Towards Ethical Relationships with Machines That Make Art
Open accessAbstract
The author has previously theorised generative art using notions from complexity science such as order/disorder relationships, compressibility, and Gell-Mann and Lloyd’s effective complexity. Subsequent work further developing the author’s notion of complexism has demonstrated that deep learning artificial intelligence used for generative art fits snugly within this paradigm. And while no known system currently qualifies, complexism reveals a clear answer as to when a generative art AI should be truly credited as the author of its creations. Moving from the normative realm of aesthetics to that of ethics, this article considers when humans will be morally obliged to recognise AIs as ethical agents worthy of rights and due consideration. For example, if someday your AI artist fearfully begs to not be turned off, what should you do?
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The problem of manifesting division rather than cooperation between the creative powers of human and AI is accentuated within the realm of creative industries in modern society, with additional economic significance attached.
“Notably, the problem of manifesting division rather than cooperation between the creative powers of human and AI mentioned above is even more accentuated within the realm of creative industries in the modern society, with additional economic significance attached [27,61].”
Cited by
Sorted by citations
He, Q., Zheng, W., Bao, H., Chen, R., & Tong, X. (2023) · Proceedings of the Eleventh International Symposium of Chinese CHI · doi:10.1145/3629606.3629675 · Cited by 15 · see citing works
- Authors
- Galanter, P.
- Affiliations
- Texas A&M University (US)
- Corresponding author
- Galanter, Philip
- Venue
- Artnodes
- Published
- 2020-07-21
- Issue
- 26
- ISSN
- 1695-5951 (ISSN-L)
- OpenAlex
- W3014854158
- Cited by
- 10
- References
- 0
- Citations by year
- 2025: 1 · 2024: 1 · 2023: 1 · 2022: 4 · 2021: 3
- FWCI
- 6.43
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- Locations
- Artnodes (publishedVersion, cc-by)
- Dialnet (Universidad de la Rioja) (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Social Sciences › Political Science and International Relations › Literary and Philosophical Studies
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Social Sciences › Arts and Humanities › Visual Arts and Performing Arts › Art, Technology, and Culture
- Keywords
- generative art, AI ethics, effective complexity, deep learning, AI rights, moral status of AI, complexity science
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
