[2603.19527] Depictions of Depression in Generative AI Video Models: A Preliminary Study of OpenAI's Sora 2

Computer Science > Computers and Society arXiv:2603.19527 (cs) [Submitted on 19 Mar 2026] Title:Depictions of Depression in Generative AI Video Models: A Preliminary Study of OpenAI's Sora 2 Authors:Matthew Flathers, Griffin Smith, Julian Herpertz, Zhitong Zhou, John Torous View a PDF of the paper titled Depictions of Depression in Generative AI Video Models: A Preliminary Study of OpenAI's Sora 2, by Matthew Flathers and 4 other authors View PDF HTML (experimental) Abstract:Generative video models are increasingly capable of producing complex depictions of mental health experiences, yet little is known about how these systems represent conditions like depression. This study characterizes how OpenAI's Sora 2 generative video model depicts depression and examines whether depictions differ between the consumer App and developer API access points. We generated 100 videos using the single-word prompt "Depression" across two access points: the consumer App (n=50) and developer API (n=50). Two trained coders independently coded narrative structure, visual environments, objects, figure demographics, and figure states. Computational features across visual aesthetics, audio, semantic content, and temporal dynamics were extracted and compared between modalities. App-generated videos exhibited a pronounced recovery bias: 78% (39/50) featured narrative arcs progressing from depressive states toward resolution, compared with 14% (7/50) of API outputs. App videos brightened over time (s...