What does it really take to innovate in emergency medicine? Dr. Matthew Strehlow talks with Dr. Dev Dash and Dr. Andy Chu about how to make innovation truly work—exploring the real-world process, common pitfalls, and human-centered approaches that turn great ideas into meaningful impact.
What does it really take to innovate in emergency medicine?
In this second episode of our Innovation in EM series, Dr. Matthew Strehlow talks with Dr. Dev Dash and Dr. Andy Chu about how to make innovation, AI, and technology truly work in the complex, high-stakes world of acute care.
They discuss what separates great ideas from successful implementation, the keys to effective collaboration between clinicians and technologists, and how empathy and communication remain essential to the innovation process.
From identifying real clinical pain points to building partnerships that last, this episode offers practical insight into how emergency physicians can drive meaningful, human-centered change in healthcare.
About Our Guests and Host
Dr. Dev Dash is an emergency physician and assistant professor who loves finding new ways to use technology to improve patient care. He’s a former vice president of the American Medical Informatics Association Clinical Fellows. His projects range from AI tools that predict heart function from real-time systems at the bedside, and helping develop tools that bring patient information closer to frontline workers.
Dr. Andrew Chu is an emergency physician and assistant professor who is passionate about bringing innovation and startup ideas into everyday medicine. He has co-led multidisciplinary teams in building award-winning healthcare technologies that are now used in more than 170 countries. He is also an independent filmmaker.
Dr. Matthew Strehlow is a Professor of Emergency Medicine at Stanford and serves as Vice Chair for Innovation and Clinical Improvement. His work focuses on improving patient care through system redesign, global health initiatives, and advancing emergency medicine education.
Dr. Matthew Strehlow: AI has the power to transform emergency medicine, but for many clinicians it can feel more intimidating than inspiring. In this episode, two emergency physicians unpack how AI and innovation in acute care can be more practical, more collaborative, and more exciting.
To help us make sense of it all. I'm joined by Dr. Dev Dash, and Dr. Andy Chu.
Dr. Dash is an emergency physician and assistant professor who loves finding new ways to use technology to improve patient care. He's a former vice president of the American Medical Informatics Association Clinical Fellows. His projects range from AI tools that predict heart function from real time systems at the bedside, and helping develop tools that bring patient information closer to frontline workers.
Dr. Chu is an emergency physician and assistant professor who is passionate about bringing innovation and startup ideas into everyday medicine. He has co-led multidisciplinary teams in building award-winning healthcare technologies that are now used in more than 170 countries outside of medicine. He channels his passion for storing, telling as an independent filmmaker. His film, “Life Support,” has been screened at many film festivals and has earned multiple jury awards for best short film.
Dr. Dash, Dr. Chu, welcome and thank you for joining us.
Dr. Andrew Chu: Thanks for having us, Matt. Thanks for having us.
Dr. Matthew Strehlow: Well, gentlemen, you guys have immense experience in AI, innovation, technology and implementation. But one thing I've noticed is that everybody's got a great idea and there's no shortage of great ideas in healthcare but turning them into real change is really where it's very difficult.
What have you learned about how innovation can actually work in the real world and the complex health systems in which we operate?
Dr. Andrew Chu: Matt, I love this question, which is essentially, how does innovation really work in the real world, right? And I think that, especially in modern Americana, there's this mythos of the lone genius, right? The lone hero, especially in Silicon Valley Drive that drives all the innovation in the world. And that's just frankly not true. That's not how innovation works. Because the literature shows and are also our own experiences show that if you want to make innovation happen, teamwork makes a dream work. And I see that based on classic and modern literature around collective intelligence, right?
It's not the smartest person in the room that drives that innovation. It's actually the teams, the smartest teams that know how to communicate effectively that take turns speaking and also showcase empathy. And there's this great talk by Bill Gross, who is the founder of IdeaLab, right? He has this legendary TED Talk that talks about what is it after studying hundreds of startups that make the best startups succeed.
And the most important controllable human factor is actually teamwork and execution. So, making sure that we communicate effectively, that we treat each other with respect. That is what drives innovation. And I think that's the north star of the lab that Dev and I have co-founded, and we lead, we optimize for the team.
So let me just give Dev a shoutout. The reason I love working with Dev is he's a brilliant guy, but there are a lot of smart people at Stanford. He’s also incredibly kind. He's a good human being. He's a reliable partner and a wonderful friend. And we treat all our teammates the same way and I think that is what truly drives innovation
Dr. Matthew Strehlow: Dev, what do you say to that? You got kudos all around. What do you think makes innovation possible and impactful in the real world? What is the difference between the great idea and the actual implementation?
Dev Dash: Yeah. Thank you. It is a great question.
I'm also with Andy on this. I definitely think it's a team and your power to communicate but also be resilient and flexible with respect to your teammates.
We co-lead a lab together and he is a great partner to work with. He understands a lot of the problems that I go through in our personal lives, because we both have young kids and growing families.
And having that connection is really important. I think being able to translate some of our difficulties in scheduling or getting things done - I think Andy's really good at balancing that teamwork aspect of it.
I have worked with a lot of teams where the flow of information is not great. And I've seen a lot of teams that struggle with this and the one thing I always mention to Andy is, my primary goal when we're working together is to minimize the information asymmetry. He should know as much as I know and vice versa, so we can come to decisions that are well thought out.
I feel like when we talk about our plans and our strategies it's not two brains. It feels like three or four brains. Sometimes we loop in a language model and there's five or six brains. And so, we work together really well. And finding somebody that you can tell everything to and be perfectly honest with is key here. Because you never want to be in a situation where you're struggling with a problem, but you're also mincing words when you talk to your team.
Dr. Matthew Strehlow: You guys have obviously formed an amazing collaborative team. And I know that we often think it's building these teams that speak and communicate well, like you mentioned, but clinicians and tech innovators - I feel like we often are speaking different languages, right?
How have you seen it work and what are the common fail points?
Dev Dash: I can speak to this a little bit. It's been a struggle for I think anybody who works in the innovation landscape. Because you personally never have all the skills necessary to execute on a project company. So always have to collaborate with people.
And often the people who have the most bandwidth are sometimes outside the Stanford ecosystem because everybody at Stanford has a lot of things on their plate and they're all very busy. So when we're trying to find partners or find good teams to work with the most effective collaboration I feel is rooted in honesty and being, Hey, these are our pain points. Are you honestly interested in working with us on this? Do you think you can help address one of our pain points?
And if you can go a little bit deeper and start with a small-scale kind of exploration and maybe grow that exploration from there. At the same time, keeping that communication band wide open and say, hey, we talked about this problem. I did a little bit digging, uh, in the charts. This is what I found. Are you still interested in this? Is this something you can still address? Or do you need to build out your own team and come back to us and say, I finally have somebody a little bit more technically versed. I can come talk to you and we can help we can build a solution together.
When I mentor informatics fellows, they often come to me and say, I really want to work on an AI project or a machine learning project. Do I need to learn how to code? My answer previously used to be no. These days it's like you need to know like the basics of programming languages, um, because you need to have that shared vocabulary.
And if you don't have that shared vocabulary, everything will take four times as long because this other person who knows nothing about medicine or maybe has not even stepped foot in a hospital, is really excited to work on a healthcare problem and doesn't have that shared vocabulary.
And I also tell my informatics fellows, not only do you need to learn the vocabulary and the lingo and the tech side, not to a senior developer level, but at least a little bit to communicate. But you also have to tell your collaborators to come find you in the ED, come to the lobby, show up. We're going to give you a tour. This is what emergency room looks like. This is what our clinical processes look like. And if you find somebody who's willing to spend hours and hours with you at the bedside , I think that's a really good sign, and that's really important for collaboration too.
Dr. Matthew Strehlow: Do you have a background, Andy, in this? Or is this something you learned, this language? Did you learn on the fly or did you get formal training? How did you make that work? Because it's pretty intimidating for me to think that I'm going to learn this coding language right now so I can speak to these innovators and these AI developers.
Dr. Andrew Chu: Yeah, I 100% agree with Dev in the sense that now it's very important to understand the language of the software engineer and learning how to code.
So, I'm having a blast learning from Dev and also learning from my wife who happens to be a software engineer. She's wicked smart, and we actually built a clinical app together and I learned from that experience very acutely how important it is to have clarity.
Dev mentioned honesty. Our amazing software engineering colleagues have a very structured way, a very clear way of thinking about how to build a tech stack, the architecture. And if you speak to them in abstractions, you don't get what you want and what the patients need. So, for example, the software engineers don't understand the clinical encounters because they're not the ones at the bedside doing CPR or leading that resuscitation.
And so if you don't make it very clear what the physician user needs, then they'll make what they think the doctor needs and that leads to a product that, needs to go through a number of iterations. So I totally agree with Dev. If you can bring software engineers to the bedside, see what we go through, breathe that air, see us watching, sitting down, holding that patient's hand, I think that is so important to speak the language of our software engineers.
Also I agree with Dev in the sense of going to where my wife was at. She would open up her GitHub and show me thousands and thousands of lines of code and libraries. And I would ask her, what does that do? What does that do? What is your backend? How does that work? And that also helps you grow and be a better team player in leading the project.
Dr. Matthew Strehlow: I feel like a lot of innovators, and people with shiny tech tools, they come with this solution that they've developed. And maybe they have not spoken the same language as physicians or care providers that they've interacted with, or maybe they didn't even have them involved early on.
And this idea that, Hey, I've got a solution now - let me go find the problem to fix, I think happens a lot. Dev, I've heard you talk about this pain point first approach to AI and innovation. Starting with real world problems instead of building shiny tools and then identifying problems to apply them to.
Can you talk a little bit about, how you think about that and how that's shaped the development of your partnerships?
Dev Dash: Yeah, absolutely. I think the pain point first is very much, rooted in biodesign principles and coming with a solution. I think when we look at technologies in the world, there are very few that where the technology was developed first, and it started solving problems afterward.
I think the classic example that people always bring up is the internet. And people are like, oh, people made the internet and all these apps and things came out of it. And I think what many people don't realize is the internet was actually created to solve a military problem. A military kind of information exchange problem and not a technology just like originated out of somebody's mind.
And then all these solutions, all these problems and solutions flew out of it. The pain point first approach is super important because within the health system and health systems are often what I feel microcosms of society. You need to have many people involved in your solution. So, there are very few workflows that don't intersect with physicians and nursing and residents and techs and like housekeeping stuff. You need to have teams that are invested in solving these problems.
So if you come with a solution, it's very hard to convince somebody to jump on board this solution when they don't have internal motivation to join your team in the first place. Whereas if you start with a pain point first problem, something that everybody understands, it's much easier to build a team around this and say, okay, now we're gonna go try to find a solution.
That being said, you should also think about what a potential solution looks like when you're addressing pain points, because if you don't do that, then you'll always have a little bit of difficulty in creating the solution in the first place. So having that 30,000-foot view is always helpful—not just thinking about the pain point, but also thinking a little bit about the solution.
But we should start at the pain point because that's how you build a team to solve a problem.
Dr. Matthew Strehlow: Andy, I know you have a lot of experience with biodesign and development and innovation and stuff. Do you have anything that you like from that biodesign angle—tips for people or other key points they should know about when they're thinking about this?
Dr. Andrew Chu: I love how Dev, you gave a shout out to the Stanford Biodesign fellowship because two words—due diligence. I a hundred percent agree with finding the right problem. Is it a hair-on-fire problem? Are we actually solving a clinical workflow issue, a patient care issue that adds value to the system, helps the metrics that we actually care about?
Or is it—and we see this all the time, Dev, when we get pitched by startups—a solution that's looking for a problem, which you want to avoid at all costs. And so when I say due diligence, I love being a doctor, Dev, and I love saving lives, but when we look at our own projects or also working with industry partners, we have to put on our MBA, our venture capital hat and think about, look at the leadership, the team—always the team.
Do they have that clinical expertise, especially if it's a health tech problem that they're creating a solution for? Do they have a doctor as a founding member or do they have a doctor that they can deeply engage with so that they understand what it's like for us as emergency doctors in the midst of the chaos and all the workflow complexities?
And if they do, that's a green flag. If they don't, that's a red flag. Also, thinking about the experience—are these serial entrepreneurs? Have they successfully exited companies with a positive ROI? And also making sure that they have the experience to understand what does it mean to go through FDA review?
How do you maintain and model safely? How do you iterate and adjust when you see data drift and make sure that you're getting the most accurate outputs for your patients? I think that's incredibly important. But also the runway—do they have enough money to have a lasting partnership with us that'll last potentially years?
Because it takes a lot of commitment for Dev and me to go through that IRB process, to speak with legal, to talk to our engineers to make sure that everything is being implemented safely. And also, what is the market capture? Are there other peer institutions like Stanford? Are they using the product so that we can actually see real-world value instead of hypotheses and abstractions?
Dr. Matthew Strehlow: I know you guys are recent parents, so shout out to you—congratulations, both of you. I think about my kids—they’re maybe 20 years or so ahead of yours—and I’m wondering, a lot of doctors have kids that become doctors or go into healthcare. Do you think that medicine in general and emergency medicine in particular is going to be a viable career path during their lifetime?
Dr. Andrew Chu: I think as long as there are humans, there will be doctors. There's this great quote by Hippocrates: “Where there is love for medicine, there is love for humanity.”
And I would say, speaking for myself, if I’m having the worst day of my life, if I feel like my life is threatened and I’m dying, as much as I rely on computers and I love machines, I would rather have a human being holding my hand, giving me a hug, telling me that it's going to be okay than any machine.
And so I’ve already asked Sarah Krzyzaniak, who's our program director for Stanford Emergency Medicine, to save a spot for Ria and baby Sarah for the class of 2050. Because even then, and hopefully many centuries afterward, humans will always be relying on humans for that deep connection and patient care.
Dr. Dev Dash: It’s so true. I think that people want to talk to people regardless of how much technologies are on board, and I don't see computers in general or automation taking our jobs away. Since 1950, only one job has disappeared due to automation—and that’s elevator operator. Every other job has changed.
There are more bank tellers now, even though people thought ATMs would replace them—there are more bank tellers now than at any point in human history. Their jobs are different and a little more customer-centric rather than doing the mechanical processes of managing money.
But all of these jobs will change. I don’t think physicians or nurses are getting replaced anytime soon by AI models. We will grow to rely on them more and more, so it’s becoming especially important to make sure our voices are present in the development of these tools rather than relegating it to large tech companies or conglomerates that don’t have a strong clinical voice in them.
Dr. Andrew Chu: I completely agree with Dev. Maybe the repetitive administrative tasks—and by maybe, I mean definitely—those will be replaced, but that’s great because it provides an opportunity for baby Sarah and baby Ria to focus on building empathy and emotional intelligence to have the best connection with their patients.
That’s the reason why Dev and I went into medicine. I didn’t go into emergency medicine to build charts. I went in because I want to be there for my patients at their time of need. And same for our children, if they choose to go into emergency medicine—no pressure.
Dr. Matthew Strehlow: No pressure. Well, it sounds like you're saying that there will be jobs available, which is great. I think that's really reassuring, especially for people as deep into this space as you both are, to hear that positive outlook.
You mentioned empathy as something that is very important to both our current work and to why physicians will be instrumental and central to healthcare in the future. Even though some people debate whether machines can at least act empathetic or mimic empathy for our patients—and there are studies that look at that—let’s move beyond empathy in that question and say: what other skills do you think might be more important moving forward as we integrate AI and other technologies into our workspace?
Dr. Dev Dash: Happy to take this question. I totally agree on the empathy part—the ability to connect to people in any patient- or people-facing job is critical. Just like bank tellers, I think they probably have to have more empathy now than they did earlier, when they were mostly managing the machines.
One skill I think will define really good physicians in the future is flexibility and the ability to pick up new skills. This brings me to another great philosopher, Nick Bostrom out of Oxford. There have been a lot of studies looking at the pace of innovation and how fast things are changing.
If you look at blocks of time and say, let’s take 1900 to 1980 as one block, a similar amount of innovation happened from 1980 to 2000, and another similar amount from 2000 to 2012. The world is changing—and it’s changing at a really fast pace. Being flexible and able to pick up new skills is paramount.
I tell all of our trainees this: if you don't know something, historically you’d have to look it up in a book or UpToDate. But now we have models and language tools that can access resources. It’s your ability to gather actionable information as fast as possible that will define your success.
That’s a unique skill you need to continue developing. You need to be well-versed in some of these newer technologies so you can stay ahead—or at least keep up—as physicians and residents are getting trained.
Dr. Matthew Strehlow: I love that—the breadth, the knowledge, the flexibility. Andy, what are your thoughts?
Dr. Andrew Chu: I definitely agree with Dev and also want to include that adaptation is important, but we also want to protect ourselves from erosion. As part of the core faculty, we teach our residents and medical students who are using AI more and more, and the big concern we have is erosion—of our critical thinking.
We have this great fear of automation bias, where our learners are more and more dependent on the outputs of AI tools, and they're not critically thinking through them. There's a lot of power from holistic experience and seeing a patient case and thinking through it, reasoning through it over and over again.
I think that makes us better doctors. But the fear I have—and what we’re seeing as well—is that if residents and medical students are too dependent, that skill never develops or erodes. I think that is one of the biggest threats to doctors, especially in this generation.
Dr. Matthew Strehlow: It’s great to think about what that's going to look like in the future and what some of us—we're seeing that change now. It's in our space, or at least it's being asked to be in our space today. And so as of today, what's some of the most transformative AI technology you've seen in the acute care space?
Dr. Dev Dash: I think I can take this one, and I'll speak from both a provider perspective as a physician and a patient perspective.
I see my pediatrician because I have two girls, and every once in a while we go for our checkups. She spends a lot more time talking to us now because she has a tool recording our entire conversation and elements of her physical exam. I can tell that she's not caught up with documenting a lot of things in the room and is just having a much more natural encounter with two parents and two little girls than before.
It feels very different from even a year ago when I was interacting with this same physician—when they would be hurriedly moving from room to room, trying to make sure their clinic was running on time, trying to make sure their documentation was done.
From a provider perspective, I use AI scribe technologies at the bedside. We have some at Stanford, and they are instrumental in making sure that the documentation reflects our conversation. I don't have to worry about remembering all of these details. I do get a little bit worried that my memory is going to get weaker because I'm not forced to keep all these encounters in my head.
But it records everything—our conversation and elements of our physical exam. For me, the review cost of looking at a generated note is lower than writing the note myself. That is the framework I have in my head on whether a generative AI technology can be transformative at the bedside.
There are providers who closely comb through the note and make a lot of changes. I’ve never really had to do that, so maybe their personal generation cost is similar to the review cost, but for me, I can review a lot faster than I can generate it myself. I’ve found these AI scribe technologies to be transformative at the bedside.
Dr. Matthew Strehlow: Andy, what's transforming acute care right now?
Dr. Andrew Chu: I agree with Dev in the sense that the transformative products and tools changing acute care are happening behind the scenes—behind the curtains. Think of the wizard vase.
We talk about ambient documentation—it makes life easier. We can have smart assistants that help with billing and coding. This is not exactly patient-facing, but it's super important for making sure the emergency department is functioning as well as it can.
Also, thinking about technology that helps us with predicting ED surges—right around when we hit 1: 00 PM, it gets pretty crazy in the waiting room, but also at other times throughout the day. If we can anticipate that, then we can optimize staffing and think about throughput.
Technologies that address these pain points allow us as doctors to spend more time with patients and provide the care that they deserve and need. I think that’s where the transformation is happening.
And just to add to what Dev said about ambient documentation, I've used tools like DAX—they’re fantastic. But again, talking about skill erosion, speaking for myself, I also feel myself slipping clinically if I'm too reliant on that. So, I actually do write my own notes. Thankfully, I'm fast enough—I've done it so many times that it’s easier for me.
But it's those types of things—when I use large language models to sanity check my thought process, it's great, but I always check it myself and think through why that’s the output I’m getting and why I might disagree. I think constantly flexing that part of our brain protects it so that we don't lose what makes us outstanding clinicians.
Dr. Matthew Strehlow: We've had some debate at Stanford, and I’ve heard this debate from colleagues around the country and others outside the U.S., around whether we turn on ambient AI for our trainees and learners. How does that look? Can we shut off the MDM? I think there are places not using it at all for them, places that are shutting off the MDM, and others saying no—they've got to learn how to learn despite this. If you've done this for 20 years or for a long time, you can spot very quickly that the MDMs need a lot of work. The differentials need a lot of work, the plans need a lot of work. Many of my colleagues—and our colleagues—are not using that component. But I think a trainee or learner is at a different place.
I’m not sure if you have ideas on how that could look in the future. I know this is an unsolved problem, but what are your early observations or potential recommendations for people out there struggling with this question?
Dr. Andrew Chu: There's a great paper from the AMA that explores how we incorporate AI in medical education. I would agree with your colleagues who are hesitant and thoughtful about incorporating ambient documentation or any large language model tool into clinical practice.
There is a danger of “never skilling”—that’s a term used in the paper. It means trainees are so reliant early on that they don't develop critical thinking; they never develop that skill set, and that has a compounding effect throughout their training.
So I agree with the health systems and academic medical centers that allow trainees to first grow and think through the problem, developing that reasoning ability, and then augment that with AI tools. That’s my humble opinion.
Dev Dash: Yeah, it's a great point. It's kind of like saying to a toddler, “Hey, you don't need to learn how to write because you'll be typing 99% of the time anyway—why do you need to learn how to pick up a pen?” There is something about putting pen to paper with your hand that changes your brain compared to typing things out.
I wouldn't want to lose that intangible thing in the process because I think writing skills have been so instrumental in developing language and thought processes—what Andy's saying about getting our trainees not too reliant on technology.
Dr. Matthew Strehlow: I definitely write like a physician. You can read the first letter or two of any sentence, and then after that, totally illegible. I had this conversation with my wife, who's a teacher, and I was like, “This is so stupid. None of my kids can write.” For some reason, all three of them inherited that gene from me and none of them can write legibly.
She was like, “That is not true,” and she argued this with me for years. Then I went to a few lectures and read a few papers on this, and you're a hundred percent right, Dev—the process of writing is one of the most important ways in which we learn and process information.
I’ve completely flipped on that. I do see that as a nice corollary to this conversation around AI and medical decision-making and building differential diagnoses. You guys have been really positive about a lot of things, and I think when there's an AI or innovation conversation in acute care, there can be a lot of fear or negativity. I appreciate that optimism.
Can you give me a little bit more on what are one or two things that are making you most optimistic about the future of innovation in our space in emergency medicine and acute care? Andy, why don't we start with you.
Dr. Andrew Chu: I think the thing that makes me most optimistic is that there are doctors who want to be engaged with AI and technology so that we're always in the loop. If we're not engaged and we're not the pioneers spearheading these efforts, then other stakeholders will make these decisions for us—insurers or administrators.
We all have the patient’s best interest in mind, but as doctors, because we provide bedside care, we can speak to the needs of physicians, patients, and their families better than anyone else. It's really exciting for me that doctors are wearing multiple hats now. We're also thinking about technology, the tech stack, business aspects, and always about QI and patient safety elements in our work.
This new generation of doctors, who are much more adaptable, flexible, and multidisciplinary in their thinking and engaging with others in different industries and fields—it’s such an exciting time to be a doctor right now.
Dev Dash: I’m going to echo that. Being a physician—just like Andy said—there’s never been a day that I go home and question my value to society because I’m a physician. That’s one of the really nice things about being a physician, but especially about being an emergency medicine physician with the schedule flexibility that comes with it.
We don't work Monday through Friday, nine to five, when everybody else works. We work all sorts of odd hours, weekends, and overnights. The advantage of that is, if you're a flexible person and can pick up some skills, guess what? Everybody else is working Monday through Friday, eight to five.
So if you're not working, you're available for those conversations, to get inserted into projects and technologies, and to be on the front line of research—just because you’re there. It’s much harder to do that when you're running a clinic. My wife’s an endocrinologist; she runs her clinic Monday through Friday, nine to five.
It’s so much harder for her to come to some of these conversations because her clinical duties happen at the same time. It’s a lot easier to do that as an ED doc, and I think that’s one of the key differentiators and benefits of being an ER physician.
Dr. Andrew Chu: I a hundred percent agree with Dev. I love being an emergency doctor. It is hard work, it’s honest work, but it’s also the greatest job in the world. There’s really nothing else I’d rather do—especially with one of my best friends at Stanford, Dev. It’s been a heck of a ride.
Dr. Matthew Strehlow: Amazing. I think you'll find that flexibility is really nice as your kids get older too—to be able to participate in their lives, whether that's at school or volunteering. I'm glad you guys pointed that out. You’ve given us a lot to think about across innovation and the AI landscape.
There’s so much coming at most of us, and somehow you guys are finding ways among everything you’re doing to stay current. Give us a few—okay, one or two things you can do to stay current on the innovation and AI landscape if this isn’t what you’re doing a hundred percent of the time like both of you are.
Dev Dash: I’ll be a little shameless in admitting I’m frequently on Y Combinator Hacker News. They discuss all sorts of topics, many well beyond my understanding—hardware, computer systems, things like that. I like to stand on the shoulders of giants, and I’m fortunate to have two parents deeply embedded in the CS world.
I can always call my dad, who’s been in that world and did his career science PhD decades ago and is one of the foremost thought leaders in the computer networking space. I’m not afraid to reach out to people and ask questions about things, and accordingly, a lot of people reach out to me about medicine.
I think that’s a really nice conversation to have. But for me, almost every day I’m on Y Combinator Hacker News for a little bit.
Dr. Matthew Strehlow: Never heard of that, so that’s going to be a big jump for me—because when my kid came home with their very first CS assignment, I couldn’t help them with it. That’s where I was starting from a few years ago. Andy, what do you suggest for the rest of us to stay up to date on the innovation and AI landscape?
Dr. Andrew Chu: We all have to start somewhere. I’m also a big fan of Y Combinator—Hacker News is fantastic. It’s nice to think outside the box and find these great resources, but also, shameless plug: podcasts like these that touch on innovation and AI make the material accessible.
Quite frankly, I’m on podcasts all the time—listening to great podcasts like this and others, around the Harvard Business Review, great case studies on startups and technology. I think that’s a really digestible way to get your foot in the door, understand what’s going on, and have your pulse on where healthcare is going—especially in the AI field.
Dr. Matthew Strehlow: We’ll make sure we put that recommendation in the show notes. We like to end on a lighter note. What’s something in your life outside of medicine that helps you think more creatively?
Dev Dash: I go on bike rides with my toddler into the Baylands up north, right around the Google campus and the Bay, and we get close to the water and chase rabbits, which she really enjoys. I think that clears my mind. I have a gallon of sunscreen in the front of my house, so we slather it on and get on the e-bike—it makes my 19-mile ride a little easier.
I’ve always found that clears my mind a little and gives me some cardio.
Dr. Andrew Chu: I’d say Dev and I naturally see the world in mathematics and probability, and that’s great for our CS side of the brain, but I need to balance that with the arts and humanities side. What I love to do is write scripts, tell stories, or make films.
When you explore the arts and humanities—questions about what makes us human, exploring existential questions about why we’re here—it helps you better understand and form deeper connections with other people. It helps you recognize emotion, subtext, and meaning.
Those experiences—reading a book, writing a book, getting outside the hospital, and exploring other hobbies—make us better innovators because we see the world in ways we otherwise wouldn’t.
I’d say the day we lose arts and humanities to technology—to AI—is when civilization ends. I know that’s a strong statement, but it’s a real testament to how much the arts and humanities have transformed my life and helped me with my innovation work and with my children. I love spending time with my beautiful baby Sarah. She makes me a better human being, more optimistic, and grateful
Top of Form
Bottom of Form
Dr. Matthew Strehlow: Well, that's wonderful. I know that there are a lot of people out there who are thinking, okay, it’s okay for me—among all these things going on—to lean into my love of life, my love of the humanities. It’s okay for us to take the time for that.
Despite the pace of innovation, I can still be a leader in that space and manage AI as it incorporates into the health systems.
That’s a wrap for today’s episode. Huge thanks to Dr. Chu and Dr. Dash for sharing their insights, their ideas, and a little bit about themselves.
For those listening, be sure to check out the show notes for links to their work and studies. If you liked today’s episode, don’t forget to subscribe, leave a review, and share it with a colleague.
And as always, we want to hear from you—send us your questions, ideas, and feedback at the link in the description.
Thanks for tuning in. We’ll see you next time. Until then, keep taking care of anyone, anything, at any time.