How AI Ideas Affect the Creativity, Diversity, and Evolution of Human
  Ideas: Evidence From a Large, Dynamic Experiment
Joshua Ashkinaze Julia Mendelsohn Li Qiwei Ceren Budak Eric Gilbert
Exposure to large language model output is rapidly increasing. How will
seeing AI-generated ideas affect human ideas? We conducted an experiment (800+
participants, 40+ countries) where participants viewed creative ideas that were
from ChatGPT or prior experimental participants and then brainstormed their own
idea. We varied the number of AI-generated examples (none, low, or high
exposure) and if the examples were labeled as 'AI' (disclosure). Our dynamic
experiment design -- ideas from prior participants in an experimental condition
are used as stimuli for future participants in the same experimental condition
-- mimics the interdependent process of cultural creation: creative ideas are
built upon prior ideas. Hence, we capture the compounding effects of having
LLMs 'in the culture loop'. We find that high AI exposure (but not low AI
exposure) did not affect the creativity of individual ideas but did increase
the average amount and rate of change of collective idea diversity. AI made
ideas different, not better. There were no main effects of disclosure. We also
found that self-reported creative people were less influenced by knowing an
idea was from AI, and that participants were more likely to knowingly adopt AI
ideas when the task was difficult. Our findings suggest that introducing AI
ideas into society may increase collective diversity but not individual
creativity.