Role and Use of Race in Artificial Intelligence and Machine Learning Models Related to Health

Area of Science:

• Health Informatics
• Artificial Intelligence
• Machine Learning

Background:

• The integration of race into health-related AI and ML models is increasingly debated.
• Existing frameworks for addressing these complex issues are insufficient.

Purpose of the Study:

• To provide a systematic analysis of race-related challenges in health AI/ML.
• To offer a guiding framework for stakeholders navigating these issues.

Main Methods:

• A crosscutting landscape analysis of race-related challenges.
• Structuring the analysis around the AI and ML life cycle.
• Developing "points to consider" for decision-making.

Main Results:

• Identified key race-related challenges across the AI/ML lifecycle.
• Proposed a structured approach to examine and resolve these challenges.
• Highlighted the need for a holistic framework.

Conclusions:

• A comprehensive framework is needed to guide responsible AI/ML development concerning race.
• Systematic examination of race-related issues throughout the AI/ML lifecycle is crucial.
• Stakeholders require actionable "points to consider" for ethical AI/ML implementation.