Toward Ethical Governance of Artificial Intelligence (AI)-Enabled Cognitive Monitoring in Aging Populations

TL;DR

This paper discusses ethical challenges in using AI for cognitive monitoring in older adults and suggests governance frameworks to ensure responsible innovation.

Contribution

The paper introduces a structured perspective on ethical governance for AI-enabled cognitive monitoring in aging populations.

Findings

AI tools in geriatric care raise ethical issues like model opacity and clinical responsibility.

Dynamic consent and equitable algorithm performance are critical for ethical AI deployment.

Governance frameworks should prioritize accountability and patient autonomy in AI applications.

Abstract

AI-enabled cognitive monitoring is increasingly being integrated into geriatric care, enabling continuous assessment of behavioral and cognitive patterns that can detect early cognitive changes. This editorial examines key ethical and governance challenges associated with these tools, including the epistemic opacity of machine-learning models, distributed clinical responsibility, dynamic consent for passive data collection, and the equitable performance of algorithms across diverse populations. It argues that addressing these challenges requires governance frameworks that clarify accountability, ensure interpretability, and protect patient autonomy while supporting clinical decision-making. By discussing these considerations, this piece provides a structured perspective on responsible innovation in AI-supported cognitive monitoring, advancing discourse on ethical integration of emerging digital tools in aging populations.