mlsanityData to 7 Oct 2026

Art and the science of generative AI: A deeper dive

arXiv 2306.04141 ↗First posted 7 Jun 2023cs.AIcited by 93

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Abstract (arXiv)

A new class of tools, colloquially called generative AI, can produce high-quality artistic media for visual arts, concept art, music, fiction, literature, video, and animation. The generative capabilities of these tools are likely to fundamentally alter the creative processes by which creators formulate ideas and put them into production. As creativity is reimagined, so too may be many sectors of society. Understanding the impact of generative AI - and making policy decisions around it - requires new interdisciplinary scientific inquiry into culture, economics, law, algorithms, and the interaction of technology and creativity. We argue that generative AI is not the harbinger of art's demise, but rather is a new medium with its own distinct affordances. In this vein, we consider the impacts of this new medium on creators across four themes: aesthetics and culture, legal questions of ownership and credit, the future of creative work, and impacts on the contemporary media ecosystem. Across these themes, we highlight key research questions and directions to inform policy and beneficial uses of the technology.

Key facts. Cited by 93 papers in the map (data through 7 Oct 2026). Builds on 42 of its 141 references that are in the map. First posted on arXiv 7 Jun 2023.

Builds on

42 of 141 references.

References · 42

  1. 2017Attention Is All You Needcited by 59,932
  2. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  3. 2018Datasheets for Datasetscited by 1,371
  4. 2019Energy and Policy Considerations for Deep Learning in NLPcited by 1,242
  5. 2023Extracting Training Data from Diffusion Modelscited by 723
  6. 2019Quantifying the Carbon Emissions of Machine Learningcited by 516
  7. 2017Men Also Like Shopping: Reducing Gender Bias Amplification using Corpus-level Constraintscited by 420
  8. 2022Diffusion Art or Digital Forgery? Investigating Data Replication in Diffusion Modelscited by 418
  9. 2020Towards the Systematic Reporting of the Energy and Carbon Footprints of Machine Learningcited by 246
  10. 2023Stable Bias: Analyzing Societal Representations in Diffusion Modelscited by 225
  11. 2021Design Guidelines for Prompt Engineering Text-to-Image Generative Modelscited by 216
  12. 2023Glaze: Protecting Artists from Style Mimicry by Text-to-Image Modelscited by 200
30 more
  1. 2018Capsule-Forensics: Using Capsule Networks to Detect Forged Images and Videoscited by 180
  2. 2020Carbontracker: Tracking and Predicting the Carbon Footprint of Training Deep Learning Modelscited by 168
  3. 2023Generative Language Models and Automated Influence Operations: Emerging Threats and Potential Mitigationscited by 157
  4. 2017No Classification without Representation: Assessing Geodiversity Issues in Open Data Sets for the Developing Worldcited by 152
  5. 2023Co-Writing with Opinionated Language Models Affects Users' Viewscited by 145
  6. 2016Mode Regularized Generative Adversarial Networkscited by 123
  7. 2023Foundation Models and Fair Usecited by 112
  8. 2018Troubling Trends in Machine Learning Scholarshipcited by 107
  9. 2019Bias Correction of Learned Generative Models using Likelihood-Free Importance Weightingcited by 70
  10. 2020Adversarial Deepfakes: Evaluating Vulnerability of Deepfake Detectors to Adversarial Examplescited by 66
  11. 2021Understanding and Creating Art with AI: Review and Outlookcited by 60
  12. 2021Deepfake Detection by Human Crowds, Machines, and Machine-informed Crowdscited by 58
  13. 2021Why AI is Harder Than We Thinkcited by 40
  14. 2022Studying Bias in GANs through the Lens of Racecited by 31
  15. 2018Can Computers Create Art?cited by 18
  16. 2021Active Divergence with Generative Deep Learning -- A Survey and Taxonomycited by 12
  17. 2022Toward Modeling Creative Processes for Algorithmic Paintingcited by 9
  18. 2022When happy accidents spark creativity: Bringing collaborative speculation to life with generative AIcited by 9
  19. 2023Generative AI and the Digital Commonscited by 8
  20. 2018Latent Structure in Collaboration: the Case of Reddit r/placecited by 5
  21. 2022Identifying the Context Shift between Test Benchmarks and Production Datacited by 5
  22. 2023Is Writing Prompts Really Making Art?cited by 5
  23. 2022Seeding Diversity into AI Artcited by 4
  24. 2020Interpolating GANs to Scaffold Autotelic Creativitycited by 3
  25. 2022Quantifying attention via dwell time and engagement in a social media browsing environmentcited by 3
  26. 2023Trash to Treasure: Using text-to-image models to inform the design of physical artefactscited by 3
  27. 2022Co-creation and ownership for AI radiocited by 2
  28. 2023Art-ificial Intelligence: The Effect of AI Disclosure on Evaluations of Creative Contentcited by 2
  29. 2021Social influence leads to the formation of diverse local trendscited by 1
  30. 2022At the Intersection of Deep Learning and Conceptual Art: The End of Signaturecited by 1

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 15; 2024: 34; 2025: 28; 2026: 16.

93 papers.

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  1. 2023Can large language models provide useful feedback on research papers? A large-scale empirical analysiscited by 195
  2. 2023From Words to Watts: Benchmarking the Energy Costs of Large Language Model Inferencecited by 168
  3. 2023Generative artificial intelligence enhances creativity but reduces the diversity of novel contentcited by 165
  4. 2023Raising the Bar of AI-generated Image Detection with CLIPcited by 163
  5. 2024Homogenization Effects of Large Language Models on Human Creative Ideationcited by 127
  6. 2023A Survey on LLM-Generated Text Detection: Necessity, Methods, and Future Directionscited by 101
  7. 2023The Data Provenance Initiative: A Large Scale Audit of Dataset Licensing & Attribution in AIcited by 73
  8. 2024A Bias-Free Training Paradigm for More General AI-generated Image Detectioncited by 67
  9. 2024Consent in Crisis: The Rapid Decline of the AI Data Commonscited by 45
  10. 2024D3: Scaling Up Deepfake Detection by Learning from Discrepancycited by 43
  11. 2023GenAI Against Humanity: Nefarious Applications of Generative Artificial Intelligence and Large Language Modelscited by 40
  12. 2023CoQuest: Exploring Research Question Co-Creation with an LLM-based Agentcited by 34
38 more
  1. 2024Image-GS: Content-Adaptive Image Representation via 2D Gaussianscited by 34
  2. 2024SketchAgent: Language-Driven Sequential Sketch Generationcited by 30
  3. 2024Evaluating Human-AI Collaboration: A Review and Methodological Frameworkcited by 25
  4. 2023Model-as-a-Service (MaaS): A Surveycited by 24
  5. 2024Data Attribution for Text-to-Image Models by Unlearning Synthesized Imagescited by 22
  6. 2024Mapping the Ethics of Generative AI: A Comprehensive Scoping Reviewcited by 19
  7. 2023A Probabilistic Fluctuation based Membership Inference Attack for Diffusion Modelscited by 17
  8. 2025GRAPHGPT-O: Synergistic Multimodal Comprehension and Generation on Graphscited by 17
  9. 2023User Experience Design Professionals' Perceptions of Generative Artificial Intelligencecited by 16
  10. 2024Data Authenticity, Consent, & Provenance for AI are all broken: what will it take to fix them?cited by 15
  11. 2025FlexOlmo: Open Language Models for Flexible Data Usecited by 14
  12. 2025Characterizing Photorealism and Artifacts in Diffusion Model-Generated Imagescited by 13
  13. 2025MLaGA: Multimodal Large Language and Graph Assistantcited by 12
  14. 2024Replication in Visual Diffusion Models: A Survey and Outlookcited by 11
  15. 2024Foundation Models for Education: Promises and Prospectscited by 10
  16. 2025Color Alignment in Diffusioncited by 10
  17. 2025AI-GenBench: A New Ongoing Benchmark for AI-Generated Image Detectioncited by 10
  18. 2025Survey on the Evaluation of Generative Models in Musiccited by 10
  19. 2024Exploring the Use of Abusive Generative AI Models on Civitaicited by 9
  20. 2025Free-Lunch Color-Texture Disentanglement for Stylized Image Generationcited by 8
  21. 2024Synthetic Human Memories: AI-Edited Images and Videos Can Implant False Memories and Distort Recollectioncited by 7
  22. 2025Fast Data Attribution for Text-to-Image Modelscited by 7
  23. 2024FoldMark: Protecting Protein Generative Models with Watermarkingcited by 5
  24. 2025AI Agents and Agentic AI-Navigating a Plethora of Concepts for Future Manufacturingcited by 5
  25. 2023Survey on AI Ethics: A Socio-technical Perspectivecited by 4
  26. 2024Algorithmic Ways of Seeing: Using Object Detection to Facilitate Art Explorationcited by 4
  27. 2024RU-AI: A Large Multimodal Dataset for Machine-Generated Content Detectioncited by 4
  28. 2023Artificial Intelligence and Aesthetic Judgmentcited by 3
  29. 2024Deceptive AI systems that give explanations are more convincing than honest AI systems and can amplify belief in misinformationcited by 3
  30. 2024Trustworthy and Responsible AI for Human-Centric Autonomous Decision-Making Systemscited by 3
  31. 2025Expertise elevates AI usage: experimental evidence comparing laypeople and professional artistscited by 3
  32. 2025AI Rivalry as a Craft: How Resisting and Embracing Generative AI Reshape Writing Professionscited by 3
  33. 2026More Human or More AI? Visualizing Human-AI Collaboration Disclosures in Journalistic News Productioncited by 3
  34. 2023Steering Language Generation: Harnessing Contrastive Expert Guidance and Negative Prompting for Coherent and Diverse Synthetic Data Generationcited by 2
  35. 2024Seizing the Means of Production: Exploring the Landscape of Crafting, Adapting and Navigating Generative AI Models in the Visual Artscited by 2
  36. 2024CUPID: Contextual Understanding of Prompt-conditioned Image Distributionscited by 2
  37. 2024Exploring Gen-AI applications in building research and industry: A reviewcited by 2
  38. 2024CRAFT: Designing Creative and Functional 3D Objectscited by 2

50 most cited of 93 All 93 (JSON)