Abstract
While art and science still functioned side-by-side during the Renaissance, their methods and perspectives diverged during the nineteenth century, creating a still enduring separation between the "two cultures". Recently, artists and scientists again collaborate more frequently, as promoted most radically by the ArtScience movement. This approach aims at a true synthesis between the intuitive, imaginative methods of art and the rational, rule-governed methods of science. To prepare the grounds for a theoretical synthesis, this paper surveys the fundamental commonalities and differences between science and art. Science and art are united in their creative investigation, where coherence, pattern or meaning play a vital role in the development of concepts, while relying on concrete representations to experiment with the resulting insights. On the other hand, according to the standard conception, science seeks an understanding that is universal, objective and unambiguous, while art focuses on unique, subjective and open-ended experiences. Both offer prospect and coherence, mystery and complexity, albeit with science preferring the former and art, the latter. The paper concludes with some examples of artscience works that combine all these aspects.
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References
Aoki, Y. (1999). Review article: Trends in the study of the psychological evaluation of landscape. Landscape Research, 24(1), 85–94.
Arslan, B., Brouse, A., Castet, J., Filatriau, J.-J., Léhembre, R., Noirhomme, Q., & Simon, C. (2005). From biological signals to music. In 2nd International conference on enactive interfaces.
Barad, K. (2007). Meeting the Universe Halfway: Quantum physics and the entanglement of matter and meaning. Duke University Press.
Bateson, G. (1980). Mind and nature: A necessary unity. Fontana.
Bergvall-Kåreborn, B., Eriksson, C. I., Ståhlbröst, A., & Svensson, J. (2009). A milieu for innovation: defining living labs. DIVA. Presented at the ISPIM innovation symposium: 06/12/2009–09/12/2009.
Bohm, D., & Peat, F. D. (2010). Science, order and creativity. London: Routledge.
Borgdorff, H., Peters, P., & Pinch, T. (Eds.). (2019). Dialogues between artistic research and science and technology studies (1st ed.). New York, NY: Routledge.
Brockman, J. (1995). The third culture. Simon & Schuster.
Brown, A. W., & Root-Bernstein, R. (2015). ReBioGeneSys—Origins of Life. Retrieved from https://adamwbrown.net/projects-2/rebiogenesys-origins-of-life/
Campbell, J. (1949). The hero with a thousand faces. Princeton: Princeton University Press.
Casti, J., & Karlqvist, A. (2003). Art and complexity. Amsterdam: Elsevier.
Clark, A. (1998). Embodied, Situated, and Distributed Cognition. In W. Bechtel & G. Graham (Eds.), A companion to cognitive science (pp. 506–517). London: Blackwell Publishing Ltd.
Csikszentmihalyi, M. (1997). Creativity: Flow and the psychology of discovery and invention. Harper Perennial.
Dominiczak, M. H. (2015). Artscience: A new avant-garde? Clinical Chemistry, 61(10), 1314–1315. https://doi.org/10.1373/clinchem.2014.236992.
Domnitch, E., & Gelfand, D. (2017). ER=EPR. Retrieved from https://www.portablepalace.com/erepr.html
Edwards, D. (2008). Artscience: Creativity in the post-Google generation. Cambridge: Harvard University Press.
Gaut, B. (2005). The cluster account of art defended. The British Journal of Aesthetics, 45(3), 273–288.
Gell-Mann, M. (2003). Regularities and randomness: Evolving schemata in science and the arts. In J. Casti & A. Karlqvist (Eds.), Art and complexity (pp. 47–58). Amsterdam, The Netherlands: Elsevier. Retrieved from https://resolver.caltech.edu/CaltechAUTHORS:20150922-090612748
Gershenson, C. (2004) Cognitive paradigms: which one is the best? Cognitive Systems Research, 5(2), 135–156.
Gimblett, H. R., Itami, R. M., & Fitzgibbon, J. E. (1985). Mystery in an information processing model of landscape preference. Landscape Journal, 4(2), 87–95. https://doi.org/10.3368/lj.4.2.87.
Goldstone, R. L., Kersten, A., & Carvalho, P. F. (2012). Concepts and categorization. Handbook of psychology, Second Edition, 4.
Grassé, P. (1960). The automatic regulations of collective behavior of social insect and “stigmergy”. Journal de psychologie normale et pathologique, 57, 1–10.
Hawkes, T. (2003). Structuralism and semiotics. Routledge.
Heylighen F. & Petrovic K. (2020). Foundations of ArtScience: Towards a synthesis of scientific investigation and artistic imagination (in preparation)
Heylighen, F. (1999). Advantages and limitations of formal expression. Foundations of Science, 4(1), 25–56. https://doi.org/10.1023/A:1009686703349.
Heylighen, F. (2006). Characteristics and problems of the gifted: Neural propagation depth and flow motivation as a model of intelligence and creativity (ECCO Working papers No. 2006-05). Retrieved from https://pespmc1.vub.ac.be/Papers/Giftednessmodel.pdf
Heylighen, F. (2009). Complexity and self-organization. Encyclopedia of library and information sciences, Third Edition (pp. 1215–1224). Taylor & Francis.
Heylighen, F. (2012). A tale of challenge, adventure and mystery: Towards an agent-based unification of narrative and scientific models of behavior (ECCO Working Papers No. 2012-06). ECCO. Brussels, Belgium. Retrieved from https://pcp.vub.ac.be/papers/TaleofAdventure.pdf
Heylighen, F. (2016a). Stigmergy as a universal coordination mechanism I: Definition and components. Cognitive Systems Research, 38, 4–13. https://doi.org/10.1016/j.cogsys.2015.12.002.
Heylighen, F. (2016b). Stigmergy as a universal coordination mechanism II: Varieties and evolution. Cognitive Systems Research, 38, 50–59. https://doi.org/10.1016/j.cogsys.2015.12.007.
Heylighen, F. (2019). Transcending the rational symbol system: How information technology integrates science, art, philosophy and spirituality into a global brain. Handbook of Human Symbolic Evolution. Oxford University Press. Retrieved from https://pcp.vub.ac.be/Papers/TranscendingRSS.pdf
Heylighen, F., Cilliers, P., & Gershenson, C. (2007). Complexity and philosophy. In J. Bogg & R. Geyer (Eds.), Complexity, science and society (pp. 117–134). Oxford: Radcliffe Publishing.
Heylighen, F., Kostov, I., & Kiemen, M. (2013). Mobilization systems: Technologies for motivating and coordinating human action. In Peters M. A., Besley T. and Araya D. (Ed.), The new development paradigm: Education, knowledge economy and digital futures (pp. 115–144). New York: Peter Lang. Retrieved from https://pcp.vub.ac.be/Papers/MobilizationSystems.pdf
Johnson, M. (2008). The meaning of the body: Aesthetics of human understanding. Chicago: University of Chicago Press.
Johnson, M. (2018). The aesthetics of meaning and thought: The bodily roots of philosophy, science, morality, and art. Chicago: University of Chicago Press.
Kahneman, D., & Egan, P. (2011). Thinking, fast and slow. Farrar, Straus and Giroux New York.
Kaplan, S. (1988). Perception and landscape: Conceptions and misconceptions. In J. Nasar (Ed.), Environmental aesthetics: Theory, research, and application (pp. 45–55). Cambridge: Cambridge University Press.
Kaplan, S. (1987). Aesthetics, affect, and cognition: Environmental preference from an evolutionary perspective. Environment and Behavior, 19(1), 3–32.
Kelley, T. D. (2003). Symbolic and sub-symbolic representations in computational models of human cognition: What can be learned from biology? Theory & Psychology, 13(6), 847–860. https://doi.org/10.1177/0959354303136005.
Kerr, B. (Ed.). (2009). Encyclopedia of giftedness, creativity, and talent. London: SAGE.
Kesner, L. (2014). The predictive mind and the experience of visual art work. Frontiers in Psychology, 5, 1417.
Kiemen, M., & Ballon, P. (2012). Living labs & stigmergic prototyping: Towards a Convergent Approach. In ISPIM conference proceedings (pp. 1–13). The International Society for Professional Innovation Management (ISPIM). Retrieved from https://www.mixel.be/files/pdf/ISPIM2012.pdf
Klein, G., Moon, B., & Hoffman, R. R. (2006). Making sense of sensemaking 1: Alternative perspectives. IEEE Intelligent Systems, 4, 70–73.
Knobloch-Westerwick, S., & Keplinger, C. (2006). Mystery appeal: Effects of uncertainty and resolution on the enjoyment of mystery. Media Psychology, 8(3), 193–212. https://doi.org/10.1207/s1532785xmep0803_1.
Lakoff, G., & Núnez, R. E. (2000). Where mathematics comes from: How the embodied mind brings mathematics into being. Basic Books.
Lakoff, G., & Johnson, M. (1980). The metaphorical structure of the human conceptual system. Cognitive Science, 4(2), 195–208.
Lakoff, G., & Johnson, M. (2008). Metaphors we live by. Chicago: University of Chicago Press.
Langton, C. G. (1997). Artificial life: An overview. Cambridge: MIT Press.
Latour, B. (1996). On actor-network theory: A few clarifications. Soziale Welt, pp. 369–381.
Latour, B. (1999). Pandora’s hope: Essays on the reality of science studies. Cambridge, MA: Harvard University Press.
Lewin, R. (1999). Complexity: Life at the edge of chaos. Chicago: University of Chicago Press.
Leydesdorff, L., & Ward, J. (2005). Science shops: A kaleidoscope of science–society collaborations in Europe, Science shops: A kaleidoscope of science–society collaborations in Europe. Public Understanding of Science, 14(4), 353–372. https://doi.org/10.1177/0963662505056612.
Loewenstein, G. (1994). The psychology of curiosity: A review and reinterpretation. Psychological Bulletin, 116, 75–75.
Maes, P. (1995). Artificial life meets entertainment: Lifelike autonomous agents. Communications of the ACM, 38(11), 108–114. https://doi.org/10.1145/219717.219808.
Merrell, F. (2001). Charles Sanders Peirce’s concept of the sign. The Routledge Companion to Semiotics and Linguistics, 28–39.
Park, C. L. (2010). Making sense of the meaning literature: An integrative review of meaning making and its effects on adjustment to stressful life events. Psychological Bulletin, 136(2), 257.
Parunak, H. V. D. (2006). A survey of environments and mechanisms for human–human stigmergy. In D. Weyns, H. V. D. Parunak, & F. Michel (Eds.), Environments for multi-agent systems II (pp. 163–186). Berlin: Springer.
Penny, S. (2017). Making sense: Cognition, computing, art, and embodiment. Cambridge: MIT Press.
Peters, J. D. (2015). The marvelous clouds: Toward a philosophy of elemental media. Chicago: University of Chicago Press.
Prigogine, I., & Stengers, I. (1984). Order out of chaos: Man’s new dialogue with nature. Bantam Books.
Prophet, J., & Pritchard, H. (2015). Performative apparatus and diffractive practices: An account of artificial life art. Artificial Life, 21(3), 332–343. https://doi.org/10.1162/ARTL_a_00174.
Root-Bernstein, B., Siler, T., Brown, A., & Snelson, K. (2011). ArtScience: Integrative collaboration to create a sustainable future. Leonardo, 44(3), 192.
Root-Bernstein, R., & Root-Bernstein, M. (2000). Sparks of genius: The 13 thinking tools of the World’s most creative people. Houghton Mifflin.
Schnugg, C. (2019). Creating ArtScience collaboration: Bringing value to organizations. Berlin: Springer.
Schnugg, C., & Song, B. (2020). An organizational perspective on ArtScience collaboration: Opportunities and challenges of platforms to collaborate with artists. Journal of Open Innovation: Technology, Market, and Complexity, 6(1), 6. https://doi.org/10.3390/joitmc6010006.
Siler, T. (2011). The artscience program for realizing human potential. Leonardo, 44(5), 417–424.
Sims, K. (1994). Evolving virtual creatures. In Proceedings of the 21st annual conference on computer graphics and interactive techniques (pp. 15–22). New York, NY, USA: ACM. https://doi.org/10.1145/192161.192167
Snow, C. P. (1993). The two cultures. Cambridge: Cambridge University Press.
Sormani, P., Carbone, G., & Gisler, P. (2018). Practicing art/science: Experiments in an emerging field. London: Routledge.
Stadler, M., & Kruse, P. (1990). Theory of gestalt and self-organization. Self-steering and cognition in complex systems. Gordon and Breach, New York, pp. 142–169.
Stamps, A. E., III. (2004). Mystery, complexity, legibility and coherence: A meta-analysis. Journal of Environmental Psychology, 24(1), 1–16.
Strosberg, E. (2001). Art and science. New York: Abbeville Press.
Thomae, H. (1999). The nomothetic-idiographic issue: Some roots and recent trends. International Journal of Group Tensions, 28(1), 187–215.
Van de Cruys, S., & Wagemans, J. (2011a). Gestalts as predictions: Some reflections and an application to art. Gestalt Theory, 33(3), 325–344.
Van de Cruys, S., & Wagemans, J. (2011b). Putting reward in art: A tentative prediction error account of visual art. I-Perception, 2(9), 1035–1062.
Walter-Herrmann, J., & Büching, C. (2014). FabLab: Of machines, makers and inventors. transcript Verlag.
Wilson, B. (2017). ArtScience and the metaphors of embodied realism. In P. Gibbs (Ed.), Transdisciplinary higher education: A theoretical basis revealed in practice (pp. 179–203). Cham: Springer.
Wilson, B., Hawkins, B., & Sim, S. (2015). Art, science and communities of practice. Leonardo, 48(2), 152–157.
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Heylighen, F., Petrović, K. Foundations of ArtScience: Formulating the Problem. Found Sci 26, 225–244 (2021). https://doi.org/10.1007/s10699-020-09660-6
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DOI: https://doi.org/10.1007/s10699-020-09660-6