# Human Creativity in the Age of LLMs: Randomized Experiments on Divergent and Convergent Thinking

arXiv: https://arxiv.org/abs/2410.03703 · HTML: https://mlsanity.com/paper/2410.03703/

## Key facts

- Cited by 43 papers in the map (data through 14 Oct 2026).
- Placed in Reasoning benchmarks and evaluation, one of 17 directions in LLM reasoning.
- Builds on 10 of its 63 references that are in the map.
- First posted on arXiv 24 Sep 2024.

## Placed in

- LLM reasoning / [Reasoning benchmarks and evaluation](https://mlsanity.com/lr/reasoning-benchmarks-and-evaluation/)

## Builds on (most cited first, 10 of 10)

- [Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks](https://mlsanity.com/paper/1908.10084/) (2019)
- [The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery](https://mlsanity.com/paper/2408.06292/) (2024)
- [Can LLMs Generate Novel Research Ideas? A Large-Scale Human Study with 100+ NLP Researchers](https://mlsanity.com/paper/2409.04109/) (2024)
- [Does Writing with Language Models Reduce Content Diversity?](https://mlsanity.com/paper/2309.05196/) (2023)
- [Homogenization Effects of Large Language Models on Human Creative Ideation](https://mlsanity.com/paper/2402.01536/) (2024)
- [Building Machines that Learn and Think with People](https://mlsanity.com/paper/2408.03943/) (2024)
- [LLM Discussion: Enhancing the Creativity of Large Language Models via Discussion Framework and Role-Play](https://mlsanity.com/paper/2405.06373/) (2024)
- [Comparing Traditional and LLM-based Search for Consumer Choice: A Randomized Experiment](https://mlsanity.com/paper/2307.03744/) (2023)
- [How AI Ideas Affect the Creativity, Diversity, and Evolution of Human Ideas: Evidence From a Large, Dynamic Experiment](https://mlsanity.com/paper/2401.13481/) (2024)
- [Inspiration through Observation: Demonstrating the Influence of Automatically Generated Text on Creative Writing](https://mlsanity.com/paper/2107.04007/) (2021)

## Built on by (most cited first, 30 of 43)

- [IdeaSynth: Iterative Research Idea Development Through Evolving and Composing Idea Facets with Literature-Grounded Feedback](https://mlsanity.com/paper/2410.04025/) (2024)
- [Creativity in LLM-based Multi-Agent Systems: A Survey](https://mlsanity.com/paper/2505.21116/) (2025)
- [Understanding, Protecting, and Augmenting Human Cognition with Generative AI: A Synthesis of the CHI 2025 Tools for Thought Workshop](https://mlsanity.com/paper/2508.21036/) (2025)
- [GODBench: A Benchmark for Multimodal Large Language Models in Video Comment Art](https://mlsanity.com/paper/2505.11436/) (2025)
- [GenTune: Toward Traceable Prompts to Improve Controllability of Image Refinement in Environment Design](https://mlsanity.com/paper/2508.15227/) (2025)
- [Recognising, Anticipating, and Mitigating LLM Pollution of Online Behavioural Research](https://mlsanity.com/paper/2508.01390/) (2025)
- [ConlangCrafter: Constructing Languages with a Multi-Hop LLM Pipeline](https://mlsanity.com/paper/2508.06094/) (2025)
- [Vibe Coding in Product Teams: Reconfiguring AI-Assisted Workflows, Prototyping, and Collaboration](https://mlsanity.com/paper/2509.10652/) (2025)
- [Novice Developers' Perspectives on Adopting LLMs for Software Development: A Systematic Literature Review](https://mlsanity.com/paper/2503.07556/) (2025)
- [Diverse AI Personas Can Mitigate the Homogenization Effect in Human-AI Collaborative Ideation](https://mlsanity.com/paper/2504.13868/) (2025)
- [Large Language Models as Search Engines: Societal Challenges](https://mlsanity.com/paper/2512.08946/) (2025)
- [Reflexis: Supporting Reflexivity and Rigor in Collaborative Qualitative Analysis through Design for Deliberation](https://mlsanity.com/paper/2601.15445/) (2026)
- [Scaffolding Recursive Divergence and Convergence in Story Ideation](https://mlsanity.com/paper/2507.03307/) (2025)
- [To Trade or Not to Trade: An Agentic Approach to Estimating Market Risk Improves Trading Decisions](https://mlsanity.com/paper/2507.08584/) (2025)
- [Exploration vs. Fixation: Scaffolding Divergent and Convergent Thinking for Human-AI Co-Creation with Generative Models](https://mlsanity.com/paper/2512.18388/) (2025)
- [AI-Associated Lexical Shifts Across 34 Languages: Cross-Lingual Convergence and Diachronic Uptake in News Writing](https://mlsanity.com/paper/2605.25358/) (2026)
- [Automated Creativity Evaluation of Language Models Across Open-Ended Tasks](https://mlsanity.com/paper/2606.11762/) (2026)
- [Beyond Text: Characterizing Domain Expert Needs in Document Research](https://mlsanity.com/paper/2504.12495/) (2025)
- [AnimAgents: Coordinating Multi-Stage Animation Pre-Production with Human-Multi-Agent Collaboration](https://mlsanity.com/paper/2511.17906/) (2025)
- [From Answer Givers to Design Mentors: Guiding LLMs with the Cognitive Apprenticeship Model](https://mlsanity.com/paper/2601.19053/) (2026)
- [Are Semantic Networks Associated with Idea Originality in Artificial Creativity? A Comparison with Human Agents](https://mlsanity.com/paper/2602.02048/) (2026)
- [Interrogating Design Homogenization in Web Vibe Coding](https://mlsanity.com/paper/2603.13036/) (2026)
- [Incentives shape how humans co-create with generative AI](https://mlsanity.com/paper/2604.03529/) (2026)
- [TeamLLM: A Human-Like Team-Oriented Collaboration Framework for Multi-Step Contextualized Tasks](https://mlsanity.com/paper/2604.06765/) (2026)
- [The Effect of Idea Elaboration on the Automatic Assessment of Idea Originality](https://mlsanity.com/paper/2604.20569/) (2026)
- [Ex Ante Evaluation of AI-Induced Idea Diversity Collapse](https://mlsanity.com/paper/2605.06540/) (2026)
- [Is Convergence Inevitable? Tracing Output Homogeneity Back to Base Models](https://mlsanity.com/paper/2608.11426/) (2026)
- [The Limits of Automatic Evaluation of Creativity in Large Language Models](https://mlsanity.com/paper/2608.23705/) (2026)
- [Local Differences, Global Lessons: Insights from Organisation Policies for International Legislation](https://mlsanity.com/paper/2503.05737/) (2025)
- [Galton's Law of Mediocrity: Why Large Language Models Regress to the Mean and Fail at Creativity in Advertising](https://mlsanity.com/paper/2509.25767/) (2025)

## Abstract (arXiv)

Large language models are transforming the creative process by offering unprecedented capabilities to algorithmically generate ideas. While these tools can enhance human creativity when people co-create with them, it's unclear how this will impact unassisted human creativity. We conducted two large pre-registered parallel experiments involving 1,100 participants attempting tasks targeting the two core components of creativity, divergent and convergent thinking. We compare the effects of two forms of large language model (LLM) assistance -- a standard LLM providing direct answers and a coach-like LLM offering guidance -- with a control group receiving no AI assistance, and focus particularly on how all groups perform in a final, unassisted stage. Our findings reveal that while LLM assistance can provide short-term boosts in creativity during assisted tasks, it may inadvertently hinder independent creative performance when users work without assistance, raising concerns about the long-term impact on human creativity and cognition.