Visualizing cancer and survivorship with generative AI?-an exploration of breast, prostate, and pancreatic cancer imagery.

Purpose: Generative Artificial Intelligence (GAI) is transforming visual communication in the context of cancer survivorship, presenting opportunities to innovate advocacy while also posing risks for social representation. This study explores how GAI visualizes cancer and survivorship, focusing on its ability to reflect diverse experiences and its limitations.

Methods: We analyzed 262 images generated by Dall-E and Stable Diffusion using prompts related to breast, prostate, and pancreatic cancer. A mixed-methods approach examines how GAI utilizes cancer signifiers, visualizes the impact of cancer on individuals, and represents people with cancer.

Results: GAI frequently reproduces cancer tropes, such as prescriptive positivity, and fails to depict medical treatments or embodied experiences unless explicitly prompted. AI-generated images predominantly featured White, female subjects, particularly in breast cancer contexts, reflecting broader biases in public discourse. While GAI tools can produce inclusive visuals, achieving this requires users to have nuanced knowledge of cancer and survivorship, limiting accessibility for lay GAI users.

Conclusions: GAI can support cancer communication but risks perpetuating stereotypes and excluding less visible experiences of cancer. Our findings offer practical insights to support the design of advocacy materials and campaigns, particularly through improved prompt literacy and inclusive image generation strategies.

Implications for cancer survivors: Inclusive and respectful visual representation is critical for capturing the diverse realities of cancer survivorship, which in turn affects the wellbeing of cancer survivors and carers. Collaborative efforts among researchers, advocates, and GAI developers are necessary to improve datasets and foster accessible tools, ensuring that GAI supports rather than undermines cancer survivorship advocacy.