Hallucinated Pornography: AI, Synthetic Erotics, and the Reverse-Engineered Image of Desire

This article explores the evolving aesthetic of AI-generated erotic images, focusing on how hallucination, estrangement, and synthetic opacity replace the immersive realism and emotional transparency typical of traditional pornography. Through a comparative analysis of works by artists Arvida Byström and Jake Elwes, I argue that synthetic erotics do not aim for representation or immediate sensuality but operate through ambiguity, ambient affect, and resistance to capture. Arvida Byström’s In the Clouds mobilises AI-generated nude self-portraiture as a feminist strategy of opacity, pushing machinic codes of sexual legibility toward the point where they collapse into aesthetic estrangement. Jake Elwes’s Machine Learning Porn exposes the spectral traces of a neural network trained to classify and censor explicit content, rendering desire as glitch, residue, and machinic symptom. Both practices utilize hallucination as a method—reconfiguring the erotic as a speculative space of friction and delay. Drawing on feminist theory, semiotics, and posthuman media aesthetics, this paper positions synthetic erotics as a critical site for intervention in the algorithmic governance of desire, recognition, and embodiment.