Creative Work in Generative AI Narratives

Creative Work in Generative AI Narratives #

Baptiste Caramiaux, Kate Crawford, Vera Liao, Gonzalo Ramos, Jenny Williams (2025)

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Generative AI is transforming creative and artistic industries. The spread of generative AI in these sectors is sparking intense debate among academics, journalists, artists, policymakers and the public. But beyond its technical capabilities, how are the public discourses on AI in the arts shaping our understanding of creative work?

Narratives matter because AI is not neutral—it comes with stories, values, and perspectives that influence how we perceive artistic work. From science fiction to marketing slogans, tech journalism to policy discussions, AI narratives have long carried stereotypes and political agendas. For instance, dominant AI narratives are “polarized between notions of threat and myopic solutionism” [1] that we can find in many fictions (movies and books), mirroring simplified emotions and values of our society [2]. AI is often presented as something magical and outside of human control, allowing companies to deflect accountability for the full impacts of their systems [3]. And, AI conveys representations that are biased towards western white societies [4].

Little research has examined how these narratives play out in creative industries, which play a fundamental role in shaping culture.

To address this gap, we analyzed AI-related narratives in online media outlets and tech companies website. Our findings reveal that the dominant voices in this conversation are not artists and the narratives reinforce specific values and convey implicit narratives:

  • Automation over manual work. Creativity is a process that can be rationalised and streamlined, with the potential impact of a loss of autonomy and agency.

  • Efficiency over exploration. Standard metrics of productivity are equally valid in artistic spheres, with the potential impact of overlooking artists’ nuanced needs, less willingness among artists to explore and increased pressure to produce

  • Concept over execution. Dominance of a cultural hierarchy of the “big idea” over the “small scale tasks” needed to bring that idea to life, with teh potential impacts of less diversity in the outcomes, effect of style exhaustion, creative and cultural stagnation

  • Artifact over process. Value in the final deliverable, rather than the transformation, self-reflection, cultural positioning, and growth occurring throughout the creative process, with the potential impacts of new market standards.

  • Short-term over long-term skills. Time invested in deeply learning a craft does not add value to the final output, with the potential impacts of continued defunding of art programs, organizations, and institutions.

As AI becomes more embedded in artistic practices, it is crucial to critically examine these dominant discourses on creative work and discuss their concrete impacts. Other perspectives, more artist-centric, could be envisaged, which could enable us to rethink the design of AI technologies for creation.

References

  1. Chubb et al., 2024. AI & SOCIETY, https://doi.org/10.1007/s00146-022-01548-2
  2. Hermann, 2023. AI & SOCIETY, https://doi.org/10.1007/s00146-021-01299-6
  3. Campolo et al., 2020. Engaging Science, Tech, and Society https://doi.org/10.17351/ests2020.277
  4. Cave et al., 2020. Philosophy & Technology, https://doi.org/10.1007/s13347-020-00415-6

Cite this work

Caramiaux, B., Crawford, K., Liao, Q. V., Ramos, G., & Williams, J. (2025). Generative AI and Creative Work: Narratives, Values, and Impacts. arXiv preprint arXiv:2502.03940.

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