Large multi-modal models (LMMs) are a fast-growing type of generative AI that can take in different types of data, such as text, images and video, and produce varied responses. The World Health Organization (WHO) has issued guidance on their use in health, with over 40 recommendations for governments, technology companies and healthcare providers. The guidance covers five broad uses: diagnosis and clinical care, patient-guided use such as checking symptoms, administrative tasks, medical and nursing education, and scientific research and drug development.
The WHO warns that LMMs can produce false, inaccurate, biased or incomplete answers, which could harm people making health decisions. They may be trained on poor-quality or biased data, including by race, ethnicity, ancestry, sex, gender identity or age. Because most of the data and research used to train them comes from high-income countries, their answers may also be biased towards a high-income perspective. In addition, health professionals may place too much trust in these tools and overlook their errors, a problem known as automation bias.
Among its recommendations, the WHO calls on governments to pass laws and regulations to ensure LMMs meet ethical and human rights standards, assign regulatory agencies to assess and approve them, and require independent audits and impact assessments after they are released. Developers should involve diverse stakeholders, including patients and health professionals, from the early stages of development, and design LMMs to carry out well-defined tasks accurately and reliably.
Learn more here: https://www.who.int/publications/i/item/9789240084759
Reference:
World Health Organization. (2024). Ethics and governance of artificial intelligence for health: Guidance on large multi-modal models.