Our Mission
AIHCHA develops and studies human-centered AI that supports older adults’ physical, mental, and social well-being while respecting dignity, autonomy, culture, relationships, and lived experience. Grounded in humanistic inquiry and community partnership, we build and evaluate technology that strengthens human care rather than standing in for it.
About Us
By 2035, China is projected to have more than 400 million people aged 60 and above, with adults aged 65 and above exceeding 20% of the population. Chronic disease, cognitive decline, and social isolation are rising while caregivers grow scarce. AI is widely proposed as a way to augment elder care, yet most such systems are designed by and for younger populations and rarely account for older adults’ cultural expectations, social relationships, or lived experience of aging.
The AI for Human-Centered Healthy Aging (AIHCHA) Lab asks how AI can genuinely serve the needs, values, and experiences of older adults. Because aging is lived through meaning, memory, dignity, and relationship, the lab treats AI as an object of humanistic reflection, and puts questions of meaning, dignity, and care at the center of how AI-assisted elder care is designed, implemented, and evaluated. Its aim is technology that strengthens human connection and community-based care rather than substituting for it. The lab brings together faculty and students from anthropology, global health, computer science, philosophy, and the arts at Duke Kunshan University and Duke University, and works with community elder care centers and urban resettlement communities in Suzhou and Kunshan. It is open to all DKU faculty and students. The lab is generously funded by the Humanities Research Center at Duke Kunshan University.
Three Dimensions of Well-being
The lab’s work is organized around three dimensions of healthy aging, and every research program addresses at least one of them.
Physical Well-being Frailty · Chronic disease · Mobility · Rehabilitation
Mental Well-being Depression · Anxiety · Cognitive health · Emotional well-being
Social Well-being Loneliness · Intergenerational connection · Community participation
Approach
The lab studies community-based AI applications that engage older adults in their everyday environments, across the three dimensions above. Its framework combines humanistic and ethnographic inquiry, community-based participatory research, and human-computer interaction to co-design, pilot, and evaluate AI-assisted interventions. It builds on the “social technology” model from Harvard Medical School, which integrates social science and engineering across planning, innovation, testing, and outcome assessment, and extends that model by foregrounding culture, narrative, meaning, and creative expression. Over three years, the lab plans to move from first-year pilots and community partnerships to multi-site studies and external funding, and toward a transferable framework for human-centered AI in elder care.
Research Programs
The lab runs three research programs. The first two generate empirical and qualitative evidence, and the third draws on both to produce policy and ethical analysis.
I. AI-Assisted Expressive Arts Therapy
A pilot study at community elder care centers in Kunshan, examining technology acceptance, user experience, and preliminary effects on mental health and social engagement.
Anticipated Outcomes
– Technology acceptance and user experience findings from participating older adults and care staff.
– Preliminary indications of effect on mood, engagement, and social interaction, at a level sufficient to size a larger study.
– One conference paper or journal submission in human-computer interaction or digital health.
– A set of design guidelines for AI-assisted creative activity with older adults, shared with the other two programs.
II. Ethnographies of Aging and Care
A qualitative study of aging in Kunshan’s urban resettlement communities, using fieldwork and in-depth interviews to inform the design of AI interventions and to contribute to the anthropology of aging and care in China.
Anticipated Outcomes
– An account of how older residents understand aging, care, dignity, and technology in everyday life.
– Design implications delivered to Program I, drawn from what the fieldwork shows about daily routine, family roles, and expectations of care.
– One journal article submitted to an anthropology or aging studies venue.
– Interview and observation material, cleared with participants, for use in the HUM Space exhibition.
III. Ethics and Policy
A policy brief on AI-assisted elder care services in Suzhou for municipal health authorities, drawing on the first two programs, alongside continuing philosophical work on dignity, consent, and the ethical limits of automated care.
Anticipated Outcomes
– A working account of consent, dignity, and the limits of automated care in community elder care settings, grounded in the first two programs.
– One paper in applied ethics or health policy.
– Recommendations feeding the lab’s Year 2 applications for external funding.
Public Programs and Student Research
HUM Space Exhibition
Co-designed with student curators, the exhibition uses digital media, moving image, and installation to reinterpret findings from all three programs and make the human stakes of AI in elder care vivid to a broad public.
Interdisciplinary Workshop
Held about six months into the funding year, bringing DKU faculty and students together with external scholars and practitioners working on AI, aging, and humanistic inquiry. The format may combine invited talks, position papers, demonstrations, a keynote, and panels, including a student panel.
Student Research
Students are part of the lab’s core research capacity. Graduate and undergraduate researchers work across all three programs, taking part in fieldwork, interviews, data analysis, and the design of the HUM Space exhibition.
The lab also funds student-led, faculty-guided signature work on human-centered healthy aging where a strong humanistic fit exists. Students bring their own questions to the lab and develop them under faculty supervision. Proposals are welcome from any discipline, and the lab is glad to advise on framing before a formal proposal is written.
Past Achievements
This section establishes the track record behind the lab.
Grants and funding
– Seed funding from the Humanities Research Center at Duke Kunshan University for the AIHCHA Lab.
– Research grants totaling over $10 million USD on which Prof. Yan is Principal Investigator or Co-Investigator.
Publications
– Over 130 peer-reviewed papers by Prof. Yan, including in JAMA, The Lancet, Circulation, and BMJ.
– Published work by Prof. Weissglass on medical artificial intelligence and global health ethics.
Prior projects
– CEEEC, establishing partnerships with community elder care centers in Suzhou and Kunshan and involving DKU graduate students as researchers.
– A pilot deployment of AI-assisted art and music therapy tools at local elder care centers.
– A policy project on improving elder care service quality in Suzhou.
– Multi-year ethnographic fieldwork in Suzhou and Kunshan, including urban resettlement communities adjacent to the DKU campus.
– Duke’s “Moral Artificial Intelligence” project, co-led by Prof. Weissglass, and DKU labs on the ethics of nudging and on values in health metrics.
Awards
– Best Experimental Animation Award, 60th Ann Arbor Film Festival, and a Jury Special Mention at the 25FPS Festival Croatia, both to Prof. Hu.
Faculty
Lijing Yan — Co-Director
Professor of Global Health, Duke Kunshan University
Chronic disease prevention and control, healthy aging, and innovation in translational health systems and implementation science.
Lijing Yan is a Professor (with tenure) of Global Health and Head of Non-Communicable Chronic Diseases (NCDs) Research at the Global Health Research Center of DKU in China since July 2014. Previously, she was the Deputy Director of the George Institute for Global Health at Peking University Health Science Center. She has a bachelor’s degree in Sociology from Peking University, a Master of Public Health degree and a doctoral degree in Demography from the University of California, Berkeley. Her main research areas are chronic disease prevention and control, healthy aging, and innovation in translational health systems and implementation science. She is the Principal Investigator or Co-Investigator on research grants totaling over $10 million USD. She has published over 130 peer-reviewed papers in journals including JAMA, Lancet, Circulation, and BMJ (Google Scholar h-index: 56).
Yucheng Jin — Co-Director
Assistant Professor of Computer Science, Duke Kunshan University
Applied AI in mental health and creativity enhancement, human-centered AI design, and technology acceptance among older adults.
Yucheng Jin is an Assistant Professor of Computer Science at Duke Kunshan University, having joined DKU in August 2024. His research focuses on applied artificial intelligence in mental health and creativity enhancement, with a particular emphasis on human-centered AI design and technology acceptance among older adult populations. He is also collaborating with Prof. Hu on projects at the intersection of AI and digital arts.
Keping Wu
Associate Professor of Anthropology, Duke Kunshan University
Anthropology of care, aging, mental health, and long-term care in contemporary China, with extensive fieldwork in Suzhou and Kunshan.
Keping Wu is an Associate Professor of Anthropology at Duke Kunshan University. Her research spans psychological anthropology, the anthropology of religion, and the anthropology of care, with a focus on aging, mental health, and long-term care in contemporary China. She has conducted extensive fieldwork in Suzhou and Kunshan, including in urban resettlement communities adjacent to DKU’s campus. She brings in expertise in ethnographic research and human-centered approach to the use of AI technology in the care of aging population.
Rui Hu
Assistant Professor of Computation and Design, Duke Kunshan University
Artist and scholar working in computer graphics, moving image, and installation. He leads the design and production of the lab’s HUM Space exhibition.
Rui Hu is an Assistant Professor of Computation and Design at Duke Kunshan University. As an artist and scholar, he works with computer graphics, moving images, installation, and game and virtual simulation technologies. His practice and research explore issues of time and temporality through the lenses of causation, prediction, decision, and language. He is the recipient of the Best Experimental Animation Award at the 60th Ann Arbor Film Festival and a Jury Special Mention at the 25FPS Festival Croatia. He will contribute to the AIHCHA Lab by leading the design and production of the lab’s HUM Space exhibition and by bringing an arts and design perspective to the lab’s interdisciplinary research agenda.
Daniel E. Weissglass
Assistant Professor of Philosophy, Duke Kunshan University
Ethics of AI, health, and technology, joining philosophy with the cognitive sciences and emerging technologies.
Daniel E. Weissglass is an Assistant Professor of Philosophy at Duke Kunshan University and an Associate Professor of the Practice at Duke University. He holds a Ph.D. in philosophy from the City University of New York and bachelor’s degrees in philosophy and psychology from the College of Charleston. His research joins philosophy, the cognitive sciences, and emerging technologies, focusing on the ethics of AI, health, and technology. He has published on medical artificial intelligence and global health ethics and led DKU labs on the ethics of nudging and on values in health metrics. He will anchor the lab’s ethical and philosophical inquiry into human-centered AI for aging.
Student Researcher
Ziyi (Thea) Xia — Student Researcher
MS in Global Health, Duke University
Community-based intervention research on aging and chronic disease, qualitative methods, and AI-assisted care. She works across all three research programs.
Ziyi Xia is a master’s student in Global Health at Duke University, and holds a bachelor’s degree in Food, Nutrition and Health from the University of British Columbia. She is a registered dietitian. She leads the CEEEC community intervention study at the DKU Global Health Research Center, a four-arm study with more than 450 older adults across 32 communities in Suzhou and Kunshan, and she helped to write and coordinate the founding proposal for the AIHCHA Lab across its five contributing disciplines. Her own research includes an AI-assisted art intervention for older adults living with multiple chronic conditions, funded by the Center for Contemporary China Studies, for which she led the focus group discussions and the qualitative analysis using the Behaviour Change Wheel and the COM-B model. She previously worked on medical datasets for large language models at MetaStar HealthTech. Within the lab she contributes study coordination, quantitative analysis, and qualitative fieldwork.
Join AIHCHA
The lab is open to all DKU faculty and students, and there are several ways to take part.
Faculty and researchers. Colleagues working on aging, care, AI, ethics, or related questions are welcome at the lab’s monthly meetings and may propose collaborative studies within any of the three research programs.
Students. The lab hires student workers for fieldwork, interviews, transcription, data analysis, and exhibition production, and it funds student-led signature work. No prior experience with AI is required. Students from the humanities and social sciences are particularly encouraged to apply.
Community and institutional partners. Elder care centers, community organizations, and municipal bodies interested in co-designing, piloting, or evaluating AI-assisted services are welcome to get in touch.
