Beyond the Algorithm: Technology, Trust & Patient Care, part 2 | Ep 83

WEBVTT
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Where is AI taking health care?
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And what could it mean for the aeromedical industry?
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In this episode, we explore the opportunities, challenges, and some of the possibilities we may see in the years ahead.
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There are five things that you have to think about whenever you buy an AI product.
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For your team.
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Number one, is it safe?
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For your teammates?
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Is it safe for you?
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Is it safe for your patients?
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Number two, is it secure?
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Is it secure for your patients?
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Your people?
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Is it secure for you?
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Data quality.
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Is your data quality good enough to start even using it?
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Is the data going into it even going to help you with good outputs?
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The fourth thing is your culture.
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Are you leaning too hard on that technology to make decisions for you?
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Or do you have a good group of clinicians who are very, very sharp, who are on the basics, who can take care of patients, who can care for them?
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And this will help offload mundane tasks so they can focus on that.
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And then the fifth thing, are your policies aligned to safely take on these technologies?
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Welcome back to the Bower Fight Crew Podcast.
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In this episode, we sit down with Christian Greengrass to talk about a topic that is quickly becoming impossible to ignore in healthcare artificial intelligence.
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We take a closer look at what AI could mean for our industry and how it can support clinical applications, decision-making processes, and reducing documentation burdens.
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There is no doubt to what this can do for clinicians as we look at connecting technology with improving patient outcomes.
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But this conversation isn't just about what AI can do.
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We also talk about what it should do and where we need to be careful.
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We explore data security, privacy, human factors, clinical intuition, and the very real risks of relying too heavily on technology when patient care is online.
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There's a lot to unpack in this episode, so sit back, relax, and let's get into it.
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Thank you to our sponsors, Global Medical Response Air.
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Precision Aviation Group.
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And Spectrum Aeromed.
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Welcome to the Valor Flight Crew Podcast.
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Brought to you by Vertical Helicast, produced in partnership with Echo, every coast helicopter operation.
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The Valor Flight Crew Podcast promotes the personnel and lifesaving equipment behind helicopter air ambulance services.
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Join hosts Mike Fidel and Blake Strider for in-depth interviews and expert insights from air medical personnel, pilots, communications specialists, and maintenance crews who play critical roles in airborne emergency response technique.
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What I truly worry about in this situation is that while AI is a great tool, is it going to make us as providers dumber?
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Are we only going to be able to look at this input from the AI and say, oh, well, AI is smarter than I am.
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They suggested I do this now.
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Like that, that to me is not okay.
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And and I I'm going to stand on my soapbox.
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I am absolutely going to stand on my soapbox here.
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Look, it's got a time and place, but I really struggle with how this is going to integrate into the clinical side of things because there are so many variables.
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And again, this is this is what I worry for our newer clinicians, who I think that our newer clinicians are very brilliant.
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And I think I love their passion and drive and desire in the industry.
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But they're also more technologically advanced and I think much more apt to tie into what's going on with them technologically.
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And that gut instinct from 27 years of medicine, in my opinion, for me, is never going to replace what a machine is telling me about that patient.
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And I struggle because we have a lot of clinicians, you know, we we as as programs, we look at those clinicians that have been in as from nursing side of things working in an ERICU for three to five years.
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That's great.
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That's good.
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I think that for most people who have the passion and and drive and desire to do this job, that they've probably got that solid gut instinct at that point.
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But that's not everyone.
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And I I I'm sorry, but I struggle to believe that this is going to make us necessarily smarter as clinicians if you don't have that gut to back up what is in front of you.
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Mike, you have no idea how much I love you right now.
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As we say in the South, preach, brother, preach.
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Listen, no, this is good.
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This is good.
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This is exactly what I'm saying.
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What you're saying right there, don't ever lose that.
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Because you're right.
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100%.
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This is why I'm a brake pedal about some of these things.
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And now you see you see exactly what I'm saying, right?
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Like we have a lot of possibilities.
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Yeah, I totally get it on like the admin or the charting or the other things.
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But when it comes to patient care, yes, I I'm I'm okay with with feedback.
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I'm okay with suggestions.
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I'm okay with, hey, this is a possibility.
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But if if I don't have that gut instinct, no, this isn't because it's a ventilator issue, this is because my patient needs sedation adjusted.
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That's right.
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Like that, it it that's that's where the gut comes in that I feel as though we're gonna we're gonna struggle.
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And I don't want to see us as clinicians lose our ability to think on our own.
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That's right.
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And that's where, Mike, the education is helpful.
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So that is why if I had to pick between education using these systems and clinical, live clinical decision support, clinical decision support is always gonna lose.
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Because for me, quality, CQI, and education are gonna be the first places that we need to really be looking at these tools for.
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Yeah.
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Right.
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Because that's where we can take our experience, we can take our knowledge, we can build scenarios, we can educate better.
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You know, your your your trainee can sit on the couch because they're tech driven anyways, because of this generation, and they can ask questions, right?
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I can't even imagine that day for me personally.
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Like that is not how I learn at all.
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Yeah.
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But being a typewriter.
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Typewriter.
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I want to see this thing, by the way.
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Maybe offline.
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You just yeah, pull it out, man.
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Pull out the typewriter.
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Well, instead of a soapbox that he stands on, it's the typewriter box that he stands on.
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Exactly.
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But that's good though.
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That's that's no, I love that because as someone who is an advocate for these tools, I'm also an advocate for using them correctly.
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And for example, right now I'm on orientation, right?
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I've got an amazing FTO.
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Guy has thousands of flights under his belt.
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You know what?
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And I'll I'll say this on a podcast, a national podcast.
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I'll say this.
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You know, the other day, he was like, hey man, get your head out of the paperwork and look at your patient.
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He's right.
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He's absolutely right.
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And I had, I had, I had to get my head out of the paperwork.
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And you know, I work tomorrow night, and that's all I'm thinking about is I'm gonna do a better job at focusing on my patient.
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I'm not gonna be focusing on paperwork, I'm not gonna be focusing on charting.
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You know, the way my brain's wired, you know, neurodivergently wired.
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Like I want to look at the paper because I want all the answers.
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But at the end of the day, you're right, Mike.
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That's where the human stays in the loop in the in these technologies.
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That's why humans should always stay in the loop.
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Do not let these technologies replace you because it can't.
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Yeah.
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At least not in the foreseeable future, um, it from what I've observed.
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But I think that is if I if anyone could take anything home from this podcast today, it would be if you feel free to let these tools help you, but not replace you.
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Because at the end of the day, you, you know, the patients need that touch, right?
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Uh, there's a lot of evidence that actually shows that you know the human touch is helpful.
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You know, that's why someone's uh someone who's not medically related was telling me it's like, oh man, robots can replace nurses when they know they're not.
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No, no, they're not.
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No.
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I'm not sitting here saying that like you were saying, oh, we should, we should absolutely go down this route.
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I know that you're talking about it as these are possibilities, right?
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Like these are things for the future.
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But I could just feel like my blood starting to boil over here because I I feel like we as clinicians have worked so hard to get to the point where we can independently care for these critically complex patients and make all of these physician-level decisions on how we are managing that particular patient or population or what have you.
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And and that is that is the part I don't want to see us lose.
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We have worked so hard as an industry to get to where we are.
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And I look at, I look at when I when I started in in Hems, when I started in healthcare, period, uh, you know, and again, uh, but back in that day, we were throwing everybody on 15 liters Domer Breather because that was that was what the book said we're supposed to be doing, right?
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Like, and and look where we've come in that time period and all the things that we have advanced as an industry.
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And I don't want to see us lose that because we have a suggestion from AI that that's what we should, the route that we should be going.
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That's where I struggle with it.
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Now, Mike, if I may add this.
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So, you know, I was watching um, it was it was like a TV show or something, right?
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You know how we all sit and watch reels and whatever.
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And there was a really, really good point that was made.
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It was like, oh, it was one of it's actually an influencer, Dr.
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Glockenfleck.
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I mean, he's hilarious.
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But he was saying to the senior physician, he's like, Well, back in my day, you know, we we would work 20-hour call days, we didn't have work, you know, work hour limitations for residency.
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And these two, you know, medical students go, oh, let me get this straight.
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So, you know, you're expecting us who have to learn three times as much information as you, you know, medicine is advancing fast because of these technologies, right?
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Like we're doing protein mapping, you know, cancer treatments are getting more customized.
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It's incredible, right?
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Sure.
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Yeah.
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And the knowledge base is getting huge.
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Like how we treat things, or there's so many pathways, right?
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Like I always go down my my methylene blue, you know, presentation pipeline, right?
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Presentations you could probably ever give, just saying.
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I thought it was good, but you know, it's just it is a little bit rabbit hole, right?
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But it I give those it incites the mind to think.
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That's that's what it's there for.
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But the point I'm that that proves the point, like right here.
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Like, Mike, that like that proves that point, right?
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And and so of why the human factor shall and always must be part of the healthcare and how we treat patients, right?
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I I'm thinking back to what you were saying earlier about let's say using AI as an assist, right?
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Helping radiology.
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Okay.
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So as the radiologist, if you miss something and then AI catches it, right?
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Who's responsible for that, right?
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And you know, to to speak to Mike's point, like the the human element factor, it it can't go away, right?
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We train and we've advocated so hard for not only the field, just all of us in healthcare.
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Like whether you're at a basic level, all the way on up to critical care, even physician level, right?
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But the human part of us, like we must always know that that we're all we're gonna make mistakes because we truly are that human, right?
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And and I think in a society where now there's almost this, like I I don't know how to describe it.
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Maybe there's like this dependence that technology and tools and all these things will like essentially make us perfect.
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I I think that's the the wrong pathway or or or way to think that this will make us, you know, it to that level.
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But the the human element will always be there, and I think we have to trust that and and never let that go.
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Like, yeah, we're gonna make mistakes, like that, but guess what?
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Artificial learning, and like it's literally in the name artificial.
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So, like, it's going to make mistakes, and we know that that's that's a possibility.
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And and I wholeheartedly agree that that human element, because if it was that easy, like if it truly was that easy to take everything that we've learned and all this data, and then create something that is so perfect, then why isn't it happening?
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You know, right?
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Which uh it isn't, and I think that really kind of rides this point where a lot of the reasons why I felt this discussion was going to be really beneficial is using it to help us and allow us to assist us as providers to get us to that next level, but we can't replace that human element to what we do and how we take care of our patients.
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Yeah, so Mike, don't lose your fire, my friend.
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That's great.
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Because but seriously, because you're you're protecting your people and your patients, and that's critical.
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Absolutely.
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And I and there's five points.
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If there's any leaders listening who have any influence on buying these things, there are five things that you have to think about whenever you buy an AI product for your team.
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Number one, is it safe for your teammates?
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Is it safe for you?
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Is it safe for your patients?
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That's number one.
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Number two, is it secure?
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Is it secure for your patients, your people?
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Is it secure for you?
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Data quality.
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Is your data quality good enough to start even using it?
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Is the data going into it even going to help you with good outputs?
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The fourth thing is your culture.
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Is your culture in a place where, to Mike's point, are you leaning too hard on that technology to make decisions for you?
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Or do you have a good group of clinicians who are very, very sharp, who are on the basics, who can take care of patients, who can care for them?
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And this will help offload mundane tasks so they can focus on that.
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And then the fifth thing, are your policies aligned to safely take on these technologies?
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So that those are the five points.
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Like you take those five points with you when you're buying these technologies, or when a salesman comes to you, if you can answer them correct in a way that's like, yes, this would help me, then okay, go for it.
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But if you can't answer those questions correctly or properly, I I would highly recommend getting yourself in a good state before you take those on.
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Yeah, and and I and I I I I love that you said that.
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And I'm I'm in agreement with you for the most part on all this stuff.
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Uh but what I keep going, you know, I I think where my fear is is stemming from in all of this is the the power of suggestion can be very compelling at times.
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And there may be that patient situation in front of you where you may not necessarily be 100% sure of what's going on, but you got a strong gut instinct of where you should potentially go.
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I don't want to see us rely on AI in those circumstances to suggest something that may not be in the best interest of our patient because not all of the contextual information is there.
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And that's what I fear for us as clinicians to be able to maintain that gut, to maintain the knowledge base that we have, to continually build upon that.
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And I think that AI is a great tool for that.
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I really do.
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I just I I'm very, very cautious about how it's going to be able to have the insight into everything that's going on with our patients, as well as we are with the years of experience and the gut that we have and the tools at our disposal.
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I mean, that that doorway assessment that we do is like one of the most important things that that we can ever do for our patients, I think, and in gathering all of that information.
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And I can't tell you how many times I have walked into this extremely critical situation, transferring an ECMO or an Impello or what have you, and just stop for 30 seconds or a minute and just look around the room and take it all in.
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And then I'm like, okay, this is how this is what helps my helps me prioritize and organize and gives me my game plan of everything that's going to happen.
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And and I I I just I don't want to see us relying on AI to take us down a path that maybe isn't where we should be going.
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I agree completely, Mike.
00:17:34.160 --> 00:17:39.119
And this is where now everything you said, we and we had talked about this on the podcast.
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To me, this is where the Future Flight Leaders program comes into play.
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And this is where good FTOs come into play, right?
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Think about the FTO I was just telling you about.
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My FTO right now, he told me, Christian, get your head out of the paperwork, man.
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Look at your patient.
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Take care of your patient.
00:17:53.440 --> 00:17:55.599
You know, that's the key.
00:17:55.839 --> 00:18:01.039
Having good FTOs, having your experienced people who are like, they know better.
00:18:01.200 --> 00:18:06.240
They like to if you were my FTO, Mike, I'd love it because you do think about that stuff, right?
00:18:06.480 --> 00:18:07.759
We have to keep that alive.
00:18:07.839 --> 00:18:09.359
And that's going to come through training.
00:18:09.519 --> 00:18:23.359
That's going to come through having those good CQI discussions, having good FTOs that are trained on how to train people and understand how people learn and those concepts that you can't just quantify.
00:18:23.519 --> 00:18:27.440
Because in my world in data, I can't quantify everything, right?
00:18:27.599 --> 00:18:31.680
Intuition is not necessarily quantifiable, despite what some textbooks might say.
00:18:31.759 --> 00:18:36.880
They say, oh, well, you know, intuition is based on data that you have that you just don't necessarily fully understand.
00:18:37.039 --> 00:18:39.359
I agree with that, but I also disagree with it too.
00:18:39.519 --> 00:18:43.359
Because I think sometimes the gut feeling is going to help you say, you know what, I think this patient needs this right now.
00:18:43.440 --> 00:18:44.720
And I've had those moments.
00:18:44.960 --> 00:18:48.240
And so to your point, I think it's once again, it's a balance.
00:18:48.559 --> 00:18:50.480
And you've seen it in the news too, right?
00:18:50.640 --> 00:18:58.079
Have you guys seen the news in the last few days about some of that stuff that's been coming out with AI and being concerned with the dangers of it?
00:18:58.240 --> 00:18:58.480
Yep.
00:18:58.799 --> 00:18:59.279
Good.
00:18:59.519 --> 00:18:59.920
Good.
00:19:00.160 --> 00:19:01.359
I'm glad they're doing that.
00:19:01.519 --> 00:19:05.920
Because as much as I am as an advocate for it, I'm also a cautious optimist about it as well.
00:19:06.000 --> 00:19:09.119
That's why I'm learning about it and wanting to become a strategist in it.
00:19:09.200 --> 00:19:20.720
Because and I think every leader should, in their own way, become a strategist in AI because uh you're gonna have your crew members coming up saying, Hey, get this tool, get this, get that, buy this, buy that, let's do this.
00:19:20.960 --> 00:19:26.640
And that might be great, but we also have vibe coded garbage that's out there too that people are gonna bring you.
00:19:26.960 --> 00:19:30.880
It's vibe coded, and they're gonna go, Oh, yeah, this is this is excellent.
00:19:30.960 --> 00:19:32.319
And you're like, Yeah, okay.
00:19:32.480 --> 00:19:33.440
No, yeah, sure.
00:19:33.599 --> 00:19:36.240
Um, let's look at the the safety and securities piece of it.
00:19:36.319 --> 00:19:40.480
And then you to tear it apart and you find it's the most unsecure, dangerous thing you've ever seen in your life.
00:19:40.720 --> 00:19:43.759
So no, I mean, I I I yeah, I think that's great, Mike.
00:19:43.839 --> 00:19:44.960
I love your insight on this, my friend.
00:19:45.039 --> 00:19:45.920
I think that's a good idea.
00:19:46.160 --> 00:19:55.440
Sorry to get so passionate there, but please I don't I don't feel like I don't feel like even and and I'll apologize to the listeners too, because I don't feel like you've heard that kind of passion come out of me in a while.
00:19:55.839 --> 00:20:02.400
But that is definitely it's just one of those things that I I I I'm that's where I struggle the biggest with all of this.
00:20:02.720 --> 00:20:06.720
But that's the whole point of like that these are conversations that we should be having, right?
00:20:06.799 --> 00:20:08.559
And and I know that we have these at base level.
00:20:08.640 --> 00:20:09.359
I have them all the time.
00:20:09.440 --> 00:20:12.480
And and Christian and Mike, I'm gonna throw this example out there, right?
00:20:12.559 --> 00:20:22.240
And this kind of leads me into kind of our like that next section when you're talking about how this can really apply into leadership, the organizational responsibility of using AI correctly.
00:20:22.319 --> 00:20:23.440
I I will never forget this.
00:20:23.519 --> 00:20:25.039
This happened to me about a year ago.
00:20:25.200 --> 00:20:30.319
I had one of my dear friends uh ask me about a patient encounter that they had.
00:20:30.640 --> 00:20:44.559
The the parameters that they used, they they they ended up going with like this this higher peep initially because of uh what they did as part of a I know this is strange, a hands-on physical assessment, right?
00:20:44.720 --> 00:20:59.359
Like, you know, using a stethoscope, touching the patient, doing a full assessment, listening to lung sounds, then getting them onto non-invasive, then going through a drug-assisted airway, and then continuing that on.
00:20:59.519 --> 00:21:16.720
And I'll never forget because the person, the the people that are responsible for reviewing those types of calls completely came back with like this whole well, why did you go to to that level of peep, you know, to start off with?
00:21:17.119 --> 00:21:29.599
And it was very clear in the documentation based on what the provider encountered and what they ended up with, and then transitioned to and kind of kept that going.
00:21:29.759 --> 00:21:33.519
And the patient did great with that therapy.
00:21:33.839 --> 00:21:38.880
And I just remember they were they were asking me, Hey, what do you think of this?
00:21:39.519 --> 00:21:45.839
And before I even read the the the QA note, I was like, Yeah, that's pretty good.
00:21:46.000 --> 00:21:47.839
I feel I feel like you you transitioned well.
00:21:47.920 --> 00:21:51.359
You continued what you you started to a position where it was working.
00:21:51.599 --> 00:21:55.359
The patient improved, but yet they still had a lot of work of breathing.
00:21:55.440 --> 00:21:58.000
So, you know, you did the things and they did better.
00:21:58.240 --> 00:22:01.680
And I was like, I feel like you're what you documented supported it.
00:22:01.759 --> 00:22:05.200
And I'll just never forget the reply from the the person.
00:22:05.920 --> 00:22:21.440
And then my bias in knowing the person that did this is someone that is experienced and their response and everything why you can read something and totally tell when it's AI written completely.
00:22:21.920 --> 00:22:33.599
And it just floored me only in the sense of like you didn't even take into consideration reading what physically had like what was documented, right?
00:22:33.680 --> 00:22:35.440
Because that's the only info that they had.
00:22:35.519 --> 00:22:53.039
They weren't on the call and just reading this um reply there was no human like empathetical like it was just all AI like well based on the our protocol or based on this and it was just like who are you and like why would you do that?
00:22:53.119 --> 00:22:59.200
And I just remember feeling for my friend and being like man that sucks.
00:22:59.440 --> 00:23:22.640
Like that's not even a way to have like a true actual like Socratic discussion about what happened and it was just it was totally reliant on an artificial like reply of well these might be my points but say this and it didn't even speak to what was really going on with the patient.
00:23:22.720 --> 00:23:35.599
And I think for me that was like wow as someone as part of like training and like leading people and with experience completely not something that I would have expected from someone in that position.
00:23:35.680 --> 00:23:55.759
That's why I'm just wondering so using that type of example and then and Mike that that also points to I think not only are we reliant on us that human element and taking care of patients that also transitions when you become a leader when you start teaching and using education.
00:23:55.920 --> 00:23:59.039
I think it's the the podcast that we just did with Dr.
00:23:59.279 --> 00:24:06.480
uh Jens the only way to get good and better at medicine is doing medicine and practicing.
00:24:06.559 --> 00:24:08.640
So that experience means something.
00:24:08.880 --> 00:24:09.039
Yeah.
00:24:09.279 --> 00:24:25.200
And I'm just curious how we can use like and not lose that part of like the AI reliance but the assistance to help us have a true foundational leadership and organizational responsibility to do it the right way as we go forward.
00:24:25.599 --> 00:24:40.720
Your situation Blake it violated two of my rules culture and policy right yeah like number one you should have policy that says for any sort of CQI interactions AI is not permitted right number two culture.
00:24:40.960 --> 00:24:47.519
If your culture's not in a place to use the tools correctly then you don't need the tools right that's that's number two.
00:24:47.680 --> 00:24:56.319
So for me that's two out of the five rules we violated in that in the in for me at least you know I have to make sure my team is in a place where it could use the tool properly.
00:24:56.400 --> 00:25:15.279
Like are is our culture in a place where we can accept using this or is this going to become a a a lever for example I once got an email cracks me up man it said hello comma in brackets teammate I was like you can't even put my name on the email you can't even write it out.
00:25:15.519 --> 00:25:48.559
Come on man like you remember that sports channel come on come on man yeah from ESP sports and then the other bit is the patterns I pick up on are like M dashes, those long dashes run on sentences, you sound like a Nobel laureate and you're from like Texas when you say y'all but you're like oh you guys and then it's like words that you know I was like is this from a like a Nobel paper or something because it's or my favorite is it's not just a job it's a calling.
00:25:48.720 --> 00:25:52.559
Like when you say it's not just this it's that like those statements too.
00:25:52.720 --> 00:26:07.279
So it's really it's funny when you when you see that but it to your point though I think it hurts culture because when you're using these tools for those reasons like for example it once again human in the loop if I write an email and being on spectrum sometimes I don't come across right.
00:26:07.440 --> 00:26:13.279
Sometimes I come across a little Sheldon Cooper like and it frustrates people right because we have social rules in society.
00:26:13.440 --> 00:26:22.079
I will put it in chat GPT and go, hey listen, this is the tone in which I think it is help me understand a better way that I could write this in a tone that works for me.
00:26:22.240 --> 00:26:26.880
You are a blank like you are a a writing expert.
00:26:27.279 --> 00:26:46.160
I use a persona prompt right and so prompt engineering can help with those things and it would give me an output and I go okay I like this then I go over on my other screen and I write the email myself using my words not copy and pasting I do not copy and paste outputs typically because I want to make sure that it's me doing it.
00:26:46.400 --> 00:26:46.720
Sure.
00:26:46.880 --> 00:26:49.839
This just suggested ways that I could do it better.
00:26:49.920 --> 00:26:57.279
It's like having that person like you know if I call Mike Fidel and go, hey listen man I got, you know, this this I took care of this kiddo he's traiked on a on event.
00:26:57.519 --> 00:26:58.480
Can you help me out with this?
00:26:58.559 --> 00:27:00.480
I know you have a lot of experience with it, right?
00:27:00.559 --> 00:27:09.279
I would look at it as a similar interaction but the one thing that you would have that the GPT or the LLM would not have is that experience, the context.
00:27:09.440 --> 00:27:13.359
Once again, context is everything when it comes to these tools.
00:27:13.519 --> 00:27:20.400
And that's where as data gets more prominent hence all these massive controversial data centers are popping up everywhere.
00:27:20.640 --> 00:27:23.519
That data that's being fed in there is going to provide it more context.
00:27:23.599 --> 00:27:24.880
So yes it will get better.
00:27:25.039 --> 00:27:31.920
But once again that's why we're talking about the five to 10 year thing that's why I say I don't know it just depends on what the context of these of these of these models are.
00:27:32.000 --> 00:27:36.480
Like are they going to be good enough to where they can create some context and nuance not really for medicine.
00:27:36.880 --> 00:27:42.000
But I think overall I think it has a place but once again your culture has to be right for it.
00:27:42.160 --> 00:27:47.599
Your policies have to be right for it you know and it that's just what it's going to come down to.
00:27:47.759 --> 00:27:55.359
And at the end of the day, you know we have to have good precepting good people are going to hold people accountable to good clinical care.
00:27:55.519 --> 00:28:01.279
Like there's no excuse for not um you can't be lazy and just rely on these on these technologies completely.
00:28:01.759 --> 00:28:05.279
But but that's where this this is something I and I get it.
00:28:05.359 --> 00:28:13.440
The technology world is going to expand at an exponential pace that none of us will ever be able to keep up with total totally understand that aspect of it.
00:28:13.680 --> 00:28:29.359
But this is one of those things where it's like we do need to pump the brakes a little bit and just because this is a cool tool that can do lots of fun stuff doesn't mean that this is supposed to be the end all be all for every industry that's out there.
00:28:29.680 --> 00:28:45.039
And and and that's where I think when something grows too fast and all of we we don't we don't slow down for a second think about all the things that yes it could benefit but also think about all the things that it could potentially hurt.
00:28:45.279 --> 00:28:45.680
Yes.
00:28:46.400 --> 00:28:49.839
That is where I fear we get into more trouble.
00:28:50.079 --> 00:28:54.960
And and I I I maybe that's where my resistance was coming from.
00:28:55.119 --> 00:29:06.640
Maybe that's where I was struggling with maybe accepting some of this right now is I see how how exponentially this is growing and I don't want us to do this the wrong way.
00:29:06.960 --> 00:29:24.480
Well I don't I don't think you're resistant Mike I think it's it's not cautious and and and rightfully so I I think that's just a natural good ethical way to to to really look really kind of look at it at least from my perspective I look at it as being cautious.
00:29:24.880 --> 00:29:25.039
Yeah.
00:29:25.359 --> 00:29:31.839
I agree completely Mike you if every leader was like you in that perspective I think we would be much safer with using these tools.
00:29:32.000 --> 00:29:57.839
Once again it's a tool man you know I mean you don't use a hammer to hit to do everything right I've been a leader for three seconds like I I it literally I've been a clinician for a heck of a lot longer and so that's where I think my my most of my fear is coming from is from the clinician side of this rotor wing pilots your experience is in demand your skills are indispensable.
00:29:57.920 --> 00:30:00.880
Now take your career vertical with global medical response.
00:30:01.039 --> 00:30:28.480
Find out about GMR significant EMS pilot pay increases sign on bonuses and stay incentive plans for select areas visit gmr.net backslash pilots to learn more and earn more today right but that's where leaders are going to have to step up and understand the strategies on these things and that's why I do hope some leaders listen to this because I want them to understand like hey you know on the business side okay you know that's analytics.
00:30:28.559 --> 00:30:43.200
That's where this stuff came from in fact a little history all right so I can put some notes up here on my screen so so this actually started in 1950 Alan Turing are you familiar with the the name the movie Enigma you familiar?
00:30:43.440 --> 00:30:46.880
So Alan Turing wrote a paper called the Imitation game.
00:30:47.119 --> 00:30:56.960
This is uh he broke the the code for Nazi Germany against Nazi Germany and the British yes yes so that's where the Turing test came from like is this human or is this a machine right?
00:30:57.200 --> 00:31:02.000
And then in 1956 John McCarthy actually coined the term artificial intelligence.
00:31:02.079 --> 00:31:05.039
So this was at uh in Dartmouth at the Dartmouth conference.
00:31:05.119 --> 00:31:45.680
So that's when the field was founded and in 1960 we actually had our first chatbot believe it or not named Eliza um and then in in 2022 that's when we had Jat GPT so this technology has been building for generations actually it it it just goes to show that like you're right Mike I think what happened was is in 2021 2022 we hit this point and now we're exponential in which that should be alarming right it's like when you look at Enron's stock prices in in the early 2000s are rising very fast why right and it turns out there are some issues but I think the same thing applies here that you know yes this is a expanding and growing technology it's going very very fast.
00:31:45.920 --> 00:31:55.440
Leaders are going to have to understand it quickly like they need to go and read on this stuff and understand what they are, what they do, what they can do, what they can't do with it, what the strategy is, where it should be safe.
00:31:55.680 --> 00:32:03.519
That's why I say you know it's gonna be uh if you really want to take on these technologies, you're gonna have to do a heck of a lot of work up front, you know?
00:32:03.920 --> 00:32:08.880
And if you can't get the basics down of your program, then these tools are not for you.
00:32:09.359 --> 00:32:12.720
You need to have the basic stuff done first.
00:32:13.039 --> 00:32:21.680
Like your pol you need to be a high performing program with a good culture and then you have to find safe niches where this will apply.
00:32:21.839 --> 00:32:30.400
For example I like I said charting is I think is a very good one right because we get tired we get fatigued that could help with fatigue risk it can help with a lot of things there.
00:32:30.799 --> 00:32:34.160
It can help with you know even overtime and other little things like that.
00:32:34.319 --> 00:32:56.880
But once again the clinical decision and support I think that is I think it is best used probably for the inpatient settings and in the academic settings um where you have more time to express these things but when the nature of our business Mike is you know as long as you've been doing Sam Blake we're a very time sensitive bunch which means that I'm not always going to have time to pull out my up to date you know when I'm in flight.
00:32:57.039 --> 00:32:57.359
Right?
00:32:57.440 --> 00:33:02.079
I'm gonna have those patients that are sick and I need to put down the freaking paperwork and take care of my patient.
00:33:02.240 --> 00:33:02.480
Right.
00:33:02.799 --> 00:33:04.240
So I love it.
00:33:04.400 --> 00:34:10.480
I do I'm just really wondering then five to ten years from now I mean I'll just be honest five to ten years from now is uh retirement you know for me and maybe just from one aspect of the job not stopping work completely but moving on to something else and I can't even imagine what younger newer clinicians are having to to learn and grow through and and do so much that are coming into this field what does this process really look like for us in that five to ten years from now what how is this how is AI helping us what should we expect for future flight clinicians five to ten years from now as you're looking to to get into this field what what should we what should they expect as they start looking and and evolving and growing because I look at people that are like brand new today that are going to be looking at in that five year mark to start embarking on getting flight jobs, breaking into the hems industry.
00:34:10.639 --> 00:34:17.920
But what does the role of AI and and helping people adapt, what does that look like in the future?
00:34:18.639 --> 00:34:42.320
So very good question once again and I think there's two pathways that we can take pathway number one is the pathway I would hope we take which is we as a as an industry start looking at ourselves and going okay we need to define our terms we need to make sure that we're consistent in all aspects of our program we need to make sure that the business use case for it is real.
00:34:42.960 --> 00:34:51.920
We need to make sure that the tools that are available to us we're using them to their fullest extent before we start looking at things like AI tools.
00:34:52.079 --> 00:34:59.760
And then when AI tools are being used there's a process for it it's you your IT team has vetted it to be safe and you begin to use it.
00:34:59.920 --> 00:35:10.320
Now for what applications I think it's gonna be where we see it now which is uh EPCR products I think it's a great and safe place for it for the most part pending that your culture is good.
00:35:10.400 --> 00:35:14.239
Remember my five points culture is one of those your culture has to be good for it.
00:35:14.400 --> 00:35:21.360
Are your clinicians just going to hit accept and submit and then be like oh yeah I just I just let the AI do it but I didn't review it.
00:35:21.599 --> 00:35:22.880
That's that's part of it.
00:35:23.280 --> 00:35:28.880
We're also gonna see it I think in things like quality tools uh the big I think that's the big stuff is quality.
00:35:28.960 --> 00:35:44.559
Uh so like running AI prompts against your charting system be like hey you know like dash one a uh metrics or or or your your CAMES metrics your your CAMES PIF when you're plugging in that data right sometimes you have to go, well, what's the definition of dash 1A metrics?
00:35:44.719 --> 00:35:47.199
What is the definition of a first pass success rate?
00:35:47.440 --> 00:35:53.760
And using AI tools to be able to help run those numbers for you based on the definition that you plug in through proper prompt engineering.
00:35:54.079 --> 00:36:00.960
I will see that coming into market I'm sure we're gonna begin to see the testing of different recording devices.
00:36:01.039 --> 00:36:09.760
So like you know in doctor's offices there's a lot of like plot and all these other tools that will record encounters so that charting and documentation is more accurate.
00:36:10.000 --> 00:37:00.880
We're also gonna see it in education clinical uh decision tools to help with uh education being able to run literature reviews being able to help develop research all these things now 10 years from now I could foresee there being more of the push into the clinical environment uh such as what Mike's concern is which once again rightfully so like if it was to happen right now I'd be very concerned um but I think that as time moves on um we're gonna learn more about these technologies and how they work and how they work for our industry and then we will begin to learn to say okay let's pump the brakes let's be smart about this let's you know answer the five questions does this work for our team will this actually work in practice yes or no the other thing is it's not like just buying a medical device where you just go, okay, we'll do a little training toss on the aircraft.
00:37:00.960 --> 00:37:15.039
This is gonna have to be full work like your your workflow integration which means you're gonna have to understand your workflow on calls to see how this thing could actually work within your program without causing patient harm.
00:37:15.280 --> 00:37:17.199
And then also we need to conduct studies too.
00:37:17.280 --> 00:37:32.480
So I I foresee a lot of people like me and others, myself and others who want to conduct more research in this realm so that we can understand what it's doing, where it's going and what we need to do to be keep our patients safe and keep our programs steady and doing the right thing.
00:37:32.960 --> 00:37:34.880
So once again it's not a clear answer.
00:37:34.960 --> 00:37:36.960
It's definitely a it depends answer.
00:37:37.119 --> 00:37:48.480
Now I will add the other way I could see it going is is a large majority of programs taking these tools out of the box and trying to replace that clinical decision, right?
00:37:48.719 --> 00:38:13.679
That to Mike your point, that that that assessment across the room hey I did this because my gut was telling me that I know this is going to work because I've seen this movie play out before I need to take care of this patient and it worked right you can't always explain it with with a clinical decision tool because it doesn't see what you see right so I could see some programs making some very bad decisions by saying hey we're just gonna buy this stuff because it's cool and well it's AI, right?
00:38:13.760 --> 00:38:18.400
But they don't have a foundation that's a proper concrete slab with rebar and everything else.
00:38:18.480 --> 00:39:08.880
It's gonna be sand you build a house on sand what happens it falls apart right I hope that's not the case but it is a real possibility I think so not to I'll be an alarmist but I think we should be realistic and go, okay, well since we're humans we know that we can either take the easy button path which is the sand or we understand this is going to be a lot of work but if we we we dial it in right, it can help reduce the noise that's out here to where we can focus on what we should be focusing on, which is exactly Mike what you outlined which is using our our brains, our intuition, our experience, our caring hearts, the things that we care about most, which is our patience, our passion, our drive things you can't put into a computer to be able to make good clinical decisions.
00:39:09.039 --> 00:39:19.199
To me that's that's the good vision here is how can I offload the stuff that's frustrating so that my clinicians can have a good culture where they can do the thing that we we we pay them for, right?
00:39:19.280 --> 00:39:22.480
We we're paid as clinicians to take care of people, right?
00:39:22.639 --> 00:39:23.760
Not let machines do it.
00:39:23.920 --> 00:39:25.199
Otherwise why would we be here?
00:39:25.360 --> 00:39:27.280
So you know that's that's how I see it.
00:39:27.440 --> 00:39:33.199
That's the future right we have one of two pathways and I certainly hope we take that good pathway uh moving forward.
00:39:33.519 --> 00:39:39.840
Yeah I certainly do too and and I hope that you just come back and tell us when it's okay.
00:39:41.679 --> 00:40:03.920
I don't you know I don't know if it's ever going to be a hundred percent okay I think we're we have to build frameworks and other things to go, yeah, that's what things I I want to do with my life's work one day is hopefully help build us some frameworks and work with other experts to understand what this stuff is and we can and do some research on where the need's going to be and where it's safe and reasonable to do so.
00:40:04.480 --> 00:40:07.360
Because right now that there's a big gold rush ongoing.
00:40:07.519 --> 00:40:31.119
I work a little bit in the software development side of things and I can tell you there's a gold rush and people are in the rush to build the next best hottest thing and um you you have to look at frameworks like NIST and others and and ask the question is this going to be safe and is this really going to be useful or is a salesman coming after me and are they just making really good work of my of my psyche, right?
00:40:31.199 --> 00:40:34.239
Are they are they doing a good job as a salesman, which is fine.
00:40:34.320 --> 00:40:41.760
I mean there's great salesmen out there but personally I like the ones who are a little more blunt than those who are not but just tell me what it can do.
00:40:41.920 --> 00:40:55.280
And so that's my big thing is don't be swayed completely by sales uh as they always jokingly say trust but verify comrade make sure you're doing that um and make sure you know what you're looking for and if you do that then you if you really care you'll make good decisions.
00:40:55.599 --> 00:41:11.760
I I hope that we go that route I really do and I I'm excited to see what this is going to look like and I I think that there are many avenues within our industry specifically in hymns and public safety aviation that AI tools can be a huge help instead of a hindrance.
00:41:11.840 --> 00:41:25.599
I really do feel that way uh I just have some significant concerns right now you know like if if AI tells me to push the the nuclear codes and like am I gonna do it like that that's right I I I I that's where I struggle.
00:41:25.760 --> 00:41:43.440
So I you know again forgive me for my soapbox earlier but I I I also want to look at ways that like we're we're in the now like this is happening all around us right and and I have many of my teammates that are actively looking at ways that this can be more integrated into everyday life.
00:41:43.519 --> 00:42:00.079
And so as clinicians and I'm because I think that there's so many other you know ways outside of being a clinician that AI can integrate and and be a useful tool for us uh despite this the fact that we're putting all of our personal information out there for all of this AI to learn about us.
00:42:00.480 --> 00:42:01.440
But I digress.
00:42:01.599 --> 00:42:03.760
I'll go back off my other soapbox.
00:42:04.000 --> 00:42:14.480
But I think that there are ways that we can do it both responsibly and ways that we should probably steer clear of for right now and and may can you give us some framework for what that should look like.
00:42:14.639 --> 00:42:18.800
So as clinicians how can we be responsible with this technology at the moment?
00:42:19.119 --> 00:42:38.880
And and also what should we kind of have more of that pause or that reservation with so I think it starts with the boring stuff like I said before start with the basics right like so number one if you're a clinician who uses ChatGPT or Grok or any of the other tools to write your narratives please stop.
00:42:39.199 --> 00:42:40.000
Don't do that.
00:42:40.320 --> 00:42:43.440
It's like that old Michael Jordan commercial please stop get help.
00:42:43.599 --> 00:42:46.159
Like don't don't don't do that.
00:42:46.320 --> 00:43:01.039
If you're doing that now you need to stop immediately because I guarantee you if you have a robust I enough IT department they know you're doing it because we track IP that I I know for a fact most companies have IT that track your IP addresses and where you go and what you do.
00:43:01.199 --> 00:43:16.800
I stop doing that right number two be very careful whenever you're using LLM to ask clinical questions right there are approved models that are out there like like uh for example open evidence if you have an NPI number or if you're a student of so like I'm an advanced practice student so I will have access to open evidence.
00:43:16.960 --> 00:43:29.760
But even then once again it's trust but verify human in the loop you make the right decision you verify anytime you look at any sort of AI output check it before you before you sign your name to it.
00:43:29.920 --> 00:43:37.360
If you're using a charting system that has AI tools in it once again trust but verify like you need to look and make sure the output is good.
00:43:37.519 --> 00:43:44.480
That is the work that you're gonna have to put into it is and make sure it's correct because I guarantee you every now and then you're gonna find something is wrong.
00:43:44.719 --> 00:43:52.320
The other thing is I would say as a crew member, talk to your leadership and and say hey listen we have our concerns about AI tools being used.
00:43:52.480 --> 00:43:54.159
Can we have a discussion about this?
00:43:54.719 --> 00:44:01.360
Have that open collaboration because it's going to incite things like hey maybe we should have a good ethical Use policy in place.
00:44:01.519 --> 00:44:04.320
Maybe we should talk to our IT and ask IT.
00:44:04.480 --> 00:44:05.199
Ask them.
00:44:05.440 --> 00:44:08.400
A lot of times they're nerdy people who really want to help you.
00:44:08.719 --> 00:44:13.440
As much as they'll tell you to restart your computer and turn it back on again and it magically fixes it every time.
00:44:13.679 --> 00:44:15.840
Like, seriously, ask your IT team.
00:44:15.920 --> 00:44:18.320
Like, hey, listen, like, I like these tools.
00:44:18.480 --> 00:44:19.360
I use them.
00:44:19.440 --> 00:44:21.760
You know, what are the limitations of them?
00:44:25.760 --> 00:44:28.159
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00:44:28.400 --> 00:44:30.000
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00:44:38.800 --> 00:44:41.840
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00:44:43.199 --> 00:44:46.239
A lot of them are very versed into it because they have to be, right?
00:44:46.320 --> 00:44:52.639
They're just as uh afraid of the dangers of it as I am, as Mike is, and Blake as you are, as all of us are.
00:44:52.800 --> 00:44:56.079
Um if you're not if you're not afraid of it to an extent, you're not doing it right.
00:44:56.239 --> 00:44:56.880
You know what I mean?
00:44:57.119 --> 00:45:01.199
So that's that's something that as a crew member, those are the starting points.
00:45:01.519 --> 00:45:09.280
Now, the other things you can do are you can advocate for certain tools, bring them to your leadership, right?
00:45:09.599 --> 00:45:15.119
Talk with them about it, but understand that at the end of the day, the IT team also needs to take a look at it.
00:45:15.360 --> 00:45:16.880
You need to make sure that it is safe.
00:45:17.039 --> 00:45:18.960
Remember the five things I was talking about, right?
00:45:19.199 --> 00:45:25.360
Ask the question is our culture good in a place where it could handle this tool, not irresponsibly use it.
00:45:25.519 --> 00:45:28.400
Are our policies in place to where it's consistent?
00:45:28.639 --> 00:45:33.119
The other thing you can do also as a crew member is consistently document.
00:45:33.519 --> 00:45:36.159
Consistently document, follow your documentation standards.
00:45:36.239 --> 00:45:37.760
That's gonna help with quality of data.
00:45:37.840 --> 00:45:40.880
So when your leaders go, you know what, we're meeting those five things.
00:45:40.960 --> 00:45:42.400
Let's go ahead and buy this thing.
00:45:42.559 --> 00:45:45.039
It's gonna have good outputs that actually can help you.
00:45:45.119 --> 00:45:48.880
But once again, you're trusting, but verifying human in the loop, right?
00:45:48.960 --> 00:45:50.400
We always stay in the loop.
00:45:50.639 --> 00:45:54.000
The other thing you can do as a clinician is just take care of your patient.
00:45:54.159 --> 00:45:58.800
Once again, I learned the other day from a very, very, very smart FTO.
00:45:58.960 --> 00:46:02.159
Hey, sometimes you get your head out of the paperwork and focus on your patient.
00:46:02.320 --> 00:46:15.599
Take good care of your patients, take good care of them because ultimately your documentation will reflect that good care you provided, which means the models will be felled with good, fed with good things and what you're actually doing.
00:46:15.760 --> 00:46:22.320
So that eventually down the line, when that 10 years comes and we're getting more clinical decision support, it's going to be more accurate.
00:46:22.480 --> 00:46:24.320
But once again, human in the loop, guys.
00:46:24.400 --> 00:46:26.239
I said it a thousand times, I'll say it again.
00:46:26.400 --> 00:46:28.559
Don't just trust things that it puts out.
00:46:28.800 --> 00:46:34.079
If, for example, it's really funny when people look at papers, because I'm in grad school and I'll tell you it's really funny.
00:46:34.239 --> 00:46:44.320
I'll click on a discussion post or something, and I'll click on a DOI link and it doesn't exist, which means that the that the the the source was fabricated.
00:46:44.400 --> 00:46:49.199
It happens, and that's every university, not just where I'm going, it's everywhere, right?
00:46:49.519 --> 00:46:57.519
So you have to trust but verify these things because you're gonna look silly when you copy and paste hello, comma teammate on an email and look silly.
00:46:57.840 --> 00:47:00.159
I'm gonna address you that way every single time.
00:47:00.559 --> 00:47:02.079
Hello, teammate.
00:47:02.559 --> 00:47:03.360
It's so funny.
00:47:03.519 --> 00:47:06.000
You're not just Christian, you're a flight nurse.
00:47:06.079 --> 00:47:09.119
Yes, like it's it's so funny with an M-dash in the middle.
00:47:09.440 --> 00:47:12.400
But I would say for crew members, that's the thing.
00:47:12.559 --> 00:47:20.400
You have to treat this stuff like you would treat anything, any medications, any therapies or treatments, you have to do it safely.
00:47:20.639 --> 00:47:23.119
This is not something just to be blindly leaned upon.
00:47:23.280 --> 00:47:29.840
As much of an advocate for it as I am, I also understand that like it's a tool that you have to really understand.
00:47:30.000 --> 00:47:38.079
It's a very, very complicated piece of technology that seems simplistic on the front end, but on the back end it's very complicated.
00:47:38.239 --> 00:47:40.880
So but yeah, that's what I'd say for crew members.
00:47:41.519 --> 00:47:49.119
I I think though that this is not gonna be the last conversation that we'll have about this.
00:47:49.199 --> 00:47:54.880
I I think that this this is just going to be part of our everyday future as as clinicians in healthcare.
00:47:55.039 --> 00:47:58.880
And I think not just in healthcare, it's gonna be in all walks of life.
00:47:59.599 --> 00:48:12.239
But what I feel, at least for myself, is I I feel like I'm at that point where I'm looking at where I started to where I'm at now.
00:48:12.639 --> 00:48:17.119
I'm finally that person that I met like 20 years ago.
00:48:17.199 --> 00:48:23.519
When you met that person, I was like, back in my day, you know, I feel like that's the point that I've that I've gotten to.
00:48:23.760 --> 00:48:34.079
And I could only imagine what when I was brand new 20 years ago, what my FTO was and seeing come down the line.
00:48:34.559 --> 00:48:40.880
So I feel like I'm now kind of or am seeing these things come out.
00:48:40.960 --> 00:48:45.280
Like it's like some of this stuff is just like unbelievable, you you know, for me.
00:48:45.599 --> 00:48:54.480
And it's not this, you know, resistance is futile, but I think caution caution is mandatory, right?
00:48:54.559 --> 00:49:26.639
Like you we have to uh I I want to embrace it and I want to believe that this can be something that will help, but I also have to remember that if I am going for me as Blake as an individual is going to be inherently a better person, a better clinician, uh, you know, all that, it's up to me to put in that work, do the things, do research, do study, do all these things.
00:49:26.719 --> 00:49:37.119
I can't rely on something fully autonomous to flash it in front of my brain and be like, boom, you got it.
00:49:37.519 --> 00:49:49.199
And until the until those futuristic movies start really coming more to life, you know, things that we saw, Terminator, Idiocracy, any of the any of these things.
00:49:49.599 --> 00:49:51.840
I still think in some places that could be a documentary.
00:49:51.920 --> 00:49:52.239
I don't know.
00:49:54.559 --> 00:50:05.360
But I just my hope is that I as I'm aging and getting older and and moving through this world of healthcare and as a clinician and and just I'm still gaining more experience.
00:50:05.599 --> 00:50:12.000
You know, it just because it's been 20 years, I I I could still have 20 years to go to continue learning and doing more.
00:50:12.159 --> 00:50:27.119
So I I don't want to say that I'm like aging out, but I feel that when I look at the this process of AI, I want to be optimistic and I want to be like in in the right cheerleader corner for it, I guess.
00:50:27.360 --> 00:50:31.920
But I also need to be cognizant of like I want to see you there with your pom-poms.
00:50:32.239 --> 00:50:33.840
Oh, it could happen.
00:50:34.320 --> 00:50:35.920
It would be fully automated, though.
00:50:36.000 --> 00:50:38.079
It would it would like tell me to cheer.
00:50:39.280 --> 00:50:49.280
But and and Blake and Mike, if I could offer a bit of sunshine here, imagine a place like let's say you have to do your monthly checks in the supply room, right?
00:50:49.679 --> 00:50:54.159
I will say there will be a time when there will be a system that really helps you with that.
00:50:54.400 --> 00:50:58.480
What usually was three to four hours, could be 20 minutes or 10 minutes.
00:50:58.559 --> 00:51:00.800
And then what can you replace that time with?
00:51:01.119 --> 00:51:18.239
You could sit with your trainee and you can go over scenarios, you can talk about experiences, you can develop that relationship with your trainee, you can work with your partner to plan, pre-plan for a flight, to practice your walkarounds, to talk about safety, to talk about the evidence and literature that's out there.
00:51:18.400 --> 00:51:32.639
For me, that's that's the the bright part of this, is that we can offload certain basic things that normally are very time consuming with the stuff that matters for the critical thinking parts of this, like being able to, you know, talk about, hey, like Mike, I don't fly Neos that often.
00:51:32.800 --> 00:51:36.079
Like, let's talk about like hypoplastic uh syndromes and things like that.
00:51:36.320 --> 00:51:37.280
I want to learn more about.
00:51:37.599 --> 00:51:41.280
Tell me your experiences of that, like those valuable conversations.
00:51:41.760 --> 00:51:44.960
We will have more of those, I think, if it's done correctly.
00:51:45.119 --> 00:51:46.719
And we and we can do that.
00:51:47.199 --> 00:51:47.679
Just wait.
00:51:47.840 --> 00:51:53.440
Next time we talk, we'll be talking about AI creating VR experiences for us.
00:51:54.639 --> 00:51:56.880
And in terms of our training.
00:51:58.159 --> 00:52:01.440
It's not it, I know those things are probably in development.
00:52:01.599 --> 00:52:06.960
Once again, I don't know every technology, but I mean, we're in the phase where a lot of things are being developed.
00:52:07.199 --> 00:52:11.440
We're in a development phase and and experimentation is going to have to take place.
00:52:11.679 --> 00:52:13.199
Projects are gonna have to be done.
00:52:13.360 --> 00:52:24.400
But once again, I think the realm of research is going to help us with those things to help us understand, like I said earlier, you know, we we we should do research to find out where this stuff could be helpful, right?
00:52:24.639 --> 00:52:37.599
And if we know for a fact like where it could be helpful, and we've done, you know, up to a meta-analysis saying, like, hey, we've done looked over 15 papers about this one particular type of AI technology, and we notice that patient care is better when we use it.
00:52:37.760 --> 00:52:38.400
Okay, cool.
00:52:38.559 --> 00:52:41.599
Patient outcomes are better, we know it's better, okay, then we can use it.
00:52:41.760 --> 00:52:47.119
I I do see some bright spots, but once again, I think we have these, we have several camps.
00:52:47.280 --> 00:52:48.400
We have three camps.
00:52:48.559 --> 00:52:54.159
We have I we have the camp where people are way overly optimistic and they're just like, use it all.
00:52:54.320 --> 00:53:05.199
And then we have the middle camp, which is where I think a lot of us lie, which is where those who who are looking into this stuff is like, okay, it's great, it can do a lot of things, but where and how?
00:53:05.440 --> 00:53:06.719
We need to do this safely.
00:53:06.880 --> 00:53:08.079
We don't want to cause harm.
00:53:08.239 --> 00:53:10.960
And then we have another group, you know, that is staunchly against it.
00:53:11.039 --> 00:53:20.960
But once again, I don't knock the staunchly against it because the the the possible unknowns from this that could cause harm are quite real.
00:53:21.119 --> 00:53:23.360
Um and once again, we have two pathways.
00:53:23.519 --> 00:53:25.840
We're at the fork in the road, which which way are we gonna go?
00:53:26.000 --> 00:53:29.039
That's the could that to those people that are staunchly against it.
00:53:29.119 --> 00:53:34.000
Uh, I have no uh I'm not against what they're saying at all because I think that's what they see.
00:53:34.159 --> 00:53:42.239
They see the fork in the road and they really want to go one way, but they're not gonna jump on board with it till they know it's gonna be going to that right direction as compared to the wrong direction.
00:53:42.400 --> 00:53:44.079
So that's that's my assessment.
00:53:44.400 --> 00:53:54.239
I feel like if my boss hears this, they're gonna be like, Man, we just cut down the date checks from four hours to like 20 minutes.
00:53:54.400 --> 00:53:57.119
Man, we could fill that up with more OSHA training.
00:53:57.280 --> 00:53:59.679
We could find more fun stuff for you to do.
00:54:00.239 --> 00:54:00.559
Yeah.
00:54:00.719 --> 00:54:01.119
Oh, good.
00:54:01.360 --> 00:54:04.480
Outside of the scope of this talk, but you know, there is that.
00:54:04.559 --> 00:54:05.840
Like that could happen too.
00:54:06.000 --> 00:54:08.000
But once again, we could fill it with good things, right?
00:54:08.159 --> 00:54:08.320
Yeah.
00:54:08.480 --> 00:54:09.599
And that's what I hope that happens.
00:54:09.679 --> 00:54:10.880
I hope we can fill it with good things.
00:54:11.199 --> 00:54:12.719
Well, thank you, Christian, for joining us today.
00:54:12.800 --> 00:54:14.320
I really appreciated the discussion.
00:54:14.480 --> 00:54:25.039
Uh, I certainly still have many more questions than answers, but I love being able to have these conversations and really kind of uh solve the world's problems, this time all about AI.
00:54:25.199 --> 00:54:28.960
So I have no doubt we could talk for hours and hours more about all of this.
00:54:29.039 --> 00:54:39.199
Uh, and I'm so grateful that you were willing to take some time out of your day to discuss with all of us and all of our listeners as well, because uh I I do think that this that we we can't resist.
00:54:39.280 --> 00:54:42.320
We just need to be cautious in how we move forward with it.
00:54:42.400 --> 00:54:48.400
And and I I appreciate you uh and all of your insight that you have been able to provide over the past couple hours for us.
00:54:48.719 --> 00:54:50.159
Yeah, no, it's it's my pleasure.
00:54:50.239 --> 00:54:52.159
And and I think it's good to get that message out there.
00:54:52.239 --> 00:54:56.719
Once again, not everyone's gonna agree with what I'm saying, and that's okay because I think we're all figuring this out.
00:54:56.880 --> 00:54:59.360
I I certainly don't have it all figured out.
00:54:59.519 --> 00:55:00.079
I don't.
00:55:00.320 --> 00:55:10.719
But I think that there is a number of places where we can get started on the back end of things, on the basic level, to help prepare us to tee us up to get us into a better position with these technologies down the line.
00:55:10.800 --> 00:55:15.199
So no, it was a great conversation, and and I love the I love I love every bit of it.
00:55:15.280 --> 00:55:16.559
So this is wonderful as usual.
00:55:16.719 --> 00:55:17.519
Thank you for having me.
00:55:18.079 --> 00:55:18.800
Always a pleasure.
00:55:18.960 --> 00:55:23.280
I'll just say again, Christian, fourth time uh on the podcast.
00:55:23.360 --> 00:55:25.119
We'll see if we can go for number five.
00:55:25.360 --> 00:55:28.159
We'll see what uh we'll we'll give you a little break.
00:55:28.239 --> 00:55:30.400
I know we're we don't want to overwork you over there.
00:55:32.320 --> 00:55:32.880
It's a pleasure.
00:55:32.960 --> 00:55:33.440
You're good.
00:55:33.679 --> 00:55:39.119
I I think a lot of this again, like you just said, that this this all has a great application.
00:55:39.440 --> 00:55:53.920
And it w whatever camp that you're in, I I just appreciate Christian the ability to really kind of take that unbiased look and really allow us to see both sides of the playing field of what can potentially be coming down the road.
00:55:54.079 --> 00:55:55.599
So I'm super grateful.
00:55:55.760 --> 00:56:04.400
Chrisha is always your one of my best friends, one of my favorite people to uh to not only hang around with, um, but to just we could talk for this for hours.
00:56:04.480 --> 00:56:08.639
I know, I know that we could, and I'm just excited to really see what's in the future.
00:56:08.719 --> 00:56:19.679
I'm probably in that middle camp, but I I just uh whether it's AI or not, I'm just really excited to see where we're gonna be in another five to ten years as as clinicians.
00:56:19.920 --> 00:56:23.920
So I I'm hoping that it will all obviously be good.
00:56:24.000 --> 00:56:27.039
I I think everything's been good so far, things that I've learned over the years.
00:56:27.119 --> 00:56:30.239
So I'm um I'm pretty stoked to see to see where we end up.
00:56:30.480 --> 00:56:31.280
Oh, for sure.
00:56:31.440 --> 00:56:33.840
I mean the possibilities are potentially endless.
00:56:33.920 --> 00:56:42.320
And it and once again, there's probably 15, 20 hours more we could probably discuss on the we didn't cover a we covered the surface today, guys.
00:56:42.559 --> 00:56:43.119
We really did.
00:56:43.199 --> 00:56:44.719
There's so much I didn't talk about on here.
00:56:44.880 --> 00:56:46.960
Some folks, well, why didn't they mention this or that?
00:56:47.119 --> 00:56:48.559
Because there's just so much to talk about.
00:56:48.719 --> 00:56:50.480
So, but like I said, great conversation.
00:56:50.559 --> 00:56:51.280
Thank you, Blake.
00:56:51.519 --> 00:56:53.039
Yeah, I have no doubt about that.
00:56:53.119 --> 00:56:55.360
We hope you enjoyed this conversation as much as we did.
00:56:55.519 --> 00:57:03.599
Once you're all caught up on the Valor Flight Crew podcast, make sure you head on over to verticalhelicast.com where you can check out the Hanger Z podcast, helicopter podcast, and the vertical MRO podcast.
00:57:03.840 --> 00:57:09.039
Special thank you to all of our listeners out there for your continued support of the Vertical Hellcast platform and the Valor Flight Crew Podcast.
00:57:09.119 --> 00:57:10.880
Be safe and we'll see you next time.
00:57:11.280 --> 00:57:14.559
Thanks for joining us for this episode of the Valor Flight Crew Podcast.
00:57:14.719 --> 00:57:20.880
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Mission critical operators and fleet managers rely on Precision Aviation Group as a worldwide leading rotor and fixed-wing MRO provider.
00:58:16.400 --> 00:58:25.440
TAG provides tech-to-tail solutions in four MRO segments avionics, components, engines, and manufacturing DER services.
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A single point of contact gives you access to over 150 million in inventory globally 24 7, Title 800, 537, 2778, Precision Aviation Group, other stealth parts, free cell support.