teleo-codex/inbox/claims/ai-ideas-increase-collective-diversity-experimental.md

type	title	confidence	domains	secondary_domains	description	created	processed_date	source	depends_on	challenged_by
claim	AI-generated ideas increase collective diversity in experimental creativity tasks	experimental	ai-alignment	collective-intelligence cultural-dynamics	In a pre-registered experiment with 800+ participants across 40+ countries, exposure to AI-generated ideas increased collective diversity on the Alternate Uses Task, even as individual creativity metrics remained unchanged or decreased.	2025-01-15	2025-01-15	type title authors year venue arxiv_id url preregistered paper AI Ideas Decrease Individual Creativity but Increase Collective Diversity Doshi Hauser 2025 arXiv 2401.13481v3 https://arxiv.org/abs/2401.13481v3 true	partial connectivity produces better collective intelligence than full connectivity collective intelligence requires diversity as a structural precondition	homogenization effect of large language models on creative diversity

AI-generated ideas increase collective diversity in experimental creativity tasks

In a pre-registered experiment (N=810, 40+ countries), Doshi & Hauser (2025) found that exposure to AI-generated ideas increased collective diversity on the Alternate Uses Task, even though individual creativity metrics (fluency, flexibility, originality) remained unchanged or decreased.

Key Findings

Collective diversity increased with AI exposure:

• High AI exposure (10 AI ideas) produced significantly higher collective diversity than low exposure (2 AI ideas) or control conditions
• Effect held across multiple diversity metrics (semantic distance, category coverage)
• Individual-level creativity did not increase; the effect was purely collective

Mechanism: AI as external diversity source:

• AI ideas introduced variation orthogonal to human ideation patterns
• Participants incorporated AI suggestions in idiosyncratic ways
• The "multiple worlds" experimental design (each participant saw different AI ideas) prevented convergence

Scope qualifiers:

• Single task type (Alternate Uses Task)
• Experimental setting with controlled AI exposure
• Short-term effects only
• Does not address naturalistic usage patterns

Challenges to Homogenization Narrative

This finding appears to contradict studies showing AI homogenizes creative output (e.g., ScienceDirect 2025 study on LLM creative diversity). The key difference:

• Homogenization studies: Naturalistic settings where users converge on similar AI outputs
• This study: Controlled exposure where each participant receives different AI ideas

Both findings can be true: AI can homogenize when users access the same outputs, but diversify when used as a source of varied external input.

Implications for Collective Intelligence

This connects to partial connectivity produces better collective intelligence than full connectivity — AI may function as a controlled diversity injection mechanism, similar to how partial connectivity prevents premature convergence while maintaining enough information flow.

The finding supports collective intelligence requires diversity as a structural precondition by demonstrating that external diversity sources (AI) can substitute for or complement human diversity in collective tasks.

Relevant Notes

• deep technical expertise is a greater force multiplier than AI assistance — this finding cuts against simple skill-amplification stories; AI's value may be in diversity injection rather than individual capability enhancement
• Flagged for Clay: implications for creative industries and entertainment production