Episode 77

Will a Robot Replace Your Surgeon? | Dr Ravi Kumar and Ryan Estes

50:24 October 20, 2026 By Dr. Ravi Kumar MD
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Show Notes

A surgical robot trained on 100,000 cases can be smart on day one, maybe smarter than a surgeon with thirty years of experience. That should feel backwards. Every surgeon learns that older surgeons are safer than younger ones, because judgment and a feel for anatomy only come from years of cases and complications. So what happens when a machine skips that apprenticeship entirely?

This episode is a replay of a live conversation Ravi streamed with his friend Ryan Estes, a serial tech entrepreneur who runs a holding company in Denver with a portfolio of service agencies, software, and media brands. One of those brands is AI for Founders, where Ryan interviews startup founders building at the edge of AI, technology, and robotics, with AI in medicine as a recurring theme. Ryan is the tech guy, Ravi is the health guy, and together they work through a docket of recent news stories on where medicine and machines are colliding.

Ryan frames the conversation with three buckets: diagnostics, therapeutics, and the administrative mess around care. That last one may be the most broken. By his estimate, a typical patient spends about thirteen minutes with their actual physician, with the rest of the visit lost to clipboards, iPads, scheduling, and insurers. Ravi has lived the fix on one side. Before AI scribes, writing a note took as long as the visit itself, so a fifteen minute slot bought about five minutes of face time. Now the scribe produces the note in about a minute, and he spends thirteen or fourteen minutes with the patient. It even understands the deep Southern accents he sometimes struggles with in North Carolina. The catch: in one NHS case, a scribe dropped the word “null” from “null demyelination,” turning a normal finding into what looked like multiple sclerosis.

On the insurance side, Ravi describes requests for cervical decompression surgery, for patients whose spinal cords are so compressed they can’t walk properly, coming back denied in a split second. Getting them approved means clearing his schedule for a peer to peer call, and most of the time the insurer reverses itself. His read is that insurers are playing the numbers, counting on a predictable share of busy doctors never appealing, and keeping premiums in their float a little longer. Connecticut became the first state to ban AI claim denials, but only for people on the state’s own health plan.

They also walk through where automation makes sense first. Utah now allows an app called Nala Health, $4.99 a month, to scan a face for acne and write a prescription, with only the first 100 prescriptions reviewed by a doctor. Ravi points out that acne, strep throat, and hypertension follow treatment algorithms that are already written down, which makes them a natural foothold for AI, though drugs like Accutane or tetracycline carry enough risk that a doctor belongs in the loop. Strep is a special case: untreated, it can cause rheumatic fever, heart valve disease, kidney injury, and PANDAS, which is why it gets treated on suspicion.

Diagnostics are moving just as fast in stranger directions. A company called Spot It Early sends you a mask to breathe into for three minutes, and 15 trained beagles wearing sensor vests sniff it for roughly four kinds of stage one cancer, something billions of dollars in liquid biopsy research still hasn’t matched. A wearable called Canary listens to someone’s voice for signs of anxiety, depression, or the subtle decline in Parkinson’s and dementia that a caregiver might miss day to day.

Then there is OpenAI moving into Epic medical records. Ravi isn’t too worried about privacy, given HIPAA, but he is worried about accuracy. A 93% accuracy rate is a great score on a math test and a failing grade in medicine, because the other 7% could include a missed penicillin allergy. He prefers tools like Open Evidence, which is trained on the medical literature and won’t answer when it doesn’t know. Ryan counters with the uncomfortable math: humans make mistakes too, and people tolerate human error far more than machine error.

The conversation ends in the operating room. Robots are already used in neurosurgery, urology, gynecology, general surgery, and orthopedics, guiding screws down a two millimeter corridor of bone between the vertebral artery and the spinal cord with sub millimeter accuracy. For now they are human controlled; the surgeon approves the plan and drives the screw. Ravi sees the next steps as less human intervention and, eventually, autonomous robots operating on strict clinical algorithms. But the things humans bring, empathy, a sense of mission, and curiosity, are not going anywhere. Combine those with machine accuracy, he argues, and medicine gets better, not replaced.

Episode Resources

In this episode, you will discover:

  • How AI scribes rewrote the office visit: Notes that used to take as long as the visit now take about a minute, turning five minutes of face time into thirteen or fourteen
  • The one word that changed a diagnosis: An NHS AI scribe dropped “null” from “null demyelination,” making a normal finding read like multiple sclerosis
  • Why 93% accuracy is a failing grade in medicine: The other 7% can include something like a missed penicillin allergy
  • Surgery denied in a split second: How requests for spinal cord decompression come back rejected almost instantly, even for patients who can’t walk properly
  • The insurer numbers game: Ravi’s theory that insurers deny claims knowing a predictable share of doctors never appeal, while premiums sit in the float
  • Connecticut’s narrow ban: The first state to ban AI claim denials, but only for people on the state health plan
  • AI prescribing in Utah: How a $4.99 a month app called Nala Health scans a face for acne and writes a prescription, with only the first 100 reviewed by a doctor
  • Why acne, strep, and hypertension come first: Their treatment algorithms are already written down, which makes them a natural fit for automation
  • Why strep throat gets treated on suspicion: Untreated strep can lead to rheumatic fever, heart valve disease, kidney injury, and PANDAS
  • Beagles that smell cancer: Fifteen trained dogs in sensor vests sniffing a breath mask for roughly four kinds of stage one cancer
  • A wearable that listens to your voice: Canary picks up signs of anxiety, depression, and subtle decline in Parkinson’s and dementia
  • ChatGPT inside Epic: Why Ravi is less worried about privacy, given HIPAA, than about accuracy, and why he likes tools like Open Evidence that won’t guess
  • Why we forgive humans but not machines: The self driving car problem and what it means for AI in medicine
  • Robots already in the operating room: Human controlled robots placing spinal screws down a two millimeter corridor with sub millimeter accuracy
  • Older surgeons versus day one robots: Why experience makes older surgeons safer, and why a robot trained on 100,000 cases may not need the apprenticeship
  • What robots can never have: Empathy, a sense of mission, and curiosity

Key Takeaways

The biggest fixable problem in medicine is administrative, not clinical. Much of a typical visit disappears into clipboards, iPads, and insurer paperwork. AI scribes are already giving that time back to patients and doctors.

A denial is not always the final word. Ravi says the peer to peer review is what gets most of his rejected surgery requests approved. If a medically necessary procedure is denied, ask your doctor about appealing.

Treat AI medical answers as drafts, not verdicts. Even 93% accuracy leaves real gaps. Tools that decline to answer when they don’t know are safer than tools that guess.

Automation fits best where the algorithm is fixed and the downside is small. Acne, strep, and hypertension are good candidates. Higher risk drugs like Accutane still call for a doctor in the loop.

New diagnostic signals are coming from unexpected places. Breath, voice, and wearables are picking up early disease cues that standard tests miss.

The goal is dividing the labor, not replacing the doctor. Machines bring precision and tireless pattern recognition. Humans bring empathy, mission, and curiosity. Together they make a better medical system.

Transcript

[00:00 –> 00:18] Dr. Ravi Kumar: Hey, everybody. Welcome to the Dr Kumar Discovery. My name is Dr. Ravi Kumar. Today is a replay of a live episode I did with Ryan Estes. He’s my good friend, serial tech entrepreneur, and host of AI for Founders, which is a fantastic podcast if you’re into AI or new technology.

[00:18 –> 00:43] Dr. Ravi Kumar: We talked about topics around healthcare and AI and technology, and how they’re coming together to make the world a different place. It was a fascinating conversation, and we covered a bunch of the latest news stories on this. So let me know if you like it, because this is something I can do once a month if it’s of interest to you. Also, anything we say today can’t be taken as medical advice. It’s just for your knowledge and your information.

[00:44 –> 01:03] Dr. Ravi Kumar: So use it, and if you’ve got things you wanna talk about, go to your doctor and talk about them. Also, I’m super excited about a new app that I’ve designed. It’s called Brain Gamer. You can find it at braingamer.app, braingamer.app. And it’s an app that I designed to intentionally work the different domains of your thinking and your brain.

[01:04 –> 01:16] Dr. Ravi Kumar: It’s like going to the gym except for your brain. It’s a workout, and it gets your mind moving in the morning. I play it every day. So please check it out, braingamer.app. Play it and let me know what you think.

[01:16 –> 01:22] Dr. Ravi Kumar: Alright. Let’s get into it. Cheers. My name is Dr. Ravi Kumar.

[01:22 –> 01:52] Dr. Ravi Kumar: I’m a neurosurgeon in search of the causes of human illness and the solutions that help us heal and thrive. I want you to join me on a journey of discovery as I turn over every stone in search of the roots of disease and the mysteries of our resilience. The human body is a mysterious and miraculous machine with an amazing ability to self heal. Let us question everything and discover our true potentials. Welcome to the Dr Kumar Discovery.

[01:57 –> 01:58] Dr. Ravi Kumar: All right, we’re live.

[01:59 –> 02:07] Ryan Estes: All right. Welcome everybody to this experiment of the Dr. Ravi Kumar Discovery. How are you Dr. Ravi Kumar?

[02:07 –> 02:11] Dr. Ravi Kumar: Good. Doing good, Ryan. Yeah. This is gonna be a first for both of us, I think. Right?

[02:11 –> 02:14] Dr. Ravi Kumar: Have you ever livestreamed on your your podcast?

[02:14 –> 02:19] Ryan Estes: You know, I I remember livestreaming back in the day with Justin TV. You know?

[02:19 –> 02:19] Dr. Ravi Kumar: Okay.

[02:19 –> 02:22] Ryan Estes: And I think they became Twitch, but it’s been a minute.

[02:22 –> 02:25] Dr. Ravi Kumar: So this Yeah. Yeah. That’s right. That’s what it was called at first. Yeah.

[02:25 –> 02:30] Dr. Ravi Kumar: Yeah. Okay. So… Yeah. So we’re going…

[02:30 –> 02:50] Dr. Ravi Kumar: This is gonna stream. It’s streaming live to my YouTube channel right now, The Dr Kumar Discovery. But we’ll repost it permanently both to AI for Founders podcast and YouTube channel and also to The Dr Kumar Discovery YouTube channel. And it’ll be available through audio for… On both of those platforms as well.

[02:50 –> 02:50] Dr. Ravi Kumar: Right?

[02:50 –> 03:01] Ryan Estes: 100%. Absolutely. And video over on my side too. So, you know, Dr. Kumar and I are are good buddies and fellow podcasters, so we thought this would be a good opportunity to talk about technology and medicine.

[03:02 –> 03:09] Dr. Ravi Kumar: Yeah. Totally, man. I think you’re the tech guru, and I’m the health guy, and we’re bringing our forces together.

[03:09 –> 03:45] Ryan Estes: You know, I I don’t know about a guru, but I think I’m curious. You know, for for your audience, you know, I have a holding company here in Denver, and I have a a portfolio of service agencies, software, and media brands. And one of the media brands is called AI for Founders, where basically I interview startup founders that are kind of at the tip of the spear of AI, technology, robotics, and a common theme for us is AI in medicine. There are so many cool opportunities and and solutions that are coming with AI in medicine in a lot of different buckets. So I always get excited to talk about it.

[03:45 –> 03:48] Ryan Estes: So really excited to hear your takes on some of this stuff today.

[03:49 –> 03:54] Dr. Ravi Kumar: Yeah, man. I’m I’m looking forward to it. Got we got a good lineups ready to go.

[03:54 –> 04:07] Ryan Estes: Okay. Cool. So to kinda get it started, you know, what I’ve seen is there’s, like, three buckets we’re seeing, like, new tools pop up in. You know, one is kind of a diagnostic. You know, what can we use AI for in particular?

[04:07 –> 04:38] Ryan Estes: And we’ll talk a lot about AI today. AI in particular for diagnostics. The other one is kind of the future of actual therapeutics and applications into health, which is really cool, really fun stuff. And then the one that’s probably most relevant right now, and I think probably is looking to solve the biggest problem in medicine, is kind of administrative stuff. I think on average, a person spends thirteen minutes with their actual physician when they go to the doctor.

[04:39 –> 05:05] Ryan Estes: Because all the other time it’s like going to the iPad or filling out the clipboard or making the appointments. And this is where a lot of medicine gets dropped or people don’t sign up or they forget to take their medications or they’re dealing with the insurance agencies. It’s the broken part of medicine. That’s the one where people are kinda scrambling to see how we can implement some of these tools to help to help the system. So maybe we start there.

[05:05 –> 05:06] Dr. Ravi Kumar: Okay. Let’s do it.

[05:06 –> 05:20] Ryan Estes: Cool. So we’ve got a pretty hefty docket. So let’s talk about this one that’s kinda teeing everything off. About Utah, It’s letting AI write prescriptions so there’s no doctor in the loop. Crazy man.

[05:20 –> 05:30] Ryan Estes: Pretty obvious banana peels here, but there’s probably some opportunity. So this is specifically for, it’s for acne medication. So I’d love to hear what you think about this broadly.

[05:31 –> 05:49] Dr. Ravi Kumar: Yeah, I mean, is fantastic. Like, that AI is moving so fast that it’s already prescribing without a doctor, essentially. And this company… You know, so basically, they have this system that you you you pay for an app. You pay $4.99 a month.

[05:49 –> 06:02] Dr. Ravi Kumar: Imagine that, $4.99. Most people’s co pays are, like, you know, $20, $30 bucks. So you pay $4.99 a month. You… It asks you some interactive questions, and then you scan your face for…

[06:02 –> 06:37] Dr. Ravi Kumar: To look at your skin and your, you know, your acne, and then it prescribes you a medication, and you go pick it up. Yeah. The productivity boost, the financial savings, the not having to wait to see a dermatologist, I mean, that is so, like, crazy that that’s happening already. And it’s not that this can only be done for acne. This company wants to expand it out to a lot of other diseases and problems, but acne, they thought, was super low risk and very straightforward.

[06:37 –> 06:58] Dr. Ravi Kumar: The treatment algorithms for acne are very straightforward. I mean, there are some medications like Accutane and doxycycline and tetracycline that you can take for acne that do have consequences, And so maybe they’re backing that up with a doctor’s opinion. But right now, I think this is cool that it’s happening so quick.

[06:58 –> 07:07] Ryan Estes: It’s super cool, you know? And it is interesting with its acne because you take a picture and it’s… You’re you’re a teenage kid. You’re like, oh, yep. That’s exactly what that is.

[07:07 –> 07:14] Ryan Estes: You know? Yeah. Probably makes sense to your point that, like, there’s… It’s not too dangerous taking the medication. So, okay.

[07:14 –> 07:31] Ryan Estes: Let’s begin here. I wonder if there’s kind of a threat, you know, particularly with doctors, and I’ll share a quick story. A good buddy of mine, he’s a he’s a family doctor. Sean went to college with him, and my daughter had… She was on that, like, strep throat cycle that, like, every six months she was getting strep throat.

[07:31 –> 07:47] Ryan Estes: So we knew all the signs of when it was strep throat also because you can look in her in her throat and be like, oh, yeah. There it is once again. So I called him and I was like, hey, Sean, can I just can I just text you when I need a prescription for antibiotics, man? We already know what it is. And he got so mad.

[07:47 –> 07:54] Ryan Estes: He was like, absolutely not. He’s like, you need to go see your physician. I was like, oh, really? Alright, man. So don’t don’t mention.

[07:54 –> 08:05] Ryan Estes: I’m sorry. You know? But but there was a threat there. So, you know, do you think… I mean, this is the beginning, but do you think doctors are gonna push back at kind of some of these, like, AI diagnosis?

[08:05 –> 08:14] Dr. Ravi Kumar: Yeah. I mean, they’re totally gonna push back. Right? But, I mean, so on this company, I I can’t remember the name of the company. Do you do you have it there in front of you?

[08:14 –> 08:15] Ryan Estes: Yeah. Let me find it.

[08:16 –> 08:26] Dr. Ravi Kumar: So they’re they’re basically saying, okay. The her… First 100 prescriptions are gonna be reviewed by a doctor to make sure we’re not making mistakes. Yeah. And then after that, you can do your thing.

[08:26 –> 08:41] Dr. Ravi Kumar: You can get your diagnosis. You can get your prescription. And then if you still want to talk to a doctor, we’ll connect you. But I think they’re hedging that they’re not going to have to pay doctors that much because most people will be like, Yeah, I got my prescription in five minutes, didn’t have to go anywhere. And they’re super happy, right?

[08:41 –> 08:42] Ryan Estes: It’s great.

[08:42 –> 09:08] Dr. Ravi Kumar: Now the thing with these, like, diagnostic algorithms for treating acne or strep throat or hypertension, I mean, there’s… I mean, these are written and codified, and doctors aren’t using any creative thought. Right? There’s no, like, curiosity or exploration in these chronic disease management protocols. So that’s the perfect place for AI to come in.

[09:08 –> 09:20] Dr. Ravi Kumar: Yeah. And there’s gonna be tons of pushback. I mean, doctors are gonna push back, nurse practitioners and PAs are gonna push back. It’s gonna be like any new technology. It scares people.

[09:20 –> 09:39] Dr. Ravi Kumar: People won’t like change. But for me, I’m a doctor, and my kids need something basic. I’d much rather go to an app that costs me $4.99 a month and get the prescription. Now I have to make the appointment, find it… My wife’s gotta find a time, pull them out of school Yeah.

[09:39 –> 09:53] Dr. Ravi Kumar: Take them to the doctor, get the prescription, go to the pharmacy, fill the drug. I mean, it’s it’s just… And then you gotta… If it’s not working, you gotta follow-up, and you gotta do the whole thing again. I mean, that productivity suck is massive.

[09:53 –> 09:59] Dr. Ravi Kumar: Yeah. And the doctors don’t like doing it too. They’re like, oh god. Another another strep throat?

[09:59 –> 10:04] Ryan Estes: Totally. Yeah. Well, we saw you a couple of months ago. Looks like it’s the same thing.

[10:04 –> 10:17] Dr. Ravi Kumar: Yeah. Exactly. And, you know, the other thing is that with strep throat that your daughter had, I mean, that is not just a a throat infection. That is serious. I mean, it can cause rheumatic fever.

[10:17 –> 10:28] Dr. Ravi Kumar: It can cause PANDAS. That’s a autoimmune disease of the brain. It can cause kidney injury. This is, you know, heart disease, rheumatic heart valves. I mean, is…

[10:28 –> 10:49] Dr. Ravi Kumar: Strep has, like, got real consequences if you don’t treat it. In fact, the consequences of untreated strep strep are much higher than giving an antibiotic when someone didn’t need it. That’s why strep gets treated like that. You think they have strep, you treat it. Usually they swab the throat, so maybe these algorithms will be like, okay, we’re overnighting you a swab.

[10:50 –> 10:57] Dr. Ravi Kumar: Swab your throat, stick it in a little tube. It’s it’s… Kindergartner can do it. Does it show two lines? It’s like a pregnancy test, you know?

[10:57 –> 11:05] Dr. Ravi Kumar: Does it show two lines? If it shows two lines, take a picture, send it to me, and I’m giving you a prescription for amoxicillin. Yeah. I mean, that that makes sense to me.

[11:06 –> 11:17] Ryan Estes: Yeah. It’s interesting too where the future is going, and that… The company’s called Nala Health. Nala Health. You know, the the input the input for the acne is basically a photo or a video.

[11:18 –> 11:41] Ryan Estes: You know? So ultimately, like a doctor could eyeball that if they needed to and be like, yep, I agree or I disagree with the AI diagnosis. But there’s certain things and indicators and signals that like AI is uniquely adapt to pick up because maybe the signal is so subtle or maybe the signal is so broad that you need something to pull it in an aggregate. There’s a couple of tools. One of them that’s really interesting is called Canary.

[11:41 –> 12:18] Ryan Estes: And basically this is an AI tool that is kind of it’s like a wearable and it’s listening to you and it can sense anxiety, it can sense depression, but really they’re using it for Parkinson’s patients and people that have dementia. So it can actually hear in your voice if you’re having an episode or if the symptoms are worsening. Which, you know, if you’re around the person all the time and there’s a subtle decay, a subtle slide, you might not become aware of it. So, you know, right now we’re figuring out what are the new ways we can input more data to get a bigger set and then use AI’s compute power to like find new diagnosis.

[12:18 –> 12:25] Dr. Ravi Kumar: Yeah. So this this wristband or this wearable is listening to the voice. Yeah. And It’s all taking up these diagnostic. Wow.

[12:25 –> 12:44] Dr. Ravi Kumar: I mean, I’ve heard that… I heard about this, and that’s just totally fantastic. I mean, computers and AI algorithms and AI systems now can pick up diagnostic cues that the human mind can’t do. I mean, you know, there’s that one company you just told me about lately that takes actually dogs.

[12:45 –> 12:45] Ryan Estes: Yeah.

[12:45 –> 12:57] Dr. Ravi Kumar: And, like, is it saliva samples? I… Or maybe it’s blood and and uses AI algorithms in dogs to detect cues for cancer that that normal person couldn’t tell. You know?

[12:57 –> 13:06] Ryan Estes: Yeah. That is a really interesting AI application because what it what it does is basically you… They send you a mask. It’s like one of those COVID masks.

[13:06 –> 13:07] Dr. Ravi Kumar: Oh, that’s right.

[13:07 –> 13:21] Ryan Estes: You wear it for three minutes, and then you just ship the mask off. And what they’ve done is they’ve trained 15 beagles to sniff the mask, and they can detect to, like, one part per five million of, like, four different stage one cancers.

[13:22 –> 13:25] Dr. Ravi Kumar: Wow. So Stage one. The very first start of it.

[13:25 –> 13:35] Ryan Estes: Yeah. The very first one. So… And so then what they do and what they’re doing with AI is they put all these sensors on the beagles, which they must be a real good boy. You know?

[13:35 –> 14:10] Ryan Estes: I mean, they’re doing a great job. But you’re assuming, like, if they get a positive, then they bark or point or do something adorable, and then they bring the other bagels… Or beagles, and then the other beagles confirm and they bark or point or whatever they do. But what they have is they have, like, these vests and sensors all over the dog so they can pick up nuance and, you know, maybe indecision, maybe something that’s triggering a response that the beagle’s actually not responding to. So basically, in a way, kind of reading the dog’s mind, you know, to find these other sensory inputs that might be indicating like a positive or a false positive or negative.

[14:11 –> 14:41] Dr. Ravi Kumar: That’s incredible. Because, you know, I mean, you know how many billions of dollars are going into these wet biopsies? That’s where you draw someone’s blood, and then you test for tumor biomarkers. And and you can test for a number of cancers, trying to catch it early. And they’ve really been, like, kind of, they’ve been okay, not super great, and they’ve spent billions and billions of dollars on them, and they’re still not like reducing the progression of stage one to stage two cancers.

[14:41 –> 14:54] Dr. Ravi Kumar: I… And then they’re bringing these dogs in with AI sensor… AI red sensors on them, and they’re they’re finding cancer in a mask that someone’s breathed into. Yeah. That’s that’s totally crazy.

[14:54 –> 15:02] Ryan Estes: It’s really cool. And I’d like to think that these dogs are wearing, like, you know, scrubs, you know, and like like maybe a a… What do you call the head scrub?

[15:02 –> 15:04] Dr. Ravi Kumar: Hat? Yeah. Surgical hat. Yeah. Surgical hat.

[15:04 –> 15:05] Dr. Ravi Kumar: Yeah.

[15:05 –> 15:38] Ryan Estes: I’d like to think they’re wearing that, but because they’re not doctors, obviously, the FDA doesn’t even need to be involved. I mean Yeah. I think they’re working towards getting it approved because then they can, you know, be in Medicaid and then like, boy, it’s like off to the races for them. It’s called Spot It Early is is the company. But I think also what’s interesting about this is, you know, through through AI and maybe robotics, there’s just gonna be all these different symptoms and signals that we can pick up on that so far, like our diagnostic tools or the fidelity of how we’re kind of like inspecting a patient isn’t there yet.

[15:38 –> 16:02] Ryan Estes: So what maybe it’s using dogs that can help smell, but like our wearables will invariably become more sophisticated where it’s checking heart rate versus your sweat versus your breath versus… I mean, all these these datasets, and it’s all individualized to a certain person, which, you know, one person… You might take a whole team to kinda analyze that for a year, but AI can do that in, seconds.

[16:02 –> 16:04] Dr. Ravi Kumar: Seconds. Yeah. Yeah. That’s the difference.

[16:05 –> 16:33] Ryan Estes: It’s cool. Which kinda takes us into the future, but I wanna hover here for a minute on kind of this administrative stuff because I think this is most pressing, and we’ll get to the future because it’s so exciting. But there was another story we had on the docket, basically, that was saying it… It’s being skeptical or critical, I guess, of AI automatically rejecting people’s insurance claims, which generally seems like a good idea.

[16:37 –> 16:50] Dr. Ravi Kumar: Oh, man. Yeah. This this story is is is also a shock to me. You know? I I had heard that AI that insurance companies were using AI to reject insurance claims.

[16:53 –> 17:31] Dr. Ravi Kumar: About the time I started hearing that, we started getting tons more of our requests to do surgery on patients with stage spine disease or brain disease. We started having them rejected. And so when I submit a claim, say I got to do a cervical decompression on a patient who’s got spinal cord compression. So their spinal canal in their neck is so narrow that it’s compressing their spinal cord, they can’t walk properly, they can’t use their hands, they’re incontinent of urine, it’s a miserable disease. And you go and you have to open up the back of the neck, basically open up the spine and get the pressure off the spinal cord.

[17:32 –> 17:46] Dr. Ravi Kumar: I’ll submit one of those for insurance approval, and it’ll just get rejected almost immediately. It’s like a split second. You send it in, and it’s rejected. And I was being told, Hey, this is probably AI rejecting this. I was like, Nah.

[17:46 –> 18:02] Dr. Ravi Kumar: They would take a better look at this. AI would look at this and be like, Yeah, this needs to be done. But you know, what happens is I have to get on, and I have to do a peer to peer call. And it can’t be any time. I have to clear my schedule to meet on their terms.

[18:03 –> 18:17] Dr. Ravi Kumar: I have to sit there, I have to wait on hold for them to talk to me and me to say, listen. This is a neurosurgical urgency. This patient’s being actively hurt, and you guys rejected their claim. And they’ll be like, oh, okay. Yeah.

[18:17 –> 18:26] Dr. Ravi Kumar: We see that. And they’ll and they’ll approve it most of the time. But, you know, the… So this story, like, when it… When I saw it, I was like, wow.

[18:26 –> 18:32] Dr. Ravi Kumar: They they are rejecting claims with AI. And Connecticut, I think that’s… This is in Connecticut. Correct?

[18:33 –> 18:35] Ryan Estes: It’s Connecticut. It’s the first to to ban it. Yeah.

[18:35 –> 18:46] Dr. Ravi Kumar: Yeah. So they’re… They… But they’re only banning it for state health employees, people who have insurance through the state health plan. And and that’s that’s basically all the power they have.

[18:47 –> 19:18] Dr. Ravi Kumar: And so Aetna and UnitedHealth and all these other companies are gonna continue denying everyone else’s claims with AI. And, you know, the the thought is, I think, you know, I’m sure they’re playing numbers with this. They’re like, well, if we don’t have as many reviewers and we can deny, you know, 30% or 40% of the requests, then maybe 10% of them won’t come back and ask for a peer to peer, or 20% won’t come back, or maybe 50% won’t come back and ask for a peer to peer because the doctor’s too busy. Yeah. And we’ll save…

[19:18 –> 19:21] Dr. Ravi Kumar: And then we’ll save $5,000,000,000.

[19:21 –> 19:21] Ryan Estes: Right.

[19:22 –> 19:34] Dr. Ravi Kumar: You know? Or we’ll keep… Maybe we’ll keep a billion dollars in our float a little bit longer. You know, this concept of an insurance float where they have the premium sitting in an account and they’re making tons of interest off of it. Oh, that’s right.

[19:34 –> 19:41] Dr. Ravi Kumar: So they want that in the account longer. So, yeah, I thought good for Connecticut, but man, we still got a long ways to go on this one.

[19:41 –> 19:59] Ryan Estes: It’s dark. I I wonder if it was even AI or if it’s just like if any email comes through here, immediately reject it. And that’s a little cynical, but honestly, for for being on the other side of the stethoscope, it’s comforting to hear your frustration with the insurance companies because, you know, it’s… You… I’ve got kids.

[19:59 –> 20:15] Ryan Estes: I’ve got a family. It’s like you’re dealing with this stuff all the time and and the bills and the insurance companies. Maybe kinda spell out the the the the problem with doctors being stuck in the middle of therapy and stuck and stuck of care. You know? So it’s like you…

[20:15 –> 20:24] Ryan Estes: It seems like the the issues that you find are acute. So talk a little bit about the frustration you see with just this whole patient insurance company doctor dynamic.

[20:25 –> 20:52] Dr. Ravi Kumar: Yeah, so I mean, there’s basically a doctor who’s interested in their patient and a patient who’s interested in their own health. So we have that connection. That’s a relationship that should be fairly unbiased in perfect situation, should be unbiased and altruistic and in the mission of medicine, which is to heal, right? But then you have the insurance company, who’s in between that. They’re the intermediate.

[20:52 –> 20:52] Ryan Estes: Yeah.

[20:52 –> 21:23] Dr. Ravi Kumar: And because of the cost of healthcare in The US, you essentially have to have health insurance. Now they control the payment of the doctor to the patient, or of the patient to the doctor for this treatment. And it’s not just to the doctor either. It’s to the hospital, it’s to the clinic, it’s to the lab, it’s to all the ancillary services that they need to have this surgery or this procedure or whatever it is they need. And the and the insurance company is controlling the payment of that.

[21:23 –> 21:44] Dr. Ravi Kumar: So if the insurance company is like, we’re we’re running behind our projections for the year. Yeah. All of a sudden, a bunch of people who need care aren’t getting care. And they’re in a system that was meant to serve an altruistic mission, and they have the opposite mission. They have the mission of just making money.

[21:44 –> 21:54] Dr. Ravi Kumar: I mean, that’s what insurance companies do. They make money, right? If they can’t make money, they go out of business. So it’s a tough situation, Ryan. You know, what do you do?

[21:54 –> 22:14] Dr. Ravi Kumar: And I would also say that there are doctors out there who abuse the system as well. They’re doing unnecessary surgeries or procedures for economic gain. It’s not super common, but it is out there, and you’ll hear about them when they happen. That’s the insurance company’s argument. We’re trying to prevent…

[22:14 –> 22:28] Dr. Ravi Kumar: They’re thinking they’re trying to prevent frivolous surgery or frivolous interventions or unnecessary interventions. That’s their excuse. I mean, I think that’s trumped by, we wanna make more money, and that’s usually the reason.

[22:28 –> 22:44] Ryan Estes: Agreed. It’s always the outliers on the the mean. It’s like if it’s less than 1% of doctors that are doing this, and also just frustrating on all accounts that if, you know, our specialists and PhDs are giving recommendation and some clerk with AI is like, Nope. You know? Yeah.

[22:44 –> 23:08] Ryan Estes: I mean, obviously there’s no easy fix, but there are all these tools and different things that are helping enable, you know, I feel like on behalf of doctors and patients, You know, that’s where I see a lot of the innovation. You don’t see a lot of innovation coming from AI companies going to help the insurance companies because, you know, you got Connecticut out there that’s like, hit the road, buddy.

[23:08 –> 23:10] Dr. Ravi Kumar: Yeah. Yeah. Good for Connecticut.

[23:11 –> 23:50] Ryan Estes: Yeah. 100%. The other big thing, kind of like with health and AI, is a couple of weeks ago, OpenAI and ChatGPT basically rolled out kind of your own kind of medical filings, you know, where you can add all of your your wearable information, you can add your doctor records and those kind of things. And they’re also getting kind of it looks like kind of enterprise support for Epic patient charts. Now I don’t know exactly what Epic patient charts, but from the summary, it kinda seems like chat GPT is becoming kind of the the the backside in the brain for large numbers of people’s medical charts.

[23:50 –> 24:13] Ryan Estes: Yeah. Which Yeah. On one side, I wanna say, you know, the good part about this is then, you know, ChatGPT is gathering all this information that it can use for future therapeutics in different ways to help people. But on the the gloom and doom side, it’s like, do we want Sam Altman to know my whole family’s medical record? You know?

[24:14 –> 24:39] Ryan Estes: Particularly now when you can use, you know, open sourced AI to to maybe give you the similar benefits, but you’re not… You don’t have the exposure of a potential nefarious company. Not that I’m casting stones, but, you know, we just really don’t know what the future of open AI entails. Kind of what’s your take as far as, like, your privacy, maybe what you do personally, how you would kind of approach this as a a person and a a dad?

[24:40 –> 24:53] Dr. Ravi Kumar: Yeah. So I mean, what OpenAI is doing right now is actually not… They’re not the first ones to do it. I mean, there’s a company called Open Evidence. They’re basically in conjunction…

[24:53 –> 25:32] Dr. Ravi Kumar: They’re working with JAMA, which is the Journal of American Medical Association, and you can actually ask questions about medical procedures and medical questions, because doctors and nurses and technicians, they all have a certain amount of information in their head, but they need to learn new things, they need to refresh on old things. And Open Evidence is basically like this AI chatbot that’s wired in in in… Into all the the medical references and all the scientific literature, so it’s trained on that data specifically. And it’s wired to not hallucinate, so it can’t hallucinate. If it doesn’t know the answer, it doesn’t give it.

[25:33 –> 25:48] Dr. Ravi Kumar: And so that’s been out there, and it’s HIPAA compliant. So HIPAA is the health rights and patient… Health information patient act. Oh gosh, I’m butchering that. But it’s the right to have privacy to your health information.

[25:49 –> 26:07] Dr. Ravi Kumar: And so it’s HIPAA compliant. It works with that law. OpenAI, I’m sure, is HIPAA compliant. If they’re in Epic, which is the biggest medical record system in the country, they’re gonna be HIPAA compliant. Now, so as as far as privacy goes, I don’t know that that’s a big risk, Ryan.

[26:07 –> 26:30] Dr. Ravi Kumar: Okay. Because there’s so many laws and and regulations around patient privacy. Now is AI learning off your data? I’m sure it is, but it’s probably for the greater good. And there may be, at some point, if there isn’t already, a way to opt out of having your medical information be used to train AI algorithms, LLMs, basically.

[26:30 –> 26:52] Dr. Ravi Kumar: Now this is the part of that story that I thought was very interesting, and I haven’t used this OpenAI in Epic yet. I use Epic, but I haven’t… It hasn’t been rolled out to me yet. But this is what I think is very interesting. They looked at the chatbot over millions of requests, and it’s 93% accurate.

[26:52 –> 27:08] Dr. Ravi Kumar: Like 93%, right? And so if you’re taking a math test, that’s good. But if you’re talking about making declarations or decisions on critical medical issues, that’s really bad. Yeah. I mean, 7% of the time, you’re getting wrong information.

[27:09 –> 27:43] Dr. Ravi Kumar: They did state that, hey, it wasn’t the wrong, the 7% that was wrong wasn’t super consequential, and that sure, right? But just one, just one, you know, mess up by a self driving car and everyone’s up in arms. Imagine if this, you know, open an AI chatbot in Epic tells someone to, Hey, give them penicillin, they’ll be fine, and they have a penicillin allergy and they die of anaphylaxis. I mean, that’s the kind of screw up that can really cause a problem, you know, drug interactions. I mean there’s so much complexity around what we do with patients.

[27:43 –> 27:49] Dr. Ravi Kumar: So I’m sure there’s gonna be a complication from this, right? Yeah. There’s no doubt about it.

[27:49 –> 27:56] Ryan Estes: And it’s it’s tough math too because, you know, it’s like those mistakes already happen with humans all the time.

[27:56 –> 27:57] Dr. Ravi Kumar: Mhmm.

[27:57 –> 28:24] Ryan Estes: And actually the the statistics are pretty staggering where error kinda enters in and people die. I mean, it’s just yeah, it’s gonna it’s gonna happen. So if it’s 7% with AI and it’s 9% with humans, like it’s just that uncomfortable math that nobody really likes to do, you know, I do appreciate the reassurance of saying that privacy is probably good because they’re like cause they’re HIPAA compliant. And they’re like, dude, we’re not releasing your information. But I hear that.

[28:24 –> 29:03] Ryan Estes: And I, I just fear that like after I use my $4.99 app to diagnose my acne, you know, that immediately when I go to ChatGPT to search something, there’s gonna be an ad that pops up for acne cream. I’ll be like, oh, oh, I thought you weren’t talking about this. What’s going on? So, you know, I think where the the tech industry right now, especially right now, has really lost a lot of trust with with kind of public, especially if we’re talking about AI, because we’re on the heels of a couple of weeks ago, where you have all these Anthropic sponsored people, and x employees coming out saying that AI is gonna kill everybody.

[29:04 –> 29:05] Dr. Ravi Kumar: Yeah. I know.

[29:05 –> 29:05] Ryan Estes: You know, which

[29:05 –> 29:06] Dr. Ravi Kumar: I know.

[29:06 –> 29:20] Ryan Estes: Which feels like a big psyop, and they’re trying to, like, create regulatory moats. And you… There’s a big story of, like, why they would do that. But on just, like, a broad scheme, like, it’s like, what an irresponsible thing to say about your product. You know?

[29:20 –> 29:32] Ryan Estes: So Yeah. I mean, if, you know, if it’s my folks or it’s, like, people that might not know all the positive things that are coming from some of this technology, then they’re gonna immediately be repelled. They’re gonna immediately throw the baby out with the bathwater.

[29:32 –> 29:36] Dr. Ravi Kumar: Yeah. No. Exactly. And and I think… This is the other thing.

[29:36 –> 29:49] Dr. Ravi Kumar: I think people’s tolerance for mistakes from AI and robots robots and machines is very low. Yeah. But their their tolerance for mistakes by people is is high. You know? I mean, you Yeah.

[29:49 –> 30:02] Dr. Ravi Kumar: If someone makes a mistake driving, kills a kid, that’s bad. They go to jail, but, you know, no one’s stopping going… Getting on the road. Everyone keeps driving. Yeah.

[30:02 –> 30:43] Dr. Ravi Kumar: But if a if a car makes a mistake self driving, even though it makes a mistake at much lower frequency than a human being, that one mistake by the machine is unforgivable. And I think the same thing is going to be in medicine. AI makes a mistake that hurts a person, even though, like you said, medication and mistakes by doctors kill a lot of people every year. The numbers are staggering, and this OpenAI system or this AI in the medical record may reduce that dramatically. But if it makes even one mistake, people are gonna be like, hey, this is enough.

[30:43 –> 30:54] Dr. Ravi Kumar: You know? We can’t we can’t have… Handle this. It’ll just be a a mindset change. Over time, we’ll come to realize that, hey, I’d much rather have my airplane flown by AI than a pilot.

[30:54 –> 30:55] Dr. Ravi Kumar: You know?

[30:55 –> 31:08] Ryan Estes: Yeah. Well, and this might be a instance where it might it might take all… Going all the way to robotics, and with one big assumption But before I say that, it’s people love their doctor. You know? There…

[31:08 –> 31:36] Ryan Estes: There’s an aging boomer population that is massive right now, and they probably all have one thing in common, and they’re starving for attention. And where they get somebody’s undivided attention is the doctor’s office. Office. You know, you probably would know better than me, but you have boomers out there going to to the doctor two, three times a week, you know, and the doctor’s just like sending them pills or whatever because, you know, they have… I’m not saying that they don’t have ailments or whatever, but I think a lot of the the the…

[31:36 –> 31:57] Ryan Estes: There’s a social aspect, you know, and an admiration for your doctor. People legitimately love their doctor. So also on the docket was, something about an AI scribe brought… They omitted a certain word, which created a prescription or a diagnostic for the wrong thing. And I I saw that, and one thing that made me think of is…

[31:57 –> 32:13] Ryan Estes: And I love doctors. But if they’re omitting one word, when I read doctor’s charts, I can’t make out of anything. I mean, that’s just an old trope. But it’s like, my doctor, I’m lucky if I get nine words on there, just kinda like half scribbled out. You know what I mean?

[32:15 –> 32:46] Dr. Ravi Kumar: I know. So this story, I mean, so this was out of The UK through the National Health Service, the NHS there, and the AI, it was an AI scribe. So basically what’s happening is a doctor’s seeing a patient. The doctor and the patient are talking, and it’s being recorded by the doctor’s phone the whole time. And then that recording goes into an AI who basically listens to the whole conversation and integrates it into a note.

[32:46 –> 33:14] Dr. Ravi Kumar: So when the doctor walks out, he just goes to the computer, reads a note, and signs it, and that’s it. And it’s a remarkable increase in efficiency, because before that, the doctor would have to go interview the patient, He had to come out. He had to mentally put together the whole clinical picture, order the things he needs, write a note. Sometimes it’s typing. Sometimes it’s dictating through a dictaphone, which is like a AI transcription device.

[33:15 –> 33:57] Dr. Ravi Kumar: And it would take just as much time or more to do that note and all the orders as it would to see the patient. So doctors would go in, they’d see the patient for five minutes because they know they’ve got fifteen minutes total for this patient, and it’s gonna take them at least ten minutes to write up their their chart, and then they’re on to the next one. So now doctors are using this AI transcription system, and they’re spending thirteen, fourteen minutes with the patient because they know when they walk out of room, it’s only gonna take them one minute to do that note. So it’s this huge… The patients are more satisfied, the doctors are more satisfied because they’re not wasting time just typing on the computer and breaking their brain, staring at a screen.

[33:57 –> 34:25] Dr. Ravi Kumar: So it actually has improved the touch rate or the touch time between doctor and patient. Now in this story that you brought up out of the NHS, the patient and doctor were talking about some nerve issues that the patient was having, and it said null demyelination. Null means no. That’s what the the imaging report said. So it means null d…

[34:25 –> 34:43] Dr. Ravi Kumar: Null demyelination, and demyelination is where the the… Basically, the neuron loses its insulative covering, and that’s called myelin. So when you demyelinate, you actually remove the covering of the nerve, and it doesn’t work anymore. And that’s what happens in multiple sclerosis. Interesting.

[34:43 –> 35:02] Dr. Ravi Kumar: So the the the the chatbot or the the AI transcription system said demyelination from multiple sclerosis instead of null demyelination from multiple sclerosis. And that one word omission changed the whole meaning of that. The patient goes home, they read it, and they get distressed.

[35:02 –> 35:02] Ryan Estes: Right.

[35:02 –> 35:12] Dr. Ravi Kumar: And then they made a whole story about it, about one word. And you’re right, man, Ryan. Like, when I… Before, I use AI transcription now too. I don’t…

[35:12 –> 35:14] Dr. Ravi Kumar: I never wanna go back. Oh, it’s great.

[35:14 –> 35:15] Ryan Estes: It’s incredible.

[35:15 –> 35:26] Dr. Ravi Kumar: Truly. But before, I would use this Dragon or… What is the other company that I would use? It was another competitor with AI with Dragon. And they would…

[35:27 –> 35:44] Dr. Ravi Kumar: I would dictate into this thing and would type out my note, and it’s like basically like using your iPhone to text dictate. It’s just making a ton of mistakes. And so you have to go and you have to try to fix these things, and you’re like, God, what was I even saying here? Because I can’t even tell anymore. Yeah.

[35:44 –> 35:57] Dr. Ravi Kumar: And then the note at the note… End of the note, you have to say, I used dictation, automatic dictation service, there… There’s gonna be errors. Because when people read through their note, they’re like, what does this mean? You know?

[35:57 –> 36:11] Dr. Ravi Kumar: Because that… You can’t go back and, like, it’ll take twice as much time to like fix every single error. You gotta get the main information out there. So this AI transcription system totally changed the world, man. It’s gonna change your…

[36:11 –> 36:13] Dr. Ravi Kumar: The time you get with your doctor.

[36:13 –> 36:58] Ryan Estes: And improve the understanding, because, you know, in a way, a conversation with anybody is kind of a psychedelic experience, where you’re like, you have their whole energy and their emotions going into it, and they’re telling stuff, and you’re processing, and you’re talking. It’s like when I listen to a lot of like my podcasts, I’ll listen to something that somebody says. I’m like, wow, I missed that part. I wish I would have gone into that deeper. So if you’re dictating, it’s like it’s still your take. But if you use these transcription services, then you’re getting the breadth of the conversation and you can see notes and see what you missed on the first time. I mean, if I if I was a doctor and I’m not and I don’t play one online, but I could imagine like if there was somebody who came in who had just the thickest Bronx accent, I I wouldn’t be able to hear a word he said. I’d just be like fixated on this accent.

[36:58 –> 37:05] Ryan Estes: I’d be like hypnotized by it. And then at the end I’ll be like, oh no. Thank God I had it transcribed so I could figure out what he’s trying to tell me. But

[37:08 –> 37:10] Dr. Ravi Kumar: Oh man. Yeah. Know this.

[37:10 –> 37:34] Ryan Estes: So yeah. Yeah. I mean, it it gives the doctor, I think, deeper insight into the patient and then of course like a summary for the patient. Again, like if every single specialist you see has their own platform and their own chat function and they all, so you’ll go see somebody for an hour and you get like one sentence, blah blah blah blah blah, email update, and you’re like, man, I would have really like a summary of that conversation, which you can do so easy now.

[37:34 –> 37:43] Dr. Ravi Kumar: Yeah. Yeah. Totally. And I’ll also say these AI transcription, AI scribes, they’re way more thorough. Just like you mentioned.

[37:43 –> 37:54] Dr. Ravi Kumar: Like, I’ll go and I’ll read the note, I’ll be like, woah. I forgot she she mentioned that to me. Yeah. Or this is the other thing that I found this very helpful is we’ll be doing a… I’ll do an appointment.

[37:54 –> 38:05] Dr. Ravi Kumar: I’m in North Carolina. So I’ll get these patients with these deep southern accents, and I can hardly understand them. Right. Right. Can understand, like, half of what they say, but the AI scribe understands everything.

[38:06 –> 38:09] Dr. Ravi Kumar: Yeah. And so I’ll be like, oh, that’s what they were saying.

[38:09 –> 38:24] Ryan Estes: Okay. Yeah. Oh, it just points out, like, truly how difficult human communication is. I mean, it’s kinda miraculous that, like, my vocal cords can vibrate, go through the microphone, go into your ears, and we kinda have an understanding. I mean, it is miraculous.

[38:24 –> 38:32] Ryan Estes: You know? So if you have that tool, and that’s kinda like just the very beginning, which is… It’s it’s incredible. But, of course, you know, mistakes will happen.

[38:32 –> 38:34] Dr. Ravi Kumar: Yeah. Exactly.

[38:34 –> 38:51] Ryan Estes: You know? Maybe maybe we go into one more thing before we wrap this up. I do wanna talk about the future a little bit. And I kinda intro it by saying that, like, people love their doctor. So they’re gonna be skeptical if AI makes any mistakes because AI feels cold.

[38:51 –> 39:17] Ryan Estes: It feels, like, detached. It feels like it it doesn’t care. Now if Elon has his way, all of us in five to ten years are gonna have a four foot robot that lives in a robot house either charging itself or vacuuming the floors or making you a chicken sandwich or potentially operating on your brain. You know? And and this is Elon’s exact words.

[39:17 –> 39:35] Ryan Estes: It’ll do your taxes. It will brush your teeth for you. It will nurture you, and it will sing you a lullaby. But also it’s gonna have the technical capabilities to be your lawyer, your doctor, all these things. So my my assumption here is people are gonna fall in love with these robots in some kind of way.

[39:35 –> 39:50] Ryan Estes: And now there’s 12 different kinds of love. You know, there are gonna be the romantic people. Every single person I’ve met that has created an AI chatbot for their business has had someone fall in love with that chatbot. But let’s not get into romantic love. Let’s just think of it as your robot cousin.

[39:51 –> 40:01] Ryan Estes: You know? So at that point, maybe I’ll tee off a question, which is like, do you feel threatened and jeopardized by robots coming for your neurosurgery?

[40:01 –> 40:15] Dr. Ravi Kumar: Yeah. Well, we’re already using them, Ryan, in neurosurgery. You know? And and maybe neurosurgery is one of the places where it’s gonna show up and progress faster than the other fields. I mean, we’re using them in neurosurgery.

[40:15 –> 40:24] Dr. Ravi Kumar: We’re using them in urology. We’re using them in gynecology. We’re using them in general surgery. They’re using them in orthopedics. So it’s it’s already here.

[40:24 –> 40:54] Dr. Ravi Kumar: Yeah. But it’s a it’s a human controlled robot the way it it works right now. So, basically, what happens is, you know, when I operate, there’s, like, millimeters of error that you can have before a patient gets really hurt. And the central nervous nervous system is very delicate, and it doesn’t tolerate mistakes. And when you do make a mistake, the the consequence is is bad because the central nervous system is so functional.

[40:55 –> 41:45] Dr. Ravi Kumar: Well, so these robots, they will basically move very deliberately based on input from a human. So for instance, right now, if you want to instrument the spine and you have to pass this screw down a two millimeter corridor with a vertebral artery that feeds your brainstem on one side and the spinal cord that controls your whole body and the other side of it, and you have to glide it down that corridor of bone, well, the robot will use imaging, use real time analysis of the alignment of the spine, and it’ll sub millimeter accuracy say, hey, I wanna put the screw right here, and you say, And then it lines it up, and then you drive the screw in. And the patient doesn’t get paralyzed. They don’t get a brainstem stroke, and everyone’s super happy. So, yeah, robotics is here already.

[41:45 –> 41:57] Dr. Ravi Kumar: It’s progressing. The next step is less human intervention. Yeah. It’s it’s a robot operating, but with a human giving the okay. So they’re…

[41:57 –> 42:16] Dr. Ravi Kumar: They don’t actually have their hands in the field. They’re just saying, I like your plan. Do this, and go for it. And And then the error of the human hands, the little tremor or the mistake or the judgment call mistake, those are gone. It’s just a planned, deliberate surgery performed by a machine.

[42:17 –> 42:45] Dr. Ravi Kumar: And then once we’ve got past that, it’s autonomous robots performing surgeries based on very strict clinical guidelines and algorithms for doing surgeries. And, you know, I’ll retire. I mean, would much rather have a algorithm that understands how to do it as safe as possible than a human being that makes mistakes. And, you know, to to is to be human. Right?

[42:45 –> 42:56] Ryan Estes: Yeah. You know, the the… There seems to be a tension, though. The the the precision, the actual physical precision of a robot’s probably unmatched, but there’s also a feel. Right?

[42:56 –> 43:08] Ryan Estes: There’s kind of a poetry to surgery, and that comes from experience, that comes from a… Like, feeling literally the environment. I mean, using the force, for lack of a better word. I’m making you a Jedi on this analogy. You know?

[43:08 –> 43:21] Ryan Estes: So what… How… What’s the trade off? Do you lose something when you have kind of the feel of the doctor with all that experience and time that that you might not have if you’re using kind of a a robot?

[43:22 –> 44:06] Dr. Ravi Kumar: You know, there’s… Older surgeons are safer than younger surgeons. That’s just that everyone in surgery knows it. If you’re a 60 year old surgeon who’s been practicing for thirty years versus a 30 year old surgeon who’s just out of training, I’ll take that 60 year old every day because they’ve got thirty years of experience using that, what you’re talking about, that feel, that understanding of how to do things safely and what things look like. They’ve seen 10,000 different spines or gallbladders, and they know that in this certain situation, arteries right around this corner that you can’t see, so you want to be careful.

[44:07 –> 44:46] Dr. Ravi Kumar: That is the limitations of a human being. They have to have empirical experience to understand complex situations. And that’s why older surgeon is safer than younger surgeon. Now, a robot with an AI system trained on a 100,000 cases is smart on day one, smarter than the older surgeon. So, yeah, yeah, there is there is something to be said for an old, wise surgeon who understands anatomy and and has had a bunch of complications to learn through learn through through their career.

[44:46 –> 45:13] Dr. Ravi Kumar: But, you know, that doesn’t have to happen anymore. You don’t have to have a 60 year old surgeon who’s had, you know, a thousand or, you know, 500 durotomies on a spine surgery to understand how to not have a durotomy anymore, the robot can do it on day one. And that’s the way we need to move. I mean, my surgical colleagues are probably planning how they’re going to lynch me right now. The young ones.

[45:13 –> 45:25] Dr. Ravi Kumar: Joking. Yeah. So… But, you know, the things that humans have that robots can never have, Ryan, empathy Yeah. A sense of mission, curiosity.

[45:25 –> 45:59] Dr. Ravi Kumar: Now maybe we’re moving towards, you know, with superintelligence and general intelligence, curiosity in robots. But still, these are things that are innately human. And that is that is something that we’re not gonna be able to give to robots anytime soon. But if we can combine the human aspects of medicine through human beings with the infallible accuracy of robotics and AI systems, then we’ll have a better medical system. Yeah.

[45:59 –> 46:02] Dr. Ravi Kumar: You know? 100%. Yeah.

[46:02 –> 46:18] Ryan Estes: And it’ll be… It’ll change, and it will feel more careful, you know, I I think, because there’ll be more time for that, and it’ll it’ll increase the margin. So, you know, the insurance companies will be happier. And I I think you made a really good point that they’re… They’ll never have empathy.

[46:19 –> 46:34] Ryan Estes: They’ll be able to fake it, but the more… The closer they get to that fake empathy to feeling real, the more you’ll kinda hate it. You know? In ten years, if I walk into the house and my robot’s like, Ryan, I can smell your serotonin levels are low. Would you like a hug?

[46:34 –> 46:42] Ryan Estes: Be like, man, get away from me and quit smelling my serotonin. You know? It’s like, no. I wanna pet the dog. Like, come on, man.

[46:42 –> 46:43] Ryan Estes: Know your space.

[46:43 –> 46:49] Dr. Ravi Kumar: Except that robot’s gonna have a perfectly human voice and probably look like a beautiful woman.

[46:49 –> 46:51] Ryan Estes: Sell them a high end for me.

[46:51 –> 47:05] Dr. Ravi Kumar: And have, yeah, and have a cup of hot coffee ready for you. I mean, there… Mean, human beings are so easily manipulatable. You know? Mean, that’s how the robots are gonna take us down.

[47:05 –> 47:17] Dr. Ravi Kumar: But no, I I I don’t wanna play into that that narrative, but still, we… You know, it’s it’s not gonna be that robotic voice saying they’re sniffing your serotonin. It’s gonna be something different.

[47:17 –> 47:21] Ryan Estes: Yeah. Exactly. Greet you with a turkey sandwich. You’d be like, wow. I feel better.

[47:21 –> 47:30] Ryan Estes: I knew you would. Nice. Oh, Ravi, this has been so much fun. I appreciate your optimism. You know?

[47:30 –> 47:52] Ryan Estes: I think it’s really good to hear about all the positive things coming our way as just people on planet Earth, You know? And so I appreciate that. Before we get out of here though, I would be remiss if I didn’t tell my audience about your new tool that I am absolutely in love with, and it’s braingamer.app. Give me a quick description of the app so we can get people over there.

[47:52 –> 48:09] Dr. Ravi Kumar: Yeah. So it’s an app that I built to exercise the different domains of your brain and your thinking. So I built nine different games. They’re just like fun little games, but they exercise knowledge or logic or planning. And they…

[48:09 –> 48:23] Dr. Ravi Kumar: And each one of those uses a different circuit of thinking, essentially. And and so you can you can play this game and get, like, a little exercise. Kinda like you go to the gym and work your muscles. This… You’re going to the gym and working your brain.

[48:23 –> 48:39] Dr. Ravi Kumar: It’s it’s something fun, and it… It’s intentional, and it it doesn’t feel like work. So, yeah, you can play for free. There’s, you know, you can play three games per day for free, and if you want unlimited plays, it’s, you know, a small monthly monthly pay… Subscription fee.

[48:39 –> 48:47] Dr. Ravi Kumar: But, yeah, it’s it’s free to play, and you can share with your friends. And I I really like it. My family and friends really like it, and it’s out there for the world to use now.

[48:47 –> 48:58] Ryan Estes: Yeah. Definitely check it out. It’s braingamer.app. And I I really like it because, you know, we all go to our phone when we have these little transitions. I mean, it’s multiple seconds you pick up Instagram, Just out of habit, you know?

[48:58 –> 49:11] Ryan Estes: Mhmm. And I’ve been trying to use this kind of like mental analogy that every time I’m doom scrolling, it’s just a sandpaper smoothing my brain up every time I swipe up. Because it just feels like it really smooths out my brain.

[49:11 –> 49:11] Dr. Ravi Kumar: So Yeah.

[49:11 –> 49:28] Ryan Estes: I’m looking for like things I can do to fill that time because, know, just out of pattern and habit, I’m gonna go pick up my phone. And, you know, Brain Gamer’s perfect because it’s like the games maybe take sixty seconds to a couple of minutes. You can just kind of whip through them and get through it. It’s it’s a really cool tool and I love it, Ravi.

[49:29 –> 49:30] Dr. Ravi Kumar: Yeah. Thanks, Ryan.

[49:30 –> 49:47] Ryan Estes: Cool. Well, let’s wrap this up. Ladies and gentlemen, definitely check out drkumardiscovery.com where you have links to everything Dr. Kumar is working on, including his podcast, his YouTube. He’s got an incredible blog for folks that are maybe new to the Dr Kumar Discovery.

[49:47 –> 50:04] Ryan Estes: He takes deep dives on every single episode into like all the things that ail us and all the things that are making us better. They’re absolutely jammed packed with information and insights. Oftentimes, I have to listen to them at least twice. So on that, Dr. Kumar, great to see you.

[50:04 –> 50:05] Ryan Estes: Thank you so much for doing this.

[50:05 –> 50:11] Dr. Ravi Kumar: Yeah. It’s been awesome, Ryan. Thanks a lot. And I would just tell the audience, if you like this, let us know. Leave a comment.

[50:12 –> 50:18] Dr. Ravi Kumar: Send us an email. I mean, because we’ll do this once a month if you want, or, you know, on a more regular basis at least.

[50:18 –> 50:22] Ryan Estes: 100%. Let’s do it. Oh, and if you wanna follow me, I’m at aiforfounders.co.

[50:23 –> 50:24] Dr. Ravi Kumar: Fantastic.

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