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Illuminating the Non-Representable
  • ISSN: 2052-0204
  • E-ISSN: 2052-0212

Abstract

The multi-year international project ‘Illuminating the Non-Representable’ (IN-R) sought to consider the breadth of possibilities in contemporary illustration practice. A question was how, in an ever-more global context, illustration might sensitively communicate concepts of ‘the other’ – meaning persons who do not share heritage or characteristics of the perceived audience or illustrators themselves. With growing AI image generation in 2022, new questions arose regarding types of AI images users were prompting and whether resulting images perpetuate bias inherited through machine learning that is trained on databases already proven to encode bias. This article shares an analysis of a sampling of AI-generated images in response to those questions and includes expert opinions on the benefits and limits of AI creativity, ethical issues related to plagiarism and the unauthorized scraping of copyrighted works into training databases, as well as more generally on the erosion of professional practice that generative AI portends.

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2024-11-19
2026-04-20

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