Can Computers Create Art?
Open accessAbstract
This essay discusses whether computers, using Artificial Intelligence (AI), could create art. First, the history of technologies that automated aspects of art is surveyed, including photography and animation. In each case, there were initial fears and denial of the technology, followed by a blossoming of new creative and professional opportunities for artists. The current hype and reality of Artificial Intelligence (AI) tools for art making is then discussed, together with predictions about how AI tools will be used. It is then speculated about whether it could ever happen that AI systems could be credited with authorship of artwork. It is theorized that art is something created by social agents, and so computers cannot be credited with authorship of art in our current understanding. A few ways that this could change are also hypothesized.
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There has been a long history of intervention of technology in art worlds, slowly impacting, shaping and being shaped by the creative context they enter into.
“There has been a long history of intervention of technology in these art worlds, slowly impacting, shaping and being shaped by the creative context they enter into.”
From AI and Non-Western Art Worlds: Reimagining Critical AI Futures through Artistic Inquiry and Situated Dialogue (2025) · cites this paper as [51]
Section 3, “How Technology Changes Art,” says new technologies have long become artists’ tools that change art and culture; Section 3.2 gives historical examples. The paper also describes artists adopting and experimenting with those tools, but the cited passages do not clearly establish the broader claim that technology itself is shaped by the creative contexts it enters. (LLM, conf=0.81)
Experimental — accuracy not yet measuredArtists experimentation was key in shaping technologies and for technologies to shape artistic practice.
“Artists experimentation was key in shaping technologies and for technologies to shape artistic practice.”
From AI and Non-Western Art Worlds: Reimagining Critical AI Futures through Artistic Inquiry and Situated Dialogue (2025) · cites this paper as [51]
The relationship between technology and art worlds is complex and mutually constitutive.
“Third, the relationship between technology and art worlds is complex and mutually constitutive.”
From AI and Non-Western Art Worlds: Reimagining Critical AI Futures through Artistic Inquiry and Situated Dialogue (2025) · cites this paper as [51]
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Cites
Intriguing properties of neural networks
Szegedy, C., Zaremba, W., Sutskever, I., Bruna, J., Erhan, D., Goodfellow, I., & Fergus, R. (2013) · arXiv · doi:10.48550/arxiv.1312.6199 · Cited by 8,143 · see citing works
Image Style Transfer Using Convolutional Neural Networks
Gatys, L. A., Ecker, A. S., & Bethge, M. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.265 · Cited by 6,025 · see citing works
ELIZA—a computer program for the study of natural language communication between man and machine
Weizenbaum, J. (1966) · Communications of the ACM · doi:10.1145/365153.365168 · Cited by 4,452 · see citing works
Texture synthesis by non-parametric sampling
Efros, A. A., & Leung, T. K. (1999) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.1999.790383 · Cited by 3,058 · see citing works
Image quilting for texture synthesis and transfer
Efros, A. A., & Freeman, W. T. (2001) · ACM SIGGRAPH Annual Conference on Computer Graphics and Interactive Techniques (SIGGRAPH) · doi:10.1145/383259.383296 · Cited by 2,426 · see citing works
AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networks
Xu, T., Zhang, P., Huang, Q., Zhang, H., Gan, Z., Huang, X., & He, X. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00143 · Cited by 1,923 · see citing works
How to grow a mind: Statistics, structure, and abstraction
Tenenbaum, J. B., Kemp, C., Griffiths, T. L., & Goodman, N. D. (2011) · Science · doi:10.1126/science.1192788 · Cited by 1,815 · see citing works
Hertzmann, A., Jacobs, C. E., Oliver, N., Curless, B., & Salesin, D. (2001) · ACM SIGGRAPH Conference (SIGGRAPH) · doi:10.1145/383259.383295 · Cited by 1,579 · see citing works
Self-citationDanto, A. C. (1964) · The Journal of Philosophy · doi:10.2307/2022937 · Cited by 991 · see citing works
Bayesian decision theory in sensorimotor control
Kording, K. P., & Wolpert, D. M. (2006) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2006.05.003 · Cited by 866 · see citing works
Reconstructing constructivism: Causal models, Bayesian learning mechanisms, and the theory theory.
Alison Gopnik, C., & Wellman, H. M. (2012) · Psychological Bulletin · doi:10.1037/a0028044 · Cited by 660 · see citing works
Painterly rendering with curved brush strokes of multiple sizes
Hertzmann, A. (1998) · ACM SIGGRAPH Annual Conference on Computer Graphics and Interactive Techniques (SIGGRAPH) · doi:10.1145/280814.280951 · Cited by 616 · see citing works
Self-citationProcessing images and video for an impressionist effect
Litwinowicz, P. C. (1997) · ACM SIGGRAPH Conference (SIGGRAPH) · doi:10.1145/258734.258893 · Cited by 386 · see citing works
Elgammal, A., Liu, B., Elhoseiny, M., & Mazzone, M. (2017) · arXiv (Cornell University) · doi:10.48550/arxiv.1706.07068 · Cited by 353 · see citing works
Principles of traditional animation applied to 3D computer animation
Lasseter, J. (1987) · ACM SIGGRAPH Computer Graphics · doi:10.1145/37402.37407 · Cited by 327 · see citing works
Levinson, J. (1979) · The British Journal of Aesthetics · doi:10.1093/bjaesthetics/19.3.232 · Cited by 310 · see citing works
Creativity INC.: overcoming the Unseen Forces that Stand in the Way of True Inspiration
Catmull, E., Wallace, A., & Srilakshmi (2015) · Adarsh Journal of Management Research · doi:10.21095/ajmr/2015/v8/i1/88250 · Cited by 248 · see citing works
A survey of stroke-based rendering
Hertzmann, A. (2003) · IEEE Computer Graphics and Applications · doi:10.1109/mcg.2003.1210867 · Cited by 242 · see citing works
Self-citationPaint by numbers: abstract image representations
Haeberli, P. E. (1990) · ACM SIGGRAPH Computer Graphics · doi:10.1145/97880.97902 · Cited by 208 · see citing works
Creativity versus the perception of creativity in computational systems
Colton, S. (2008) · Cited by 183 · see citing works
Snow, C. P. (1959) · Science · doi:10.1126/science.130.3373.419 · Cited by 172 · see citing works
BAM! The Behance Artistic Media Dataset for Recognition Beyond Photography
Wilber, M. J., Chen, F., Jin, H., Hertzmann, A., Collomosse, J. P., & Belongie, S. (2017) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2017.136 · Cited by 158 · see citing works
Self-citationThe Painting Fool: Stories from Building an Automated Painter
Colton, S. (2012) · Springer eBooks · doi:10.1007/978-3-642-31727-9_1 · Cited by 158 · see citing works
Image and Video-Based Artistic Stylisation
Rosin, P. L., & Collomosse, J. P. (2012) · Computational imaging and vision · doi:10.1007/978-1-4471-4519-6 · Cited by 134 · see citing works
The further exploits of Aaron, painter
Cohen, H. (1995) · Cited by 123 · see citing works
Fišer, J., Jamriška, O., Lukáč, M., Shechtman, E., Asente, P., Lu, J., & Sýkora, D. (2016) · ACM Transactions on Graphics · doi:10.1145/2897824.2925948 · Cited by 121 · see citing works
Bernstein, M. S., Little, G., Miller, R. C., Hartmann, B., Ackerman, M. S., Karger, D. R., Crowell, D., & Panovich, K. (2015) · Communications of the ACM · doi:10.1145/2791285 · Cited by 116 · see citing works
The Cluster Account of Art Defended
Gaut, B. (2005) · The British Journal of Aesthetics · doi:10.1093/aesthj/ayi032 · Cited by 116 · see citing works
Alexander, R. M. (1997) · Princeton University Press eBooks · doi:10.1515/9780691221601 · Cited by 87 · see citing works
Non-Photorealistic Rendering and the science of art
Hertzmann, A. (2010) · International Symposium on Non-Photorealistic Animation and Rendering (NPAR) · doi:10.1145/1809939.1809957 · Cited by 76 · see citing works
Self-citationThe further exploits of Aaron, painter
CohenHarold (1995) · doi:10.5555/212154.212174 · Cited by 56 · see citing works
Nguyen, A., Yosinski, J., & Clune, J. (2016) · Evolutionary Computation · doi:10.1162/evco_a_00189 · Cited by 46 · see citing works
Art in the Age of Machine Intelligence
y Arcas, B. A. (2017) · Arts · doi:10.3390/arts6040018 · Cited by 45 · see citing works
Epstein, R. (2007) · Scientific American Mind · doi:10.1038/scientificamericanmind1007-16 · Cited by 14 · see citing works
Cohen, M. F. (2000) · IEEE Computer Graphics and Applications · doi:10.1109/38.814562 · Cited by 2 · see citing works
Shein, E. (2017) · Communications of the ACM · doi:10.1145/3048381 · Cited by 1 · see citing works
Flagged first, then by citations
2 of the 38 references couldn’t be matched to a known paper.
Research works printed but not linked: 19
- Bernstein, Michael S., Greg Little, Robert C. Miller, Björn Hartmannn, Mark S. Ackermann, David R. Karger, David Crowell, and Karina Panovich. 2015. Soylent: A Word Processor with a Crowd Inside. Communications of the ACM 58: 85-94.
- Brooks, Rodney. 2017. The Seven Deadly Sins of AI Predictions. MIT Technology Review 120: 79-86.
- Cohen, Harold. 2014. ACM SIGGRAPH Awards-Harold Cohen, Distinguished Artist Award for Lifetime Achievement. Available online: https://youtu.be/_Xbt8lzWxIQ?t=13m20s (accessed on 9 May 2018).
- Danto, Arthur. 1964. The Artworld. The Journal of Philosophy 61: 571-84.
- Dickie, George. 1969. Defining Art. American Philosophical Quarterly 6: 253-56.
- Dutton, Denis. 2000. But They Don't Have Our Concept of Art. In Theories of Art Today. Edited by Noel Carroll. Madison: University of Wisconsin Press.
- Dutton, Denis. 2009. The Art Instinct: Beauty, Pleasure, and Human Evolution. New York: Bloomsbury Press.
- Fišer, Jakub, Ondřej Jamriška, Michal Lukáč, Eli Shechtman, Paul Asente, Jingwan Lu, and Daniel Sýkora. 2016. StyLit: Illumination-guided Example-based Stylization of 3D Renderings. ACM Transactions on Graphics (SIGGRAPH) 35: 92:1-92:11.
- Gaut, Berys. 2000. Art as a Cluster Concept. In Theories of Art Today. Edited by Noel Carroll. Madison: University of Wisconsin Press.
- Goodfellow, Ian J., Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio. 2014. Generative Adversarial Nets. Paper presented at the Advances in Neural Information Processing Systems, Montreal, QC, Canada, December 8-13.
- Haeberli, Paul. 1990. Paint By Numbers: Abstract Image Representations. ACM SIGGRAPH Computer Graphics 24: 207-14.
- Hertzmann, Aaron. 2001. Algorithms for Rendering in Artistic Styles. Ph.D. thesis, New York University, New York, NY, USA.
- Koblin, Aaron Michael. 2009. The Sheep Market. Paper presented at the Proceedings of the Seventh ACM Conference on Creativity and Cognition (C&C '09 ), Berkeley, CA, USA, October 26-30, pp. 451-52.
- Levinson, Jerrold. 1979. Defining art historically. The British Journal of Aesthetics 19: 232-50.
- Rosenblum, Naomi. 1984. A World History of Photography. New York: Abbeville Press.
- Scharf, Aaron. 1968. Art and Photography. Harmondsworth: Penguin.
- Shein, Esther. 2017. Computing the Arts. Communications of the ACM 60: 17-19.
- Sternberger, Paul Spencer. 2001. Between Amateur & Aesthete: The Legimitization of Photography as Art in America, 1880-1900. Albuquerque: University of New Mexico Press.
- Weizenbaum, Joseph. 1966. ELIZA-A computer program for the study of natural language communication between man and machine. Communications of the ACM 9: 36-45.
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Epstein, Z., Levine, S., Rand, D. G., & Rahwan, I. (2020) · iScience · doi:10.1016/j.isci.2020.101515 · Cited by 157 · see citing works
Lyu, Y., Wang, X., Lin, R., & Wu, J. Y. (2022) · Applied Sciences · doi:10.3390/app122211312 · Cited by 160 · see citing works
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Abid, A., Abdalla, A., Abid, A., Khan, D., Alfozan, A., & Zou, J. Y. (2019) · arXiv.org · doi:10.48550/arxiv.1906.02569 · Cited by 395 · see citing works
Chang, M., Druga, S., Fiannaca, A. J., Vergani, P., Kulkarni, C. E., Cai, C. J., & Terry, M. A. (2023) · Creativity and Cognition · doi:10.1145/3591196.3593515 · Cited by 112 · see citing works
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Shen, X., Efros, A. A., & Aubry, M. (2019) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2019.00950 · Cited by 102 · see citing works
Chiarella, S. G., Torromino, G., Gagliardi, D. M., Rossi, D., Babiloni, F., & Cartocci, G. (2022) · Computers in Human Behavior · doi:10.1016/j.chb.2022.107406 · Cited by 105 · see citing works
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Caporusso, N. (2023) · Research Directs in Psychology and Behavior · doi:10.53520/rdpb2023.10795 · Cited by 91 · see citing works
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Wei, T., Gao, S., & Yuan, Y. (2023) · Frontiers in Psychology · doi:10.3389/fpsyg.2023.1185880 · Cited by 52 · see citing works
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Bueno, C. C., Chow, P.-S., & Popowicz, A. (2024) · AI & Society · doi:10.1007/s00146-024-01921-3 · Cited by 58 · see citing works
Wasielewski, A. (2023) · The MIT Press eBooks · doi:10.7551/mitpress/14268.001.0001 · Cited by 49 · see citing works
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Furtado, L. S., Soares, J. B., & Furtado, V. (2024) · Journal of Creativity · doi:10.1016/j.yjoc.2024.100086 · Cited by 47 · see citing works
Arar, K. H., Özen, H., Polat, G., & Turan, S. (2025) · Smart Learning Environments · doi:10.1186/s40561-025-00403-3 · Cited by 60 · see citing works
Daniele, A., & Song, Y.-Z. (2019) · Proceedings of the AAAI/ACM Conference on AI Ethics and Society · doi:10.1145/3306618.3314233 · Cited by 40 · see citing works
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Guo, A., Sathyanarayanan, S., Wang, L., Heer, J., & Zhang, A. X. (2025) · Creativity and Cognition · doi:10.1145/3698061.3726910 · Cited by 38 · see citing works
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Moruzzi, C. (2025) · Philosophy Compass · doi:10.1111/phc3.70030 · Cited by 44 · see citing works
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Hertzmann, A. (2024) · Empirical Studies of the Arts · doi:10.1177/02762374241288696 · Cited by 16 · see citing works
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Cross, A. (2024) · The British Journal of Aesthetics · doi:10.1093/aesthj/ayae055 · Cited by 15 · see citing works
Grassini, S. (2024) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2024.2422755 · Cited by 19 · see citing works
Automatic analysis of artistic paintings using information-based measures
Silva, J. M., Pratas, D., Antunes, R., Matos, S., & Pinho, A. J. (2021) · Pattern Recognition · doi:10.1016/j.patcog.2021.107864 · Cited by 16 · see citing works
Hagtvedt, H. (2023) · Foundations and Trends® in Marketing · doi:10.1561/1700000082 · Cited by 14 · see citing works
ASLAN, T., & AYDIN, K. (2023) · Ondokuz Mayis Univ Egitim Fakultesi · doi:10.7822/omuefd.1293657 · Cited by 14 · see citing works
Spatially-Consistent Feature Matching and Learning for Heritage Image Analysis
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Liu, W., & Tao, F. (2022) · Philosophies · doi:10.3390/philosophies7060127 · Cited by 13 · see citing works
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Cajulis, R. C. J., Tuazon, J. A., & Cabauatan, R. R. (2025) · International Journal of Arts Recreation and Sports · doi:10.47941/ijars.2444 · Cited by 13 · see citing works
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Young, N., & Terrone, E. (2024) · The Philosophical Quarterly · doi:10.1093/pq/pqae120 · Cited by 12 · see citing works
Understanding Visual Artists’ Values and Attitudes towards Collaboration, Technology, and AI
Johnston, H., & Thue, D. (2024) · Graphics Interface · doi:10.1145/3670947.3670973 · Cited by 12 · see citing works
Large-scale interactive retrieval in art collections using multi-style feature aggregation
Ufer, N., Simon, M., Lang, S., & Ommer, B. (2021) · PLoS ONE · doi:10.1371/journal.pone.0259718 · Cited by 11 · see citing works
Qadri, R., Mirowski, P., & Denton, R. (2025) · Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3706598.3714049 · Cited by 12 · see citing works
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Oppenlaender, J. (2024) · Springer eBooks · doi:10.1007/978-3-031-66528-8_14 · Cited by 12 · see citing works
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Zhou, E., Lee, D., & Gu, B. (2025) · Science Advances · doi:10.1126/sciadv.adu5800 · Cited by 11 · see citing works
Mathematical limit theorems for computational creativity
Varshney, L. R. (2019) · IBM Journal of Research and Development · doi:10.1147/jrd.2019.2893907 · Cited by 10 · see citing works
In the eye of the beholder: A viewer-defined conception of online visual creativity
Herman, L. M., & Hwang, A. H. (2022) · New Media & Society · doi:10.1177/14614448221089604 · Cited by 10 · see citing works
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Guljajeva, V., & Solà, M. C. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-29956-8_23 · Cited by 10 · see citing works
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Srinivasan, R., & Uchino, K. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2010.13266 · Cited by 10 · see citing works
Jiang, Q., Qian, J., & Zang, Y. (2024) · Kybernetes · doi:10.1108/k-02-2024-0471 · Cited by 9 · see citing works
Art, Identity, and AI: Navigating Authenticity in Creative Practice
Lewis, M. (2025) · Creativity and Cognition · doi:10.1145/3698061.3726959 · Cited by 9 · see citing works
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Cheong, B. C. (2024) · Journal of Digital Technologies and Law · doi:10.21202/jdtl.2024.42 · Cited by 9 · see citing works
Ufer, N., Lang, S., & Ommer, B. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-66096-3_12 · Cited by 9 · see citing works
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Rasyad, F., Kongguasa, H. A., Onggususilo, N. C., Anderies, Kurniawan, A., & Gunawan, A. A. S. (2023) · International Conference on Computer Science, Information Technology and Engineering (ICCoSITE) · doi:10.1109/iccosite57641.2023.10127706 · Cited by 9 · see citing works
Disentangling Style and Content in Anime IllustrationsPreprint
Xiang, S., & Li, H. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1905.10742 · Cited by 9 · see citing works
Vásquez, L. (2020) · Revista Iberoamericana de la Propiedad Intelectual · doi:10.26422/ripi.2020.1300.vas · Cited by 8 · see citing works
Creative intra-actions: co-creating with generative AI in the age of climate change
Ferreira, R. (2025) · Learning Media and Technology · doi:10.1080/17439884.2025.2532550 · Cited by 8 · see citing works
Artificial creativity: can there be creativity without cognition?
Pelo, M. D. (2025) · AI & Society · doi:10.1007/s00146-025-02682-3 · Cited by 7 · see citing works
An empirical study on the use behavior towards AI painting tools based on TAM3 model
Li, Y., Siek, H. L., & Guo, J. (2025) · Scientific Reports · doi:10.1038/s41598-025-24405-w · Cited by 7 · see citing works
Qualitative Study of Text-to-Image AI Generators and their Relationship with NFTs
Arikan, E., & Aram, S. (2022) · International Conference on Computational Science and Computational Intelligence (CSCI) · doi:10.1109/csci58124.2022.00046 · Cited by 7 · see citing works
The role of digitalization in today’s art: A perspective from NFT and artificial intelligenc
Düzenli, K., & Perdahçı, Z. N. (2024) · JOURNAL OF ARTS · doi:10.31566/arts.2291 · Cited by 7 · see citing works
What AI “art” can teach us about art
Chiodo, S. (2024) · Journal of AESTHETICS & CULTURE · doi:10.1080/20004214.2024.2395511 · Cited by 7 · see citing works
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Siri, A., Olcese, G., & Spulber, D. (2024) · Geopolitical, Social Security and Freedom Journal · doi:10.2478/gssfj-2024-0001 · Cited by 6 · see citing works
Robots and Dance: A Promising Young Alchemy
LaViers, A. (2024) · Annual Review of Control Robotics and Autonomous Systems · doi:10.1146/annurev-control-060923-100542 · Cited by 7 · see citing works
- Authors
- Hertzmann, A.
- Affiliations
- Adobe Research, San Francisco, CA 94103, USA
- Corresponding author
- Hertzmann, Aaron
- ORCID
- Hertzmann, Aaron
- Venue
- Arts
- Publisher
- MDPI AG
- Published
- 2018-05-10
- Volume
- 7
- Issue
- 2
- Pages
- 18
- ISSN
- 2076-0752 (ISSN-L)
- OpenAlex
- W2963820570
- Cited by
- 265
- References
- 38
- Citations by year
- 2026: 50 · 2025: 49 · 2024: 46 · 2023: 43 · 2022: 25 · 2021: 18 · 2020: 19 · 2019: 11 · 2018: 2 · 2017: 2
- FWCI
- 213.93
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Arts (publishedVersion, cc-by)
- arXiv (Cornell University) (submittedVersion)
- TSpace (University of Toronto) (submittedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- arXiv (Cornell University)
- Topics
- Social Sciences › Arts and Humanities › Visual Arts and Performing Arts › Art, Technology, and Culture
- Social Sciences › Arts and Humanities › History and Philosophy of Science › Cybernetics and Technology in Society
- Physical Sciences › Computer Science › Computer Graphics and Computer-Aided Design › Digital Media and Visual Art
- Keywords
- artificial intelligence in art, computer art, photography, animation, social agency
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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