AI and the social construction of creativity

Paul Atkinson · Richie Barker

66 citations0/0 files storedConvergence The International Journal of Research into New Media Technologies

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Art, Technology, and Culture Creativity in Education and Neuroscience Cybernetics and Technology in Society

Abstract

Artificial Intelligence (AI) encroaches on new terrains of human activity by dint of its efficacy and an expanding ability to autonomously incorporate information from many disciplines and sources. In this paper, we focus specifically on how AI affects the communicative practices associated with creativity. AI has the capacity to reshape discipline and taste communities by providing new content that competes with human production and by mediating between human activity and information sources. To frame these issues, we turn to the influential systems model of creativity devised by Mihaly Csikszentmihalyi (1996) , which Csikszentmihalyi and Daniel Gruner (2018) recently extended to incorporate AI, redubbing it Creativity 4.0. The model assesses how AI affects the social structure of creative practice without overly accentuating the similarity between humans and AI, or questioning whether computational devices will replace creative jobs. The paper examines Gruner and Csikszentmihalyi’s revised systems model, arguing that it does not sufficiently take into account the variety of ways that AI can be incorporated into creative practice. Prompted by a theoretical reflection on the nature of the model and the emerging features of AI, we propose a new version of the model that highlights how embedded AIs play a key role in filtering and gatekeeping, as well as the importance of generative systems in informing creative practice. We propose that any discussion of AI and the future of creative practice should look at where and how AI supported technologies are used. We examine how AI can reduce and shape the qualitative diversity of sources of inspiration drawn into the creative process, with the associated technological biases, as well as provide an emergent platform for the development of novel ideas.

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References

1996The Rules of Art 2014The Relevance of Algorithms 2007Explaining Creativity: The Science of Human Innovation 1994The Bridge from Text to Mind: Adapting Reader-Response Theory to Consumer Research 2009What is generative art?

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