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.