Datica Podcast

April 21, 2020

Quantitative Futurist on Healthcare in the age of AI and COVID-19

tag ai

In this episode of 4x4 Health, we talk with Amy Webb a quantitative futurist and a bestselling, award-wining author. She is a professor of strategic foresight at the NYU Stern School of Business and the Founder of the Future Today Institute, a leading foresight and strategy firm that helps leaders and their organizations prepare for complex futures.

Her research focuses on artificial intelligence, and she has advised three-star generals and admirals, White House leadership and CEOs of some of the world’s largest companies on their futures. Given the emerging role of AI in healthcare in general and the massive disruption to the traditional healthcare delivery system in the face of the COVID-19 pandemic, the thoughts she shares on the future of healthcare and the role of AI couldn’t be more timely.


Transcript

Dr. Dave Levin: Welcome to 4 x 4 Health, sponsored by Datica. Datica, bringing healthcare to the cloud. Check them out at www.datica.com. I'm your host, Dr. Dave Levin. Today I'm talking with Amy Webb, a quantitative futurist and a bestselling award-winning author. She is a professor of strategic foresight at the NYU Stern school of business and the founder of the future today Institute, the leading foresight and strategy firm that helps leaders in their organizations prepare for complex futures. Her research focuses on artificial intelligence and she's advised three-star generals and admirals, white house leadership and CEOs of some of the world's largest companies on their futures. Amy is the bestselling author of "The Signals Are Talking", "Why Today's Fringe is Tomorrow's Mainstream", which explains how to forecast emerging technology. Her new book, "The Big Nine - How The Tech Titans and Their Thinking Machines Coul Warp Humanity" is a call to arms about the broken nature of artificial intelligence and the powerful corporations that are turning the human machine relationship on its head. Giving the emerging role of AI in healthcare in general and the massive disruption to the traditional healthcare delivery system in the face of the covid-19 pandemic. Her thoughts on the future of healthcare and the role of AI couldn't be more timely. Welcome to 4 x 4 Health Amy.

Amy Webb: Hey Dave. Thanks for having me.

Dr. Dave Levin: So let's get right started. I'd like you to tell us a little bit about yourself and the organizations that you work with.

Amy Webb: Sure. I'm a quantitative futurist. My job is to reduce uncertainty. So much of what I do is use data to find emerging signals, model trends. And the trends that we focus on are not trendy, they're longitudinal. So we are looking for signals of change over long periods of time. And we primarily focus on emerging science and technology. And it's those trends that we use to calculate the trajectory and velocity of change. And that is what we use to develop scenarios and scenarios are what help us understand plausible future states. And all of that gets used for the purpose of strategic planning and assessment. So a lot of what I do is risk modeling, looking for new opportunity, understanding change. And we do this in the near and long-term. And as the founder of The Future Today Institute, we work with Fortune 100's, we work with government agencies, we do some work with private equity and investment firms. And much of what we're being asked to do is to think through, what the future states are and how business needs and governing names will shift and change. And basically, how do you reverse engineer a preferred future state back to the present.

Dr. Dave Levin: Can you give us a relatively simple example of the process or some of the process that you go through to illustrate this.

Amy Webb: Yeah, I guess on the gathering information side, I'm actually standing in my home office where I'm talking to you and across from me is an enormous whiteboard that it looks like a, this is a podcast or is this also a video?

Dr. Dave Levin: It's just the podcast.

Amy Webb: Okay. But maybe you and I can have, I’ll sort of show you.

Dr. Dave Levin: That would be great. So it's going to be a scary trip inside your head?

Amy Webb: Yeah. There's a light in the way that you can kind of see there. There's like a giant network map of information and there are nodes where we see concentrations of activity connecting out to other signals, questions, things that we're seeing. And it's this gigantic map of information that we create just to get to a baseline. So the trick for most people when they're thinking about the future, I'm going to turn you back around here cause, oh, sorry were you taking a screenshot or something? So the trick when you are thinking about the future is that most organizations only focus on trends within their or changes specifically within their ecosystems. So for people interested in health, they're really just looking at health trends and for people who are focusing on agriculture, just looking at trends and ag. And the challenge of course, is that change comes from many different directions. So if you're not thinking about, you know, healthcare as it relates to artificial intelligence, as that relates to shifts in demographics or climate change or education, then you miss disruption that's on the horizon. So the process that we use is incredibly intensive. It is technology led and data driven. But we create this map of signals. We then have a pattern recognition system that we use to try to look for inflections and contradictions and basically what does this blob of information tell us? And that's where we get to you know, trends. And again, our trends are not trendy. They are really just a framing to help us think through plausible next order implications. But the methodology that we use has seven steps. And while anybody can do it, it's hard work. So you kind of have to show up and there's very little speculation involved. It's all looking for information and data.

Dr. Dave Levin: So that's really interesting. I think a lot of us walk around with the idea that a futurist, does some reading and they have a glass of wine and they sit under a tree and they think big thoughts and eventually the light bulb comes on and they know what's going to happen in the future. You're describing something very different from that very structure. As you said, quantitative, you're looking for data.

Amy Webb: I mean, the end part of that process maybe gets a little bit to that. When we get to the point where we're working on scenarios, again, we use a data driven model, but there's some element of creativity there. So we're still, our job is to imagine the unimaginable. In fact, the other thing that nobody listening can see, but you can see there's a black and white picture of a guy from what looks like the forties behind me on a shelf. That's Herman Kahn. Herman Kahn is the sort of foreparent of modern scenario writing. He was also known as "The Fat Man". He was prolific. He was at Rand Corporation and he wrote something that became known as ON THERMONUCLEAR War which for some people, you will remember at the height of the Cold War the vivid and visceral descriptions of what the aftermath of the Russians dropping a nuclear bomb on us might look like and that all goes back to him. So there is an element of writing incredibly descriptive narratives to help put some context and texture around what the next order implications are. Because if somebody's just sitting looking at a spreadsheet or a pile of data, they're probably not going to be ready to act. And the point of all of this work is not to wait for some moment in time when you take some kind of grand action. The point of all of this is to create a state of readiness within an organization to help an organization become more nimble and agile and importantly to take incremental actions on the future all of the time. Most people don't think that way and most organizations are not set up to work in that manner.

Dr. Dave Levin: This is really terrific. I'm definitely going to drag you into a discussion about artificial intelligence and its application in healthcare and with the COVID pandemic upon us. That's a fruitful topic too. But before I force you into that, from your own perspective, what's the most important or interesting thing that you're working on right now?

Amy Webb: Gosh, I'm actually working on a new book. I've written several books. My new book is about the future of synthetic biology and synthetic biology, genomic editing and CRISPR are sort of all related and I had been interested in them anyways as the result of some research I was doing a few years ago. You know, I think we are moving away from applied physics to applied biology and people should get used to thinking about biology as a technology platform. I think if they do and if we are willing to confront our cherished beliefs, there is a world of opportunity ahead. I think it's highly unlikely that we'll get a singular global point of view on what to do about climate change. And yet everybody agrees that climate change has given rise to extreme weather events, which wreak havoc on global supply chains and not to mention travel, and other things. So if it's the case that it is highly unlikely that we will achieve a global point of view and that there will be uniformity throughout all policies. China will do its own thing. The EU is going to do its own thing. The United States apparently will just not do anything anymore related to climate change. So like, that's the plan going forward then let's acknowledge that for geopolitical reasons, we're never going to be on the same page no matter what happens, and yet that problem's not going to go away. Could we engineer ourselves out of the problem? Right? So could we use synthetic biology for geoengineering? Could we use synthetic biology? And synthetic biology is simply, it's creating new organisms, new organic material that didn't exist before. And this is already being done with viruses. So I know at this particular moment in time, it's terrifying to think of somebody engineering millions of new viruses and printing them. But the truth is that, a virus is not something that's alive. It's basically just code and its code that interacts with the source code within our bodies and offers instructions on what to do next. So what's kind of interesting there, what's interesting about that is if you think of Australia, which has been ravaged by wildfires. The soil after a fire, it's difficult to get things to grow again without a lot of intervention. However, could you engineer microbes to enable better growth? Could we engineer plants and livestock that can withstand huge shifts in climate change and droughts or floods. And quite frankly, could we engineer ourselves? Could people in the future, when we talk about synthetic biology and CRISPR and genomics, we tend to talk about either designer babies or creating people who live forever. But there's other flavors here as well. So could we engineer ourselves to maybe withstand more heat or more cold? I just think that there's, in addition to all of the other stuff like precision medicine, and maybe being able to identify in advance where the next viral outbreak will be versus scrambling to try to do something after the fact. So I would say I was already interested in that and I'm already, I was already working on a book about that. Then COVID-19 happened. And we're seeing where there was already a pretty significant global investment and synthetic biology. I mean, we were looking at, I am trying to read my notes on my board, like $23 billion by 2023 I think is our, what we were looking at. It's a pretty big market. Given all of the investment now in racing to find some kind of vaccine to build out tests, to look for antibodies. This is going to catalyze additional funding in the area.

Dr. Dave Levin: So let's go ahead and stay on COVID-19 since we're there. And asyou and I discussed right before we started the podcast, when we originally scheduled this, maybe this was on your radar, but it wasn't on the general public's radar. But here it is now. And so my questions around this for you are really twofold. One is, it's kind of the Metta question. How do you even think about predicting the future around an event like this? And then after that, if we can push you a little, we'll see if you've got any predictions, you're ready to make now. So again, how do you even begin to think about attacking something like this?

Amy Webb: Sure. So I would say the first thing to notice that futurists typically don't make predictions. Our job really is just to reduce uncertainty. So the goal really is about preparation versus prediction. Now we've got a discreet, now you can build models. So, given what we know, I don't know all of the models that are being talked about right now, the South Korean model, the Italian model, gauging the curve and exact numbers and exact time, that would all be predicated on having accurate data. And we know that we don't have accurate or comprehensive data. We don't have it city by city, state, by state, country by country. Bad data in means bad data out. Now, it doesn't mean that we're not in the middle of a crisis, but I use this as a point to illustrate the challenges in thinking about the future. Humans are just wired against uncertainty. So because we don't like uncertainty and we want answers, we tend to wait until some model or some prediction tells us that this is the time, and that's exactly how we wound up in this mess. The problem is that there were conflicting ideas, the wrong data and rather than at some point in December or November, folks in the United States as well as elsewhere around the world saying, "This appears to be a new virus". Historically we don't do well with novel viruses because it takes us a very long time in our existing, because of our existing policies and government structures. It takes a long time for us to look for a vaccine to get through FDA regulations and all of that stuff. So it would have been good for somebody to acknowledge that and then say, we have to think through what our next step is and what our next step and the step after that. So what are all, what's the chain and what are the implications? The problem is that we tend to be inactive and to be reluctant to take action until there is some kind of proven, if I was talking to a business, I would say like proven ROI. ROI seems like a weird acronym to use with a life-threatening disease, but you know what I mean, like some kind of proven whatever number, a data set that describes catastrophe and this is a problem that I think plagues business, it plagues government. And it's something that we should acknowledge that as individual people, this is something that we, this is a problem. We have a cognitive bias. So, going forward, this really isn't about making predictions. It's about being prepared. And I actually think that if we could shift our mindset on this a little bit, there's opportunity here on the other side. I mean, I know that sounds crazy now that we're facing 200,000 potential deaths. But there is some opportunity here as well.

Dr. Dave Levin: Yeah, I agree completely there. There's opportunity here. There's danger as we navigate through this. The other thing that you said earlier that's sort of strikes me is, the fact that we're having a pandemic or that a pandemic is occurring is not a surprise. People have known for a while this has happened in the past, but I read something the other day though that there was a failure if you will, to connect the dots and the way you described earlier of recognizing more. If this is a pandemic that spends rapidly, what's the economic impact of everybody needs to go home.

Amy Webb: And also the next order impacts, because there's the economic impact of what happens if everybody has to go home and also stay at home for X amount of time. I mean stop like, so stop and think through the implications of that in weird ways. So most city governments rely on parking tickets and speeding tickets as a central part of their budgets. So if we are all, I'm under stay at home order. I'm assuming you're an under a state home order, shelter in place. So I’ve not gotten into a car now in three weeks. So I am a very low probability event of like getting a speeding ticket. When we're not in a shelter, in place order. I might be on the higher side of that...

Dr. Dave Levin: Theoretically.

Amy Webb: Theoretically speaking. But the fact remains. I live in a neighborhood with multiple, I mean like a ghastly number of cameras to catch people speeding, going through lights, whatever. So we know that that is a fundamental part of our local city budget, and we also know that most city budgets don't run surpluses in the United States. Most of them are running either at a deficit or they're right on the line. So that means, what does a two month or even one-month shelter in place order mean for a city budget if there's no parking tickets and there's no speeding tickets. So now let's think about education. So everybody's staying at home. Yes, that means everybody's now, homeschooling. But think about the budget implications of this as well. So most States have lotteries and there's two national lotteries. The money from those lotteries goes into state education budgets. So I haven't looked at the data, but I think it's highly improbable that the number of people buying lottery tickets is at the same level, anywhere close to the same level as it was before. There's nobody's hanging out in grocery stores or gas stands or whatever. So this is why if you're only paying attention to the news and you're looking for signals about what the future is going to look like, it's a little bit like looking through the entire world, looking at the entire world through a pinhole. You have to think through all of these other areas. Now, I just presented two risks scenarios that I think are high probability, but there's also a bunch of opportunity scenarios. So in the United States, there's been no Telemedicine. I am married to a doctor, so I will be the first person to say Telemedicine may or may not be good for my family. If all of a sudden, we've got increased competition from other doctors out of the area on a network. However, that being said, I mean, if we don't have to, if, if people in the United States don't have to go all the way to a doctor's office for that initial 10 minute consultation, which we all know only leads to the follow-up visit, and if that's still HIPAA compliant and if the ICD 10 codes still cover it, then like, I think that's a win for everybody. I mean, it potentially means we have better, a little bit of better access to our physicians in a way that we didn't have before. So to me, we're rolling back Telemedicine policies all over the country. I don't necessarily think that's bad. And I also think it's going to, it's not necessarily bad, but it's also potentially catastrophic as I'm saying this out loud, because that opens the door for like a huge CVS or a Walmart to set up, to set up economies of scale at a much bigger level. So anyhow, lots of changes.

Dr. Dave Levin: Yeah. I think the Telehealth was a really good example. It's playing out in the real world right now. My thing's digital health and what I’ve seen is, I think we've made more progress in the last two weeks than we made in the last two decades. When I talked to my colleagues about this, there's a sense of, it is a kind of ratchet. We're not going back. I mean, there'll be some retrenchment, some return to the way we did things, but very disruptive. One analogy I heard is, this is going to be like the way air travel changed after 9/11 and we can debate what was good or bad about that. But we haven't, for the most part, we have not rolled back the things that we put in place in terms of TSA.

Amy Webb: I don't know. I guess when I think of, I don't know if that analogy works for me because in the wake of 9/11, we wound up with more restrictions. I think in the wake of this virus, we are seeing fewer restrictions.

Dr. Dave Levin: Right, yeah. I think the point was that big change and unlikely to see things revert back to what they were before. Yeah, there's no question that the demands of the pandemic as well as the relaxation of some of the licensing restrictions that now CMS has come beside and has really trued up on the payment side is driving that. So the other sort of second order things I’ve been thinking about because I live in healthcare day to day is, what’s going to be the impact of all these delayed elective procedures? What's going to be the impact of people with chronic disease that aren't going to get the access and the quality they need? And I'm particularly worried about mental health and where being together as part of the therapy. We've got an opioid crisis in this country. We have issues with other substance abuse, alcoholism, and a big part of the treatment for that is to gather together. So how's that going to work? I'm seeing people replace some of that with virtual meetings in the like, hard to know how that's going to be.

Amy Webb: So I’ll address that last question last. I think the first part of the question really goes to the heart of healthcare in America. So I’ve lived in a couple of different countries. I've had access to a couple of different countries worth of healthcare systems. When I at one point lived in Japan, I remember I got sick once and I was living kind of in a rural area at that point, and there was just like, I could walk to this like doctor's clinic and it was like, it was his clinic. It was not owned by; it was not part of a healthcare system. It was just a guy with his clinic. And it felt a little bit like for those who watch Northern exposure, like I felt like I was in the middle of nowhere, going to some quacks' crazy practice. It was one of the better exams I’ve ever had. When I walked in, there was a nurse type of person, but there wasn't, there was not an onerous amount of paperwork to fill out. I simply handed my identification card over and then he sat with me and asked me a bunch of questions, which began with, what is my temperature? Has anybody ever asked you what your temperature is without holding a thermometer? So here's why I bring that up. And I was like, I don't know, it's 98.7, you tell me, like whatever that is in Celsius. Why are you asking me that question? And he was like, why don't you know what's your temperature is, what is your blood type? And I was like, I think it's, whatever. They thought it was ridiculous that I did not know my own baseline biometrics. And when you stop and think about it everybody's normal temperature is different. It's not 98.7 that's simply like an amalgam that we kind of use as a benchmark. But the truth is it's totally different for everybody. So if your normal temperature is 97.4 and today it's 98.9, guess what? You actually do have a little bit of a temperature. But if we're all saying 98.7 then it doesn't matter. That to me was this revelation that I was like, wow, it never occurred to me. And I said, well, how do I know what my, hey doctor, how do I know what my temperature is? And he was like, you take your temperature every day for a couple of days and then you are like know what it is. Do they not teach you anything in American schools? And so every person knows their normal temperature. Every person at some point has had a urinalysis. So they have some basic understanding. These are just, and the key difference. And then like, I got to the end of my visit and I had a choice between Western medicine or Eastern medicine. Now for cancer, you don't get a choice. You're going to have the Western, but if you've got the flu or if you've got like a head cold, would you rather take herbs from this packet or would you rather take these this cough syrup or these pills you decide? And again, I was flummoxed. I was like, what do you mean I have a choice? Like I'm not a pharmacist. You tell me what I'm supposed to take. They said, but I don't know your body. And all of these things have been formulated differently. Do you tolerate herbs better or do you tolerate... So, I just remember coming out of this thinking, Holy hell, like there's all totally different way to do healthcare? Now, six weeks ago I had what I thought was some kind of head cold that was going around, the thing that's going, the virus. Whatever, before thee virus, right. I've got something rhino virus that's going around. And I felt fatigued. I felt a little bit of a body ache and a little bit of a lowgrade fever, which I knew because now I know what my temperature is. And I like slept for two days, which for me is highly, highly, highly unusual. After this, I had a cough and the cough was persistent and nonproductive, and I called my primary care physician who was like, I’ll prescribe you over the phone, something, some kind of drop. And I'm like, but don't you need to figure out what's going on here? Well, you don't have to, if you don't want to, just try the medicine, which I thought was stupid. I like my doctor, but I thought that was a dumb response because I'm somebody who has in the past had a couple of these colds that morphed into persistent coughs. And so I was like, okay my husband who was an eye doctor and literally doesn't do anything from the nose down is all I got to help me with my diagnosis. Well, you had childhood asthma, you got that weird tracheal bronchitis thing like 20 years ago, so you must just, I'm assuming that my diagnosis is anytime you have a cold that's respiratory, it inflames. Like there must be scar tissue. And I'm like, that sounds reasonable. What do I do? Eh, just wait it out. So it got to the point where I was coughing literally nonstop and could not breathe. At which point, I don't know what I'm supposed to do. I called the local hospital; I don't know if I’ve got Corona virus. I don't know, that would have been on the very early side of community spread, but because of where I live and what I do for a living, and then I travel, it's tough. I don't know what to do. There was no guy at the corner of my block who I could walk down to ask. So I call pulmonology specialists, nobody can get me in for months. And I said, but I can't stop coughing. And they said, well, why don't you go to the emergency department? And I said, because I don't want to catch, I don't know. So then I decided to go to an urgent care because there was nothing left for me. Super nice people, nurse practitioner, probably very, very knowledgeable, but not a pulmonary specialist. And ultimately, I said, listen, in the past, like a combination of albuterol and some steroids has stopped the cough. Just give me that and I guess I’ll deal with this later. That's crazy. Did you understand that, and so I think what we are going to learn during this virus period, we're already seeing the fragility of our healthcare systems and we have a very different system in the United States that is predicated on, it's a commercial system. We've got fewer beds than in the past because of, so normally when we're not facing a pandemic, the system doesn't fall apart. We are now seeing; I think in great magnification the problems that the existing system had and the challenges going forward.

Dr. Dave Levin: Yeah. Very little resilience built into the system. And typical whole systems operating on a very thin margin. So there's no surprise they don't have 500 extra ventilators in a storage shed somewhere.

Amy Webb: I totally agree, but there's also a regulatory breakdown. I mean the fact that, if it’s a regulatory and a patent breakdown, so, I’ve got a house full of robots, I’ve got a 3D printer sitting idle. I am more than happy to donate that printer to start mass producing the missing parts of respirators. There was something going around a couple of weeks ago, no problem. And there was somebody used CAD, they like created the design so that anybody could print it. It violated the patent and the company that had the patent on that, threatened patent infringement. And it's like, at some point, and I understand that the FDA exists for a reason and that all of the regulatory frameworks and the oversight and the audits, I understand why all of that exists. The challenge is that there is no flexibility built into any of this. There is none. And because there is no flexibility, the only time that works is if you somehow know exactly what the future is going to look like. So it's fine. You build yourself a system that has zero flexibility and absolute rigidity. That's cool. As long as you are omniscient and you know everything that's going to happen in the future, that does not describe any person or entity or company that I know. Which tells us that every strategic plan must account for uncertainty. It means that every government agency, every policy body, everybody must have some firebreaks in there. There must be some accounting for uncertainty and the acceptance that we do not control every single variable. That is how we got to now. Right?

Dr. Dave Levin: I think that's right. And I definitely agree with you. There's this, there's been a kind of breakdown in oversight in regulation as well. And the role of state and federal government to mitigate some of the things that, I don't think it's realistic to think that the private sector on a for-profit basis is going to last.

Amy Webb: I totally agree with you. And again like, I think if we were going to saddle the States with all of this responsibility, it would have been useful to tell them in November/ December. "Hey, if it gets bad, this is the plan. We all have to figure this out." But to waffle back and forth and to have so little decisiveness at a federal level, poses a huge challenge. It's crazy to me. I could not, yes, we always track pandemics. Yes, we're always tracking, but I could not have predicted that Corona virus, this COVID-19 was going to break out at this particular time and have this particular impact. I could not do that. Right. However I could, I could have absolutely said, something that involves a virus that we detect too late and can't control the spread of will happen. Why? Because we've got plenty of historical examples, because we've only identified what 3000 viruses, I mean, some poultry number. So again, like basic statistics tells us this is high probability event. Just plan for it. Plan and exacute.

Dr. Dave Levin: So this is really good. I want to pivot now to a little bit of discussion about artificial intelligence. This is an area of special interest for you and research. And I'd like to explore a little bit about what’s what you see coming for healthcare and to use your language, the risks that we need to think about that come with this as well. So begin by giving us your definition of what you mean when you use the term artificial intelligence.

Amy Webb: So, artificial intelligence is not a tech trend. It's not a single technology. It's sort of an umbrella term that encapsulates many different technologies. But at a base level, what we're talking about is having a set of data and creating insights from that data. In order to automate something. So automate a process, automate a part of a workflow, automate something as simple as the spell correct in your email. When we talk about artificial intelligence, we tend to conflate that with something like the Terminator. I don't know how like, it depends on when you were born, there was a science fiction movie or book. Right? So I think what's important to remember is not to conflate the robot, which is the container with the code, that is the, AI system. So that's in a nutshell what we're talking about and we use AI all day long. The interview that you and I are having is made possible by artificial intelligence. So this is, it's been a part of our lives for a while and we are on a many decade trajectory into the future where this is simply the next era of computing.

Dr. Dave Levin: So let's start generally and share with us what you see in terms of the pros and cons or the potential benefits or pitfalls of artificial intelligence. And then I'd like to drill more specifically into your thinking around it in healthcare.

Amy Webb: Well, I mean, I think it's easier to talk about pitfalls and opportunities using a subject.

Dr. Dave Levin: Go right there then.

Amy Webb: So some of the opportunities are, should at this point be I think obvious for companies and organizations that are going through digital transformation or if you haven't started yet, you should. Robotic process automation. So this is a lot of the simple repetitive tasks involving structured data. Like think of every patient who comes through every office that fills out 10 pages of the same information over and over and over again. It's a lot of redundant work on the patient side that somebody has to then enter all of that data into a system somewhere. So RPA offers some efficiencies, ways to automate that process. And just to make it easier, reduce staff hours, increase accuracy and then once you've got all that data into a meaningful place, which may or may not be your EMR or your EHR, what's interesting is that you can then learn from that data over time. So there's a ton of opportunity and I think efficiencies with the patient data and the patient records, but then also efficiencies in the work streams within the various different organizations. And this would be true of any industry. Where do you have productivity lapses? Where could you be finding greater insights? Where are there costs savings? And I think this can be done in a way that doesn't jeopardize the overall quality of care being given to the patient or to the learning that might happen at an institutional level. And there's a ton of opportunities there. There's some obvious ones like using AI for diagnostics. So, everybody likes to, is this a clean podcast?

Dr. Dave Levin: We are PG 13.

Amy Webb: So everybody, well then, I can't say what I was going to say. Everybody likes to make disparaging remarks about IBM Watson. Especially those, sort of within healthcare. And what I often hear is the system doesn't work. People still do it better. And I think that that's coming from a place of concern and uncertainty about the future. It's not that the algorithms didn't work, it's that the data is locked away in somebody else's proprietary system. And if you don't have a big enough Corpus, you got to supplement. And so they wound up using synthetic data. The challenge was synthetic data is that it's made by humans and we're going to forget stuff. So if we can think through, there has to be a way for us to protect privacy in a reasonable way and also learn from the available data from all of these people who have all of these things wrong with them. I mean, it's insane to me that we've allowed proprietary systems to sort of take over and pollute what otherwise might be a real opportunity to improve diagnostics. And by the way, that does not obviate the job of a doctor. I mean it might obviate some of the jobs that currently exist in some fields like radiology. I mean let's face it, do we really need, does it really makes sense for a person to do all of that work or does it make better sense or the first pass to be an AI system where it's looking for anomalies and then even if it doesn't find any at that point, have your radiologist or your oncologist go through and look at this, just for verification. So again, I think we've been attacking this the wrong way, and everybody loves to point to failures. Everybody's afraid to think through opportunities. So there's a bunch of great things happening. Now on the flip side, there's a lot to be concerned about. For one, our big technology companies are very quickly getting into the healthcare space. That in and of itself is not bad. The question is around what happens with those data and really what does it mean for a commercial entity to...we've already seen challenges with making much of our health care under the sort of purview of the private sector alone. And it's not that the private sector is bad. I think the consolidation is the problem. So we've kind of gotten ourselves into this bind in the US where we have just a few corporate labs doing all of the testing. We have just a few companies that make the stuff that the corporate labs need. We have just a few EMRs. We've reduced competition and therefore we have, usually reduced competition leads to increased rigidity and that's a good recipe for failure. So on the one hand, it's not bad for Amazon, Google, Microsoft, IBM, to be getting into the healthcare space, which they are. That being said we really need to think through the next order impacts of huge technology companies which already have unbridled ability to persistently surveil us. We need to think through the implications of also giving them home diagnostics for example. And the ability to track us, and our wellbeing and our health wherever we are.

Dr. Dave Levin: Boy, there was a ton in there. Like you, I actually welcome these new entrance. I do think that they're going to find out healthcare is a lot more complicated than they understood upon entry. I also think those of us that have marinated in healthcare for a long, long time need to be shaken up a little bit and that it's going to be the mashup of the old and the new that will get us there. And its sort of something I’ve tried to practice in my own work and health IT. It requires a constant psychological vigilance; I think to be open there.

Amy Webb: Yeah. That's the key. It's the open-mindedness. There are too many, I run into too many doctors who just will like, just now to be fair, I was going to say is they like, they will not change. However, that being said, any physician or surgeon, anybody who's at an upper echelon of the medical profession who's like 55 or older, has lived through an incomprehensible transition from, small practices to small practices plus computers to all of that plus consolidation like MNA, and consolidation to all of that plus crazy insane changes in insurance and insurance billing. So I can't imagine what that professional transition must've been like. So I understand. I totally understand the resistance, I get it. I mean, I'm sure people at this point are like, screw it. I'm not doing anything else. I'm just going to retire, be done with all of this. Like, I get all that. I do.

Dr. Dave Levin: There's some of that. I think the changing social contract has played a role too. And I do get a little frustrated when people say, well, doctors don't like technology. I hear that typically from health IT people. And my answer is obviously you've not been in an OR, an ICU anytime recently. They're full of technology, but what doctors and nurses and others don't like is bad technology, technology gets in the way of them doing their job or it introduces unnecessary complexity and that sort of thing. You've touched on something else though that I think is really interesting. I think I do expect to see disruptions in that work force. When people ask me, my general advice has been, if your job involves a lot of pattern recognition, that's probably not a field that's going to do well in this new world. And you mentioned radiology, I think pathology is another one that subject to that. And I do like the way you framed it, which is I think of it as a kind of hierarchy and there's going to be stuff where the machine as you were to a very high degree of reliability is correct and those to just pass right on through. And then they're going to be edge cases and confusing cases and others where you probably want a human being involved as well, or a group of human beings or some other sort of combination of process. Does that make sense to you? I'm a little nervous speculating here in front of an expert.

Amy Webb: No, I mean, here's what I would say. So one of the core questions as a futurist, I'm always asking myself and others is what would it take for X to be Y? So what would it take for your field of medicine to be fully automated? And you have to answer that in a granular way. So, at some point that would mean somewhere along the way a bunch of people got together to figure out what all the factors are, that would go into diagnosing somebody. And at some point, like a machine learning system would be able to develop its own factors. But there still has to be a sort of a pool of information. And the challenge is, there's no way wherever going any group of people is ever going to be comprehensive. That's why sometimes it's just a back and forth and back and forth. Also, there's the fluid diagnostics or the physical diagnostics and then there's the talking part. And the question is, are people more willing to give honest and open information to a person they're looking at or to a machine? That's a little different for every person. But let me give you a quick example. So my husband was seeing this patient, I'm not going to violate HIPAA, I promise. There was a person, not going to reveal the gender or the location. And this person had some kind of crazy like, look like maybe they were losing vision, couldn't figure out what's going on, had seen a bunch of specialists, winds up with my husband who goes through the usual sort of set of checks. So the usual set of questions that would show up that ostensibly one would put into that AI system. So he get to the end of this and of course, like nothing is showing up out of the ordinary. And then he starts saying, well, by any chance do you take some kind of herbal supplement or I don't know what it was. But he was like, Hey, by any chance, are you taking, because she had mentioned, she was feeling kind of lonely, she was feeling. And so he surmised, Oh, she must be feeling anxious, depressed. There are herbal things. So like, you have to think creatively and then once he figured that out, he was like, just stop taking that. You'll be fine. And she was. The thing that humans can still do pretty well, but machines cannot, is think creatively. So you're sort of wrote brute force pattern recognition. There is a something here that should not be. That's probably going to go away. Those jobs will go away. But a lot of this more complicated diagnostic work especially as people are living older and our diseases are getting weirder, and we learn more about the body. I think that there is still very much a role for humans to play. It's just a matter of having a different set of skills and being open minded using technology in concert with the work that you're doing and taking a more holistic approach, which takes me back to Northern Japan and that crazy guy down the street from me.

Dr. Dave Levin: Well I love the crazy doctor story cause I trained in primary care and practice primary care and the two things I would say in response are the science can tell you what the options are and perhaps some of the probability of the outcomes, but it doesn't necessarily tell you what the right choice is for you as an individual. And the other thing is, and you touched on this, I think this is a really fascinating question about how people engage and at least to my read, it's not clear that there are some circumstances where people appear to be more comfortable and more forthcoming when they're dealing with an inanimate machine than they are when they're dealing with another human being. And then the reverse is true as well. And I think this is part of the art that we're going to have to figure out here. Talk to any one of my primary care colleagues and they probably have a story. I have many of them where the patient has come in and whatever has gone on before is not working for them and it just doesn't make sense. And you close the door and you sit down, and you look them in the eye and either you or they say something that completely changes the course. And I don't say that to be defensive about that style of practice, but just to point out that there's a place for both. And part of the wisdom we're going to have the divine is how do we use the two in the most effective way. Before we run out of time, I want to talk about this issue of the quality of the data. Because this is one that concerns me greatly. At least in my understanding, if you look at sort of traditional medical research, the research tends to bias towards study in white, middle aged males. And so a lot of the data that we have is based on that population. Obviously, our population is far more diverse about that. And so when you talk about the power of some of these algorithms is based on those data sets, I really wonder how that's going to play out.

Amy Webb: Well, it's not playing out well. We already know this. And to try to resolve some of that problem. I think it was the Obama administration, I think this was tied to the Obama administration. There was a plan to try to get a million people of color to take some kind of genomic screening or tests. You probably know more about that than I do.

Dr. Dave Levin: Don't know the details of that, but I know there've been a number of efforts to get greater diversity of those data sets.

Amy Webb: The problem of course is historically things have not gone well for certain demographics when they've been asked to, stand up and be counted. And I think if we all recognize that there is a problem with the data and there is, this is like not a big secret. If that's the case, then again, what would it take for X to be Y? What would it take for there not to be a problem? The answer to that is obviously more data from a diverse, from a much broader diverse data set. What would it take for that X to be Y? It would take people, it would take trust. People would have to be willing to fork over their data. But then what would it take for that X to be Y? They would have to be in a circumstance where they are visiting healthcare practitioners when they are not under duress only. So that tells us a bunch of things. Cleaning up the data isn't just a matter of cleaning up the algorithms and like making better algorithms, having better data sets. There's a systemic issue. So you need to get people to trust in the testing and you're not going to build that trust when they are only visiting you when they are having some kind of crisis. And by the way, you know going to an emergency department is not all, like it's not as much fun as it used to be. I mean, you're there for hours and hours and hours. So I think if we want to advance, I think if we all like, why are we doing all this? What's the point? What's the point of artificial intelligence in healthcare? What's the point of all of this? The point to live a better quality of life, I think. Maybe that means a slightly longer life or a really long life. But I think it means basically being healthier. And if you're healthier, you have a better quality of life, you're happier, all of the rest of it. So that tells us that we need to shift our mindsets from triage to preventative care, to holistic wellness and to build the kinds of relationships and to make that affordable. I realize I sound like I'm shelling for Bernie right now. I'm not, but we have to have a system where people have better access to healthcare on a more regular basis, not just when they're sick.So that they understand, every person should know what their temperature is. Every person should know what their blood type is, and a bunch of other things that. That will create a situation I think in which more people are giving over more of their data. We have better systems and sort of like all of that leads to better outcomes. I mean, to me the explanation is an easy one. Implementing that is more challenging.

Dr. Dave Levin: Yeah, I agree with so much of that. And I would add just from a technology standpoint, we've essentially completed the first round of what I call health IT 1.0, the basic digitalization of healthcare. We've got obviously much, much more to do to build on that foundation, but for the first time in history, we're approaching the place where it's reasonable to think that that kind of data could be collected, shared, analyzed to do the sort of things we're talking about. We got doctors and nurses to put down their pens and start using a keyboard, which is sounds kind of trivial when you say it, but actually it was pretty major accomlishment in healthcare. So Amy I could talk to you all day long, but mindful of time. I'd like to wrap by asking you one of my favorite questions. What is your most sage advice?

Amy Webb: I think the one recommendation that I would make to everybody is to be willing to confront deep uncertainty with deep questions. And to do that all of the time. And if you are not somebody who believes you are swimming in deep uncertainty you must be living a very blissful, very sheltered, very confusing life.

Dr. Dave Levin: That's a good one. Embracing the ambiguity, learning to navigate that, all of that. I really very much like that. Amy, thank you so much. We've been talking with Amy Webb, professor of strategic foresight at the NYU Stern school of business and the founder of The Future Today Institute. Perhaps we'll get you to come back in a few months and we can pick up this conversation.

Amy Webb: Sounds good. Stay well or as well as you can be given the circumstance. Thank you.

Dr. Dave Levin: You've been listening to 4 x 4 Health sponsored by Datica. Datica, bringing healthcare to the cloud. Check them out at www.datica.com. I hope you'll join us next time for another 4 x 4 discussion with healthcare innovators. Until then. I'm your host, Dr. Dave Levin. Thanks for listening.