PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
August 28, 20246 citationsOpen Access

Visual Artists, Technological Shock, and Generative AI

View Full Paper
CJCaroline A. JonesHGHuma GuptaMRMatthew Ritchie

Key Points

Key points are not available for this paper at this time.

Abstract

The impact of generative AI (GenAI) programs on visual art is comparable to earlier historical moments of technological shock, when literary and visual artists grappled with unprecedented reproductive tools such as the printing press, photography, and cinema. Metabolizing the shock of those once radical inventions eventually yielded great bursts of artistic innovation. Yet, unlike those prior revolutions, the current one presents a deeper threat to artistic innovation by smoothing its source material into endless variants of seamless pastiche. By definition, the corpus of imagery currently being scraped for training already exists—it is overwhelmingly photographic, representational, and Western-hemispheric. As a result, algorithmic aesthetics visually echo the hundred-year-old art movement of Surrealism at its most banal. GenAI thus jeopardizes a singular function of visual artists in contemporary culture: to continuously innovate never-before-seen forms, artistic movements, styles, cognitive concepts, and theories of representation. Moreover, GenAI is a cultural technology. Since generative programs make secondary and tertiary materials by inputting their own outputs, they both intensify the bias found in the corpus and bury ever deeper the historical sources of that bias, neglecting significant future markets and constituencies who could be welcomed in to build richer archives with better metadata. We argue that more inclusive and transparent training sets, permeable models, and significant investment in what we call "public intelligence" can better shape the potential of GenAI tools, confronting technological shock in ways more likely to encourage rather than dampen artistic innovation for the public good.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Jones et al. (2024) studied this question.

synapsesocial.com/papers/68e5a94ab6db643587542e0ahttps://doi.org/10.21428/e4baedd9.b4f754fd
Ask AI
Helpful
Bookmark
Share
View Full Paper

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Generative AI and Creative Learning: Concerns, Opportunities, and Choices2024 · 48 citations
  2. 2LAION-5B: An open large-scale dataset for training next generation image-text models2022 · 1,042 citations
  3. 3Artificial Eloquence: Style, Citation, and the Right to One’s Own Voice in the Age of AI, or, A Drama in Three Acts2024 · 2 citations
  4. 4Data Action: Using Data for Public Good2021 · 40 citations
  5. 5The Cloud Is Material: On the Environmental Impacts of Computation and Data Storage2022 · 119 citations