identity apart from humans.

Fields of Study & Subjects

Humor Studies and Applications AI in Service Interactions Artificial Intelligence in Healthcare and Education

Publication details

Journal / source
Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems
Publisher
ACM
Pages
1–27
Publication date
13 April 2026
Language
EN