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Types of Creativity in Artificial Intelligence

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In the past years, people have been fascinated by AI and often wonder where its boundary is, if there is one at all. We try to further develop them, making them more human like each time. One aspect that emerged is creativity. Creativity isn’t magical. It’s an aspect of normal human intelligence, not a special faculty granted to a tiny elite (Margaret A. Boden, 2009). A creative idea is one which is novel, surprising, and valuable. There are three main types of creativity, based on the different ways of generating it. The first type involves novel combinations of familiar ideas. The second type is the exploration of structured conceptual spaces, and the third type includes the transformation of some (one or more) dimension of the space so that new structures could arise (Margaret A. Boden, 1998).

All three techniques can be modeled by AI, in some cases, with impressive results. AI techniques underlie various types of computer arts (Margaret A. Boden, 2009). AI will have less difficulty in modelling the generation of new ideas than in automating their evaluation. They are able to create new ideas in all three ways; by producing novel combinations of familiar ideas, by exploring the potential of conceptual spaces, and by making transformations that enables the generation of new ideas. (Margaret A. Boden, 1998). An example of AI creativity can be seen in IBM’s Watson. IBM’s machine learning system, Watson, was fed hundreds of images of artist Gaudi’s work along with other complementary material to help the machine learn possible influences for his work including Barcelona, its culture, biographies, historical articles and song lyrics. Watson analyzed all the information and delivered inspiration to human artists who were charged with the creating a sculpture “informed’ by Watson in the style of Gaudi (Bernard Marr, 2018).

In another case, people were unable to differentiate between art created by Watson and by real life artist. In a randomized-controlled double blind study, subjects were unable to distinguish the computer art from two sample sets of acclaimed work created by flesh-and-blood artists (one culled from the canon of Abstract Expressionist paintings, the other from works shown at the 2016 edition of Art Basel in Hong Kong). In fact, the computer-made pictures were often rated by subjects as more “novel” and “aesthetically appealing” than the human-generated art (Rene Chun, 2017). This goes to show how close it is for computers to “create” their own ideas and art.

Notions relating to computational systems exhibiting creative behaviors have been explored since the very early days of computer science, and the field of computational Creativity research has been formed in the last dozen years to scientifically explore the potential of such systems (Simon Colton, 2012). Whether computers could “really” be creative isn’t a scientific question but a philosophical one, to which there is no clear answer (Margaret A. Boden, 2009). It is clearly possible for computers, AIs to be able to produce and generate their own novel and unique ideas in the near future. Whether we call that “creativity” or not, depends on the person’s personal view.

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