AI’s Role in Creative Processes: A Functionalist Approach
A non-anthropocentric notion
Keywords:
creativity, artificial intelligence, anthropocentric bias, AI-generated art, GAN, AI fairness
Abstract
From 1950 onwards, the study of creativity has not stopped. Today, AI has revitalised debates on the subject. That is especially controversial in the artworld, as the 21st century already features AI-generated artworks. Without discussing issues about AI agency, this article argues for AI’s creativity. For this, we first present a new functionalist understanding of Margaret Boden’s definition of creativity. This is followed by an analysis of empirical evidence on anthropocentric barriers in the perception of AI’s creative capabilities, which is later criticised for considering insights from media theory. Finally, benefits derived from including AI as an artistic creative producer and supportive tool are discussed. It is then argued that AI can contribute to democratising the artworld. Therefore its creative role must be recognised.References
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Brewer, M. B. (2001). Ingroup identification and intergroup conflict: When does ingroup love become outgroup hate? In Social identity, intergroup conflict, and conflict reduction (pp. 17–41). Oxford University Press.
Bunz, M. (2007). La utopía de la copia: El pop como irritación (C. Pavón, Trans.). Interzona.
Campbell, D. T. (1960). Blind variation and selective retentions in creative thought as in other knowledge processes. Psychological Review, 67(6), 380–400. https://doi.org/10.1037/h0040373
Cetinic, E., & She, J. (2021). Understanding and Creating Art with AI: Review and Outlook. ArXiv:2102.09109 [Cs]. http://arxiv.org/abs/2102.09109
Chamberlain, R., Mullin, C., Scheerlinck, B., & Wagemans, J. (2018). Putting the art in artificial: Aesthetic responses to computer-generated art. Psychology of Aesthetics, Creativity, and the Arts, 12(2), 177–192. https://doi.org/10.1037/aca0000136
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Corazza, G. E. (2016). Potential Originality and Effectiveness: The Dynamic Definition of Creativity. Creativity Research Journal, 28(3), 258–267. https://doi.org/10.1080/10400419.2016.1195627
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Elgammal, A., Liu, B., Elhoseiny, M., & Mazzone, M. (2017). CAN: Creative Adversarial Networks, Generating ‘Art’ by Learning About Styles and Deviating from Style Norms. http://arxiv.org/abs/1706.07068
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Giacomello, E., Lanzi, P. L., & Loiacono, D. (2018). DOOM Level Generation Using Generative Adversarial Networks. 2018 IEEE Games, Entertainment, Media Conference (GEM), 316–323. https://doi.org/10.1109/GEM.2018.8516539
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Hertzmann, A. (2020). Computers do not make art, people do. Communications of the ACM, 63(5), 45–48. https://doi.org/10.1145/3347092
Hong, J.-W. (2018). Bias in Perception of Art Produced by Artificial Intelligence. In M. Kurosu (Ed.), Human-Computer Interaction. Interaction in Context (pp. 290–303). Springer International Publishing. https://doi.org/10.1007/978-3-319-91244-8_24
Hsu, H. (2019, May 20). Machine Yearning. The New Yorker, 95(13), 83–84.
Jefferson, G. (1949). The Mind of Mechanical Man. British Medical Journal, 1(4616), 1105–1110. https://doi.org/10.1136/bmj.1.4616.1105
Jennings, K. E. (2010). Developing Creativity: Artificial Barriers in Artificial Intelligence. Minds and Machines, 20(4), 489–501. https://doi.org/10.1007/s11023-010-9206-y
Kasy, M., & Abebe, R. (2021). Fairness, Equality, and Power in Algorithmic Decision-Making. Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, 576–586. https://doi.org/10.1145/3442188.3445919
Kaufman, J. C., & Beghetto, R. A. (2009). Beyond Big and Little: The Four C Model of Creativity. Review of General Psychology, 13(1), 1–12. https://doi.org/10.1037/a0013688
Kelly, S. D. (2019). A philosopher argues that an AI can’t be an artist. MIT Technology Review. https://www.technologyreview.com/2019/02/21/239489/a-philosopher-argues-that-an-ai-can-never-be-an-artist/
Knight, W. (2017). 35 Innovators Under 35, Inventors: Ian Goodfellow. MIT Technology Review. https://www.innovatorsunder35.com/the-list/ian-goodfellow/
Kohs, G. (2017, September 29). AlphaGo [Documentary, Sport]. Moxie Pictures, Reel As Dirt.
Lawson, C. (2010). Technology and the Extension of Human Capabilities. Journal for the Theory of Social Behaviour, 40(2), 207–223. https://doi.org/10.1111/j.1468-5914.2009.00428.x
MacKinnon, D. W. (1966). What makes a person creative? Theory Into Practice, 5(4), 151–156. https://doi.org/10.1080/00405846609542017
Mazzone, M., & Elgammal, A. (2019). Art, Creativity, and the Potential of Artificial Intelligence. Arts, 8(1), 26. https://doi.org/10.3390/arts8010026
McCormack, J., Gifford, T., & Hutchings, P. (2019). Autonomy, Authenticity, Authorship and Intention in Computer Generated Art. In A. Ekárt, A. Liapis, & M. L. Castro Pena (Eds.), Computational Intelligence in Music, Sound, Art and Design (pp. 35–50). Springer International Publishing. https://doi.org/10.1007/978-3-030-16667-0_3
McLuhan, M. (1994). Understanding media: The extensions of man. MIT Press.
Mehrabi, N., Morstatter, F., Saxena, N., Lerman, K., & Galstyan, A. (2019). A Survey on Bias and Fairness in Machine Learning. USC, Information Sciences Institute.
Miller, A. (2019). The Artist in the Machine: The World of AI-Powered Creativity (Kindle ed.). MIT Press.
Miller, A. (2020). Creativity in the Age of AI: Computers and artificial neural networks are redefining the relationship between art and science. American Scientist, 108(4), 244–250.
Moffat, D. C., & Kelly, M. (2006). An investigation into people’s bias against computational creativity in music composition. Proceedings of the 3rd International Joint Workshop on Computational Creativity. ECAI06 Workshop.
Mori, M. (2012). The Uncanny Valley [From the Field] (K. F. MacDorman & N. Kageki, Trans.). IEEE Robotics Automation Magazine, 19(2), 98–100. https://doi.org/10.1109/MRA.2012.2192811
Moruzzi, C. (2020a). Artificial Creativity and General Intelligence. Journal of Science and Technology of the Arts, 12(3), 84–99. https://doi.org/10.34632/jsta.2020.9481
Moruzzi, C. (2020b). Learning through creativity: How creativity can help machine learning achieving deeper understanding. Rivista Italiana Di Filosofia Del Linguaggio, 14(2). https://doi.org/10.4396/AISB201904
Moruzzi, C. (2021). Measuring creativity: An account of natural and artificial creativity. European Journal for Philosophy of Science, 11(1), 20. https://doi.org/10.1007/s13194-020-00313-w
Novitz, D. (1999). Creativity and Constraint. Australasian Journal of Philosophy, 77(1), 67–82. https://doi.org/10.1080/00048409912348811
Ragot, M., Martin, N., & Cojean, S. (2020). AI-generated vs. Human Artworks. A Perception Bias Towards Artificial Intelligence? Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems, 1–10. https://doi.org/10.1145/3334480.3382892
Ridler, A. (2021, June 5). Mosaic Virus, 2019. ANNA RIDLER. http://annaridler.com/mosaic-virus
Runco, M. A., & Jaeger, G. J. (2012). The Standard Definition of Creativity. Creativity Research Journal, 24(1), 92–96. https://doi.org/10.1080/10400419.2012.650092
Sen, A. (1974). Informational bases of alternative welfare approaches: Aggregation and income distribution. Journal of Public Economics, 3(4), 387–403. https://doi.org/10.1016/0047-2727(74)90006-1
Sen, A. (1980). Equality of What? In S. M. McMurrin (Ed.), The Tanner Lectures on Human Values (Vol. 1). Cambridge University Press.
Sen, A. (2000). Development as Freedom. Oxford University Press.
Simon, H. (1985). What We Know About the Creative Process. In R. L. Kuhn (Ed.), Frontiers in Creative and Innovative Management (pp. 3–22). Ballinger Publishing Company.
Simonton, D. K. (1999). Target Article: ‘Creativity as Blind Variation and Selective Retention: Is the Creative Process Darwinian?’ Psychological Inquiry, 10(3), 309–328. https://doi.org/10.1207/S15327965PLI1004_4
Stein, M. I. (1953). Creativity and Culture. The Journal of Psychology, 36(2), 311–322. https://doi.org/10.1080/00223980.1953.9712897
Still, A., & d’Inverno, M. (2019). Can Machines Be Artists? A Deweyan Response in Theory and Practice. Arts, 8(1), 36. https://doi.org/10.3390/arts8010036
Turing, A. (1950). Computing Machinery and Intelligence. Mind, 59(236), 433–460. https://doi.org/10.1093/mind/LIX.236.433
Walia, C. (2019). A Dynamic Definition of Creativity. Creativity Research Journal, 31(3), 237–247. https://doi.org/10.1080/10400419.2019.1641787
Wellner, G. (2021). Digital Imagination, Fantasy, AI Art. Foundations of Science. https://doi.org/10.1007/s10699-020-09747-0
Wu, Q., Zhu, B., Yong, B., Wei, Y., Jiang, X., Zhou, R., & Zhou, Q. (2021). ClothGAN: Generation of fashionable Dunhuang clothes using generative adversarial networks. Connection Science, 33(2), 341–358. https://doi.org/10.1080/09540091.2020.1822780
Arriagada, L. (2020). CG-Art: Demystifying the anthropocentric bias of artistic creativity. Connection Science, 32(4), 398–405. https://doi.org/10.1080/09540091.2020.1741514
Arriagada, L. (2021). Artistas mecánicos: Una mirada a la capacidad estética de máquinas y algoritmos desde la música pop y el pop art. Calle 14 revista de investigación en el campo del arte, 16(29), 54–66. https://doi.org/10.14483/21450706.17401
Barron, F., & Harrington, D. M. (1981). Creativity, Intelligence, and Personality. Annual Review of Psychology, 32(1), 439–476. https://doi.org/10.1146/annurev.ps.32.020181.002255
Bartneck, C., Lütge, C., Wagner, A., & Welsh, S. (2021). Trust and Fairness in AI Systems. In C. Bartneck, C. Lütge, A. Wagner, & S. Welsh (Eds.), An Introduction to Ethics in Robotics and AI (pp. 27–38). Springer International Publishing. https://doi.org/10.1007/978-3-030-51110-4_4
Boden, M. (2004). The Creative Mind: Myths and Mechanisms. Routledge. https://doi.org/10.4324/9780203508527
Boden, M. (2017). Is deep dreaming the new collage? Connection Science, 29(4), 268–275. https://doi.org/10.1080/09540091.2017.1345855
Brewer, M. B. (2001). Ingroup identification and intergroup conflict: When does ingroup love become outgroup hate? In Social identity, intergroup conflict, and conflict reduction (pp. 17–41). Oxford University Press.
Bunz, M. (2007). La utopía de la copia: El pop como irritación (C. Pavón, Trans.). Interzona.
Campbell, D. T. (1960). Blind variation and selective retentions in creative thought as in other knowledge processes. Psychological Review, 67(6), 380–400. https://doi.org/10.1037/h0040373
Cetinic, E., & She, J. (2021). Understanding and Creating Art with AI: Review and Outlook. ArXiv:2102.09109 [Cs]. http://arxiv.org/abs/2102.09109
Chamberlain, R., Mullin, C., Scheerlinck, B., & Wagemans, J. (2018). Putting the art in artificial: Aesthetic responses to computer-generated art. Psychology of Aesthetics, Creativity, and the Arts, 12(2), 177–192. https://doi.org/10.1037/aca0000136
Colton, S. (2008). Creativity Versus the Perception of Creativity in Computational Systems. In AAAI Spring Symposium—Technical Report (p. 20).
Corazza, G. E. (2016). Potential Originality and Effectiveness: The Dynamic Definition of Creativity. Creativity Research Journal, 28(3), 258–267. https://doi.org/10.1080/10400419.2016.1195627
Dickie, G. (1969). Defining Art. American Philosophical Quarterly, 6(3), 253–256. JSTOR.
Dickie, G. (1997). Art: Function or Procedure: Nature or Culture? The Journal of Aesthetics and Art Criticism, 55(1), 19. https://doi.org/10.2307/431601
Elgammal, A., Liu, B., Elhoseiny, M., & Mazzone, M. (2017). CAN: Creative Adversarial Networks, Generating ‘Art’ by Learning About Styles and Deviating from Style Norms. http://arxiv.org/abs/1706.07068
Epstein, Z., Levine, S., Rand, D. G., & Rahwan, I. (2020). Who Gets Credit for AI-Generated Art? IScience, 23(9). https://doi.org/10.1016/j.isci.2020.101515
Fontanille, J. (2018, May 7). Interacción ser humano/máquina. 12a escuela Chile-Francia, Facultad de Derecho de la Universidad de Chile.
Gabora, L., & Kaufman, S. B. (2019). Evolutionary Approaches to Creativity. ArXiv:1106.3386 [q-Bio]. http://arxiv.org/abs/1106.3386
Gaut, B. (2010). The Philosophy of Creativity. Philosophy Compass, 5(12), 1034–1046. https://doi.org/10.1111/j.1747-9991.2010.00351.x
Giacomello, E., Lanzi, P. L., & Loiacono, D. (2018). DOOM Level Generation Using Generative Adversarial Networks. 2018 IEEE Games, Entertainment, Media Conference (GEM), 316–323. https://doi.org/10.1109/GEM.2018.8516539
Goodfellow, I. J., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., & Bengio, Y. (2014). Generative Adversarial Networks. ArXiv:1406.2661 [Cs, Stat]. http://arxiv.org/abs/1406.2661
Google Arts & Culture. (2019). Anna Ridler: Can datasets create art? - Barbican Centre. Google Arts & Culture. https://artsandculture.google.com/exhibit/anna-ridler-can-datasets-create-art-barbican-centre/iALiolnI1pkrLg
Guilford, J. P. (1950). Creativity. American Psychologist, 5(9), 444–454. https://doi.org/10.1037/h0063487
Hertzmann, A. (2018). Can Computers Create Art? Arts, 7(2), 18. https://doi.org/10.3390/arts7020018
Hertzmann, A. (2020). Computers do not make art, people do. Communications of the ACM, 63(5), 45–48. https://doi.org/10.1145/3347092
Hong, J.-W. (2018). Bias in Perception of Art Produced by Artificial Intelligence. In M. Kurosu (Ed.), Human-Computer Interaction. Interaction in Context (pp. 290–303). Springer International Publishing. https://doi.org/10.1007/978-3-319-91244-8_24
Hsu, H. (2019, May 20). Machine Yearning. The New Yorker, 95(13), 83–84.
Jefferson, G. (1949). The Mind of Mechanical Man. British Medical Journal, 1(4616), 1105–1110. https://doi.org/10.1136/bmj.1.4616.1105
Jennings, K. E. (2010). Developing Creativity: Artificial Barriers in Artificial Intelligence. Minds and Machines, 20(4), 489–501. https://doi.org/10.1007/s11023-010-9206-y
Kasy, M., & Abebe, R. (2021). Fairness, Equality, and Power in Algorithmic Decision-Making. Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, 576–586. https://doi.org/10.1145/3442188.3445919
Kaufman, J. C., & Beghetto, R. A. (2009). Beyond Big and Little: The Four C Model of Creativity. Review of General Psychology, 13(1), 1–12. https://doi.org/10.1037/a0013688
Kelly, S. D. (2019). A philosopher argues that an AI can’t be an artist. MIT Technology Review. https://www.technologyreview.com/2019/02/21/239489/a-philosopher-argues-that-an-ai-can-never-be-an-artist/
Knight, W. (2017). 35 Innovators Under 35, Inventors: Ian Goodfellow. MIT Technology Review. https://www.innovatorsunder35.com/the-list/ian-goodfellow/
Kohs, G. (2017, September 29). AlphaGo [Documentary, Sport]. Moxie Pictures, Reel As Dirt.
Lawson, C. (2010). Technology and the Extension of Human Capabilities. Journal for the Theory of Social Behaviour, 40(2), 207–223. https://doi.org/10.1111/j.1468-5914.2009.00428.x
MacKinnon, D. W. (1966). What makes a person creative? Theory Into Practice, 5(4), 151–156. https://doi.org/10.1080/00405846609542017
Mazzone, M., & Elgammal, A. (2019). Art, Creativity, and the Potential of Artificial Intelligence. Arts, 8(1), 26. https://doi.org/10.3390/arts8010026
McCormack, J., Gifford, T., & Hutchings, P. (2019). Autonomy, Authenticity, Authorship and Intention in Computer Generated Art. In A. Ekárt, A. Liapis, & M. L. Castro Pena (Eds.), Computational Intelligence in Music, Sound, Art and Design (pp. 35–50). Springer International Publishing. https://doi.org/10.1007/978-3-030-16667-0_3
McLuhan, M. (1994). Understanding media: The extensions of man. MIT Press.
Mehrabi, N., Morstatter, F., Saxena, N., Lerman, K., & Galstyan, A. (2019). A Survey on Bias and Fairness in Machine Learning. USC, Information Sciences Institute.
Miller, A. (2019). The Artist in the Machine: The World of AI-Powered Creativity (Kindle ed.). MIT Press.
Miller, A. (2020). Creativity in the Age of AI: Computers and artificial neural networks are redefining the relationship between art and science. American Scientist, 108(4), 244–250.
Moffat, D. C., & Kelly, M. (2006). An investigation into people’s bias against computational creativity in music composition. Proceedings of the 3rd International Joint Workshop on Computational Creativity. ECAI06 Workshop.
Mori, M. (2012). The Uncanny Valley [From the Field] (K. F. MacDorman & N. Kageki, Trans.). IEEE Robotics Automation Magazine, 19(2), 98–100. https://doi.org/10.1109/MRA.2012.2192811
Moruzzi, C. (2020a). Artificial Creativity and General Intelligence. Journal of Science and Technology of the Arts, 12(3), 84–99. https://doi.org/10.34632/jsta.2020.9481
Moruzzi, C. (2020b). Learning through creativity: How creativity can help machine learning achieving deeper understanding. Rivista Italiana Di Filosofia Del Linguaggio, 14(2). https://doi.org/10.4396/AISB201904
Moruzzi, C. (2021). Measuring creativity: An account of natural and artificial creativity. European Journal for Philosophy of Science, 11(1), 20. https://doi.org/10.1007/s13194-020-00313-w
Novitz, D. (1999). Creativity and Constraint. Australasian Journal of Philosophy, 77(1), 67–82. https://doi.org/10.1080/00048409912348811
Ragot, M., Martin, N., & Cojean, S. (2020). AI-generated vs. Human Artworks. A Perception Bias Towards Artificial Intelligence? Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems, 1–10. https://doi.org/10.1145/3334480.3382892
Ridler, A. (2021, June 5). Mosaic Virus, 2019. ANNA RIDLER. http://annaridler.com/mosaic-virus
Runco, M. A., & Jaeger, G. J. (2012). The Standard Definition of Creativity. Creativity Research Journal, 24(1), 92–96. https://doi.org/10.1080/10400419.2012.650092
Sen, A. (1974). Informational bases of alternative welfare approaches: Aggregation and income distribution. Journal of Public Economics, 3(4), 387–403. https://doi.org/10.1016/0047-2727(74)90006-1
Sen, A. (1980). Equality of What? In S. M. McMurrin (Ed.), The Tanner Lectures on Human Values (Vol. 1). Cambridge University Press.
Sen, A. (2000). Development as Freedom. Oxford University Press.
Simon, H. (1985). What We Know About the Creative Process. In R. L. Kuhn (Ed.), Frontiers in Creative and Innovative Management (pp. 3–22). Ballinger Publishing Company.
Simonton, D. K. (1999). Target Article: ‘Creativity as Blind Variation and Selective Retention: Is the Creative Process Darwinian?’ Psychological Inquiry, 10(3), 309–328. https://doi.org/10.1207/S15327965PLI1004_4
Stein, M. I. (1953). Creativity and Culture. The Journal of Psychology, 36(2), 311–322. https://doi.org/10.1080/00223980.1953.9712897
Still, A., & d’Inverno, M. (2019). Can Machines Be Artists? A Deweyan Response in Theory and Practice. Arts, 8(1), 36. https://doi.org/10.3390/arts8010036
Turing, A. (1950). Computing Machinery and Intelligence. Mind, 59(236), 433–460. https://doi.org/10.1093/mind/LIX.236.433
Walia, C. (2019). A Dynamic Definition of Creativity. Creativity Research Journal, 31(3), 237–247. https://doi.org/10.1080/10400419.2019.1641787
Wellner, G. (2021). Digital Imagination, Fantasy, AI Art. Foundations of Science. https://doi.org/10.1007/s10699-020-09747-0
Wu, Q., Zhu, B., Yong, B., Wei, Y., Jiang, X., Zhou, R., & Zhou, Q. (2021). ClothGAN: Generation of fashionable Dunhuang clothes using generative adversarial networks. Connection Science, 33(2), 341–358. https://doi.org/10.1080/09540091.2020.1822780
Published
2022-08-24
Section
Monographica