Abstract
Machine learning programs are getting better at solving problems every day. As manufacturing jobs are being replaced with increasingly competent algorithms, it is important to consider how, if at all, artificial intelligence can replicate human creativity. Indeed, the capacity to create beauty or harm lies at the core of this enterprise. And considering the means by which human consciousness is capable of introducing new ways of thinking and doing provides a useful entry point to discussing the role of artificial intelligence in creative work. In this chapter, we first contextualize human creativity vis-à-vis individuals, societies, and cultures. After employing a systems approach to creativity, we offer insights into the various ways artificial intelligence is becoming better poised to generate creative works. We then introduce a new model of creativity, called Creativity 4.0, and discuss how this model can be applied to the emerging fields of artificial intelligence. Our aim here is to situate proneness for creativity within emotional, cognitive, and sociocultural systems that fall outside the scope of machine learning programs. Implications for advancing creativity research and applications are discussed.
Keywords
- Creativity
- Innovation
- Artificial intelligence
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Notes
- 1.
“Ethics of Autonomous Vehicles.” Retrieved from MIT Media Lab. https://www.media.mit.edu/projects/ethics-of-autonomous-vehicles/overview/
- 2.
“If an AI Creates a Work of Art, Who Owns the Rights to It?” In Quartz. https://qz.com/1054039/google-deepdream-art-if-an-ai-creates-a-work-of-art-who-owns-the-rights-to-it/
- 3.
“The Future of Human Work is Imagination, Creativity, and Strategy.” In Harvard Business Review. https://hbr.org/2018/01/the-future-of-human-work-is-imagination-creativity-and-strategy
- 4.
“More Efficient Machine Learning Could Upend AI Paradigm.” In MIT Technology Review. https://www.technologyreview.com/s/610095/more-efficient-machine-learning-could-upend-the-ai-paradigm/
- 5.
“How Google is Making Music with Artificial Intelligence.” In Science Magazine. http://www.sciencemag.org/news/2017/08/how-google-making-music-artificial-intelligence
- 6.
“Artificially Intelligent Painters Invent New Styles of Art.” In New Scientist. https://www.newscientist.com/article/2139184-artificially-intelligent-painters-invent-new-styles-of-art/
- 7.
“Robots Have Been Taking Our Jobs for 50 Years, so Why are we Worried?” Retrieved from World Economic Forum. https://www.weforum.org/agenda/2017/07/robots-have-been-taking-our-jobs-for-50-years-so-why-are-we-worried-now/
- 8.
“Harnessing Automation for a Future that Works.” In Mckinsey Global Institute. https://www.mckinsey.com/featured-insights/digital-disruption/harnessing-automation-for-a-future-that-works
- 9.
“Facial Recognition is Accurate, if You’re a White Guy.” In New York Times. https://www.nytimes.com/2018/02/09/technology/facial-recognition-race-artificial-intelligence.html
- 10.
“Study Finds Gender and Skin-type Bias in Commercial Artificial-Intelligence Systems.” In MIT News. http://news.mit.edu/2018/study-finds-gender-skin-type-bias-artificial-intelligence-systems-0212
- 11.
“New Research Attempts to Solve the Problem of AI Bias in Black Box Algorithms.” In MIT Technology Review. https://www.technologyreview.com/s/609338/new-research-aims-to-solve-the-problem-of-ai-bias-in-black-box-algorithms/
- 12.
“How Trump Exploited the Facebook Data of Millions.” In New York Times, March 17, 2018. https://www.nytimes.com/2018/03/17/us/politics/cambridge-analytica-trump-campaign.html
- 13.
“For Many Facebook Users, a ‘Last Straw’ that Led Them to Quit.” In New York Times. https://www.nytimes.com/2018/03/21/technology/users-abandon-facebook.html
- 14.
“How the Chess Was Won.” In MIT Technology Review, August 1, 1997. https://www.technologyreview.com/s/400089/how-the-chess-was-won/
- 15.
Google Deep Dream Generator. https://deepdreamgenerator.com
- 16.
“Using Artificial Intelligence to Improve Early Breast Cancer Detection.” In MIT News, October 16, 2017. http://news.mit.edu/2017/artificial-intelligence-early-breast-cancer-detection-1017
References
Alpaydin, E. (2016). Machine learning: The new AI (MIT Press essential knowledge series). Cambridge, MA: MIT Press.
Bahl, M., Barzilay, R., Yedidia, A., Locascio, N., Yu, L., & Lehman, C. (2018). High-risk breast lesions: A machine learning model to predict pathologic upgrade and reduce unnecessary surgical excision. Radiology, 286, 810–818.
Baker, C. L., Jara-Ettinger, J., Saxe, R., & Tenenbaum, J. B. (2017). Rational quantitative attribution of beliefs, desires and percepts in human mentalizing. Nature Human Behaviour, 1(4).
Beaty, R. E., Benedek, M., Silvia, P. J., & Schacter, D. L. (2016). Creative cognition and brain network dynamics. Trends in Cognitive Sciences, 20, 87–95.
Cacha, F. (1976). Figural creativity, personality, and peer nominations of pre-adolescents. Gifted Child Quarterly, 20, 187–195.
Csikszentmihalyi, M. (1988). Society, culture, and person: A systems view of creativity. In R. J. Sternberg (Ed.), The nature of creativity: Contemporary psychological perspectives (pp. 325–339). New York: Cambridge University Press.
Csikszentmihalyi, M. (1996). Creativity: Flow and the psychology of discovery and invention. New York: HarperCollins.
Furnham, A., Batey, M., Anand, K., & Manfield, J. (2008). Personality, hypomania, intelligence and creativity. Personality and Individual Differences, 44, 1060–1069.
Gardner, H. (1993). Creating minds: An anatomy of creativity seen through the lives of Freud, Einstein, Picasso, Stravinsky, Eliot, Graham, and Gandhi. New York: BasicBooks.
Gardner, H. (2013). Reestablishing the commons for the common good. Daedalus, 142, 199–208.
Gardner, H., & Shulman, L. S. (2005). The professions in America today: Crucial but fragile. Daedalus, 134, 13–18.
Gardner, H., & Weinstein, E. (2018). Creativity: The view from Big C and the introduction of tiny c. In R. Sternberg & J. Kaufman: The Nature of Human Creativity (pp. 94–109). New York, NY: Cambridge University Press.
Gopnik, A. (2009). The philosophical baby: What children’s minds tell us about truth, love, and the meaning of life (1st ed.). New York: Farrar, Straus and Giroux.
Harari, Y. (2016). Homo deus: A brief history of tomorrow. London: Harvill Secker.
Kaufman, J. C., & Beghetto, R. A. (2009). Beyond big and little: The four C model of creativity. Review of General Psychology, 13, 1–12.
Kuhn, T. (1996). The structure of scientific revolutions (3rd ed.). Chicago, IL: University of Chicago Press.
Lipson, H., & Kurman, M. (2016). Driverless: Intelligent cars and the road ahead. Cambridge, MA: The MIT Press.
Lyubomirsky, S., King, L., & Diener, E. (2005). The benefits of frequent positive affect: Does happiness lead to success? Psychological Bulletin, 131, 803–855.
Murphy, K. (2012). Machine learning: A probabilistic perspective (Adaptive computation and machine learning). Cambridge, MA: MIT Press.
Sawyer, R. K. (2012). Explaining creativity: The science of human innovation. New York: Oxford University Press.
Simonton, D. (2009). Varieties of (scientific) creativity: A hierarchical model of domain-specific disposition, development, and achievement. Perspectives on Psychological Science, 4, 441–452.
Sternberg, R. (1988). The Nature of creativity: Contemporary psychological perspectives. Cambridge/New York: Cambridge University Press.
Susskind, R., & Susskind, D. (2015). The future of the professions: How technology will transform the work of human experts (First ed.). Oxford, UK: Oxford University Press.
Tan, S., Caruana, R., Hooker, G., & Lou, Y. (2017). Auditing black-box models using transparent model distillation with side information. arXiv:1710.06169
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Gruner, D.T., Csikszentmihalyi, M. (2019). Engineering Creativity in an Age of Artificial Intelligence. In: Lebuda, I., Glăveanu, V.P. (eds) The Palgrave Handbook of Social Creativity Research. Palgrave Studies in Creativity and Culture. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-319-95498-1_27
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