# Generative artificial intelligence enhances creativity but reduces the diversity of novel content

arXiv: https://arxiv.org/abs/2312.00506 · HTML: https://mlsanity.com/paper/2312.00506/

## Key facts

- Cited by 167 papers in the map (data through 14 Oct 2026).
- Builds on 4 of its 42 references that are in the map.
- First posted on arXiv 1 Dec 2023.

## Builds on (most cited first, 4 of 4)

- [GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models](https://mlsanity.com/paper/2303.10130/) (2023)
- [Art and the science of generative AI: A deeper dive](https://mlsanity.com/paper/2306.04141/) (2023)
- [Art-ificial Intelligence: The Effect of AI Disclosure on Evaluations of Creative Content](https://mlsanity.com/paper/2303.06217/) (2023)
- [6 Seconds of Sound and Vision: Creativity in Micro-Videos](https://mlsanity.com/paper/1411.4080/) (2014)

## Built on by (most cited first, 30 of 167)

- [Echoes in AI: Quantifying lack of plot diversity in LLM outputs](https://mlsanity.com/paper/2501.00273/) (2024)
- [We're Different, We're the Same: Creative Homogeneity Across LLMs](https://mlsanity.com/paper/2501.19361/) (2025)
- [Human-LLM Compound System for Scientific Ideation through Facet Recombination and Novelty Evaluation](https://mlsanity.com/paper/2409.14634/) (2024)
- [The Homogenizing Effect of Large Language Models on Human Expression and Thought](https://mlsanity.com/paper/2508.01491/) (2025)
- [On the Challenges and Opportunities in Generative AI](https://mlsanity.com/paper/2403.00025/) (2024)
- [The Shrinking Landscape of Linguistic Diversity in the Age of Large Language Models](https://mlsanity.com/paper/2502.11266/) (2025)
- [Generating Interesting Scientific Ideas using Knowledge Graphs and LLMs: Evaluations with 100 Research Group Leaders](https://mlsanity.com/paper/2405.17044/) (2024)
- [AdaDetectGPT: Adaptive Detection of LLM-Generated Text with Statistical Guarantees](https://mlsanity.com/paper/2510.01268/) (2025)
- [The Use of Generative Search Engines for Knowledge Work and Complex Tasks](https://mlsanity.com/paper/2404.04268/) (2024)
- [Which Contributions Deserve Credit? Perceptions of Attribution in Human-AI Co-Creation](https://mlsanity.com/paper/2502.18357/) (2025)
- [Large Language Models show both individual and collective creativity comparable to humans](https://mlsanity.com/paper/2412.03151/) (2024)
- [From tools to thieves: Measuring and understanding public perceptions of AI through crowdsourced metaphors](https://mlsanity.com/paper/2501.18045/) (2025)
- [Can We Predict Before Executing Machine Learning Agents?](https://mlsanity.com/paper/2601.05930/) (2026)
- [Diverse, not Short: A Length-Controlled Data Selection Strategy for Improving Response Diversity of Language Models](https://mlsanity.com/paper/2505.16245/) (2025)
- [Can Good Writing Be Generative? Expert-Level AI Writing Emerges through Fine-Tuning on High-Quality Books](https://mlsanity.com/paper/2601.18353/) (2026)
- [StoryScope: Investigating idiosyncrasies in AI fiction](https://mlsanity.com/paper/2604.03136/) (2026)
- [AI Assistance Reduces Persistence and Hurts Independent Performance](https://mlsanity.com/paper/2604.04721/) (2026)
- [Readers Prefer Outputs of AI Trained on Copyrighted Books over Expert Human Writers](https://mlsanity.com/paper/2510.13939/) (2025)
- [Deep Associations, High Creativity: A Simple yet Effective Metric for Evaluating Large Language Models](https://mlsanity.com/paper/2510.12110/) (2025)
- [Just-In-Time Objectives: A General Approach for Specialized AI Interactions](https://mlsanity.com/paper/2510.14591/) (2025)
- [One world, one opinion? The superstar effect in LLM responses](https://mlsanity.com/paper/2412.10281/) (2024)
- [Poor Alignment and Steerability of Large Language Models: Evidence from College Admission Essays](https://mlsanity.com/paper/2503.20062/) (2025)
- [Has the Creativity of Large-Language Models peaked? An analysis of inter- and intra-LLM variability](https://mlsanity.com/paper/2504.12320/) (2025)
- [A New Era in Human Factors Engineering: A Survey of the Applications and Prospects of Large Multimodal Models](https://mlsanity.com/paper/2405.13426/) (2024)
- [Generative AI and Creativity: A Systematic Literature Review and Meta-Analysis](https://mlsanity.com/paper/2505.17241/) (2025)
- [GenTune: Toward Traceable Prompts to Improve Controllability of Image Refinement in Environment Design](https://mlsanity.com/paper/2508.15227/) (2025)
- [The Basic B*** Effect: The Use of LLM-based Agents Reduces the Distinctiveness and Diversity of People's Choices](https://mlsanity.com/paper/2509.02910/) (2025)
- [Death of the Novel(ty): Beyond n-Gram Novelty as a Metric for Textual Creativity](https://mlsanity.com/paper/2509.22641/) (2025)
- [Expertise elevates AI usage: experimental evidence comparing laypeople and professional artists](https://mlsanity.com/paper/2501.12374/) (2025)
- [Multi-Novelty: Improve the Diversity and Novelty of Contents Generated by Large Language Models via inference-time Multi-Views Brainstorming](https://mlsanity.com/paper/2502.12700/) (2025)

## Abstract (arXiv)

Creativity is core to being human. Generative artificial intelligence (GenAI) holds promise for humans to be more creative by offering new ideas, or less creative by anchoring on GenAI ideas. We study the causal impact of GenAI on the production of a creative output in an online experimental study where some writers are could obtain ideas for a story from a GenAI platform. Access to GenAI ideas causes an increase in the writer's creativity with stories being evaluated as better written and more enjoyable, especially among less creative writers. However, GenAI-enabled stories are more similar to each other than stories by humans alone. Our results have implications for researchers, policy-makers and practitioners interested in bolstering creativity, but point to potential downstream consequences from over-reliance.