Artificial Intelligence (AI), now routinely being used to generate images, film, poetry, and literature that fascinate and delight human audiences, has re-invigorated discussion about how human artists, writers, and musicians themselves create. A common argument against AI artworks is that recombining materials from a given data set is merely generative activity and not creativity. Yet the assumption that human creativity necessarily entails individual originality has long been contested, and multiple alternative theories of creativity have been proposed. These include theories which pose that human creativity arises via novel reworkings of existing inspirational works. An early example of such alternative models of creativity is Harold Bloom’s 1973 ‘Anxiety of Influence’ theory, which outlays six ways poets can unknowingly misread and rewrite their precursors’ poems in creatively un/original ways. This article explores Bloom’s aging theory by asking neural.love to generate images in response to prompts based on The Anxiety of Influence (Bloom 1973), which we then asked ChatGPT to analyse for their symbolic meaning. We describe the interactions between ChatGPT, neural.love and ourselves chronologically. This structural decision best reflects how each actor in the network is affected by the previous events in the process. In doing so, we use inquiry methodology and further Human Machine Communication (HMC) (Guzman 2020) to probe the insights of current agents in the field of AI, whose own creativity or generativity is still in question.
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http://doi.org/10.54375/001/m4tpr8qvgx