Dynamics of collective creativity in AI art competitions

Event Description

IACS Research Theme: Human Centered Computing Seminar

Abstract: The AI art platform Artbreeder hosts daily remix parties where users build on each other's work, creating transparent evolutionary chains of images from a single seed. This study analyzes 130,882 images from 368 remix parties to identify the drivers of novelty, complexity, and competitive success. The results reveal an interesting tension: while more novel parent images produce more novel and complex children and attract more likes, users paradoxically prefer to remix images that are less novel and complex. At the group level, larger remix parties produce more novelty at the cost of lower complexity. Additionally, images tend to converge towards common thematic attractors (e.g., steampunk scenes, alien architecture, furries) over the course of remix parties. These results provide quantitative insights into collective creativity--the production of novelty by groups of people--a typically opaque aspect of human cultural evolution.

Speaker: Dr. Mason Youngblood

Location: Institute for Advanced Computational Science, Seminar Room

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