Interdisciplinary Studies

Experimental narratives: A comparison of human crowdsourced storytelling and AI storytelling

N. Beguš

This research by Nina Beguš explores a groundbreaking framework that merges behavioral and computational experiments using fictional prompts to unveil cultural artifacts and social biases in storytelling. Delving into 250 human stories and 80 AI-generated narratives, it uncovers how AI, particularly GPT-4, portrays progressive themes in gender roles and sexuality, while highlighting the imaginative superiority of human storytelling. Discover how fiction can bridge understanding between human and AI social dynamics.

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Index

Abstract

This paper introduces a framework combining behavioral and computational experiments using fictional prompts to investigate cultural artifacts and social biases in storytelling by humans and generative AI. Analyzing 250 human stories and 80 AI-generated stories (GPT-3.5 and GPT-4), the study reveals that AI narratives, particularly those from GPT-4, show more progressive gender roles and sexuality than human-authored texts. While AI can offer innovative plot twists, human stories demonstrate more imaginative scenarios and rhetoric. The framework suggests fiction as a tool for understanding human and AI collective imaginary and social dimensions.

Publisher

HUMANITIES AND SOCIAL SCIENCES COMMUNICATIONS

Published On

Oct 28, 2024

Authors

Nina Beguš

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