{"ID":2891612,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2507.16207","arxiv_id":"2507.16207","title":"A Human-Centered Approach to Identifying Promises, Risks, \u0026 Challenges of Text-to-Image Generative AI in Radiology","abstract":"As text-to-image generative models rapidly improve, AI researchers are making significant advances in developing domain-specific models capable of generating complex medical imagery from text prompts. Despite this, these technical advancements have overlooked whether and how medical professionals would benefit from and use text-to-image generative AI (GenAI) in practice. By developing domain-specific GenAI without involving stakeholders, we risk the potential of building models that are either not useful or even more harmful than helpful. In this paper, we adopt a human-centered approach to responsible model development by involving stakeholders in evaluating and reflecting on the promises, risks, and challenges of a novel text-to-CT Scan GenAI model. Through exploratory model prompting activities, we uncover the perspectives of medical students, radiology trainees, and radiologists on the role that text-to-CT Scan GenAI can play across medical education, training, and practice. This human-centered approach additionally enabled us to surface technical challenges and domain-specific risks of generating synthetic medical images. We conclude by reflecting on the implications of medical text-to-image GenAI.","short_abstract":"As text-to-image generative models rapidly improve, AI researchers are making significant advances in developing domain-specific models capable of generating complex medical imagery from text prompts. Despite this, these technical advancements have overlooked whether and how medical professionals would benefit from and...","url_abs":"https://arxiv.org/abs/2507.16207","url_pdf":"https://arxiv.org/pdf/2507.16207v2","authors":"[\"Katelyn Morrison\",\"Arpit Mathur\",\"Aidan Bradshaw\",\"Tom Wartmann\",\"Steven Lundi\",\"Afrooz Zandifar\",\"Weichang Dai\",\"Kayhan Batmanghelich\",\"Motahhare Eslami\",\"Adam Perer\"]","published":"2025-07-22T03:53:25Z","proceeding":"cs.HC","tasks":"[\"cs.HC\",\"cs.AI\",\"cs.CY\"]","methods":"[\"LoRA\"]","has_code":false}