Rethinking Health Recommender Systems for Active Aging: An Autonomy-Based Ethical Analysis

Area of Science:

• Artificial Intelligence in Healthcare
• Gerontology
• Bioethics

Background:

• Health Recommender Systems (HRS) leverage AI to promote healthy lifestyles and treatment adherence.
• Active aging (AA) is a key area for HRS application.
• Current HRS for AA face significant, yet under-explored, ethical challenges.

Purpose of the Study:

• To re-evaluate Health Recommender Systems for active aging through an autonomy-based ethical lens.
• To identify and analyze ethical risks associated with HRS in aging populations.
• To propose an ethical framework for developing autonomy-enabling HRS for AA.

Main Methods:

• Review of technical aspects of HRS to identify ethical risks.
• Ethical analysis focused on the core AI ethics principle of autonomy.
• Categorization and proposed mitigation strategies for identified ethical risks.
• Elaboration on autonomy-related ethical theories.

Main Results:

• Technical features of HRS can pose ethical risks to the well-being of aging individuals.
• A clear categorization of risks and potential mitigation actions were developed.
• An autonomy-based ethical framework was proposed.

Conclusions:

• Rethinking HRS for active aging through an autonomy-centric approach is crucial.
• The proposed framework can guide the development of ethical and autonomy-enabling HRS.
• Prioritizing autonomy in HRS design is essential for supporting healthy and independent aging.