mlsanityData to 7 Oct 2026

Artificial muses: Generative Artificial Intelligence Chatbots Have Risen to Human-Level Creativity

arXiv 2303.12003 ↗First posted 21 Mar 2023cs.AI cs.HCcited by 24

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Abstract (arXiv)

A widespread view is that Artificial Intelligence cannot be creative. We tested this assumption by comparing human-generated ideas with those generated by six Generative Artificial Intelligence (GAI) chatbots: alpa.!ai, Copy.!ai, ChatGPT (versions 3 and 4), Studio.!ai, and YouChat. Humans and a specifically trained AI independently assessed the quality and quantity of ideas. We found no qualitative difference between AI and human-generated creativity, although there are differences in how ideas are generated. Interestingly, 9.4 percent of humans were more creative than the most creative GAI, GPT-4. Our findings suggest that GAIs are valuable assistants in the creative process. Continued research and development of GAI in creative tasks is crucial to fully understand this technology's potential benefits and drawbacks in shaping the future of creativity. Finally, we discuss the question of whether GAIs are capable of being truly creative.

Key facts. Cited by 24 papers in the map (data through 7 Oct 2026). Builds on 2 of its 67 references that are in the map. First posted on arXiv 21 Mar 2023.

Builds on

2 of 67 references.

References · 2

  1. 2023ChatGPT: Jack of all trades, master of nonecited by 204
  2. 2022A very preliminary analysis of DALL-E 2cited by 82

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 3; 2024: 9; 2025: 6; 2026: 6.

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  1. 2023Generative AIcited by 119
  2. 2024Knowledge Mechanisms in Large Language Models: A Survey and Perspectivecited by 50
  3. 2024CoGenesis: A Framework Collaborating Large and Small Language Models for Secure Context-Aware Instruction Followingcited by 32
  4. 2023Probing the Creativity of Large Language Models: Can models produce divergent semantic association?cited by 31
  5. 2024Divergent Creativity in Humans and Large Language Modelscited by 29
  6. 2024Large Language Models show both individual and collective creativity comparable to humanscited by 9
  7. 2025Beyond Static Responses: Multi-Agent LLM Systems as a New Paradigm for Social Science Researchcited by 9
  8. 2025Has the Creativity of Large-Language Models peaked? An analysis of inter- and intra-LLM variabilitycited by 6
  9. 2025Generative AI and Creativity: A Systematic Literature Review and Meta-Analysiscited by 5
  10. 2023Domain-specific ChatBots for Science using Embeddingscited by 4
  11. 2024Deconstructing the Veneer of Simplicity: Co-Designing Introductory Generative AI Workshops with Local Entrepreneurscited by 4
  12. 2024Speaker effects in language comprehension: An integrative model of language and speaker processingcited by 4
12 more
  1. 2024Towards a Science Exocortexcited by 3
  2. 2025Expertise elevates AI usage: experimental evidence comparing laypeople and professional artistscited by 3
  3. 2025Beyond Automation: Socratic AI, Epistemic Agency, and the Implications of the Emergence of Orchestrated Multi-Agent Learning Architecturescited by 1
  4. 2026Are Semantic Networks Associated with Idea Originality in Artificial Creativity? A Comparison with Human Agentscited by 1
  5. 2026The Effect of Idea Elaboration on the Automatic Assessment of Idea Originalitycited by 1
  6. 2024It's a Feature, Not a Bug: Measuring Creative Fluidity in Image Generatorscited by 0
  7. 2024Is GPT-4 conscious?cited by 0
  8. 2025Stable diffusion models reveal a persisting human and AI gap in visual creativitycited by 0
  9. 2026Creativity in AI as Emergence from Domain-Limited Generative Modelscited by 0
  10. 2026Creativity Reconsidered: Generative AI and the Problem of Intentional Agencycited by 0
  11. 2026Artificial Intelligence and Innovation Ecosystem: Evolutionary Developments, Challenges, and Future Directionscited by 0
  12. 2026Recipes for Creativity: Iterative Generation and Evaluation in Large Language Modelscited by 0