Kozinets, RobertAshman, Rachel2024-12-262024-12-262025-01-07978-0-9981331-8-84cd39e9f-e5dc-495e-b134-b2d4f76ac0d5https://hdl.handle.net/10125/109170Auto-netnography provides a nuanced understanding of human interactions with a generative visual AI platform, through an in-depth analysis of over 900 AI-generated cyborg adult entertainment images collected by a two-person netnographer team during a 15-month period of immersive engagement. After describing and developing the method and findings, including positioning the two researchers’ perspectives and queering the method, the research introduces, unpacks, and then inverts "abject visualization" to describe how AI images transgress and provoke. Likening concerns over humanity in the age of AI to LGBTQ threats to heteronormativity, this study challenges a range of dominant positions prevalent in the system sciences by emphasizing the need for research that delves deeply and longitudinally into the affective responses to technological systems and the complex intersection of human and artificial desires they inhabit.10Attribution-NonCommercial-NoDerivatives 4.0 InternationalNetnography in System Sciences Researchadult entertainment, artificial intelligence, desire, netnographyConference Paper10.24251/HICSS.2025.329