Focus Group on Artificial Intelligence for Health

TL;DR

This paper discusses the establishment of the ITU-WHO Focus Group on AI for Health, aiming to create standards and benchmarks to evaluate AI solutions in healthcare, enhancing trust and global application.

Contribution

It introduces the FG-AI4H initiative, which will develop a standardized assessment framework and open benchmarks for AI in health.

Findings

Development of a standardized evaluation framework for AI in health

Creation of open benchmarks for AI-based diagnosis and treatment

Promotion of international collaboration and trust in AI health solutions

Abstract

Artificial Intelligence (AI) - the phenomenon of machines being able to solve problems that require human intelligence - has in the past decade seen an enormous rise of interest due to significant advances in effectiveness and use. The health sector, one of the most important sectors for societies and economies worldwide, is particularly interesting for AI applications, given the ongoing digitalisation of all types of health information. The potential for AI assistance in the health domain is immense, because AI can support medical decision making at reduced costs, everywhere. However, due to the complexity of AI algorithms, it is difficult to distinguish good from bad AI-based solutions and to understand their strengths and weaknesses, which is crucial for clarifying responsibilities and for building trust. For this reason, the International Telecommunication Union (ITU) has established a new Focus Group on "Artificial Intelligence for Health" (FG-AI4H) in partnership with the World Health Organization (WHO). Health and care services are usually the responsibility of a government - even when provided through private insurance systems - and thus under the responsibility of WHO/ITU member states. FG-AI4H will identify opportunities for international standardization, which will foster the application of AI to health issues on a global scale. In particular, it will establish a standardized assessment framework with open benchmarks for the evaluation of AI-based methods for health, such as AI-based diagnosis, triage or treatment decisions.