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Autonomy, Authenticity, Authorship and Intention in Computer Generated Art

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Computational Intelligence in Music, Sound, Art and Design (EvoMUSART 2019)

Abstract

This paper examines five key questions surrounding computer generated art. Driven by the recent public auction of a work of “AI Art” we selectively summarise many decades of research and commentary around topics of autonomy, authenticity, authorship and intention in computer generated art, and use this research to answer contemporary questions often asked about art made by computers that concern these topics. We additionally reflect on whether current techniques in deep learning and Generative Adversarial Networks significantly change the answers provided by many decades of prior research.

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Notes

  1. 1.

    The name is derived from the French interpretation of “Goodfellow”: Bel ami.

  2. 2.

    Ada Lovelace is famously known as one of the first people to record ideas about computer creativity [6].

  3. 3.

    A great resource is the EvoMUSART Index, available at: http://evomusart-index.dei.uc.pt.

  4. 4.

    This is conceptually similar to co-evolutionary strategies, such as creator/critic systems [24], used at least since the 1990s.

  5. 5.

    It is worth noting that artistic styles or idioms share similar characteristics too.

  6. 6.

    https://twitter.com/fchollet/status/885378870848901120.

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Acknowledgements

This research was support by Australian Research Council grants DP160100166 and FT170100033.

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Correspondence to Jon McCormack .

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McCormack, J., Gifford, T., Hutchings, P. (2019). Autonomy, Authenticity, Authorship and Intention in Computer Generated Art. In: Ekárt, A., Liapis, A., Castro Pena, M.L. (eds) Computational Intelligence in Music, Sound, Art and Design. EvoMUSART 2019. Lecture Notes in Computer Science(), vol 11453. Springer, Cham. https://doi.org/10.1007/978-3-030-16667-0_3

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  • DOI: https://doi.org/10.1007/978-3-030-16667-0_3

  • Publisher Name: Springer, Cham

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