Responsible Use of AI: Ethical Considerations for Marginalized Groups

Abstract

This chapter addresses the ethical considerations essential for the responsible use of AI in healthcare, with a focus on marginalized populations such as ethnic minorities, people with disabilities, and underserved communities. It highlights key dimensions including data equity, algorithmic fairness, explainability, participatory design, and governance for accountability. The chapter emphasizes that AI systems must be trained on diverse and representative data to avoid perpetuating biases that disproportionately harm marginalized groups. Algorithmic fairness requires ongoing bias detection and mitigation, combined with transparent and interpretable AI models that build trust. Inclusive development through community participation ensures AI tools reflect the needs and values of those they serve. Strong governance frameworks, aligned with regulatory standards like the EU AI Act, are necessary to enforce accountability and protect vulnerable populations. When ethically implemented, AI can improve access, personalize care, and support proactive health management for underserved groups. However, the chapter cautions that these benefits depend on continuous commitment to equity, collaboration among stakeholders, and ongoing dialogue with affected communities to prevent exacerbating existing health disparities.

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