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Philosophy & Technology

, Volume 30, Issue 3, pp 263–265 | Cite as

Special Section: Rethinking Art and Aesthetics in the Age of Creative Machines

Editor’s Introduction
  • David J. Gunkel
Editorial notes

As machines of various sorts and configurations encroach on human abilities in areas like manufacturing, decision making, communication, transportation, etc., the one remaining bulwark of human exceptionalism appears to be creativity and artistry. But maybe not for long. There are already technologies that can produce what appear to be creative work. There is, for example, Shimon, a marimba-playing jazz-bot from Georgia Tech University that can improvise with human musicians in real time (Hoffman and Weinberg 2011); Experiments in Musical Intelligence or EMI, a PC-based digital composer that can create new classical music scores that are (by some accounts) virtually indistinguishable from the master works of Bach, Beethoven, and Mozart (Cope 2001); The Painting Fool, an algorithmic painter that aspires to be “taken seriously as a creative artist in its own right” (Colton 2012, 16); and Narrative Science’s Quill and Automated Insight’s Wordsmith, natural language generation systems that are designed to write original, human-readable stories by drawing down and reassembling data residing in the cloud (Dörr and Hollnbuchner 2016). Consequently, it appears that what we have called “creativity” and “artistry” may not be as uniquely human as one might have initially thought. This special section of Philosophy and Technology examines the philosophical opportunities, challenges, and repercussions of increasingly creative machines. In one way or another, the three essays collected here seek to address and respond to one seemingly simple question: Can machines create art?

This question, however, is something of a matryoshka, that Russian folk art (also called nesting dolls) where every figure contains another hidden inside it. There are, in the first place (or on the initial layer of the matryoshka), technical aspects to the question: Is it possible to design and develop technology that has the capability to produce what would be widely recognized as a work of art? Or stated more precisely, Can art be made computable? This is the domain of “computational creativity”—“a subfield of Artificial Intelligence (AI) research…where we build and work with computational systems that create artefacts and ideas” (Colton and Wiggins 2012, 21). Responses to this technical question require the hacker’s art of argument by doing. It calls for the design, development, and demonstration of actual working prototypes like EMI, Shimon, The Painting Fool, and D.O.U.G_1. It is, in other words, a mode of response that calls on and involves the practical efforts of artists/programmers, like David Cope (EMI), Guy Hoffmann and Gil Weinberg (Simon), Simon Colton (The Painting Fool), and Sougwen Chung (D.O.U.G._1).

But it is also a question that necessitates deeper philosophical reflection on the nature of art itself. Very quickly the questions “Can machines create art?” or “Is creativity computable?” turn into “What do we mean by art?” and “What is meant by verb ‘to create?’” The way these concepts come to be defined and characterized makes a difference when it comes to deciding whether or not AI, robots, and algorithms are capable of producing art. And in this debate, as with everything having to do with philosophical reflection since the time of the linguistic turn (if not before via the insight provided in Plato’s Cratylus, 1977), words definitely matter. The questions, therefore, are not just technical but also profoundly philosophical—involving concepts and terminology that are anything but univocal and settled.

Furthermore, the principal philosophical challenge is not simply about applying aesthetic terminology and theory to the technical efforts of programmers and the various mechanisms they produce. It is also about permitting these efforts and products to question and critically reassesses the language and theories of axiology. In other words, the question “Can machines create art?” moves in two directions simultaneously. On the one hand, it requires that we draw upon the philosophy of art and apply its various insights to technological innovation in an effort to sort out and evaluate what are purported to be machine-generated artworks. In this effort, some brands of aesthetic theory, like the various versions of formalism, will be more open to and accommodating of machine-generated content than others, like Romanticism and its veneration of the figure of artistic genius. This is just good-old applied philosophy. On the other hand, however, it requires that we permit and make room for machine-generated content to challenge and stress-test existing aesthetic theory, terminological definitions, and conceptual categories. Machine-generated efforts make possible new questions about art and new modes for thinking about artistry, authorship, and aesthetics. For this reason, the critical task involves (1) using philosophy to investigate and understand new developments in computer and robotic technology and (2) applying innovations in computational creativity to reevaluate existing standards and practices of philosophical thinking.

Finally we need to recognize that these questions, despite initial appearances, are not simply about art, entertainment, or even aesthetics. Because “art” already involves complex assumptions about the “human experience,” consciousness, intentionality, and value, a lot rides on this seemingly simple query. Consequently, what transpires in this investigation about art and technology is something that cannot be contained, controlled, or quarantined. It inevitably releases a fundamental examination of what it means to be human. In the end, the three essays that comprise this special section target and grapple with this profound question. They are, then, “philosophical” in the proper sense of the word. That is, they do not aim to resolve the question concerning computational creativity and machine-generated art; they seek to articulate and further develop the question by tracing its general importance, consequences, and significance. As Daniel Dennett (1996, vii) once explained, the task of philosophy has never been to supply answers to existing questions but to critically investigate the questions in order to refine the mode, purpose, and significance of the inquiry.

References

  1. Colton, S. (2012). The painting fool: Stories from building an automated painter. In J. McCormack & M. d’Inverno (Eds.), Computers and creativity (pp. 3–38). Berlin: Springer Verlag.CrossRefGoogle Scholar
  2. Colton, S., & Wiggins, G. A. (2012). Computational creativity: The final frontier. In L. De Raedt et al. (Eds.), Frontiers in artificial intelligence and applications (Vol. 242, pp. 21–26). Amsterdam: IOS Press http://ebooks.iospress.nl/volume/ecai-2012.Google Scholar
  3. Cope, D. (2001). Virtual music: computer synthesis of musical style. Cambridge: MIT Press.Google Scholar
  4. Dennett, D. C. (1996). Kinds of minds: toward an understanding of consciousness. New York: Basic Books.Google Scholar
  5. Dörr, K. N., & Hollnbuchner, K. (2016). Ethical challenges of algorithmic journalism. Digital Journalism, 5(4), 404–419.CrossRefGoogle Scholar
  6. Hoffman, G., & Weinberg, G. (2011). Interactive improvisation with a robotic marimba player. Autonomous Robots, 31(2–3), 133–153.CrossRefGoogle Scholar
  7. Plato. (1977). In H. N. Fowler (Ed.), Cratylus. Cambridge: Harvard University Press.Google Scholar

Copyright information

© Springer Science+Business Media B.V. 2017

Authors and Affiliations

  1. 1.Northern Illinois UniversityDeKalbUSA

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