This report, published by the European Parliamentary Research Service’s Scientific Foresight Unit (STOA), looks at how AI is being used in healthcare and the risks it brings. It identifies seven main risks: patient harm due to AI errors, misuse of medical AI tools, bias and the perpetuation of existing inequities, lack of transparency, privacy and security issues, gaps in accountability, and obstacles to implementation in real-world healthcare.
On bias, the report explains that the most common cause of unfairness in medical AI is bias in the data used to train it. Some groups are underrepresented in medical datasets; for example, skin cancer datasets mostly contain fair-skinned patients. Data can also carry existing human biases, such as the dismissal of women’s pain or doctors taking Black patients’ pain less seriously. Among the examples given is a chest X-ray algorithm that most often missed disease in young female patients, Black patients and patients on public insurance for people with low incomes.
To address these risks, the report proposes seven policy options. These include extending AI regulation to cover healthcare-specific risks, involving all stakeholders throughout the development of medical AI, creating an “AI passport” for transparency and traceability, defining accountability, educating health professionals and the public, promoting further research, and reducing the divide in medical AI across Europe.
Learn more about this report here: https://doi.org/10.2861/568473
Reference:
Lekadir, K., Quaglio, G., Tselioudis Garmendia, A., & Gallin, C. (2022). Artificial intelligence in healthcare: Applications, risks, and ethical and societal impacts (PE 729.512). European Parliamentary Research Service, Scientific Foresight Unit (STOA).