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 in 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 transfer 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 not a technology gap, Professor Kim argues, but a fundamental design gap. 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.

Semiconductors: The Limits of Containment?
The conference returned repeatedly to America’s use of export controls—and whether they are working. The verdict was nuanced. Philip Wong, the Willard R. and Inez Kerr Bell Professor of Electrical Engineering at Stanford, argued that in the semiconductor space the strategy has plainly backfired. By cutting China’s firms off from American chip-making equipment and advanced logic chips, the controls created a large captive domestic market for China’s equipment suppliers who previously had no customers. “It basically enabled the indigenous supply chains to have a wonderful set of customers within China,” Wong said, “and so they were able to climb up the learning curve really quickly, much more quickly than before.” Other speakers suggested that may be a tolerable cost as long as export controls allow the US to reach certain frontier capabilities first—as has been the case with Anthropic’s Mythos model.

Wong pushed back on both alarmism and dismissiveness about China's broader technological rise. China, he argued, has genuine world-class talent and infrastructure across multiple sectors—a peer competitor, not a pretender. "If you are among the best athletes, sometimes you win, sometimes other people win. That happens all the time." To treat any given Chinese breakthrough as proof of American collapse, or to wave it away as a fluke, both miss the point: China is, in his words, "a bona fide good athlete."

Wong’s recommended alternative to export controls was direct: rather than trying to slow a competitor, the United States should focus on “how do we make ourselves run faster.” That sentiment echoed throughout the day, particularly after he noted that the National Science Board had recently been dismissed and that American R&D funding continues to be primarily focused on defense-oriented research. 

Biotech: From Follower to Leading Force
Physician-scientist Chenjian Li, a research fellow at the Hoover Institution, offered striking data on China’s advancement in biotech. In the active pharmaceutical ingredients that form the basis of medicines taken by hundreds of millions of Americans daily, China has achieved near-total global dominance—some categories are 100% Chinese-sourced. “Medicine, be it advanced experimental drugs, high-end prescriptions or just daily over-the-counter pills, are actually much more impactful than weapons of mass destruction,” Li said, “because they affect 80% of the United States and global population.”

At the cutting edge of drug discovery, the picture is more nuanced but equally notable. Chinese biotech startups are increasingly producing competitive "me-too, me-better" drugs that improve on existing treatments, and pushing into "first-in-class" drugs—the crown jewels of pharmaceutical innovation. Major multinational corporations (MNCs) are paying billions to acquire them. The fact that Pfizer, Merck, and Eli Lilly are spending at this scale, Li argued, says something important: “The MNCs buy those new therapeutic assets because they are solid and unique, and because the MNCs don’t think that they can be as fast and as good in those lines.”

Economist Ruixue Jia of UC San Diego connected this pharmaceutical surge to China’s education system, which has spent decades steering enormous numbers of students toward engineering and STEM fields, including biology and life sciences. The founder of one of last year’s biggest biotech deals—a $5.6 billion transaction—fit a pattern Jia’s research keeps finding: educated in China, PhD in Canada, postdoc in the United States, returned to China in 2008. “It’s not just a success story of Chinese education,” she noted. “It’s also a success story of North American education.”

Fragmentation and the AI Race
A central tension runs through the broader debate: what do the world’s two largest economies actually gain or lose from their escalating technological confrontation?

Tsinghua economist Hong Ma argued that, measured by its own goals, the American trade war has largely failed. US import dependence on Chinese value-added has remained roughly constant despite years of tariffs, as goods simply reroute through third countries. Beyond tariffs, he warned of a longer-term cost: fragmentation into two separate innovation ecosystems, neither large enough to fully benefit from the other. The US would lose access to the Chinese market, Chinese engineering feedback, and the scale that sustains rapid innovation. “On both sides,” he said, “this is not the optimal equilibrium.”

Panelists pointed to China’s open-weight AI models as evidence of a different kind of competition playing out below the frontier. China’s models from Alibaba, Moonshot AI, and others are being used across the globe—often simply because they are cheaper and good enough for most applications. In this way, big US labs may be ahead on raw benchmarks, but that advantage does not automatically translate into leading global adoption.

Impressive Achievements, Costly Failures
Another useful synthesis came from Scott Kennedy of the Center for Strategic and International Studies. Kennedy’s “bumpy success” framework holds that China’s innovation trajectory is clearly positive—it now ranks tenth globally on the Innovation Index, ahead of Japan in the Asia-Pacific—but deeply uneven across sectors. He described China as a “slow tech dragon”: vast misallocation of resources produces genuine breakthroughs alongside enormous waste, and that waste is a real drag on the broader economy. Commercial aviation was one such example—despite being a signature priority for China’s leadership and the single largest recipient of state investment, the result is, in Kennedy’s words, “an American plane with Chinese paint.” The lesson is not that China cannot innovate, but that state-directed industrial policy produces highly variable results.

That framework—impressive achievements, structural waste, uneven outcomes—runs as a quiet undercurrent through the broader debate. Structural challenges remain: a domestic market that cannot yet absorb the premium prices of cutting-edge drugs; an education system optimized for solving known problems rather than identifying unknown ones; and an economy in which the benefits of technological investment are not yet reaching ordinary households.

The picture that emerges resists easy predictions, but carries a clear message: the old frameworks—China as technological follower, export controls as sufficient means to maintain America’s remaining technological edge, global supply chains as something susceptible to political redirection—often no longer fit the evidence. The task now is building better ones.
 

Discover more from the 2026 SCCEI China Conference. 
 

"That advantage is entirely theoretical," Doshi conceded. "Unlocking its potential, though, is the central task of American statecraft in this century." In practice, that might mean Japan and South Korea investing in American shipbuilding; Taiwan building semiconductor plants in the U.S.; allies co-producing advanced weapons systems; and all parties maintaining a shared tariff or regulatory wall against China's excess industrial capacity. On the economic side, Doshi called for common investment screening, coordinated industrial policy, and an "economic Article 5" ensuring that when China uses economic coercion against one ally, all respond together.

Addressing the Skeptics
Doshi acknowledged "the new pessimism," the view that Trump-era damage to U.S. alliances has made allied scale impossible. The strain is real, he said, but not terminal, for three reasons:

1. The alternatives are worse. Spheres of influence, unrestrained multipolarity, and a China-led order all leave the U.S. and its partners poorer and less secure. 
2. Alliances have absorbed serious shocks before and survived. For example, France's withdrawal from NATO's unified command, Nixon's opening to China, the Plaza Accord. 
3. The underlying logic of interdependence persists. Allied economies are growing more dependent on U.S. markets as China buys less from them, allies are purchasing record numbers of American weapons, and even the Trump administration has not escaped the pull of allied scale, with Vice President Vance publicly calling for a trading bloc among allies to break China's chokehold on critical minerals.

Eight Principles to Achieve Allied Scale
Doshi closed with a practical blueprint — eight principles for building allied scale.

1. Turn the page on the Trump era. Persuade allies that the most damaging recent policies were products of individual leadership rather than durable features of the American political system.

2. Begin with humility. Start with small, achievable projects: a joint shipbuilding effort, a critical minerals offtake agreement, a co-production line. Build from there.

3. Build mutually beneficial bargains. Allies invest in America; America invests in allies. All extend each other more preferential terms than they do to non-market economies like China.

4. Pay attention to domestic politics. “The danger of the ‘Trump Approach’ is alienation and polarization of allied politics that makes diplomacy impossible.” Any allied scale strategy must be first grounded in domestic politics.

5. Build ad hoc coalitions. Allied scale does not mean doing everything with everyone. It means assembling the right groupings for specific challenges and opportunities.

6. Bolster credibility through congressional legislation. Executive orders are too easily reversed. Durable commitments to allies require legislative backing that is harder to undo with a change in administration.

7. Build on existing platforms. Frameworks like the Quad, AUKUS, the U.S.-Japan-South Korea trilateral, and the G7 already exist. Allied scale should strengthen what works, not start from scratch.

8. Articulate an affirmative vision. "Allied scale can't just be about balancing China," Doshi said. "It has to be about building the kind of world that we want to see and live in."

“That work is hard,” Doshi concluded, but “it's not impossible. And the alternatives are far more concerning than the future that I’m outlining.” Doshi ended his address on a note of optimism: a call to action for the U.S. to reforge our alliances and rebalance the world order to create a better world for not just the U.S., but for nations across the globe.

A full recording of Dr. Rush Doshi’s talk is available on YouTube and below.

This blog first appeared in The National Interest.

The return of President Donald Trump to the White House has not only increased geopolitical volatility – it has fundamentally altered expectations about how far major powers are willing to go to secure strategic advantage. What once seemed rhetorical excess—such as his repeated remarks about acquiring Greenland – now appears less implausible in light of recent events. From the escalating crisis in Venezuela in early 2026 to the ongoing Iran War as of May 2026, the United States has signaled a willingness to pursue geopolitical advantage with fewer constraints than before.

Against this backdrop, the Arctic is no longer a peripheral theater. It is rapidly emerging as a central arena where climate change, energy security, and great-power competition intersect. The question is not whether the Arctic matters, but how states will position themselves in a region where the rules are still being written.

A Strategic Arctic, not a Peripheral One

The renewed US interest in Greenland should not be understood narrowly as a territorial ambition. Rather, it reflects a broader strategic calculation about the Arctic. The melting of Arctic ice – combined with technological advances—is making previously inaccessible resources and shipping routes increasingly viable. In this sense, Greenland is not the story – the Arctic is.

The Arctic is estimated to hold roughly 13 percent of the world’s undiscovered oil and 30 percent of its natural gas, making it one of the last major frontiers of global energy development. At the same time, new maritime routes such as the Northern Sea Route (NSR) and the emerging Transpolar Sea Route (TSR) promise to significantly shorten shipping distances between Asia and Europe.

For major powers, the implications are profound. Russia has already positioned itself as the dominant Arctic actor, leveraging its geography and resource base. China, through its “Polar Silk Road” initiative, seeks to embed the Arctic into its broader connectivity strategy. Meanwhile, the United States, increasingly viewing the region through a strategic lens, is attempting to mobilize its alliances to counterbalance these moves.

As recent studies suggest, the Arctic is becoming a new frontier of great-power competition – one where economic, military, and legal dimensions are deeply intertwined.

Why South Korea Is Paying Attention to the Arctic 

For South Korea, interest in the Arctic may appear surprising at first glance – especially given the ideological orientation of its current progressive government. Traditionally, progressive administrations in Seoul have emphasized engagement with continental powers such as China and Russia, while seeking rapprochement with North Korea. They have also shown interest in infrastructure connectivity across the Eurasian landmass.

Yet the Arctic presents a different kind of opportunity – one that aligns with both geopolitical necessity and economic ambition.

Eunjung Lim, a professor in the Division of International Studies at Kongju National University (KNU), is a visiting scholar at Shorenstein APARC from April 2026 to February 2027. She is also a member of the governing board of the Asia-Pacific Leadership Network and a member of the Subcommittee on Energy and Just Transition of the Presidential Commission on Carbon Neutrality and Green Growth. She earned a BA from the University of Tokyo, an MIA from Columbia University’s School of International and Public Affairs, and a PhD from Johns Hopkins University’s School of Advanced International Studies.