The World Health Organization (WHO) is releasing new guidance on the ethics and governance of large multi-modal models (LMMs) – a type of fast growing generative artificial intelligence (AI) technology with applications across healthcare.
The guidance outlines over 40 recommendations for consideration by governments, technology companies, and healthcare providers to ensure the appropriate use of LMMs to promote and protect the health of populations.
The new WHO guidance outlines five broad applications of LMMs for health:
- Diagnosis and clinical care, such as responding to patients’ written queries;
- Patient-guided use, such as for investigating symptoms and treatment;
- Clerical and administrative tasks, such as documenting and summarizing patient visits within electronic health records;
- Medical and nursing education, including providing trainees with simulated patient encounters, and;
- Scientific research and drug development, including to identify new compounds.
The guidance also details broader risks to health systems, such as accessibility and affordability of the best performing LMMs. LMMS can also encourage ‘automation bias’ by healthcare professionals and patients, whereby errors are overlooked that would otherwise have been identified or difficult choices are improperly delegated to a LMM. LMMs, like other forms of AI, are also vulnerable to cybersecurity risks that could endanger patient information or the trustworthiness of these algorithms and the provision of healthcare more broadly.
To create safe and effective LMMs, WHO underlines the need for engagement of various stakeholders: governments, technology companies, healthcare providers, patients, and civil society, in all stages of development and deployment of such technologies, including their oversight and regulation.
The new WHO guidance includes recommendations for governments, who have the primary responsibility to set standards for the development and deployment of LMMs, and their integration and use for public health and medical purposes.
