Bibliography #
Research in Human-Computer Interaction, Science and Technology Studies, Algorithm Studies has documented and investigated the link between AI and the Arts. This page aims to provide a corpus of the academic research addressing the topics at the core of the project.
The corpus is neither exhaustive nor definitive. The corpus is constantly evolving, given the constant developments in AI technologies for the creative and artistic sectors.
Articles #
Daniele, Antonio and Song, Yi-Zhe (2019). Ai+ art= human. In: Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, .
World Economic Forum, (2018). The impact of emerging technologies on the creative economy. In: World Economic Forum, Geneva, .
Caramiaux, Baptiste and Fdili Alaoui, Sarah (2022 11 11). "Explorers of Unknown Planets": Practices and Politics of Artificial Intelligence in Visual Arts. Proceedings of the ACM on Human-Computer Interaction, 6(CSCW2), 477:1–477:24.doi: 10.1145/3555578.
Sanchez, Téo (2023 6 19). Examining the Text-to-Image Community of Practice: Why and How do People Prompt Generative AIs? In: Proceedings of the 15th Conference on Creativity and Cognition, New York, NY, USA.doi: 10.1145/3591196.3593051.
Epstein, Ziv et al. (2023 6 16). Art and the science of generative AI: A deeper dive. Science, 380(6650), 1110–1111.doi: 10.1126/science.adh4451.
Stark, Luke and Crawford, Kate (2019). The work of art in the age of artificial intelligence: What artists can teach us about the ethics of data practice. Surveillance & Society, 17(3/4), 442–455.https://ojs.library.queensu.ca/index.php/surveillance-and-society/article/view/10821.
Edwards, Steven Marc (2001 4 1). The Technology Paradox: Efficiency Versus Creativity. Creativity Research Journal, 13(2), 221–228.doi: 10.1207/S15326934CRJ1302_9.
Molnar, Vera (1975). Toward aesthetic guidelines for paintings with the aid of a computer. Leonardo,, 185–189.https://www.jstor.org/stable/1573236?casa_token=LS23fMhPmpEAAAAA:bzu56Bqz1y0I-Hd2OJt9-ODUxpEFdeQ4egB4CGh00Dd4gNlkYAei1jSpg9j7lK_QZhu9ZgHRi9z4QfAnYmcGp82wsSrD5b1XMMVZdvSS4WtvypbnhbgK.
Doshi, Anil R. and Hauser, Oliver P. (2024 7 12). Generative AI enhances individual creativity but reduces the collective diversity of novel content. Science Advances, 10(28), eadn5290.doi: 10.1126/sciadv.adn5290.
Lovato, Juniper et al. (2024). Foregrounding Artist Opinions: A Survey Study on Transparency, Ownership, and Fairness in AI Generative Art. ArXiv Preprint ArXiv:2401.15497,.https://arxiv.org/abs/2401.15497.
Park, Sungjin (2024 5 3). The work of art in the age of generative AI: aura, liberation, and democratization. AI & SOCIETY,.doi: 10.1007/s00146-024-01948-6.
Rajcic, Nina et al. (2024 5 11). Towards a Diffractive Analysis of Prompt-Based Generative AI. In: Proceedings of the CHI Conference on Human Factors in Computing Systems, Honolulu HI USA.doi: 10.1145/3613904.3641971.
Shelby, Renee et al. (2024 4 17). Creative ML Assemblages: The Interactive Politics of People, Processes, and Products. Proceedings of the ACM on Human-Computer Interaction, 8(CSCW1), 1–30.doi: 10.1145/3637315.
Sivertsen, Christian et al. (2024 5 11). Machine Learning Processes As Sources of Ambiguity: Insights from AI Art. In: Proceedings of the CHI Conference on Human Factors in Computing Systems, Honolulu HI USA.doi: 10.1145/3613904.3642855.
Chang, Minsuk et al. (2023 6 19). The Prompt Artists. In: Creativity and Cognition, Virtual Event USA.doi: 10.1145/3591196.3593515.
Hemment, Drew et al. (2023 6 12). AI in the Public Eye: Investigating Public AI Literacy Through AI Art. In: 2023 ACM Conference on Fairness, Accountability, and Transparency, Chicago IL USA.doi: 10.1145/3593013.3594052.
Jiang, Harry H. et al. (2023 8 8). AI Art and its Impact on Artists. In: Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society, Montr\'{e}al QC Canada.doi: 10.1145/3600211.3604681.
Shan, Shawn et al. (2023). Glaze: Protecting artists from style mimicry by {Text-to-Image} models. In: 32nd USENIX Security Symposium (USENIX Security 23), .https://www.usenix.org/conference/usenixsecurity23/presentation/shan.
Elgammal, Ahmed (2017). Can: Creative adversarial networks, generating “art” by learning about styles and deviating from style norms. ArXiv Preprint ArXiv:1706.07068, 6, 2017.
Li, Jingyi et al. (2023 10 29). Beyond the Artifact: Power as a Lens for Creativity Support Tools. In: Proceedings of the 36th Annual ACM Symposium on User Interface Software and Technology, San Francisco CA USA.doi: 10.1145/3586183.3606831.
Benford, Steve et al. (2023 7 11). Five Provocations for a More Creative TAS. In: Proceedings of the First International Symposium on Trustworthy Autonomous Systems, Edinburgh United Kingdom.doi: 10.1145/3597512.3599709.
Shelby, Renee et al. (2024 5 11). Generative AI in Creative Practice: ML-Artist Folk Theories of T2I Use, Harm, and Harm-Reduction. In: Proceedings of the CHI Conference on Human Factors in Computing Systems, Honolulu HI USA.doi: 10.1145/3613904.3642461.
Hsueh, Stacy et al. (2019 11 7). Deconstructing Creativity: Non-Linear Processes and Fluid Roles in Contemporary Music and Dance. Proceedings of the ACM on Human-Computer Interaction, 3(CSCW), 1–21.doi: 10.1145/3359305.
Shneiderman, Ben (2007 12). Creativity support tools: accelerating discovery and innovation. Communications of the ACM, 50(12), 20–32.doi: 10.1145/1323688.1323689.
Hsueh, Stacy et al. (2024 5 11). What Counts as ‘Creative’ Work? Articulating Four Epistemic Positions in Creativity-Oriented HCI Research. In: Proceedings of the 2024 CHI Conference on Human Factors in Computing Systems, New York, NY, USA.doi: 10.1145/3613904.3642854.
Li, Jingyi et al. (2021 5 6). What We Can Learn From Visual Artists About Software Development. In: Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems, Yokohama Japan.doi: 10.1145/3411764.3445682.
Hertzmann, Aaron (2018). Can computers create art? In: Arts, .https://www.mdpi.com/2076-0752/7/2/18.
Kawakami, Reishiro and Venkatagiri, Sukrit (2024 6 23). The Impact of Generative AI on Artists. In: Creativity and Cognition, Chicago IL USA.doi: 10.1145/3635636.3664263.
Vyas, Bhuman. Ethical Implications of Generative AI in Art and the Media. ,.
Books #
Audry, Sofian (2021). Art in the Age of Machine Learning. MIT Press.
Manovich, Lev (2018). AI Aesthetics. Strelka press.
Others #
Akten, Memo (2021). Deep Visual Instruments: Realtime Continuous, Meaningful Human Control Over Deep Neural Networks for Creative Expression. PhD Thesis. Goldsmiths, University of London.
Pieters, Roelof and Winiger, Samim (2016). Creative AI: On the Democratisa- tion & Escalation of Creativity. https://medium.com/@creativeai/creativeai-9d4b2346faf3.
Caramiaux, Baptiste and Donnarumma, Marco (2021). Artificial Intelligence in Music and Performance: A Subjective Art-Research Inquiry. In: Miranda (Ed.), Handbook of Artificial Intelligence for Music (Springer International Publishing, Cham).https://link.springer.com/10.1007/978-3-030-72116-9_4.
McCormack, Jon et al. (2023). Is Writing Prompts Really Making Art? In: Johnson et al. (Eds.), Artificial Intelligence in Music, Sound, Art and Design (Springer Nature Switzerland, Cham).https://link.springer.com/10.1007/978-3-031-29956-8_13.
Galanter, Philip (2016 4 25). Generative Art Theory. In: Paul (Ed.), A Companion to Digital Art (Wiley).https://onlinelibrary.wiley.com/doi/10.1002/9781118475249.ch5.