In countries far along in the demographic transition, rapidly aging populations are colliding with a severe shortage of health care and elder care workers. Japan may be the most pertinent case study of this and other impacts of demographic disruption. The country’s fertility rate is decreasing faster than projected, and as of 2025, 30% of its population was aged 65 or older. These trends have contributed to a persistent gap between surging demand for elder care and a shrinking care workforce.

To cope with this crisis, the Japanese government has implemented several programs to promote the use of robots in nursing home care. These care robots (or “kaigo robots”) assist care workers and support residents with daily needs. But how does their adoption affect workflows, staff retention, and overall staffing of long-term care facilities? Few studies have empirically examined these questions.

Shedding light on the debate surrounding new automation technologies and their impact on workers, a recent study, published on August 6 in the inaugural issue of the journal Health Affairs Review, finds that care robots help address challenges posed by population aging and care-labor shortages without necessarily displacing workers or lowering care quality.

The study, titled Robots and Labor in the Service Sector: Evidence from Nursing Homes, is part of a collaborative effort driven by the Asia Health Policy Program (AHPP) at the Walter H. Shorenstein Asia-Pacific Research Center. The study’s co-authors are Stanford health economist Karen Eggleston, the director of AHPP; Toshiaki Iizuka of the University of Tokyo’s Graduate School of Economics, a former AHPP visiting scholar; Yong Suk Lee of the University of Notre Dame’s Keough School of Global Affairs, formerly the SK Center Fellow at Stanford’s Freeman Spogli Institute for International Studies; and Ellie Xi, a rising junior at Stanford studying biomedical computation on the pre-med track and a former research assistant to Dr. Eggleston.

“One of the aspects of the paper that I found most interesting is its attempt to move beyond simply documenting where robots are being adopted and instead ask what their adoption may actually do to the long-term care workforce, especially given the sector’s high turnover rates and physically demanding working conditions,” says Xi.

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Lessons from Early Diffusion of Robotics in the Long-Term Care Sector

The researchers grouped the robots prevalent in Japanese nursing homes into three main categories:

• Transfer aids: Wearable and non-wearable devices that assist staff with lifting frail residents from beds to wheelchairs, significantly reducing back strain, a leading cause of caregiver burnout.
• Mobility robots: Assistive systems that help residents move, use the restroom, or bathe more independently.
• Monitoring and communication systems: Sensors that alert staff when a resident has slipped out of bed or fallen, as well as social robots designed to offer companionship and cognitive stimulation.

To examine early diffusion of these robots, the researchers used 2017 survey data on long-term care work across approximately 860 Japanese nursing homes. A second source of data is their compilation of prefecture-level care robot subsidy availability, using regional variation in robot subsidies as an instrumental variable. Think of this as a natural experiment driven by a “geographic nudge.” Starting in 2015, Japan’s central government began providing prefectural governments with funds to subsidize the cost of adopting care robots. Because different prefectures introduced these subsidies at different times and with varying levels of generosity, nursing homes in some regions had a much easier path to acquiring and deploying robots than those in neighboring areas.

By comparing staffing trends between nursing homes that received this external, subsidy-driven "nudge" to adopt robots and those that did not, the researchers could confidently isolate the technology’s causal effects on the caregiving workforce.

The results indicate that nursing homes that adopted robots saw a significant decrease in staffing retention problems. Robot adoption was also associated with a 28% increase in care workers and a 39% increase in nurses, resulting in approximately 26% higher total employment at the facility level. Importantly, this employment growth occurred entirely among non-regular employees – that is, staff members on flexible, often part-time, contracts. The findings also suggest that robot adoption may improve continuity and quality of care while mitigating careworker shortages.

“Using nationally representative data from Japan and an instrumental-variable strategy, the study provides evidence suggesting that robots can complement rather than simply replace care workers, including by alleviating retention difficulties in a sector facing persistent labor shortages and potentially supporting quality of care,” explains Xi. “The paper’s central finding is that robot adoption is associated with reduced retention difficulties and increased employment of care workers and nurses under flexible contracts.”

A Human-Robot Collaborative Future for Elder Care

Caregiving is a physically demanding and high-stress occupation. The study’s findings indicate that, by introducing robots to ease staff burdens and monitor residents, nursing homes were able to promote more flexible work, either by increasing the tasks performed by non-regular employees or potentially encouraging part-time work. This type of work structure is encouraged by the Japan Nursing Association as a means for reducing stress, preventing burnout, and promoting a healthier work-life balance.

“Given recent debates about AI use in healthcare and the future of work, I found it especially interesting that this research highlights the potential for technology to augment caregivers, particularly by supporting physically demanding or indirect tasks, while preserving the human aspects of care that are more difficult to reproduce,” says Xi.

The study's findings are relevant for policymakers seeking evidence on the social value of collaborative robots and their impacts on staffing and care delivery, particularly as aging societies facing demographic pressures similar to Japan consider how to meet growing demand for long-term care.

A Mentorship Story

The study is part of Eggleston’s Innovation for Healthy Aging research track, which investigates how East Asian economies adopt and adapt to emerging technologies, design incentives, and adjust their workforces to support older adults. It builds on an earlier research project focused on the impact of robots on nursing home care in Japan.

For Xi, co-authoring the paper represents an academic milestone. "As someone deeply interested in geriatrics, I first began working with Dr. Karen Eggleston as a research assistant during the summer after my freshman year," Xi recalls. "Last spring, we decided to continue working together through a directed reading."

During that directed reading, Xi was invited to help revise and update a project that had previously circulated as an Asia Health Policy Program working paper. She worked to update the research, framing the original findings within the rapidly shifting landscape of care robotics and artificial intelligence in long-term care.

"I worked on situating the original findings within more recent research and developments in care robotics and considering what Japan’s experience can tell us about the role of these technologies in aging societies today," Xi says. "It was an incredible opportunity to work closely with Dr. Eggleston, Professor Toshiaki Iizuka, and Professor Yong Suk Lee. I was especially grateful to see firsthand how a collaborative project evolves and to contribute to that process as the paper moved from a working paper toward publication.”

The Trans-Altai Sustainability Dialogue-2026, jointly organized by the Secretariat of the State Great Hural of Mongolia, the Ban Ki-moon Foundation for a Better Future, and the Walter H. Shorenstein Asia-Pacific Research Center (Shorenstein APARC) at Stanford University, will take place at the State Palace on 3 July 2026. This year's conference will be held under the theme: "SDG 17: Partnerships for the Goals."

This year's conference will be attended by distinguished international scholars and researchers, including the eighth Secretary-General of the United Nations, Ban Ki-moon; Professor Kiyoteru Tsutsui, Director of the Shorenstein Asia-Pacific Research Center at Stanford University; Professor Zhiyun Ouyang of the Chinese Academy of Sciences and Foreign Member of the United States National Academy of Sciences; Mengye Zhu, Senior Scientist at the Natural Capital Alliance of Stanford University; Professor James Fishkin of Stanford University; Professor Leif-Eric Easley of the Division of International Studies at Ewha Womans University, specializing in International Security and Political Economy; and Asset Abdualiyev, Founder and Chief Executive Officer of Silicon Valley's Silkroad Innovation Hub. Members of the State Great Hural and the Government of Mongolia will also participate and share their views.

Within the framework of the theme "Partnership for the Goals," four parallel sessions will be organized under the following main topics: "Artificial Intelligence, Technology and Inclusive Innovation," "Critical Minerals, Mining and Green Technology," "Women's Leadership and Empowerment," and "Democracy and Civil Engagement." Scholars from leading universities around the world, along with representatives of government agencies and international organizations, will deliver presentations and participate in discussions.

For example, Mongolia's 34th Prime Minister, G. Zandanshatar, will speak at the opening session, followed by a discussion on democratic civil participation, featuring former Permanent Representative of the Republic of Korea to the United Nations Kim Sook and Professor James Fishkin of Stanford University.

Since its inception, the Trans-Altai Sustainability Dialogue has been convened on three occasions. Previous conferences addressed global challenges including gender equality, peace and justice, strong institutions, and regional cooperation, resulting in policy recommendations and numerous collaborative initiatives.

According to the Media and Public Relations Department of the State Great Hural, the Trans-Altai Sustainability Dialogue 2026 places particular emphasis on strengthening cooperation among countries, international organizations, academia, and the private sector; accelerating the implementation of the Sustainable Development Goals; and fostering a shared understanding of regional development, security, and good governance.

The Trans-Altai Sustainability Dialogue builds upon the ongoing Trans-Pacific Sustainability Dialogue initiative launched in 2022 by Shorenstein APARC and the Ban Ki-moon Foundation for a Better Future. 

Across the world, populations are aging rapidly as people live longer and fertility rates continue to decline. Asia is at the vanguard of this demographic shift. The number of older adults (aged 60 and above) in the region is projected to triple between 2010 and 2050, reaching nearly 1.3 billion people. As Asian economies face this “silver wave,” helping older adults live safely and independently at home – a concept known as aging in place – has become a policy imperative.

At a recent webinar held during Stanford Health AI Week, the Asia Health Policy Program (AHPP) at Shorenstein APARC brought together experts from China, Singapore, and South Korea to share insights into the potential of health AI to allow older adults to enjoy healthy aging and avoid or postpone institutionalization. 

Moderated by Stanford health economist Karen Eggleston, the director of AHPP, the webinar featured Hongsoo Kim, a professor of health policy and aging at Seoul National University’s Graduate School of Public Health and director of its Artificial Intelligence Institute’s Center for AI in Health and Care; Xiaochen Ma, an assistant professor of health economics at Peking University’s China Center for Health Development Studies; and Tien Yin Wong, a physician-scientist-innovator and the senior vice-chancellor of Tsinghua Medicine and vice-provost of Tsinghua University, who has also worked and held senior leadership roles in Singapore and Australia as a practicing retinal specialist with a research portfolio on retinal diseases, ocular imaging, AI, and digital technology.

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Here are six lessons from the front lines of Asia’s efforts to integrate AI into elderly health care and advance aging in place:

1. Adopt a Whole Systems Approach

In South Korea, the world's fastest-ageing society, automated systems like "CLOVA CareCall" – an AI-powered well-being dialer – conduct natural-sounding check-ins with solo-dwelling seniors, boasting a 96% response rate. Yet, Professor Kim emphasizes that checking in with people in need of health care is only half the battle.

If an AI flags an isolated senior at risk of depression, cognitive decline, or a physical abnormality, but the local community lacks the social workers or clinical pathways to intervene, then the health care system has failed.

“The question is not only whether AI can detect something, but how a health and care system acts on it,” she says. “Detection by itself changes nothing. A warning that no one follows up on helps no one. So the gap I care about is not the model’s cleverness itself. It is whether the system delivers.”

2. Solve the Entire "Care Cascade"

In rural China, traditional diabetic screening rates hover below 33%, leaving millions at risk of Diabetic Retinopathy (DR), a leading cause of blindness. Professor Ma shared how deploying an AI screening model successfully pushed screening rates past 85%.

The research team, however, discovered a glaring bottleneck: only 21% of high-risk patients actually followed up to receive sight-saving treatments. To fill this gap, Ma’s team designed an "AI Plus” model (v2.0) that integrates immediate, local-language counseling at the point of screening. To keep seniors healthy at home, AI solutions must address the entire clinical journey, from initial scan to final treatment.

“Many of the AI tools have been focused on diagnosis accuracy or validation rather than going downstream to the entire cascade of whether improved screening will translate into improved referral and the ultimate health outcomes,” says Ma.

3. Align with Local Workflows and Incentives

AI and other technology solutions for health often fail because they expect overworked care workers to adopt entirely new habits. Professor Ma noted that digital health interventions in rural China succeeded only when they integrated seamlessly into existing daily routines.

Instead of forcing clinicians to use complex new software, successful pilots utilized WeChat, the ubiquitous messaging app already open on every phone. Furthermore, the technology must align with the financial and professional incentives of frontline health workers. If an AI tool increases their administrative burden without simplifying their day or boosting their clinical efficiency, then it will remain unused.

4. Design Human-Centered AI for Health Equity

Professor Wong highlighted the ethical risk that AI tools will worsen, rather than reduce, health care disparities. This challenge is driven by the dynamics of “Inverse Care Law,” where AI disproportionately benefits the already advantaged, and the “Recursive Care Law,” where this inequality becomes a self-reinforcing cycle embedded in the system.

Because younger, more tech-savvy individuals generate more health data, AI models become better at serving them than the intended users of aging-in-place technologies. This creates a vicious cycle where the very tools designed to support aging populations end up marginalizing them. Governments must devise policies to mandate fair data coverage and usability, ensuring that AI serves society's most vulnerable members equitably, Wong stated.

Professor Kim noted that her team found that only about 38% of community care agencies in Korea have adopted AI and that the adoption rate varied sharply by region. In fact, districts with the greatest need may have the least access to these powerful tools. This challenge is a fundamental design gap rather than a technology gap, Professor Kim argues. To be genuinely equitable, a system must be built from the start to actively track who is missing and automatically route support back to them. This requires two  human-centered design key principles:

I. Universal by Default: The hardest-to-reach should not have to be the most persistent in navigating the technology.

II. Connected Across Sectors: Long-term care, social care, and health care must act as one integrated system rather than disconnected silos, each of which sees only part of the person’s needs.

5. Augment, Do Not Replace, the Human Touch

The panelists rejected the trope of robots replacing human caregivers. Instead, they view AI as an essential force multiplier for an overstretched workforce.

Whether it is South Korea’s deployment of 12,000 AI companion robots to combat senior isolation, or automated triage tools in clinics, the goal should be to offload administrative and routine tasks. This frees up human social workers and clinicians to do what they do best: deliver hands-on, empathetic care.

6. Value Real-World Outcomes Over Technical Novelty

Healthcare systems should prioritize rigorous, real-world case studies that prove actual clinical value, such as reduced mortality, lower rates of blindness, or fewer nursing home admissions, rather than celebrating high validation benchmarks in a laboratory.

To build robust future health AI systems, the experts concluded, the academic and tech sectors must also courageously publish and analyze their failed trials to understand what truly works in the chaotic reality of home-based care.

While AI holds immense promise for helping people grow old at home, “age tech” alone cannot solve the elder care crisis, the panelists agreed.

In the Media

Dr. Eggleston joined Jeffrey Snyder, host of the Broadcast Retirement Network, to discuss highlights and takeaways from the webinar discussion. Watch below:

Stanford University’s Walter H. Shorenstein Asia-Pacific Research Center (APARC) is delighted to welcome a new cohort of fellows joining us starting in summer 2026.

APARC offers multiple prestigious fellowship opportunities for Stanford doctoral students, emerging scholars of exceptional promise, and accomplished faculty and mid-career experts researching contemporary Asia topics. Supported by these fellowships, our incoming fellows will complete dissertation research, work on book manuscripts, undertake new research projects, and engage with the center's scholarly community.

Meet the Fellows

Herbert Chang is an assistant professor of quantitative social science at Dartmouth College and a Forbes 30 Under 30 honoree in Science for his work on network science and offshore finance. His research examines how emerging technologies reshape democratic behavior, including recent work on AI and misinformation in the 2024 Taiwan and U.S. presidential elections. His work has been featured in the New York Times, the Washington Post, and Scientific American, and has informed both academic and policy debates.

Chang will use his time at APARC to write a monograph on the interdependence of AI infrastructure and information ecosystems, with Taiwan and the United States as central empirical sites. He will also collaborate with SNAPL to quantify its talent-portfolio theory and empirically model how Asian Pacific nations cultivate and retain scientific expertise. 

Alicia R. Chen is a doctoral candidate in the Department of Political Science at Stanford University. She studies international relations and political economy, with a focus on China. Her dissertation examines the domestic political economy of China's international aid and finance, revealing how domestic politics and institutions shape its overseas economic activities.

Her research is published in the British Journal of Political Science and has been generously supported by Stanford’s King Center on Global Development, the Freeman Spogli Institute for International Studies, the Stanford Center on China’s Economy and Institutions, and the Stanford Institute for Economic Policy Research, among others.

Before her doctoral studies, Chen was a research specialist with the Empirical Studies of Conflict project at Princeton University. She holds a master's degree in international policy from Stanford University and a bachelor's degree in political science from the University of Southern California. 

Dr. Sheikh Jamal Hossain is a researcher and academic specializing in child development, maternal mental health, health promotion, and health economics. His professional interests center on advancing evidence-based interventions through rigorous research, teaching, and capacity strengthening, with a commitment to translating scientific evidence into policies and programs that improve the lives of women and children globally.

With over two decades of experience spanning academia, public health research, and international development, Dr. Hossain has led and contributed to large-scale randomized controlled trials, implementation research, and economic evaluations addressing early childhood development, nutrition, maternal mental health, and health system strengthening. He has successfully secured and managed research grants from international donors, including Grand Challenges Canada, UNICEF, FCDO, and Sida.

Dr. Hossain has authored more than 30 peer-reviewed scientific publications, including 13 as first author, in leading international journals such as The Lancet Regional Health, Pediatrics, Social Science & Medicine, The American Journal of Clinical Nutrition, and BMJ Global Health. He currently mentors multidisciplinary research teams and supervises early-career researchers and graduate students.

He earned his doctorate in women’s and children’s health from Uppsala University, with research focused on the effects of parenting interventions integrated with social protection programs on child development and maternal well-being in Bangladesh. He also holds master's degrees in public health and in health economics from the University of Dhaka.  

Angela Ju is an associate professor of international affairs and political science at St. Edward's University in Austin, Texas. She uses mixed-methods approaches to study race/ethnicity, gender, international migration, social determinants of health, the nonprofit sector, and urban politics in North America, Latin America, Europe, and East Asia. Her first book, Identities Matter: The Politics of Immigration and Incorporation (Oxford University Press), was published last year. 

While at APARC, Angela will be working on her second monograph, Taiwan's Migration Diplomacy Towards Mainland Chinese Migrants and Refugees. In this book, she will examine why Taiwan has not formed consistent immigration policies for migrants from Mainland China.

Using textual analysis of Taiwanese government legislation and publications, the book's primary argument is that Taiwan uses its migration policies to manage its foreign relations with Mainland China. It also argues that one way in which Taiwan pursues international participation, despite lacking international recognition as a state, is through its migration diplomacy.

Siyu Liang is a doctoral candidate in political science at the University of California, Los Angeles (UCLA). Her research lies at the intersection of political communication, public opinion, and computational social science, focusing on how media and information environments shape political attitudes in both democratic and authoritarian contexts.

Her dissertation examines the role of media in shaping perceptions of China in contemporary U.S.-China relations. In particular, she studies foreign influencer propaganda and the downstream effects of U.S.-China competition on public opinion and intergroup relations. As a computational social scientist, she develops and applies natural language processing and machine learning methods to study political communication and international politics, with particular interests in stance detection, transfer learning, and soft-label modeling.

At the Stanford Next Asia Policy Lab, she will expand this research agenda by examining how digital media and geopolitical conflict shape public opinion and social exclusion, with a particular focus on U.S.-Asia relations. She will also pursue projects on nationalism and racism in East Asia. Together, these projects seek to advance a more global understanding of how international politics shapes social inclusion and group relations across the Asia-Pacific region.

Siyu received master's degrees in statistics and political science from UCLA and holds bachelor's degrees in political science and statistics from the University of Wisconsin–Madison.

Deepika Padmanabhan is a political scientist whose research examines nationalism, language politics, and self-determination, with a regional focus on South Asia. 

Her book project explores how nation-building unfolds not only through grand policies and formal institutions, but also from the ground up, in everyday life. It examines how states promote national languages through routine, informal interactions with citizens, a process she terms the Everyday Imposition of language.

More broadly, her research explores how everyday practices shape political identities and collective belonging. In related projects, she examines the politics of language, food, film, and symbolic rituals as sites through which nationalism is cultivated, contested, and reproduced in daily life.

At APARC, Deepika will revise her book manuscript and develop additional projects on nationalism and political behavior. 

She received her doctorate in political science from Yale University in 2025. She holds a bachelor's degree in political science from St. Xavier’s College, Mumbai, and master’s degrees from the School of Advanced International Studies at Johns Hopkins University and the Department of Politics at New York University.

Grace Zeng is a political scientist specializing in international political economy, with a focus on China's use of trade and investment to influence global regulatory governance. Her research examines how states leverage economic tools to shape international rules and institutions. Her work on China's trade practices shows how China uses seemingly technical health and safety regulations to exert pressure on other nations, systematically increasing import restrictions in response to political tensions.

At APARC, she will pursue projects that extend this research agenda by examining China's growing influence in global governance. One project investigates whether China strategically uses infrastructure investment and foreign subsidiaries to shape international environmental standards. Another examines China’s information control system through the lens of its WTO commitments and the global governance of cyberspace.

Before joining Stanford, Grace was a lecturer in the Department of Political Science at the University of California, Berkeley. She received her doctorate in politics from Princeton University. She also holds a master's degree in the social sciences (MAPSS) from the University of Chicago and a bachelor's degree in mathematics from the University of Hong Kong.