Creative AI Futures: Theory and practice

Conference theme: Use of new and emerging technologies in Digital Art, Data, Scientific and Creative Visualisation, Digitally Enhanced Reality and Everyware, 2D and 3D Imaging, Display and Printing, Mobile Applications, Museums and Collections, Music, Performing arts, and Technologies, Open Source and Technologies, Preservation of Digital Visual Culture, Virtual Cultural Heritage, Ethical Issues, Historical Issues, Digital Culture, Artificial Intelligence, NFTs

Conference date: 4–8 July 2022

Keywords: AI, Artistic collaboration, Back-end environments, Co-creation, Creative AI Lab, Creativity, Critical theory, Future of art

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Abstract

This paper analyses creative activity enabled by ML and recognised under the banner of ‘AI art’ or ‘creative AI’. The theoretical discussion is anchored in the critical reflection on the activities in which the authors have been involved as part of the Creative AI Lab, which is a collaboration between the R&D Platform at Serpentine Galleries and King’s College London’s Department of Digital Humanities. The paper proposes a 5C model (‘Creative – Critical – Constructive – Collaborative – Computational’), which brings together technical research and conceptual inquiry into AI art, while shifting focus from artefacts to their wider contexts, processes and infrastructures. It also outlines directions for future research.

Content

Author and article information

Contributors

Mercedes Bunz

Eva Jäger

Alasdair Milne

Joanna Zylinska

Conference

Publication date: July 2022

Publication date (Print): July 2022

Pages: 90-93

Affiliations

[0001]King’s College London

Department of Digital

Humanities

Strand

London WC2R 2LS, UK

[0002]Serpentine

Kensington Gardens,

London

W2 3XA

UK

Article

DOI: 10.14236/ewic/EVA2022.20

SO-VID: 9600b307-43df-480c-86bf-23402cee931c

License:

This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

Conference name: Proceedings of EVA London 2022

Conference acronym: EVA 2022

Conference number:

Conference location: London

Conference date: 4–8 July 2022

Conference sponsor: Electronic Workshops in Computing (eWiC)

History

Product

1477-9358 BCS Learning & Development

Self URI (article page): https://www.scienceopen.com/hosted-document?doi=10.14236/ewic/EVA2022.20

Self URI (journal page): https://ewic.bcs.org/

REFERENCES

R. Amaro (2022) Machine Learning, Sociogeny, and the Substance of Race. Sternberg Press, Berlin.
G. Arrigoni (2016) Epistemologies of prototyping: knowing in artistic research, Digital Creativity, 27(2), pp. 99–112.
R. Ascott (2005) Distance Makes the Art Grow Further: Distributed Authorship and Telematic Textuality in La Plissure du Texte. In A. Chandler and N. Neumark (eds.). At a distance: precursors to art and activism on the Internet, The MIT Press (Leonardo), Cambridge, MA.
S. Audry (2021) Art in the Age of Machine Learning. The MIT Press, Cambridge, MA.
J. Brouwer (ed.) (2005) Art & D: Research and Development in Art. V2_NAi Publ, Rotterdam.
M. Bunz (2019) The calculation of meaning: on the misunderstanding of new artificial intelligence as culture. In Culture, Theory and Critique, 60(3–4), pp. 264–278.
R. Crease (1993) The Play of Nature: Experimentation as Performance. Indiana University Press, Bloomington.
M.D. DubberF. Pasquale and S. Das (eds.) (2020) The Oxford Handbook of Ethics of AI. Oxford University Press, Oxford.
M.B. Fazi (2020) Beyond Human: Deep Learning, Explainability and Representation. In Theory, Culture & Society 38(7–8), pp. 55–77.
V. Ivanova and B. Vickers (2020) Research & Development at the Art Institution, Serpentine Galleries. https://www.serpentinegalleries.org/artand-ideas/research-development-at-the-art-institution/ (retrieved 13 September 2021).
N. Khan (forthcoming) Art in the Age of Artificial Intelligence. Lund Humphries, London.
L. Manovich (2018) AI Aesthetics. Strelka Press, Moscow.
L. Parisi (2019) The alien subject of AI. In Subjectivity, 12(1), pp. 27–48.
A. Ploinet al(2022) How Machine Learning Is Changing Artistic Work. Oxford Internet Institute.
Serpentine R&D (2020) Creative AI Lab. https://www.serpentinegalleries.org/whatson/creative-ai-lab/ (retrieved 2 March 2022).
B. Spatz (2020) Making a Laboratory: Dynamic Configurations with Transversal Video. Punctum Books, Santa Barbara.
T. Stejskalová (2021) Online Weak and Poor Images: On Contemporary Feminist Visual Politics. In Tomas Dvořák and Jussi Parikka, eds. Photography Off the Scale: Technologies and Theories of the Mass Image. Edinburgh University Press, Edinburgh.
L. Weatherby, and B. Justie (2022) Indexical AI. In Critical Inquiry, 48(2), pp.381-415.
S. Vallor (2021) Mobilising the intellectual resources of the arts and humanities, Ada Lovelace Institute. https://www.adalovelaceinstitute.org/blog/mobilising -intellectual-resources-arts-humanities/ (retrieved 20 July 2021).
M. Zeilinger (2021) Tactical Entanglements: AI Art, Creative Agency, and the Limits of Intellectual Property. Meson Press.
J. Zylinska (2020) AI Art: Machine Visions and Warped Dreams. Open Humanities Press.

Comments

Comment on this article

[1] R. Amaro (2022) Machine Learning, Sociogeny, and the Substance of Race. Sternberg Press, Berlin.

[2] G. Arrigoni (2016) Epistemologies of prototyping: knowing in artistic research, Digital Creativity, 27(2), pp. 99–112.

[3] R. Ascott (2005) Distance Makes the Art Grow Further: Distributed Authorship and Telematic Textuality in La Plissure du Texte. In A. Chandler and N. Neumark (eds.). At a distance: precursors to art and activism on the Internet, The MIT Press (Leonardo), Cambridge, MA.

[4] S. Audry (2021) Art in the Age of Machine Learning. The MIT Press, Cambridge, MA.

[5] J. Brouwer (ed.) (2005) Art & D: Research and Development in Art. V2_NAi Publ, Rotterdam.

[6] M. Bunz (2019) The calculation of meaning: on the misunderstanding of new artificial intelligence as culture. In Culture, Theory and Critique, 60(3–4), pp. 264–278.

[7] R. Crease (1993) The Play of Nature: Experimentation as Performance. Indiana University Press, Bloomington.

[8] M.D. DubberF. Pasquale and S. Das (eds.) (2020) The Oxford Handbook of Ethics of AI. Oxford University Press, Oxford.

[9] M.B. Fazi (2020) Beyond Human: Deep Learning, Explainability and Representation. In Theory, Culture & Society 38(7–8), pp. 55–77.

[10] V. Ivanova and B. Vickers (2020) Research & Development at the Art Institution, Serpentine Galleries. https://www.serpentinegalleries.org/artand-ideas/research-development-at-the-art-institution/ (retrieved 13 September 2021).

[11] N. Khan (forthcoming) Art in the Age of Artificial Intelligence. Lund Humphries, London.

[12] L. Manovich (2018) AI Aesthetics. Strelka Press, Moscow.

[13] L. Parisi (2019) The alien subject of AI. In Subjectivity, 12(1), pp. 27–48.

[14] A. Ploinet al(2022) How Machine Learning Is Changing Artistic Work. Oxford Internet Institute.

[15] Serpentine R&D (2020) Creative AI Lab. https://www.serpentinegalleries.org/whatson/creative-ai-lab/ (retrieved 2 March 2022).

[16] B. Spatz (2020) Making a Laboratory: Dynamic Configurations with Transversal Video. Punctum Books, Santa Barbara.

[17] T. Stejskalová (2021) Online Weak and Poor Images: On Contemporary Feminist Visual Politics. In Tomas Dvořák and Jussi Parikka, eds. Photography Off the Scale: Technologies and Theories of the Mass Image. Edinburgh University Press, Edinburgh.

[18] L. Weatherby, and B. Justie (2022) Indexical AI. In Critical Inquiry, 48(2), pp.381-415.

[19] S. Vallor (2021) Mobilising the intellectual resources of the arts and humanities, Ada Lovelace Institute. https://www.adalovelaceinstitute.org/blog/mobilising -intellectual-resources-arts-humanities/ (retrieved 20 July 2021).

[20] M. Zeilinger (2021) Tactical Entanglements: AI Art, Creative Agency, and the Limits of Intellectual Property. Meson Press.

[21] J. Zylinska (2020) AI Art: Machine Visions and Warped Dreams. Open Humanities Press.

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