What if AI could help older adults stay healthy and independent—without replacing the human care they still need? In this conversation, Karen Eggleston, PhD. discusses Stanford Health AI Week and shares insights from health systems across East Asia, including how AI is being used to support aging in place. We explore the importance of ethical guardrails, evidence-based evaluation, and designing care pathways that connect AI predictions to real next steps—especially in rural and underserved communities.
Jeffrey Snyder, Broadcast Retirement Network
Well, Dr. Eggleston, it’s great to see you. Thanks for joining us on the program this morning.
Karen Eggleston, PhD., Stanford University
My pleasure, great to be here.
Jeffrey Snyder, Broadcast Retirement Network
Yeah, and I guess before we kind of dive into the recent webinar you moderated, I was wondering if you might give us a little bit of background about the Stanford Health AI Week. What was that week, what did it entail, and what does it mean?
Karen Eggleston, PhD., Stanford University
Great, well, the Health AI Week here at Stanford is an ongoing event for a few years now that involves activities. Some are in person here on campus, bringing people from many parts and walks of life, looking at applications of artificial intelligence in health and medicine.
Jeffrey Snyder, Broadcast Retirement Network
So I have to think that it’s so pervasive. I don’t know if that’s the right word or not, but in a lot of different industries, it’s become part of everything that those industries do. I come from the financial services and retirement industry.
I’ve seen it being deployed to speed up our operations or to even answer financial types of questions. I have to imagine similarly, it’s being deployed in health and I would think for the betterment or the more efficient treatment of patients.
Karen Eggleston, PhD., Stanford University
That is certainly the goal of our parties concerned, but being a health economist, I’m soon to point out that how it’s actually used in practice and to whose benefit goes back to aligning incentives with what the goals are of an organization or of society. So I actually direct the Asia Health Policy Program. So I contributed within the Stanford Health AI Week, an Asian perspective on deployment in health systems in Asia.
Jeffrey Snyder, Broadcast Retirement Network
So let’s talk about Asia. It’s no secret that Asia, like the United States, like Europe has a lot of aging people. I think that’s probably the norm when you look at their global population, a lot of people turning age 65 and older.
How is AI being deployed in Asia today to help those that are aging in place?
Karen Eggleston, PhD., Stanford University
Well, great question. Something that many of us focus a lot of time looking at and thinking about. I am not on the technology side.
The people I spoke with are experts mostly from the health systems and medicine side, thinking about how AI is actually being used in practice rather than sort of the technical development. And Asia is a huge and diverse part of the world. But we focus mostly on East Asia, partly because that’s the part of the world that is sort of leading the whole globe in terms of population aging and older age structures.
So I talk with experts from South Korea and China and Singapore about their perspectives, their own research and that of their colleagues. So there’s a lot going on, but the bottom line might be that there’s still a long way to go and we all need to prepare for and think about how we want this technology to be applied for the benefit of all, including our older population. So that was the focus, thinking about keeping people healthy to older ages so that they can what’s called age in place rather than go to a nursing home or be institutionalized.
Jeffrey Snyder, Broadcast Retirement Network
Do our counterparts or your counterparts in Asia, East Asia share some of the concerns that many of us here, the general population might have about AI? Do they have some concerns or do they want more standards or more, I’m gonna call them guardrails. I don’t even know if that’s correct or not.
But is that something that when you were moderating the panel, did that seem like something that was necessary?
Karen Eggleston, PhD., Stanford University
Yes, despite differences across the economies and societies, even in this short webinar, there was a common thread that thinking about sort of the ethics of deploying AI and having guardrails, as you said, about how it’s used, in particular thinking about how you evaluate and continuously evolve, thinking about the evidence about what works and for whom, because this technology might exacerbate existing issues with access or affordability for some populations. So for example, in rural parts of China have different issues than say in the center of Seoul.
Jeffrey Snyder, Broadcast Retirement Network
What I always hear from experts and I wanna get your sense from your panel and the folks in Eastern Asia, this isn’t, AI doesn’t replace the humanity that’s gonna help those that are aging in place. So they’re still gonna need doctors or medical care or caregivers. Was the consensus that AI is gonna be used to maybe augment or enhance what the human touch can do so that maybe the humans can focus on more qualitative aspects of caregiving?
That make sense?
Karen Eggleston, PhD., Stanford University
Yes, definitely. That was also a common theme that AI needs to be used to augment humans, not to replace or automate the process. And many systems have different strategies for doing that.
But connecting between a diagnosis or prediction to actually getting care for the individuals is one of the goals. Like the AI enabled calls to people living alone in Korea is supposed to be designed to talk to people and then connect to them with individuals or the deployment of AI in healthcare in Singapore and China that is supposed to help busy physicians actually look at and connect with their patients rather than have to deal with a lot of the routine aspects of care. Those are some of the goals.
It’s much easier said than done, but a lot of systems are working on it systematically.
Jeffrey Snyder, Broadcast Retirement Network
Are there, I mean, it’s hard to paint with a, you really can’t paint people with a general brush, but when you look at the elderly population or mature population here in the United States, and there’s always the bias that they don’t have the technological wherewithal. I can tell you by talking to my mom and dad, they’re pretty technology savvy. So they know how to use the phone, do all those types of things.
Is it analogous or similar in Eastern Asia where people there have phones and tablets and computers and televisions and everything in between that they’re fairly technologically savvy like we are here in the States?
Karen Eggleston, PhD., Stanford University
Well, yes and no. Yes, they are very technology savvy, but more among the younger generation than the older generation, which often didn’t have as many opportunities for education or use of technology. So some pockets are much more tech savvy than some places we might be familiar with and some much less so.
So, you know, anybody in China might know how to use WeChat, but if in the rural areas it’s all older individuals may not be familiar with any other tools. So this was an important theme that also came through in the webinar is that we shouldn’t require the user to be the one that finds the technology and uses it for their own health and wellbeing. We need a system of care that aligns incentives so the people that help the older individuals can use this technology.
Of course, the individuals and perhaps their adult children or other caregivers can also use the technology to provide more information, empower them to ask questions and so on. But as discussed by our three speakers, a key aspect is for the guardrails at the policy level and then the caregivers in medicine or healthcare to be the ones that select the appropriate AI tool and put it into place so that’s just seamlessly part of the system of care that improves the care experience and hopefully the health outcomes.
Jeffrey Snyder, Broadcast Retirement Network
So we’re having a, you know, I think we’re having similar conversations, Elise, how to care, how to age in place, how to care for loved ones that are aging. Are there some lessons that maybe are some good takeaways for our policymakers, those that are responsible for maybe developing the policies, the procedures of the future to help this population here in the States, I should say. Are there some lessons?
Karen Eggleston, PhD., Stanford University
Yes, we can learn from other places and they can learn from us. I think all parties tend to emphasize the success stories, which is very important, but it’s also important to gather evidence about what hasn’t worked. As they say in Texas, you know, it’s dry holes that find oil, right?
So you kind of need to be open to sharing experience and a lot of that is embedded in just local little experiments. So there’s an important role for policymakers and objective evaluation, maybe from academic institutions to share experience and find out what works for something specific like screening eyes when you have diabetes is a common use of AI, but not just here’s a report three weeks later, maybe you should do something about it, but actually point of care, we’ve used AI, now we’re gonna direct you to the next person you can actually talk to to get the care you need.
So those are some of the ways where different systems are experimenting. And I think particularly in our system of care for older adults, there are a lot of challenges here as elsewhere, where we really need to share ideas about how technology can support our strained workforce and provide better outcomes to our older adults.
Jeffrey Snyder, Broadcast Retirement Network
Well, you know, obviously there’s a huge need globally, not just in East Asia, it’s important research, important information and look at the end of the day, whether you live in East Asia, the United States or Europe, you’re just, we’re all people, right? So we’re all gonna get older, we’re all gonna have diseases, I know the circumstances are different, but clearly, you know, we need to do a lot of sharing and help each other kind of work through these challenges. Dr. Eggleston, we’re gonna have to leave it there. Thanks so much for joining us, really appreciate you coming on the program and we look forward to having you back again very soon.
Karen Eggleston, PhD., Stanford University
Thank you, it was a pleasure.