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Towards a Methodology for Field Work in Computational Creativity

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Abstract

This work proposes a methodology for conducting field work in computational creativity, referring to field work as the effort of actively making a system or its artifacts widely accessible outside the academic world. Field work aims to study how creative computer agents and/or their products influence society, and how the dynamics that arise from the interaction between people and those inventive machines or their artifacts can inform the design of computational creativity methods, systems and artefacts. In this paper, we reflect on our experiences making our systems ALYSIA and MEXICA broadly available. In the case of ALYSIA, the system itself was made accessible, whereas MEXICA’s artifacts (stories) were shared through a traditionally published book for a broad readership. We then propose a five step methodology for effectively conducting field work in Computational Creativity. The participation of the computational creativity community is essential to test and enrich this methodology.

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Notes

  1. https://www.aaronshome.com/aaron/biography/index.html accessed 24 July 2020.

  2. https://www.abdn.ac.uk/ncs/departments/computing-science/standup-315.php accessed 20 August 2020.

  3. https://joking.abdn.ac.uk/ accessed 20 August2020.

  4. https://www.newscientist.com/article/mg23231043-500-machine-learning-lets-computer-create-melodies-to-fit-any-lyrics/ accessed 25 July 2020.

  5. An unpublished manuscript on the system included a user study that compared ALYSIA's rankings of vocal melodies to how humans would rank the same melodies. While helpful, the insights resulting from that study were limited in scope, particularly when compared with the wealth of diverse feedback received when taking ALYSIA to broader audiences.

  6. https://counterpathpress.org/crossborders-the-aesthetics-of-migration-at-counterpath-and-cu-boulder-november-9-and-10-2018 accessed 25 July 2020.

  7. https://livestream.com/hammermuseum/events/8632947 accessed 25 July 2020.

  8. https://aiforgood.itu.int/2019-event/ accessed 25 July 2020.

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Acknowledgements

The authors would like to thank the reviewers for their useful comments and Lee Cheatley for helpful discussions.

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Authors and Affiliations

  1. Depto. de Tecnologías de la Información, Universidad Autónoma Metropolitana at Cuajimalpa, México City, México

    Rafael Pérez y Pérez

  2. Department of Computer Science and Engineering, Santa Clara University, Santa Clara, USA

    Margareta Ackerman

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  1. Rafael Pérez y Pérez
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  2. Margareta Ackerman
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Correspondence to Rafael Pérez y Pérez.

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Pérez y Pérez, R., Ackerman, M. Towards a Methodology for Field Work in Computational Creativity. New Gener. Comput. 38, 713–737 (2020). https://doi.org/10.1007/s00354-020-00105-z

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