Tool or Partner: The Designer’s Perception of an AI-Style Generating Service | SpringerLink
Skip to main content
Springer Nature Link
Log in

Tool or Partner: The Designer’s Perception of an AI-Style Generating Service

  • Conference paper
  • First Online:
Artificial Intelligence in HCI (HCII 2021)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 12797))

Included in the following conference series:

  • 3358 Accesses

Abstract

Recent advances in artificial intelligence have resulted in developments in various creative arts, specifically in terms of the creator’s instrumental expression and perception of use in the visual domain. Based on actual examples, we confirm the expansion of expression and stimulation of the artist’s creative will. We examine the process of selection, judgment, and interpretation of the outcome by the creator and AI. A creator uses the AI algorithm program as a “tool” initially. However, based on numerous attempts and data sets, the creator himself makes various interpretations of the results and receives inspiration. Such judgment and interpretation of the creator lead to new possibilities and expansion of work through creative will and inspiration. Expert interviews were conducted on the evaluation of works using AI and interpretation of art-related creativity. Results reveal various opinions on the interpretation criteria for instrumental recognition of artists and the evaluation of AI artworks by experts in related fields to date. Based on this, we hope to spark interdisciplinary discussions about responsibilities of AI’s current instrumental use; further, we explore new partner potential based on AI and collaboration in the creative process.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
¥17,985 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
JPY 3498
Price includes VAT (Japan)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
JPY 5719
Price includes VAT (Japan)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
JPY 7149
Price includes VAT (Japan)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

Change history

  • 03 July 2021

    In the originally published version of chapter 16, the corresponding author was not correctly marked. This has now been corrected.

References

  1. Is artificial intelligence set to become art’s next medium?|Christie’s. https://www.christies.com/features/A-collaboration-between-two-artists-one-human-one-a-machine-9332-1.aspx. Accessed 08 Feb 2021

  2. Is the art market ready to embrace work made by artificial intelligence? Christie’s will test the waters this fall. https://news.artnet.com/market/artificial-intelligence-christies-1335170. Accessed 08 Feb 2021

  3. Hertzmann, A.: Can computers create art? Arts 7, 18 (2018). https://doi.org/10.3390/arts7020018

    Article  Google Scholar 

  4. Nguyen, A., Yosinski, J., Clune, J.: Understanding innovation engines: automated creativity and improved stochastic optimization via deep learning. Evol. Comput. 24, 545–572 (2016)

    Article  Google Scholar 

  5. Mumford, M.D.: Where have we been, where are we going? Taking stock in creativity research. Creat. Res. J. 15, 107–120 (2003). http://www.springer.com/lncs. Accessed 21 Nov 2016

  6. Veron, P.E.: The nature-nurture problem in creativity. In: Glover, J.A., Ronning, R.R., Reynolds, C.R. (eds.) Handbook of Creativity, pp. 93–110. Plenum Press, New York (1989)

    Chapter  Google Scholar 

  7. Guilford, J.P.: Creativity: yesterday, today and tomorrow. J. Creat. Behav. 1, 3–14 (1967)

    Article  Google Scholar 

  8. Olwell, R.: Bohm-Biederman Correspondence. In: Bohm, D., Biederman, C., Pylkkanen, P., (eds.) Volume 1: Creativity in Art and Science. Isis, vol. 91, pp. 194–195 (2000)

    Google Scholar 

  9. McFadzean, E.: Creativity in MS/OR: choosing the appropriate technique. interfaces (1999)

    Google Scholar 

  10. Hennessey, B.A., Amabile, T.M.: Creativity. Annu. Rev. Psychol. 61, 569–598 (2010)

    Article  Google Scholar 

  11. Adobe sensei. https://www.adobe.com/sensei/ai-innovations.html/. Accessed 05 Dec 2020

  12. OCULA. https://ocula.com/magazine/art-news/interest-in-google-arts-culture-skyrockets-as/. Accessed 17 Dec 2020

  13. Manovich, L.: The language of new media. https://mitpress.mit.edu/books/language-new-media. Accessed 17 Dec 2021

  14. Ridler, A.: Missing datasets. http://annaridler.com/missing-data. Accessed 08 Feb 2021

  15. Ridler, A.: Fall of the House of Usher II (2017). http://annaridler.com/fall-of-the-house-of-usher-ii. Accessed 01 Feb 2020

  16. Parolo, L.: Ars Electronica 2017 : Festival für Kunst, Technologie und Gesellschaft = Festival for Art, Technology, and Society. Critique d’art. Actualité internationale de la littérature critique sur l’art contemporain (2019)

    Google Scholar 

  17. Colton, S., Halskov, J., Ventura, D., Gouldstone, I., Cook, M., Pérez-Ferrer, B.: The painting fool sees! new projects with the automated painter. Presented at the July 1 (2015)

    Google Scholar 

  18. Shinseungback Kimyonghun. http://ssbkyh.com/works/cloud_face/. Accessed 18 Feb 2021

  19. Saunders, R.S.: Issues of authenticity in autonomously creative systems. In: Proceedings of the Ninth International Conference on Computational Creativity, Salamanca, Spain, 25–29 June 272–279 (2018)

    Google Scholar 

  20. Ren, X.: Rethinking the relationship between humans and computers. Computer 49, 104–108 (2016)

    Article  Google Scholar 

  21. AI Illustrator. https://enpulse9.imweb.me/Paintly. Accessed 20 Feb 2021

  22. Trending Dreams|Deep Dream Generator. https://deepdreamgenerator.com/. Accessed 20 Feb 2021

  23. MGatys, L.A., Ecker, A.S., Bethge, M.: A neural algorithm of artistic style. arXiv:1508.06576 [cs, q-bio]. (2015)

  24. Louise Barriball, K., While, A.: Collecting data using a semi-structured interview: a discussion paper. J. Adv. Nurs. 19, 328–335 (1994)

    Article  Google Scholar 

  25. Palmer, T.: UXtools.co. https://uxtools.co. Accessed 20 Feb 2021

  26. Art, T.A.: TingaTinga African Art|African Art & Paintings Online. https://www.tingatingaart.com/. Accessed 13 Feb 2021

  27. Davis, N., Hsiao, C.-P., Singh, K.Y., Magerko, B.: Co-creative drawing agent with object recognition, p. 7 (2016)

    Google Scholar 

  28. Agüera y Arcas, B.: Art in the age of machine intelligence. Arts 6, 18 (2017)

    Google Scholar 

  29. Regulations for the Implementation of the Copyright Law of the People’s Republic of China, Arts. 2, 3: “Tencent Dreamwriter.” IIC. 51, 652–659 (2020)

    Google Scholar 

  30. Ricketson, S., Ginsburg, J.C.: International Copyright and Neighbouring Rights: The Berne Convention and Beyond. Oxford University Press, Oxford, New York (2006)

    Google Scholar 

  31. Shoyama, R.: Intelligent Agents: Authors, Makers, and Owners of Computer-Generated Works in Canadian Copyright Law. Social Science Research Network, Rochester (2015)

    Google Scholar 

  32. Rub, G.A.: Contracting around copyright: the uneasy case for unbundling of rights in creative works. Univ. Chicago Law Rev. 78, 257–279 (2011)

    Google Scholar 

  33. Netanel, N.: Copyright alienability restrictions and the enhancement of author autonomy: a normative evaluation. Rutgers L.J. 24, 347 (1992)

    Google Scholar 

  34. Elgammal, A., Liu, B., Elhoseiny, M., Mazzone, M.: CAN: Creative adversarial networks, generating “Art” by learning about styles and deviating from style norms (2017)

    Google Scholar 

  35. Srinivasan, R., Uchino, K.: Biases in generative Art—a causal look from the lens of art history (2020)

    Google Scholar 

Download references

Acknowledgments

Thank you to the curator, creator, engineer, and IP experts who participated in expert interviews. They do not mention specific real names according to their wishes. We do not mention specific real names according to their wishes.

Author information

Authors and Affiliations

  1. Kookmin University, Seoul, South Korea

    Kyungsun Kim & Jeongyun Heo

  2. Mokwon University, Daejeon, South Korea

    Sanghoon Jeong

Authors
  1. Kyungsun Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jeongyun Heo
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Sanghoon Jeong
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jeongyun Heo .

Editor information

Editors and Affiliations

  1. Siemens Corporation, Princeton, NJ, USA

    Helmut Degen

  2. Foundation for Research and Technology – Hellas (FORTH), Heraklion, Greece

    Stavroula Ntoa

Rights and permissions

Reprints and permissions

Copyright information

© 2021 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Kim, K., Heo, J., Jeong, S. (2021). Tool or Partner: The Designer’s Perception of an AI-Style Generating Service. In: Degen, H., Ntoa, S. (eds) Artificial Intelligence in HCI. HCII 2021. Lecture Notes in Computer Science(), vol 12797. Springer, Cham. https://doi.org/10.1007/978-3-030-77772-2_16

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-77772-2_16

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-77771-5

  • Online ISBN: 978-3-030-77772-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation