Ownership and Creativity in Generative Models

Omri, Avrahami,; Tamir, Bar

doi:10.48550/arxiv.2112.01516

Cited by 3 publications

(1 citation statement)

References 24 publications

(25 reference statements)

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“…But it is possible to view this as a form of high-tech plagiarism, where the AI repackages intellectual property without consent or compensation to the original creators. There can also be concerns about the potential of generative AI to displace human artists, writers, and coders by cheaply replicating their work (Avrahami, O., & Tamir, B., 2021). This article focuses specifically on the argument that AI is not creative because it is merely recombining previous artwork.…”

Section: Introductionmentioning

confidence: 99%

Are Generative AIs like Midjourney and Sora creative? The “Generative AI Mary’s room” thought experiment.

Bellini-Leite

2024

Preprint

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This article examines the debate of whether generative AI systems like Midjourney and Sora can be considered truly creative or are merely remixing existing data. It reviews Finke, Ward, and Smith's creative cognition approach which proposed constraints on human creativity. A new thought experiment, the "Generative AI Mary's Room", is proposed to explore whether a person with comprehensive artistic knowledge but no real-world experience could produce original creative works. The argument is that one who believes generative AI is not creative because it works based solely on previous artistic data, should not believe that Mary would be creative either, otherwise, they are inferring mysterious properties to the human mind.

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Section: Introductionmentioning

confidence: 99%

Are Generative AIs like Midjourney and Sora creative? The “Generative AI Mary’s room” thought experiment.

Bellini-Leite

2024

Preprint

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Not “what”, but “where is creativity?”: towards a relational-materialist approach to generative AI

Celis Bueno,

Chow,

Popowicz

2024

AI & Soc

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The recent emergence of generative AI software as viable tools for use in the cultural and creative industries has sparked debates about the potential for “creativity” to be automated and “augmented” by algorithmic machines. Such discussions, however, begin from an ontological position, attempting to define creativity by either falling prey to universalism (i.e. “creativity is X”) or reductionism (i.e. “only humans can be truly creative” or “human creativity will be fully replaced by creative machines”). Furthermore, such an approach evades addressing the real and material impacts of AI on creative labour in these industries. This article thus offers more expansive methodological and conceptual approaches to the recent hype on generative AI. By combining (Csikszentmihalyi, The systems model of creativity, Springer, Dordrecht, 2014) systems view of creativity, in which we emphasise the shift from “what” to “where” is creativity, with (Lievrouw, Media technologies, The MIT Press, 2014) relational-materialist theory of “mediation”, we argue that the study of “creativity” in the context of generative AI must be attentive to the interactions between technologies, practices, and social arrangements. When exploring the relational space between these elements, three core concepts become pertinent: creative labour, automation, and distributed agency. Critiquing “creativity” through these conceptual lenses allows us to re-situate the use of generative AI within discourses of labour in post-industrial capitalism and brings us to a conceptualisation of creativity that privileges neither the human user nor machine algorithm but instead emphasises a relational and distributed form of agency.

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An ethical framework for trustworthy Neural Rendering applied in cultural heritage and creative industries

Stacchio,

Balloni,

Gorgoglione

et al. 2024

Front. Comput. Sci.

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Artificial Intelligence (AI) has revolutionized various sectors, including Cultural Heritage (CH) and Creative Industries (CI), defining novel opportunities and challenges in preserving tangible and intangible human productions. In such a context, Neural Rendering (NR) paradigms play the pivotal role of 3D reconstructing objects or scenes by optimizing images depicting them. However, there is a lack of work examining the ethical concerns associated with its usage. Those are particularly relevant in scenarios where NR is applied to items protected by intellectual property rights, UNESCO-recognized heritage sites, or items critical for data-driven decisions. For this, we here outline the main ethical findings in this area and place them in a novel framework to guide stakeholders and developers through principles and risks associated with the use of NR in CH and CI. Such a framework examines AI's ethical principles, connected to NR, CH, and CI, supporting the definition of novel ethical guidelines.

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Ownership and Creativity in Generative Models

Cited by 3 publications

References 24 publications

Are Generative AIs like Midjourney and Sora creative? The “Generative AI Mary’s room” thought experiment.

Are Generative AIs like Midjourney and Sora creative? The “Generative AI Mary’s room” thought experiment.

Not “what”, but “where is creativity?”: towards a relational-materialist approach to generative AI

An ethical framework for trustworthy Neural Rendering applied in cultural heritage and creative industries

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