Jewish Ethnic Subgroups and Artificial Intelligence Clinical Decision Support

Area of Science:

• Medical Ethics
• Health Equity
• Artificial Intelligence

Background:

• Artificial intelligence (AI) is increasingly used in clinical decision-making.
• Algorithmic bias in AI can exacerbate health disparities for minority groups.
• The impact of AI bias on Jewish communities is largely unexamined.

Purpose of the Study:

• To explore the underexamined risks of AI in clinical decision-making for Jewish populations.
• To investigate potential algorithmic biases affecting healthcare for diverse Jewish subgroups.
• To summarize the unique clinical susceptibilities within Jewish ethnicities.

Main Methods:

• A narrative review of scientific and gray literature was conducted.
• The review focused on identifying shared and distinct clinical susceptibilities.
• Analysis considered Jewish people as an ethno-religious group with distinct ethnicities.

Main Results:

• Jewish people comprise multiple ethnicities (Ashkenazi, Sephardi, Mizrahi), each with specific health profiles.
• Commonly perceived as a single religious group, their ethnic diversity influences health risks.
• Existing AI bias research has not addressed these specific ethnic subgroups.

Conclusions:

• AI in healthcare requires careful consideration of diverse ethnic populations, including Jewish subgroups.
• Further research is needed to mitigate AI bias and ensure equitable healthcare for all Jewish ethnicities.
• Understanding ethnic-specific health risks is crucial for developing unbiased AI clinical tools.