Humane Intelligence in Geropsychiatric Care: Relational Artificial Intelligence, Clinical Wisdom, and the Moral Grid...

Area of Science:

• Geriatric Psychiatry
• Health Informatics
• Artificial Intelligence Ethics

Background:

• Artificial intelligence (AI) increasingly impacts older adult care identification, support, and referrals.
• Current AI governance often overlooks the experiences of older adults and caregivers, focusing on algorithms and infrastructure.
• A gap exists in patient-centered ethical frameworks for AI in geriatric care.

Purpose of the Study:

• Introduce the Humane Intelligence framework for designing, evaluating, and monitoring AI in older adult care.
• Establish a patient-centered, ethically attuned, relational approach to AI governance.
• Align AI development with geriatric psychiatry priorities and patient well-being.

Main Methods:

• The Humane Intelligence framework is built on four pillars: Relational Intelligence, Transparency with Care, Reciprocity and Consent, and Ethical Governance in Strategic Regions.
• Guidelines follow a signal-problem, take-action, verify-benefit-or-harm sequence for each pillar.
• Prioritizes geriatric psychiatry outcomes like function, distress, caregiver burden, utilization, equity, and harm.

Main Results:

• The framework recommends clinical-grade standards for patient-facing AI, including human-in-the-loop safeguards and postmarket monitoring.
• It establishes boundaries against fully automated clinical actions to protect patients.
• The proposed blueprint aligns with current AI priorities from major health organizations and regulatory bodies.

Conclusions:

• Humane Intelligence translates ethical principles into practical, testable routines for AI in older adult care.
• The framework aims to build trust among clinicians, healthcare systems, and leaders for AI procurement.
• The ultimate goal is to ensure AI augments, rather than displaces, compassionate care for older adults.