The study, "Designing Ethical AI Grief Support: A Value Sensitive Design Framework for Chronic Illness Care," was published in the August 2026 issue of The DATA BASE for Advances in Information Systems.

Led by Jasper Jia, assistant professor of business analytics and information systems at Quinnipiac University, the research examines how AI-powered chatbots can provide compassionate, personalized emotional support while protecting patients' privacy, autonomy and well-being.

"Chronic illness often brings a form of grief that extends far beyond a medical diagnosis," Jia said. "Patients and caregivers experience ongoing losses related to health, independence, relationships, careers and identity. AI has the potential to provide meaningful support, but only if it is designed with human values and ethical safeguards at its core."

Unlike grief following a single loss, chronic illness can create an ongoing and evolving grieving process. Using Alzheimer's disease as a case study, the researchers explored how AI-driven chatbots could assist patients and caregivers while addressing complex ethical considerations such as informed consent, privacy, trust, safety and appropriate human oversight.

To develop the framework, the research team reviewed 85 peer-reviewed studies, evaluated representative healthcare and grief-support chatbots, and validated their findings through interviews with geriatric psychiatrists, a grief counselor specializing in dementia care and digital health researchers.

The study integrates value sensitive design, an approach that incorporates human values throughout the technology design process, with the dual process model of grief. The resulting framework identifies seven human values that should guide AI-enabled grief-support systems: autonomy, calmness, informed consent, privacy, courtesy, human welfare and trust.

The researchers found that while many existing AI systems effectively help users adapt and move forward, they often provide less support for processing loss, anticipatory grief, sadness and changes in personal identity. Few systems comprehensively address all seven ethical values identified in the framework.

The study also introduces several new concepts for designing more responsive AI systems.

One, called value-oscillation-aware design, recognizes that individuals move between confronting loss and rebuilding their lives, causing their emotional and ethical priorities to change over time.

Another, adaptive autonomy, enables chatbot interactions to evolve as users' emotional needs and cognitive abilities change.

A third concept, dynamic privacy handoff, outlines a transparent and accountable process for gradually transferring certain information-management responsibilities from patients to caregivers as cognitive decline progresses.

The researchers emphasize that AI should complement — not replace — human care.

"AI can improve access to support and provide continuity between clinical visits, but it cannot replace the judgment, empathy and cultural understanding that healthcare professionals and caregivers bring," Jia said. "Situations involving crisis intervention, contested consent or complex clinical decisions require human expertise."

The research contributes to the growing fields of responsible AI, healthcare information systems and chronic illness care by translating ethical principles into practical design and governance recommendations. It also highlights Quinnipiac University's expanding scholarship at the intersection of artificial intelligence, healthcare and human well-being.

The study's co-authors include researchers from the University of South Florida, the University of Maryland and National Chengchi University in Taiwan.