Taking Healthcare by Storm: Industry Insights with Dr. Anuruddh Kumar Misra & Anuruddh Mishra

In this episode of Taking Healthcare by Storm, Quality Insights Medical Director Dr. Jean Storm speaks with Anuruddh Kumar Misra, MD, FACP, FAMSSM, QME, DIP ABLM, a triple board-certified physician and non-operative sports medicine specialist, and Anuruddh Mishra, founder of August AI.

Dr. Misra and Anuruddh share their journeys into medicine and technology while exploring the evolving role of AI in healthcare, its benefits, limitations, and future impact, as well as the importance of balancing innovation with human empathy and clinical judgment in patient care. 

If you have any topics or guests you'd like to see on future episodes, reach out to us on our website.

The views and opinions expressed by the host and guests are their own and do not necessarily reflect the views, positions, or policies of Quality Insights. Publication number QI-020626-GK

Transcript

Welcome to "Taking Healthcare by Storm: Industry Insights," the podcast that delves into the captivating intersection of innovation, science, compassion, and care. 

In each episode, Quality Insights’ Medical Director Dr. Jean Storm will have the privilege of engaging with leading experts across diverse fields, including dieticians, pharmacists, and brave patients navigating their own healthcare journeys. 

Our mission is to bring you the best healthcare insights, drawing from the expertise of professionals across West Virginia, Pennsylvania and the nation.

Subscribe now, and together, we can take healthcare by storm.

 Hello everyone and welcome to another episode of Taking Healthcare by Storm. I am Dr. Jean Storm, the medical director of Quality Insights, and today we are gonna be exploring the intersection of human intelligence and artificial intelligence and what it really means for the future of medicine. I am joined by two incredible guests, Dr.

Anuruddh Kumar Misra, a return guest. I will say he's a triple board certified lifestyle and sports medicine physician, medical director, and consultant to several major league baseball teams. And Anuruddh Mishra, a visionary health tech leader and founder of Beyond a Research led startup. Reimagining how people understand and manage their health through AI driven insights.

So we're gonna be talking about how they came to do what they do, what AI is getting right and wrong in healthcare, and the balance between data and humanity, and how both believe we can build a healthier, more intelligent future. Gentlemen, Anuruddh and Anuruddh when we were set Chatting Yes. Before the show.

 Same name.  Different spelling, but pronounced the same. Thank you very much for joining me today. So grateful. So let's just jump in. You both came from very different paths, one from medicine and one from technology. What first inspired you both to pursue your respective fields and how did your journeys eventually intersect around AI and healthcare?

Sure. I, I'll go first on that one.  Obviously in the medical profession  things early in life sometimes make quite an impact or impression on you. And, and in summary, um, had uh, some family members who had some, some, some pretty striking health issues. I've seen you know, what, to me seem miraculous interventions from a medical standpoint too.

Get someone back to a better place with their condition, let's put it that way. And, um, seeing that, was captivating for me and I always wanted to be sort of a healer. I think that's kind of where it comes from. So that was sort of my personal inspiration and, and secondly, that's ducktails back to the prior episode, which was that also as a child, I've always been very big.

Enthusiast, if you will, about sports, whether I was a fan or liked to play, and I always looked at athletes as  like the paragon of health, and I always envisioned. Wow, it'd be great to be in that ecosystem of the athlete, as I understood it, as a child. And as you progress in your growth and career, come to learn like, hey, there's something called sports medicine and hey, there's a whole field dedicated to.

Keeping these people going, it isn't just merely getting to the highest levels.  It's also staying in that   you know, these careers tend to be short.  So what are they doing that's keeping them performing at such a high level and sometimes for many, many years. So that's sort of where my medical kind of start, got christened, and then from which point it evolved with those priors from my passions, my enthusiasm, and just my, my, my zeal for all this.

And Anuruddh. Do you wanna answer the same question? Yes. So I think one small correction Jean  the company is called August ai. Now Beyond was a working name before the product had a name. And yeah, I think my journey has been interesting. So I'm an engineer by trade.

 I've also been writing code since like I was 10 years old and I was formally sort of working in that world until at 25 I had a misdiagnosis for rheumatoid arthritis.  So, to paint you a, a little bit of a picture and I think we are familiar with what arthritis is, but. When you're 25 years old and you're giving, giving them, a diagnosis for rheumatoid arthritis, that pretty much means it's gonna be early onset, rapid onset, and you can manage it.

All of that is fine. But the scariest thing is somebody who's not a healthcare practitioner, right? That, that you read is somewhere on WebMD and says, if you get rheumatoid arthritis at 25, you have two to three years and then you're gonna end up in end state ra. And so I lived as a patient because a rheumatologist had told me, Hey, this is rheumatoid arthritis.

 I lived as a patient for four months in pain,  trying to manage this condition that I thought I had, and I think that's what shifted my attention to healthcare. Once that misdiagnosis got cleared, I think that attention stayed and, and I got really curious about the space because.

What I think people don't realize truly until something goes wrong with their health is that  is just how important like health and healthcare as a system are to a patient's life. And yeah, I mean, thought about that a bit  and decided to start something in this day. I'll say I'm, I'm a big fan of curiosity and  yeah, getting curious really, I think lead you to interesting spaces.

So  when you look at where AI is today from predictive analytics to personalized medicine, what do you think represents the current state of AI in healthcare?

Are we still experimenting or are we actually already transforming care delivery?  I think the answer is a little bit of both.   I'd say it's mixed and not entirely well understood by most   where things are. And I'm glad you asked the question that way because there is what's happening.

There's also the fact. There's a lot of detachment from what people would know is taking place. Just a, sidebar  it's been shown not pointedly in the industry of medicine, but just as such that many times when people get these messages to do whatever  pick up their laundry or who knows what, they actually can't even tell a difference between whether it was AI generator or some human actually.

Stimulated them to do that.  So some of the things I see in real time is like the electronic medical record. If a patient messages and says, Hey, I have  some problem, or I need med refill, or whatever it is, it now autogenerates a response, which is sort of a draft and it's pretty okay.  But if someone knows that person well, like if. Two of you know me, if I just send that, like you would know, I didn't write it like it's my writing style, the way I talk or how punctuation like, so that's already going on and there are much more advanced things than that and I'll let him speak to this, but there are LLMs where you can just walk in and outta the room and the whole note is done.

   You would appreciate. State this, that one of the biggest areas of inefficiency for physicians is just the EMR.  Just like charting itself is    feels like for the birds, right? So I see it in some ways that it's an assistant or kinda like having an intern or a student.

It can do some basic things  well.  But it does require a little refinement. So that's sort of how I see it from my perspective. That and then more broadly, right, if there's a patient I'm stumped on, it can help expand the thought bubble. Definitely for sure.  Differential diagnosis expanding different treatment options, things you may not have thought of that could be useful.

So those are other things. We've always sort of done that. Going back to residency, like a Google search, whatever, not to say that  something like chat GBT or these sort of commercial products are just like a glorified Google search in some sense. They are at times, but. This is where the interface is in real time and, but there's a lot more exciting things around the corner.

So I'll let him speak to this 'cause he knows more about it than I do. Yeah, please. Yeah, I think in order to look at sort of where AI is in healthcare, there are a couple of things that we need to  put into perspective, right?  And one is the scope, right? So let's only talk about like generative AI systems because traditional AI has been around for a long time, right?

Like AI that analyzes a radiology scan and does something. And when you look at like generative AI systems, which is like large language models, those have only been around for  three years and we've made a lot of progress. So it feels like they've been around for a very long time. But these systems are getting much better every day.

So to that extent, I think everybody's constantly in an experimenting phase. One of the most interesting things that happened with buck trend that  most people predicted was that healthcare is actually adopting AI a lot and in a lot of places, in a lot of ways, right? So there's the perspective from a clinician where we had like an AI scribe, and then those are just getting much, much better.

Some of them are now entering into sort of the CDSS kind of role where they'll not just transcribe, but also give like a draft. And I think that's what Dr. Misra is referring to. But then you also have a lot of work on the front office and back office part of healthcare where a lot of AI is being deployed.

So between health systems and insurance, between insurance and health system, on the back office side, a lot of the admin workflows.   I recently somebody had said this to me that there are 200,000 nurses in the US that man telephone lines. And we should like  they're all slowly being replaced with AI that can just speak and sort of attempt to do their job. And those systems are, I think, when it comes to healthcare early there, there are some clear winners, particularly on like the admin and just  do very road test site, which where we're gonna see things stick. And for the rest, I think it, it's still like we're gonna see some combination, especially like front office voice, ai I think that's here to stay.

But just how much of the entire answering a phone role that it can do is something that we're going to find out as these systems keep getting better. I'm very excited to see how it goes. And you kind of on that, thread in your, both of your experiences, what are the areas where AI is excelling?

 Is it clinical practice, is it population health or patient engagement, which is a huge growing area. I was happy to speak to that first. I think what he spoke to there really is a good lead into that because those. As he said, areas which are here to stay, which is you call into a clinic and then it can walk you through a lot of things.

Are you calling for med refill? And  it can make things a lot smoother and reduce the the scut work, if you will  for things like this. So I think those are areas where it really can take a burden off a practice in many ways. But I think the other thing to speak to about this is one of the concerns that come up with respect to AI is.

Like where it goes off in different directions that don't make any sense. That's partly, I know we'll get to this, but the hi before AI stuff is kind of important.  I remember the other day just randomly not related to medical field. I cause I like sports. I just asked, it's a random question like, who won the World Series and whatever year and it got it wrong.

I couldn't believe, how could you get it wrong? Like you have all the information, right? And then I told us like, you're incorrect. This is not right. That, and then it apologized to me.  so, when that kind of stuff starts to happen, I'm like, man, what is going on here? There, there are things like this, which I think when we think like, you know, it's almost like if it's like the old saying, if it's on tv, then it must be true.

There's something about if it's on a computer, it must be like beyond reproach. Well I think we have to be very careful of what this AI's actually telling us sometimes. But I think where it helps the most answer your question directly is in these kind of things,  kind of like I was speaking to earlier.

Like it's almost like having an intern or like an assistant.  And also I think it. Does help aggregate data nicely where people can look at, Hey, what's the rate of colon cancer in Texas or something.  So there's areas like this where I think it can be particularly helpful or it has been already.

Yeah, I think there are clear areas where AI is excelling today, and one of the reasons I started August as a company right, was from. The sense that patient engagement from a patient's lens in healthcare is fundamentally broke. And the bar to sort of doing something there is actually extremely low.

And in my opinion, which I never got to battle test was so low that I could have used like GPD three, which was a sentence completion model in computational algorithms and made something that. Would actually solve for patient engagement. That's how I lo how low I thought the bar was. And August is a patient engagement platform.

And we've gone from sort of zero to 4 million users organically over the past year and a half. and we see the, we see the gaps every time we talk to our users of just how isolated they feel. So I think from that lens it's actually excelling there. Even in terms of clinical decision making, I think you can see a lot of papers.

We have some, Google has published papers. I think a couple of universities have published papers where AI is phenomenal at actually giving a diagnosis. But one of the things that we have to keep in mind, and I think this framing is a framing that applies to why do some AI.

Initiatives fail, right while others succeed. Or why is this AI that is able to solve a PhD level math problem, which is what some of these frontier models are able to do today, getting a simple thing like a sports score wrong. And what ends up happening is that these systems are broadly intelligent, but broad intelligence means nothing.

They need to be aligned to a specific use case and you can do that alignment well or you can do that alignment poorly, right? So we could use the same sort of architecture that's inside August and build something that is completely unusable if we're, if we don't align the intelligence inside of August, and like multiple places where we use intelligence in the system.

If all of those are not aligned properly, you end up with a system that's  five x words, even though you're using quote unquote the same models. So I think when we look at like where is AI excelling? I think anywhere where it's aligned well with a use case where the bar is not set super high, right?

So simple customer support or simple front office cases, right? And then if you build that and you align that well, it does really well. And alignment can also mean like escalating to a human at the right time. I like this very, I like that a lot. And that, and I think this is gonna lead into our next question, is what are the biggest limitations or the blind spots of AI right now?

I think you really pointed, both of you pointed out well, where it's, what it's doing well   What things still require uniquely human insight, empathy, judgment.  I've done a lot of work with people who are at the end of life within hospice.   I don't see AI getting there.

So what is the biggest limitation with AI and healthcare?  Sure. I mean, As I said earlier, it's sometimes nice when the. The E EMR will generate a nice little draft email or you know what it terms now generates summary. Said patient. Let's say you don't even know the patient, so click on it.

It gives you a little, Hey, this is a 46-year-old, whatever,  da has this and such. It's on this and such medicines. Okay, great. So you're right. The other side of this is problems such as confabulation and  we're talking about inaccuracies and of course I'd be remiss not to plant a flag on this one, which I think is not meant to be edge case or some sort of marginal point.

Made here certainly isn't for the family of this unfortunate teenager. I'm sure you saw there was this family that got one of these, I don't wanna blame ChatGPT, maybe it was ChatGPT. I don't remember which one it was.  To help 'em with school, which is great, right? A research tool. It can get data.  We're talking about the good sides, right?

Well, somehow this child got depressed somewhere along the line, I think you know this case. And then it basically told him to kill himself and he did. So there is nothing worse than that,   If it somehow the algorithmic structure of it can go down a pathway to that point again, it got considerable media attention.

Now they are suing that company, the parents because these safeguards weren't in place. So these are I think what it is and I know this much also I'm sure you do, is that, people will come. I have a pretty area that I patient uh, grouping that I tend to. So they come pretty informed, but they still come  it is to say that in medicine, generally speaking, people are looking for an opinion, a medical opinion.

Whether they wanna incorporate it or not is their own thing, or they feel edified by it, given what they've already thought or have researched on their own. Many times we learn from the patients, you know that, right? So,    I, I think that this integration of the human touch with the elegance and nuance of AI is where the value proposition for the physician and the bedside is going to be at, and the fact that people still want to have, as you spoke to, empathy, clinical experience.

 Talked about this last time, right? I'm about 30 years of clinical. Experience station in my career about Q3, if you will.  That has whatever value it has to the person coming in to see me, right?  They want that integrated with the things that could be known and had by way of the internet and AI and these things.

 So that's sort of how I think of it. Anuruddh I'd love to hear what, how, what you think about the biggest blind spots are. Okay. How much time do we have? No  I think see, the way I look at it, I'm gonna, I'm gonna try and make  a couple of  nuanced points. It's not just limitations of, or blind spots of the ai, right?

I think it's very easy for us to point to an AI and say, this AI bill. I think it's also that and this is more so to give you a builder's perspective, right? Like my perspective of saying, okay, these are all alignment problems, is not a common way that I see builders even articulating how they work with language models.

And that's not to say I'm doing something special, it's to say that like the fundamental technology we used to build. Is changing because intelligence in a pipe was not available before. The way that we build that technology is changing, which is like AI generates code, right? So, and most of these are tech products.

 They're being partially written by the same AI system,  And then they're being tested in some benchmarks and evals. A lot of which don't really make sense because they don't represent how those systems are being used. And so all of that, even on the, like outside of the limitations of the or blind spots of the model, actually adds extra difficulty in building like a well aligned AI system.

The other, I think, important way for us to look at it because. One of the things I've realized, right, is you can dismiss a lot of the arguments made on you know, what are the limitations of AI by saying, oh, the model is gonna get better by next year. But I don't think that like when we look at like what are gonna always gonna be true limitations of AI systems, we have to assume that, okay, assume we achieved a SI, we have artificial super intelligence. It is  something that is a thousand iq that is an API call away. One of the most important blind spots for AI today is context, right? And I think that flows into the empathy side to an extent, right? Like when you look at somebody in hospice care, if you give the AI like a complete context of that person, and I think Jean, when you walk into that room with somebody who's on hospice care, you're taking in a lot of data just by being present in that.

Then you have all of the information that you have about, that patient, and then you have like your years of experience of dealing with similar patients and then your training, all of that comes together to decide what you say, These AI systems, getting smarter is sure in some way that years of practice, Reviewing the files is a function of can they ingest this? Can they understand this? Can they read this accurately? Which itself is a hard problem. But then they also don't have that input right, of what is happening on   to this person. Like What is truly happening to that person? A lot of things that humans can just infer.

We don't have a way of getting that into an ai. So I think that context is like a very large blind spot. And something that like a lot of people that are building in AI are trying to figure out ways. to sort of get it better, right? So software engineering is now turning more into context and behavior engineering more than anything else.

And that's true even in non-health related systems as well.

I'll just say, I, I really appreciate all of your insights, Anuruddh It that we could talk a lot about, I think all those blind spots, but I, I wanted to talk about something that Dr. Misra mentioned in the podcast that we did, which is.

The phrase human intelligence before artificial intelligence, and it has become a powerful reminder in medicine. What does that mean to each of you personally, and how do you think healthcare professionals can embody that principle?

No, I think it's a great point. I, can maybe he can support me on this one culturally, just to make a point in medicine for a long time  and not by the way, unique to our heritage which we share and we're proud to represent.  It always was thought that the doctor was this paragon of everything.

And it would. B by the way, patient would look at the doctor as beneath the doctor, quote unquote, to have a book open or a note, or be looking something up in the context of attending to their need. They should know it all basically. Right. So  I think that. Cultural paradigm is something which, and I mean from the medical professional side of it has been evolving in a way where  if I asked a question to a doctor when I'm a patient, I, and I may have obviously asked something they weren't prepared or ready for.

I'd be very disappointed if they didn't say, well, I don't know's a good question. Let me try to help look. This up or work through it here in real time with you and let's, figure this out together.  I would be very happy about that.  The, it's often said the best doctor's one who's very comfortable and confident in their place to say, I don't know as opposed to what I was mentioning earlier where the thing just confabulate some answer that doesn't make any sense, right?

So I think that this is one of those things where the best of both worlds can be had of this sort of. Kind of the words you were using earlier. Good judgment and empathy and insight on how to use AI as a force multiplier for the value proposition at the bedside.

I love that. Anuruddh. What do you think? Okay. I think my framing is not gonna go to the bedside because that's something I don't think I can, speak to both of you have a lot more experience than I do on that. But I think one of the forcing functions that this current generation of AI is applying on all of us is this is the first time that generalized intelligence at a human level, or reaching a human level, or sometimes above a human level is.

Available to us,  This is the first time you say something to a computer and it writes you something that is coherent or it solves a problem that you couldn't have solved. Or  it solves a problem that you would've solved but saves you a lot of time. So  we are reckoning  with the fact that there's this other system that has intelligence that is eerily similar to ours.

And I think the worst thing that we could do is fight it. what I mean by that is, and this I think speaks to Dr. Misra's point as well is that I think it should absolutely be okay for a physician to be using an AI tool to actually do their job better, because that's what's gonna happen in every other profession and is happening in every other profession as well.

Is that you're gonna have really good, aligned AI systems that are just gonna make us better. So that's, I think, one part of it. The other part, I think generally,  saying human intelligence before artificial intelligence does a disservice as a blanket rule to the fact that human intelligence is scarce.

What I mean is we're gonna have 10 million less positions than we need by 2030, and 2030 is five years away. We are not training our way out,  There's no way that we can address that shortfall by 2030 by scaling up the amount of human thousands available. So I think it does make sense for us to recognize that there are a lot of patients.

There are a lot of cases, there is a lot of sort of distribution of those cases from simple to complex and say that for some parts of this artificial intelligence should be leveraged. And let me make this a little bit more concrete, right? Like I live in Bangalore, India, and I would argue Bangalore has better access to care and access to really good care than most places in the world.

Wow, this is tier one India. Right. I can go see a doctor tomorrow. In fact, I think I'm pretty sure, but if I leave right after this podcast ends, I can go meet a doctor.   And that's just access that we take for granted. But then there's another site to India where you have this is like the tier two, tier three, tier four India, where.

Tier two, tier three, India access is still there, but access to quality care is not there. Tier three, tier four, India, there are places that struggle for access, right? Like you have to take a bus, you have to take a train, you have to go 80 kilometers. I think that's roughly like, 30 odd miles to even go meet a doctor.

And this is somebody that is earning less than $500 a month. That person doesn't have access to care at all. And then if we try to protect human intelligence and say that it is something sacred, what we are saying is that this person should not have access to any form of intelligence, right?

Even if they have a something that's very manageable and simple, they still need to make that 30 mile trip, take a day off work, take the loss of pay. Because there's something inherently amazing about human intelligence, and so it should be dealing with even the simplest case of anything, And I feel like over the next couple of years, we're gonna have to really reckon with this and pass it apart, ask the hard questions  and really make sense of this in a way that can actually benefit. Over a billion people today. A billion people is a lot of people. Yeah. yeah. No, I, I think that's so well said.

 And actually  he and I have a called contemporary, a mentor or friend if you will, who is a real leader in speaking to how, what he just spoke to. In India has gotten particularly sophisticated to the point that  people in their own native languages  India is a country that's extremely diverse in many ways, one of which is language.

 And just imagine you have these AI products that are able to speak to someone in, let's say Gujarati, some random Indian language, and then synthesize, oh, okay, you need to get to this for that purpose.  Okay. Deliver that. So I really appreciate this point he brought up because  actualizing an outcome wherein you can minimize the need for human oversight is I think very helpful.

I think it's a little scary too, but at the same time, he's right to say this doesn't mean that we cut off people from things which could be effectively basic services and he can speak more to it, but I. That, that is, I think, where we're going. And in many ways we already are at, and in many ways in India, they're ahead of what we're doing here in the United States.

 And   it's really transformational. It's remarkable. It's impressive. And it's here. Yeah. I, yeah. I agree. So, so the last question I'm really interested in this. If you were both put in charge of the national or global strategy for AI in healthcare, what would your first three priorities be for each of you to ensure AI improves care rather than disrupts it?

 I'm happy to kinda be lead off hitter on that one.  I don't know if I would speak to them in the context of three, but I have a couple comments about how I think about this.  One is, and I think you know this, right, when it comes to, remember like residency, doing research and whatever, the IRB, like you had to get something through that and the IRB was expand that out for a minute.

Institutional review board, it's supposed to be a broad representation of society, right. John Q. Public from the street, common person, someone who is just do the rounds here, a nurse, a physician, or whatever. I mean, Just all these people who would agree or say, or not that a research project has ethical merits, Versus something to a bad place if we didn't have those things in place. I think when major decisions are at a pivot point, I think an IRB kind of analogous thing would be useful so things don't spin outta control.  And I'm saying that from the standpoint of quote unquote keeping AI in check and a little bit of a touchstone to our prior conversation being a Gen Xer and having grown up watching Terminator and like always wondering  gosh  how are we going to be thought of by a super intelligence  are we gonna be looked at as some sort of news.

 By ai, meaning we as a collective, the human race, where we're just swept aside, like ants or at best  or worst sprayed at by raid. So  I, I think trying to get out in advance of that point being arrived at would be probably a good thing.  And  even many people like on earth here who speak with much more authority, with specifically ai.

They're also giving voice to a you know, not a non-zero potential outcome that  AI could eviscerate the entire human race well. So I don't think that's a good thing. And I think to the extent we can get out in front of that from  a, again, to borrow from our profession, a preventative medicine gesture, I'd like to employ something on those lines.

So I think of ai. AI is like the beach. Okay? You can have a fun day at the beach, but you can also drown at the beach. So I think it's about how you use it.  So that's sort of how I think about it. Broad strokes. Anuruddh. What are your three priorities? so I think to the point that that Dr.

Misra spoke to like getting to super intelligence and like going from there to a GI is something that we should be doing  very thoughtfully. Because if you've seen the entire theme of what I was saying, right? Like we're nowhere, like we're not at Super intelligence today and it's still really hard to align these systems and we're solving like really simple alignment problems in inside systems that don't have agency.

 And still doing it like a not great job at it, So I think from that lens, like we have to take alignment seriously before we start talking about these systems. Having any agency, bringing that back to a healthcare context, I think, see, so there, there are a couple of things that, that I don't talk about very publicly  today, but I think it, it seems like  we're at the right time where I can.

I can bring it up on this podcast. With August we are seeing sort of its ability to give a differential diagnosis and have  the first thing it's saying in that differential diagnosis while it conducts a proper medical interview with like actual people. We're seeing that accuracy. Hit sort of higher percentages  than human physicians in a lot of areas.

And we're seeing it have like exceptional triaging accuracy, so like a triaging accuracy that in absolute numbers hits like a 98, 90 9% across  14 sort of specialties and a bunch of diseases that we look at. So I, think it's inevitable for us to have AI in some limited scope give like a license to an AI system.

I feel like that has to happen. And again, like doubling down on, the main reason, right. That random language, I think that Dr. Misra mentioned in India that Gujarati, there are 55 million people that speak, that ran random language, And so there are a lot of people that don't have access to care, that communicate differently, that think differently, and they can benefit from having a system like that.

But the main thing that we have to worry about today is evidence and lack of evidence in that system working. So first we reframe the conversation from that AI system versus some ideal version of the doctor that everybody has in their head to  that AI system versus. What is actual, like what is an, how does an actual physician function?

Then we cut scope a lot because like I said, these are alignment problems, aligning a generalized AI to have human intelligence. We're pretty far from that.  But when you cut the scope right, then  we need to  establish a mechanism to get the kind of evidence. That is required to say, Hey, this thing can operate at least as well as a human right.

Let's give it to people that don't have access to care at all. I think that's gonna be one very important thing for us to figure out. And it's scary, but human beings do scary things and we do those scary things because they make the future better.  And I think we have a real opportunity for that.

I love that. And I think that's the perfect way to end that we can do scary things to make the future better.  I agree. And I will just say, I think that we could talk for a very long time on this topic and maybe we'll talk again. I look forward to hearing about  where you're all going, where you both are going in this area.

If our viewers want to hear more  or learn more about what each of you are doing, can you both share where they can find you?  I know one thing that both he and I are both on LinkedIn, so we're not hard to find.  

But specifically beyond that, my website is, and I think it's probably gonna be, especially with he and I both on the podcast at the same time, better for me to actually spell it out this time rather than just say it like I did last time. So www. A-K-M-I-S-R-A md.com.  Not to have it spelled the way he spells his last name, which is phonetically the correct way.

Yeah, so that's how you can find me. Anuruddh. How can people find more about you? Yeah, I think  LinkedIn is the, easiest.  I write on LinkedIn is spelling. And then if people wanna learn more about August, it is@meetaugust.ai, M-E-E-T-A-U-G-U-S t.ai. and I mean, it's, it's out there. People can try it.

And we're at that point where we welcome a lot of very critical feedback because I think that's the only way that we get better. Yeah, I think  that would be those would be the two points. Wonderful. I encourage everyone to take a look, Dr. Anuruddh Kumar Misra & Anuruddh Mishra.  Thank you so very much for joining us today.

Perfect. Thank you for having us, Jean.  It was a pleasure. No, thank you again. I, I hope this conversation advances the conversation for all listeners and those who are interested at the intersection of uh, medicine and ai.

Thank you for tuning in to Taking Healthcare by Storm: Industry Insights with Quality Insights Medical Director Dr. Jean Storm. We hope that you enjoyed this episode. If you found value in what you heard, please consider subscribing to our podcast on your favorite platform.

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