March 26, 2025 • 37 mins
Does your doctor seem more focused on their screen than on you?
Two-thirds of physicians are now using AI for everything from billing to diagnosis - but here's the kicker - only 38% actually trust the technology. This brewing healthcare disaster isn't just about robots taking doctors' jobs; it's about who's accountable when AI makes a potentially life-altering mistake with your medical information, and why insurance companies are salivating at the thought of using algorithms to deny your claims even faster.
Listen as Jeremy, Jason, and Zach dive into the alarming rise of AI in healthcare, how to find meaning in your fitness journey when depression makes everything feel pointless, and why sometimes treating your workout like wiping your ass is the perfect mental approach to consistency.
Topics Discussed
- Why 66% of physicians are using AI despite only 38% trusting it - creating a dangerous accountability gap in healthcare
- How insurance companies will likely use AI to deny claims faster rather than improve patient care
- The potential for errors in medical records when AI is used to generate and update patient information
- The challenge of determining liability when AI contributes to medical errors
- Using workout data tracking to combat depression's lie that "nothing is working"
- How Jeremy discovered he'd doubled his strength despite feeling like he wasn't making progress
- The value of consistency over intensity when building healthy habits
- Why treating workouts like mundane necessities (like wiping your ass) helps with consistency
- Finding meaning in fitness when battling existential crises
- The importance of "showing up" rather than focusing solely on specific fitness goals
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
(00:03):
Welcome to the Fit Mess.
My name is Jeremy.
Joined today by my co-hosts, co-hosts, that's the word, Zach and Jason.
Glad to see you guys here.
Thanks for being here today.
I had a moment the other day where, you know, I tend to live in sort of a depressed statemost of the time.
And I had one of those moments the other day where I was like, the fucking gym.
(00:23):
I don't want to go today.
What's the point?
It's not doing anything.
I look like shit.
I feel like shit.
And I had this like, aha, duh moment.
that relates to AI and we're going to talk about it a little bit.
So I want to tell you that story a little bit later because it's not our top story.
It's just a kind of a funny thing that happened to me that is a good reminder for a betterway for me to consider all these little things that I'm trying to do to improve my life.
(00:46):
But the big story I want to talk about today is why two in three physicians are usinghealth AI, which is up 78 % from 2023.
And on the surface, what's the problem?
Right?
They're saving all kinds of time.
This is going to make healthcare better.
It's going to make it cheaper.
It's going to make it more affordable, especially in the US where it's a finely tunedmachine.
(01:10):
Jason, you stumbled across this story.
Your reaction to more doctors using more AI to do more.
Well, so essentially the whole point of AI is to provide a level of intelligence thataugments human intelligence in some sort of way.
So that's how we're using it today.
But eventually, you know, it'll get to the point where it could subsume certain humanintelligence functions.
(01:36):
The artificial part of it suggests that these are things that are being generated bylarger sets of data.
And if you look at how physicians interoperate with things to become a doctor, you have togo to school for a certain period of time.
Sometimes that's seven years.
mean, some people go to community college for seven years.
I may have been one of them to go through and get their level of education.
(01:56):
it.
That was the you just really you're having a good time.
You wanted to stretch that out as long as you could.
I did.
I did.
mean, most people that end college after 14 years with my BA, they are not just doctors.
They have multiple doctors.
I didn't go down that path.
Anywho, yes, exactly.
(02:18):
The strange thing is that when you look at the way the data is actually collected andpulled in, they basically pull data in from multiple different sources.
And AI systems use large language models and then large learning principle functions to gothrough and create things that are verifiably usable for different use cases.
And physicians and healthcare in general has a whole battery and set of information forits use cases.
(02:44):
And the data that they bring in is not limited to your medical records.
It's not limited to your behavioral records or the inputs the doctor has.
The information they use to make decisions can be broadly based upon macro information.
So it could be, you know, people in your area react this way to certain health criteria.
(03:06):
It could be you react these ways to different types of things in the environment.
All these things are ways and mechanisms that feed these AI systems.
And doctors are trying to take advantage of it.
So two and three doctors out there are using artificial intelligence in this way to gothrough and help them make decisions about patients' health.
about billing systems, about record systems, all these different component pieces.
(03:31):
At the same time, only 38 % of doctors feel that AI is good enough from a privacyperspective, a security perspective, and a reliability perspective to say they trust it
and its capabilities more than the potential downsides.
(03:53):
So what that means is you've got an inverted model.
You have 66, about two thirds of doctors out there using AI, about a third of doctorssaying they trust AI.
So that means you've got one third of doctors using something that they think that they'renot sure that they trust for your health.
And it's, it's scary.
(04:13):
so Zach, you're the IT security professional.
I want to get your take on this.
But I just want to sort of explain a little bit about how these doctors are using AI.
So mean, according to this article from the American Medical Association, documentation ofbilling codes, creation of discharge instructions, translation services, summaries of
medical research and standards, assistive diagnosis.
(04:35):
That one scares me a little bit.
Generation of chart summaries.
So mean, it does sound like it's lot of admin work.
They're trying to free up a little bit of admin space to focus on other things.
But what's the risk here?
What's the danger?
Zach, what red flags are going off for you as you hear doctors are using AI to do part oftheir jobs?
(04:55):
I wouldn't, mean, so the diagnosis part doesn't scare me as much as all the other parts dobecause again, like we all Google our own symptoms and right.
That cough is definitely a brain tumor, like all those things.
But, and I've, I've used AI to write performance reviews.
(05:18):
I've used AI to like, you know,
It really does help if you're one of those people who like, you're looking at a blankcanvas, you can't do anything.
You can generate something to edit and then you can go edit it.
Now, if my medical charts and my, my information that other doctors and otherprofessionals are going to make decisions on is based on AI stuff that could be wrong,
(05:40):
could be right.
That's where it gets scary is like how long before my medical chart is like way off base,right?
from what it should be because AI was like, we'll just put this in there because I thinkthis sounds cool.
you know, the doctor told me to write this in, you know, Donald Trump style.
So it's all about like, it's going to be great.
It's going you know, like, who knows?
(06:04):
Exactly.
So I think that doctors will more than likely, if they use it for diagnosis assistance,right, they're probably going to double check that work.
I wouldn't be as concerned about that.
because they're using other sources for that anyway.
It's more like the, you know, again, my personal records not being updated correctly,errors that people aren't catching because I know everyone else does this.
(06:30):
You ask AI to write something and you skim it and you say it looks good and you don't readit in detail.
I mean, I do read it in detail, but most people don't read it in detail.
Yeah.
Well, that's what I was thinking too, as I was sort of considering the different pros andcons of this, is that this could open up an entire new industry in healthcare of basically
proofreaders.
So if the AI is going to create the content, we need somebody who can actually, with aneye for detail, figure out is this correct?
(06:56):
Is this what the doctor said?
But I guess the other thing that scares me, and I think this is maybe what you're gettingto, Jason, is the idea that this information is being fed through some external tool.
And again, what kind of data is being collected?
How is it going to be used?
Who has access to it?
I mean, that's the thing that scares me.
Aside from, you know, Dr.
Google telling me I have brain cancer because I coughed, what does Elon Musk suddenly knowabout me because AI was used to figure out that I don't really have brain cancer?
(07:24):
Yeah, so there's a couple of pieces here.
So you can use AI and ML to collect information and to enrich it and to put theinformation into context.
And when you do that, you create a data set.
And now you have a new data set in place.
And that data set gets reused and updated and changed over time, just like regular humanintelligence.
(07:45):
Like as a kid, you go through and you learn basic math.
And then you build upon those skills to learn more advanced math.
Well,
If you were shit at addition and subtraction when you were a little kid and it didn't getany better and you came up with the wrong answers and then you start doing more higher
order math later on, you still haven't solved the fact that you were shit at doingaddition and subtraction and that's going to affect all future calculations.
(08:12):
The same is true with AI.
We are not aware necessarily yet of how good the information and data they collected is.
We're just assuming that it's okay.
And the reality is that the people that are writing these models, doing these checks, mostof them are not medical professionals and are not professionals in those industries.
(08:34):
So you have human augmented intelligence and human augmented auditors.
Like there's entire companies out there, like Scale AI, for example, that does this.
And there's the Mechanical Turk from Amazon.
All these pieces in place where they say, we're going to take these models and then we'regoing to learn on them.
And I think it's called real human augmentation validation, something like that.
(08:55):
But the idea is that you're going to take experts to review these things to try to makethese models better.
That's great for companies that do that.
A lot of companies aren't going to do that because it's expensive.
It's not cheap.
And going through and validating these pieces and level of validation you put into placeis hard.
(09:15):
And if you start taking this content and you start learning from it,
creating collateral material as learning material, spread these things out.
Well, now you've got a disinformation problem where the AI itself could be putting outfalse information and bad things.
And it's hard to correct that when we ever become so addicted, complacent and compliantwith what these things are saying.
(09:37):
Cause if we turn over our sense of authority from doctors into the hands of AI, well nowwho actually knows and who's doing the right thing.
It's difficult, if not impossible, to be able to extract those things from each other.
And over a prolonged period of time, like you guys said, WebMD is going to become thething that you're going to use to validate the thing that your doctor said.
(10:10):
And we're going to have the Denning-Kruger effect all over again.
And we're going to have the Denning-Kruger effect with our health.
our belief system, everything else.
And it's just going to create so many competing signals that a lot of people are justlike, fuck it.
I'm not listening to any of you.
People already don't trust doctors.
People already don't trust medical institutions.
People already don't trust the authorities in this space.
(10:30):
And we have doctors who are supposed to be authorities saying, I don't trust this, but I'mgoing to have to use this because I know that in order for me to stay alive in the
business world and be able to do the things that I need to do at scale, I have to havethese things in place.
And it's incredibly dangerous.
It's incredibly
misguided, it's ineffective from a costing perspective in terms of going through and usingthese tools to make these things faster.
(10:52):
AI is going to help us do a lot of things much, much quicker, including fucking up.
We're going to fuck up quicker and at scale.
And we're going to go, that was great.
It only cost us, you know, the earth in the process because we're going to burn everythingup.
Yeah.
I mean, you mentioned cost a couple times there.
If in the end, the goal here is to reduce the cost of American health care, okay, there'sa case to be made.
(11:15):
There's no way that's gonna be the end result.
They're gonna argue that this costs more and that's why all of a sudden your costs need togo up, which is why insurance premiums need to go up.
This is not going to solve that problem.
And just to your point about the doctors themselves, mean, according to this article,nearly half of physicians surveyed.
47 % ranked increased oversight as the number one regulatory action that needs to happen.
So again, now we're bringing in more people to oversee the AI that humans have been doingfor a really long time pretty badly already.
(11:44):
So do we really need robots to also do it badly?
Well, not just that, you mentioned a really salient point and that's the idea of havinginsurance companies involved in this and the point of using AI.
So the point of using AI is not to make things cheaper.
The point of using AI is to not do anything other than make things faster.
(12:05):
That's all it's really meant to do.
It's meant to shortcut these pieces so you can execute things quicker and go much quicker.
And I guarantee you, insurance companies are going to use it to deny your claims faster.
because they're going to use it to go through, scrape this bit of information, understandthese things in context and say, now I don't need someone to go through and read these
charts.
I can say no fast because they're going to use keyword searches and indexing functions andeverything else.
(12:26):
And they're going to stick these things together and then hope people don't look too hard.
And we're not exactly in a position right now as consumers and as citizens where we'regoing to have the US government try to help us and protect us.
These are things that are just going to fall apart.
of now hiring jobs up in the federal government.
(12:50):
Right.
I mean, the government is not, the current administration does not want the government totry to help consumers.
They want the administration to enable businesses to be able to do more business likethings.
And we already know that businesses in general, especially corporations, you know, aresociopathic.
they're, they're to extract money from you and pull in.
And I'm not saying that businesses are the problem here.
(13:12):
I'm saying that our adoption of a technology that we don't understand at scale, at rate,
going into actually critical infrastructure, your body, and being said, now we're going tostart making decisions based upon this, and then punch it into a database, and then hope
for the best in the future, is probably not a great way to work on health.
(13:33):
I think, I mean, you guys hit on a couple of points where, you know, the healthcare systemin America is for sure for profit, right?
And they make money on it.
And even in the business I'm in AI is the buzzword that executives are hearing too, right?
I have been told, get AI into our systems.
(13:55):
I don't know what that means.
They don't know what that means.
And it, you know,
I always hesitated and was like, I'm not going to put AI into our product, but I'll put AIinto the backend part of it and make lives easier for us.
But at the end of the day, you know, Jeremy, you said make healthcare cheaper.
way.
(14:15):
Jason's right.
It's going to be faster and prices won't go down.
Their cost of doing business is going to go down and they're just going to keep moreprofits.
But where are they going to choose to put that AI?
Because some executive in the healthcare system is going, Hey,
put AI into the system, put AI into the system.
And you've got people who don't know what they're doing putting it in where it doesn'tbelong or where it's not necessary, where it's dangerous, where it could cause so many
(14:42):
problems.
like on top of all the other things that Jason's talking about, like it could be a hugeclusterfuck with AI all over the place where it shouldn't be.
Well, and can imagine a scenario too where, you know, right now when you go to the doctor,you fill out the intake form and list out all the symptoms you've had.
That's essentially what we're doing now with WebMD.
So now I'm doing it in my doctor's lobby while I'm waiting to be seen, probably on sometablet that's going to be telling AI, these are my symptoms.
(15:05):
And the doctor is going to basically validate what the decision AI came up with ratherthan using the, you know, the brain they have that they developed from all those many
years of community college sitting next to Jason.
And,
And now my diagnosis is coming from Dr.
Google.
And I would hope that's not the end result.
But in a push to do more faster to reduce cost, I see that as a pretty likely endingscenario here.
(15:34):
Yeah, and that we also have to take into consideration is that using AI to get informationand to do to diagnose treatments, I mean, all these pieces, it's not necessarily a bad
thing.
I mean, doctors today use Google and they use research magazines and they use industrytrade publications to go through and try to understand what medical journals are saying
(15:58):
nowadays.
These are all things that they're already doing, and they're already using the Google todo this.
It's the summarization of this information and putting these things into these augment orthese really generative AI capabilities to go through and actually give you a generative
response before it becomes scary.
And it's not necessarily that it's going to be entirely wrong or any worse than what wehave today.
(16:21):
It's just that it's going to be harder to point the finger and say who to blame.
Because if I go through and I misdiagnosed somebody and I give them the wrong drug and itcauses vasodilation and they pass out and they crash their car on the way home from the
doctor's office and kill somebody, who's at fault?
(16:43):
Because is it the AI?
Is it the doctor?
Is it the person driving the car?
Who is really to blame for all these pieces?
And we don't know yet.
And it's the accountability factor and the fact that there really is no accountabilitylane in this.
And there's no way to reverse engineer some of the AI pieces that come out of it and someof the information that it gives you.
And most people wouldn't even know how to do it.
And that's the scary part is that these things are, they're just way outside of our zoneof control.
(17:08):
I, doctors don't move fast.
Like they don't change their opinions quickly.
They tend to move slowly.
They're moving fast on AI and they're moving fast on AI because there is a economic reasonand incentive for them to do that.
But also all the tools out there.
that are in the medical industry are making this shift towards AI capabilities as well,because they're trying to get rid of their back end developers.
(17:31):
They're trying to get rid of the people that actually do data entry.
So we're just handing more and more of these things over without looking at what thecontrolling functions are going to be over time.
As the signals go up and the data gets more polluted, what you're going to wind up with ismore noise.
And the signal to noise ratio
(17:51):
is the really, really big thing.
So we have a ton of noise coming in.
We don't know how to decipher it and turn it into a signal that says, this is what youshould do.
AI is supposed to help us with that.
But the way that we're implementing it and instrumenting it, it's going to make it worsebecause we're not putting filters on those signals.
Those signals are rapid firing coming towards us and they're just turning into noise.
(18:17):
And then we're relying on these experts to try to tune these things down.
And don't think they were equipped for it.
I mean, I'll be honest.
My, my, old air force physician that worked on me as a kid when I had allergies or thetime that I like blew my ankle out, like if you told that dude, Hey, talk to this robot
and have you tell you what's going on.
I'd get a fuck you kid as he's smoking a cigarette and blowing smoke in my face from myallergy discussion.
(18:41):
But he's also the guy that probably would have done the best job treating me for myallergies compared to how things are today, because he actually would taken the time to do
a test and run through these things.
And not just said.
denied because your healthcare doesn't support these pieces based upon some arbitraryinformation that we extracted in these layers.
It just makes things harder and people are going to give up and they're going to not try.
And then I'm like, I don't care.
(19:03):
I'm going to go take ginseng and ginger and hope that I live.
So that's, yeah, okay.
That's exactly what I wanted to go next with this is desperately clinging to any glimmerof hope in this.
What do we do, right?
What's the solution?
And to me, I wonder, you know, are the naturopaths out there chomping at the bit becausethis means people are going to want the more, you know, a holistic approach to healthcare.
(19:26):
They're going to want the hour with their doctor to talk about their diet and what they'redoing differently and what's going on.
Does, does this shift us more into hippie mode where we suddenly, where we're a littleless reliant on
the traditional medical system and starting to look for alternatives because we don'ttrust the robots that they're using.
Yeah, so my end is an MD and I've had a couple of discussions about with him about, youknow, how do you feel about AI to generate diagnoses or feeding this information?
(19:53):
And he goes, well, I mean, we've been using it to some degree for a long time anyways,whether it's, you know, the naturopathic side or the actual medical doctor side.
And looking at these bits of information and understanding these things doesn'tnecessarily mean you're not going to get good outcomes.
It all depends on who's probing the system, inputting information.
I think what it's a false dichotomy to think that it's one or the other.
(20:19):
think the reality is it's going to be an amalgamation of these pieces.
And the net result is that it could be good in the end, but it's going to hurt along theway.
mean, we all work out and we go and lift heavy things and then we feel like shit after it.
because we're tired and that's part of the process.
(20:39):
Part of the process is breaking things down so you can actually get better, stronger andfaster.
This AI is like all of us being forced to do like the Batan Death March together on thisparticular area.
And you're going to be sore whether you like it or not.
You didn't volunteer for it, but you're on board.
So pack your fucking trail mix and get your boots on because we're going.
(21:01):
And this is what's happening.
And
Along the way, you're either going to figure out a way to adapt and make these pieces workand get stronger, or you're going to fall off the trail and you're going to become a
casualty in this process.
And I think there will be a lot of casualties along the way and who owns that and who isaccountable for that.
(21:22):
Everyone's just going to go, sorry.
Certainly not the insurance companies.
Has nothing to with them.
I agree with you a hundred percent.
I have, I have put a few models in place at work that, you know, augmented humans or made,or made humans super humans to some extent.
And you're not kidding.
(21:43):
Like you are absolutely right.
The people who can't go on that march fall off and die.
Like it's, I've seen it at very, very small scale.
But I totally believe you, like, that's the way it's gonna be.
All right, well, since we've solved that global crisis, let's move on to my duh moment.
(22:03):
You mentioned working out, Jason, and that just reminds me, you know, a few days ago I wasin one of my slumps, you know, when you live with depression, that's kind of part of the
deal.
And so you start, you know, when it comes to everything in your life, you're like, oh,what's the point?
Everything's pointless.
I'm not doing this anymore.
And so I'm considering the amount of time I'm spending in the gym and, you know,
(22:23):
There's some days I look in the mirror and I'm like, Oh, hey, this is working.
This is all right.
And then there's some days I'm like, what a waste of time.
Yeah.
Disgusting.
And so I got curious and started looking through, you know, the data that is automaticallytracked with my workout tool.
I use fit bottom.
I'm a big fan of the thing.
It's not a sponsor, although there should be.
And I just was curious, like, what, what is it collecting about me?
What does it know?
(22:44):
Is this doing anything for me?
And so not only do I see an incredibly consistent streak over a number of weeks, I'm like,wow, I've never worked out that much that consistently in my entire life.
That's incredible.
But it also, they have this number and you know, it's, one of these numbers where you takeit with a grain of salt, but they take all of your data and they gather how much stronger
you've gotten over the course of, of using the app.
(23:05):
And they have this arbitrary number and, and they say on their scale of zero to a hundred,most users of their app should be at about a 50.
And so when I started, according to this calculation, it shows that my numbers were downin the 30, know, weak as a bird.
And so now it's up around 60.
(23:25):
And I just thought like, well, that's incredible.
Like I'm, I'm twice as strong as when I started this little adventure in October.
And it just hit me over the head with something that Zach, you and I have talked about onthe show forever.
And that I've always been incredibly miserably bad at, which is tracking things.
I'm not a details person.
It's the kind of thing that drives me crazy.
(23:46):
I will track something for about four minutes and then I'll get bored and give up on it.
But it reminded me of the value of doing that if there's a way to do it.
Like to have this little robot in my pocket for the last four months calculating how muchbetter I'm getting made me go, okay, I don't have to question this anymore.
Like the proof is in my hand, I'm doing it.
(24:07):
And so it just made me curious, you know,
as someone who struggles to track things if it's not done automatically, what do you guysdo to track the things in your lives that you're trying to improve?
Zach, I'll let you go first on this one.
Well, I don't think we have enough time to go through all that, I do.
(24:28):
have.
I didn't, I am.
I actually, took a shower right before this, so like you can't see it, but like I don'thave my Apple watch which tracks things and my whoop that tracks things and my aura ring
and my bed that tracks things.
I mean, these are all just like the general things I wear every day.
Yeah.
I know.
Like I feel like I should be making gang times with my.
(24:50):
I know, that's what we're doing over here.
but you know, I also, you know, I also track like, you know, it's just a habit.
Like, you know, I use my fitness pal just because I like it.
You know, it's got good, macro that you can track with it and things like that.
And it's a good catalog of, of things of, of food there.
(25:12):
But I also track a lot of, I mean, I work in data, so like, I'm just, just a super bigfan.
So whenever I see anything that I want to track, I don't know, it's just about discipline.
I.
You know, I look over and I see Jaco's book, like, and you know, the initials good.
And I'm okay, it's going to suck to track all this stuff.
And I just get down with it.
I've got so many spreadsheets and so many things and you know, my better half calls me anerd.
(25:39):
And, you know, she says it in a, a negative way.
I think it's a positive thing because I like to do that stuff.
So I don't know.
It's just part of my culture.
It's part of my DNA.
I don't know.
I love looking at that data and looking at.
You the changes, but like the things you're talking about, like, know, you, gotta becareful what you're looking at.
(26:00):
Like if you look one day to the next, there's going be nothing.
Even if you look one week to the next, you'll probably see nothing.
Like you need to, you need to understand that in order to see those differences, you'vegot to be consistent and have that months and months and months worth of data in there to
see the changes.
You know, like it's not up and down like.
(26:21):
volatile stock market or something like that on different days.
But I don't know.
That's just how I do it.
just have tons of, I automate it wherever I possibly can.
And I've, it is sad.
have a bunch of code that automates a lot of data tracking, but a lot of it's manual,right?
You just have to punch the things in.
(26:41):
Yeah.
Which gets measured gets changed if you don't measure a thing your ability to change it isIrrelevant because you have no way to understand it So if you're not going to record it,
you're not doing the thing So Jeremy this app that you had that said you are stronger.
What signaling what signal messages was it based in that office?
(27:02):
have to imagine that it's measuring the amount of weight that I'm lifting in any givensession, session after session.
Yeah, yeah, it's like how many reps, how much weight over the course of a period of time.
I'm sure if I looked back, I was lifting probably half of what I'm lifting now, that's,I'm inferring in their description that that's how they come up with that data.
(27:23):
And is that strength a one rep max?
Is that 10 rep max?
Is it supersets?
Like, these are arbitrary things.
And to have something tell you that and arbitrarily say you're 50 % stronger.
They're all point in time snapshots of things that you've done over a certain period oftime.
(27:43):
So it's nice because it shows progress.
Now, what it also does is it encourages you to keep going with the application so that youkeep paying for it.
And whether you actually pay out of pocket or you are the data itself, it's a differentstory.
But at the end of the day, it's about do I feel like I'm improving?
Do I feel like I'm getting better and having a hard having something that says I am a harddata asset says here's how.
(28:07):
makes all of us want to keep going.
So like I've always been fairly strong.
And I ripped my distal bicep tendon off in 2021.
And during that period of time, my deadlift was about 495 to 505.
Ripped my distal bicep tendon off, came back six months later, was working out.
(28:28):
And now my deadlift was like under 400.
So I've had to take time to rebuild those things, put those things back together, getmyself
Strong again, but I also went during that time for 295 to the 205 and then back to 245 soNow my deadlift is about 455 which is about 45 pound about 40 to 50 pounds off of what it
(28:50):
used to be when I was heavier But am I stronger now?
like Maybe if you look at it as a relative ratio of what my weight was before how thosepieces go through I'm certainly my cardiovascular improvements have occurred then I can do
a lot more pull-ups and I can do a lot more other things but
Strength is a relative term and it's nebulous because it's on a definition.
It's defined in context, the thing that you're trying to look at.
(29:14):
So measuring those things over time is the only way you can figure out if this shit'sworth it or not.
And by the way, if you're looking to not feel bad when you work out, no.
I mean,
Neatie basically, from a philosophical perspective, said that the experience of humanityis suffering.
(29:37):
So in order for you to improve and get better, you're going to have to suffer for a periodof time to make those things better.
Diamonds happen because you put them under, you put coal under extreme pressure.
So you can be happy coal that's not meant to do anything, or you can be a diamond gettingshaped into something better.
But at the end of the day, does that matter to you?
Do you give a fuck?
Like, do you care whether or not these things pan out?
(29:58):
And that's an individual thing.
And you're going to have to figure that every person has to figure that out forthemselves.
What the value is of this and what the real meaning behind it is.
And nobody is going to be able to give that to you.
You're going to have to figure that out for yourself.
And talking about this in the context of depression and going, what am I doing?
What's the meaning behind this?
I find that when I go to work out, if I just go, there is no meaning to any of this.
(30:18):
I'm just putting myself through suffering makes it much easier for me to just go and dothe thing.
And then come back and look at it later on and go, all right, it doesn't matter whether ornot anything's better or not.
I decided I committed myself to go and do this.
I'm going to go and make it happen because I'm a stubborn asshole.
And I think if other people take stubborn asshole approaches, just going and doing thesethings and then looking at the results at the end, that's when you actually see the real
(30:42):
value in the benefit.
And if you set your goal as I want to be X amounts stronger over this period of time, no,because there are physical and physiological things that might change.
You could break something, could get wrecked.
But that's not it.
If your real goals should be, I showed up.
I showed up this period of time.
I tried these things.
(31:03):
And part of that is that data tracking.
I tracked my data.
That's a showing up piece.
And showing up consistently, trying to do those things and measuring them at the end willgive you motivation to keep showing up and doing the shitty thing.
Yeah, and in the end, that is it, right?
Like my goal is not to weigh X, it's not to bench X, it is literally to show up every dayand do the thing as much as I possibly can.
(31:25):
But when the darkness comes and everything feels pointless to a point that it is kind of,I don't like to use the word crippling, I just can't think of a better word, but it just,
it's this very, it shuts me down.
And so it was encouraging for me, and we talked a little bit about this on another episodeabout like the...
million points of data that all these things gather to give you this arbitrary number thatyou're supposed to mean something to you.
(31:49):
So like the aura ring and how my readiness score, like what the hell's readiness?
I don't know, but if it says I'm at 90, let's go.
I don't know what that means, but I'm pretty ready.
And there are some days when it says I'm at 90 and I feel like it's at 60.
And I'm like, well, I don't believe you, you're wrong.
But it was just, it was a cool thing that I needed from an external point of view to gosomething, something is measuring progress in a positive direction.
(32:12):
whether my, whether I'm
actually have, you know, or double my strength that I was in October.
I don't know.
But this arbitrary tracker says that I'm in a better place than I was then.
And it's because of the fact that my goal is to show up every day.
And so that was what I needed from an external point of view, because I know that for alot of my life, I've depended on this doesn't feel right.
(32:33):
This doesn't feel like it's doing it.
My feeling about this isn't pushing me in the right direction.
Sometimes I need that number that says, no, you're fine.
Like it might feel like it sucks right now, but it's actually working.
So just keep going.
So that I think in the end, no matter what path you're on, tracking it will help you havethe external data that tells you, yes, this is working.
(32:56):
So that was, that was just sort of the duh aha moment that I had that I thought was worthsharing in case anyone else struggles like I do to pay attention to those terrible
details.
Well, this brings up a really good point.
So there's this common thought process of, you know, change your thinking from don't workharder, work smarter.
(33:16):
No, work harder.
Motivate smarter.
Do things smarter that keep you doing hard work, because if your entire goal is that I'm Idon't want to work as much as I'm going to do something smart, I'm going to make things
peel off.
No.
Like find other shit to do, put things in that place.
(33:39):
Don't stop working hard, working hard.
mean, even if it's a mental health thing, like sometimes the working hard part when you'rehaving a rough day is it is hard for me to get out of bed and go take a shower.
Like that's a thing.
And you should be proud when you're like, I'm going to fight entropy and the universe'sdecision to, you know, essentially annihilate me and turn me back into the stardust from
(34:02):
which I came.
If you just make all of these small little tiny things, little tiny incrementalexistential crises that you're going to deal with.
Perfect.
Do that.
Make them small, measurable, repeatable, attainable.
All those things are great.
But be smart with how you motivate yourself.
Don't beat the shit out of yourself.
Like, I'm going to do better if I keep beating myself up.
(34:25):
Like, no, you're probably not.
You're probably going to do better if you get proper rest.
And that's one of those things that people don't take into account.
Like they go through, I'm going to work harder.
Great, how are you gonna rest harder?
Well, you're not.
I mean, that's part of the motivation factor.
How do you do those things, prioritize those pieces and put them in?
And that's the whole point is like, if you're gonna have an existential crisis, make itthis big, make it a little tiny, make it a little tiny existential crisis that you can get
(34:51):
to the other side of.
Don't set yourself up with big existential crises of not knowing if you're valuable, ifyou have good worth, what am I doing?
No, just make the little tiny thing.
And sometimes you can go, all right,
I lost this existential crisis battle.
I'll get the next one.
Just change the model.
I'll put it into really, I'll put it into a way that I think about it occasionally whenI'm in those dark moments.
(35:15):
So I work out, it's who I am.
It's what I do.
I do hard things on purpose so that when the things that I don't expect that are hard comealong, I know I can do hard things.
But when I'm in that dark place and I'm thinking about, I want to go to the gym.
have to go to the gym.
I want to go to the gym.
I think about it when I take a dump.
(35:36):
I don't think I don't want to my ass.
Like you just wiped your ass, And so you just go to the gym, right?
You do the things that you need to do, put it into that small term.
So when you're like, I don't want to go to the gym, just think that in your head.
I got to wipe my ass too.
And then you'll go to the gym.
to defend myself a little bit here, it wasn't a moment of, don't want to go to the gym.
(35:58):
was an overall, what's the meaning of it all?
This stupid thing I do sucks.
right.
you are, even in those moments where you're like, what's the purpose of life?
You're still gonna wipe your ass, aren't you?
Right.
Well, and I like, I'm sure this is, I know this has been said millions of times, but MarkManson is the one that drilled it into my head in a way that was effective.
He's just like, the whole concept of you can look at it as life is pointless.
(36:23):
So what's the point?
This sucks or life is pointless.
Cool.
That means nothing matters and I can do whatever I want.
This is amazing.
So it's, totally just a perspective shift of like, when you're in that place, maybemeaning this is meaninglessness is exactly what you need it to be.
Nihilism can be very, very freeing.
And if you just take that approach to things and just go, all right, none of this mattersanything until I'm going to give it meaning and purpose.
(36:48):
Great.
Give it your meaning and purpose and say, is what it is today.
Well, cool.
We solved the problem.
We fixed that one.
I don't know about the whole AI thing.
We'll figure that out down the road as how many of us are left when this is all done.
I suspect Skynet's going to fix that problem for us.
Probably.
But that's gonna do it for this episode.
Thanks so much for sticking around.
If you have gotten any value out of this and you know someone who would also benefit fromhearing it, please share this with them.
(37:11):
There are links to do so at our website, thefitmess.com.
But that's it for this week.
Jason, Zach, thanks so much for being here.
And you, the listener, thanks for being here.
We'll be back in about a week with a brand new episode at thefitmess.com.
Thanks for listening.
Welcome to the Fit Mess.
My name is Jeremy.
Joined today by my co-hosts, co-hosts, that's the word, Zach and Jason.
Glad to see you guys here.
Thanks for being here today.
I had a moment the other day where, you know, I tend to live in sort of a depressed statemost of the time.
And I had one of those moments the other day where I was like, the fucking gym.
(00:23):
I don't want to go today.
What's the point?
It's not doing anything.
I look like shit.
I feel like shit.
And I had this like, aha, duh moment.
that relates to AI and we're going to talk about it a little bit.
So I want to tell you that story a little bit later because it's not our top story.
It's just a kind of a funny thing that happened to me that is a good reminder for a betterway for me to consider all these little things that I'm trying to do to improve my life.
(00:46):
But the big story I want to talk about today is why two in three physicians are usinghealth AI, which is up 78 % from 2023.
And on the surface, what's the problem?
Right?
They're saving all kinds of time.
This is going to make healthcare better.
It's going to make it cheaper.
It's going to make it more affordable, especially in the US where it's a finely tunedmachine.
(01:10):
Jason, you stumbled across this story.
Your reaction to more doctors using more AI to do more.
Well, so essentially the whole point of AI is to provide a level of intelligence thataugments human intelligence in some sort of way.
So that's how we're using it today.
But eventually, you know, it'll get to the point where it could subsume certain humanintelligence functions.
(01:36):
The artificial part of it suggests that these are things that are being generated bylarger sets of data.
And if you look at how physicians interoperate with things to become a doctor, you have togo to school for a certain period of time.
Sometimes that's seven years.
mean, some people go to community college for seven years.
I may have been one of them to go through and get their level of education.
(01:56):
it.
That was the you just really you're having a good time.
You wanted to stretch that out as long as you could.
I did.
I did.
mean, most people that end college after 14 years with my BA, they are not just doctors.
They have multiple doctors.
I didn't go down that path.
Anywho, yes, exactly.
(02:18):
The strange thing is that when you look at the way the data is actually collected andpulled in, they basically pull data in from multiple different sources.
And AI systems use large language models and then large learning principle functions to gothrough and create things that are verifiably usable for different use cases.
And physicians and healthcare in general has a whole battery and set of information forits use cases.
(02:44):
And the data that they bring in is not limited to your medical records.
It's not limited to your behavioral records or the inputs the doctor has.
The information they use to make decisions can be broadly based upon macro information.
So it could be, you know, people in your area react this way to certain health criteria.
(03:06):
It could be you react these ways to different types of things in the environment.
All these things are ways and mechanisms that feed these AI systems.
And doctors are trying to take advantage of it.
So two and three doctors out there are using artificial intelligence in this way to gothrough and help them make decisions about patients' health.
about billing systems, about record systems, all these different component pieces.
(03:31):
At the same time, only 38 % of doctors feel that AI is good enough from a privacyperspective, a security perspective, and a reliability perspective to say they trust it
and its capabilities more than the potential downsides.
(03:53):
So what that means is you've got an inverted model.
You have 66, about two thirds of doctors out there using AI, about a third of doctorssaying they trust AI.
So that means you've got one third of doctors using something that they think that they'renot sure that they trust for your health.
And it's, it's scary.
(04:13):
so Zach, you're the IT security professional.
I want to get your take on this.
But I just want to sort of explain a little bit about how these doctors are using AI.
So mean, according to this article from the American Medical Association, documentation ofbilling codes, creation of discharge instructions, translation services, summaries of
medical research and standards, assistive diagnosis.
(04:35):
That one scares me a little bit.
Generation of chart summaries.
So mean, it does sound like it's lot of admin work.
They're trying to free up a little bit of admin space to focus on other things.
But what's the risk here?
What's the danger?
Zach, what red flags are going off for you as you hear doctors are using AI to do part oftheir jobs?
(04:55):
I wouldn't, mean, so the diagnosis part doesn't scare me as much as all the other parts dobecause again, like we all Google our own symptoms and right.
That cough is definitely a brain tumor, like all those things.
But, and I've, I've used AI to write performance reviews.
(05:18):
I've used AI to like, you know,
It really does help if you're one of those people who like, you're looking at a blankcanvas, you can't do anything.
You can generate something to edit and then you can go edit it.
Now, if my medical charts and my, my information that other doctors and otherprofessionals are going to make decisions on is based on AI stuff that could be wrong,
(05:40):
could be right.
That's where it gets scary is like how long before my medical chart is like way off base,right?
from what it should be because AI was like, we'll just put this in there because I thinkthis sounds cool.
you know, the doctor told me to write this in, you know, Donald Trump style.
So it's all about like, it's going to be great.
It's going you know, like, who knows?
(06:04):
Exactly.
So I think that doctors will more than likely, if they use it for diagnosis assistance,right, they're probably going to double check that work.
I wouldn't be as concerned about that.
because they're using other sources for that anyway.
It's more like the, you know, again, my personal records not being updated correctly,errors that people aren't catching because I know everyone else does this.
(06:30):
You ask AI to write something and you skim it and you say it looks good and you don't readit in detail.
I mean, I do read it in detail, but most people don't read it in detail.
Yeah.
Well, that's what I was thinking too, as I was sort of considering the different pros andcons of this, is that this could open up an entire new industry in healthcare of basically
proofreaders.
So if the AI is going to create the content, we need somebody who can actually, with aneye for detail, figure out is this correct?
(06:56):
Is this what the doctor said?
But I guess the other thing that scares me, and I think this is maybe what you're gettingto, Jason, is the idea that this information is being fed through some external tool.
And again, what kind of data is being collected?
How is it going to be used?
Who has access to it?
I mean, that's the thing that scares me.
Aside from, you know, Dr.
Google telling me I have brain cancer because I coughed, what does Elon Musk suddenly knowabout me because AI was used to figure out that I don't really have brain cancer?
(07:24):
Yeah, so there's a couple of pieces here.
So you can use AI and ML to collect information and to enrich it and to put theinformation into context.
And when you do that, you create a data set.
And now you have a new data set in place.
And that data set gets reused and updated and changed over time, just like regular humanintelligence.
(07:45):
Like as a kid, you go through and you learn basic math.
And then you build upon those skills to learn more advanced math.
Well,
If you were shit at addition and subtraction when you were a little kid and it didn't getany better and you came up with the wrong answers and then you start doing more higher
order math later on, you still haven't solved the fact that you were shit at doingaddition and subtraction and that's going to affect all future calculations.
(08:12):
The same is true with AI.
We are not aware necessarily yet of how good the information and data they collected is.
We're just assuming that it's okay.
And the reality is that the people that are writing these models, doing these checks, mostof them are not medical professionals and are not professionals in those industries.
(08:34):
So you have human augmented intelligence and human augmented auditors.
Like there's entire companies out there, like Scale AI, for example, that does this.
And there's the Mechanical Turk from Amazon.
All these pieces in place where they say, we're going to take these models and then we'regoing to learn on them.
And I think it's called real human augmentation validation, something like that.
(08:55):
But the idea is that you're going to take experts to review these things to try to makethese models better.
That's great for companies that do that.
A lot of companies aren't going to do that because it's expensive.
It's not cheap.
And going through and validating these pieces and level of validation you put into placeis hard.
(09:15):
And if you start taking this content and you start learning from it,
creating collateral material as learning material, spread these things out.
Well, now you've got a disinformation problem where the AI itself could be putting outfalse information and bad things.
And it's hard to correct that when we ever become so addicted, complacent and compliantwith what these things are saying.
(09:37):
Cause if we turn over our sense of authority from doctors into the hands of AI, well nowwho actually knows and who's doing the right thing.
It's difficult, if not impossible, to be able to extract those things from each other.
And over a prolonged period of time, like you guys said, WebMD is going to become thething that you're going to use to validate the thing that your doctor said.
(10:10):
And we're going to have the Denning-Kruger effect all over again.
And we're going to have the Denning-Kruger effect with our health.
our belief system, everything else.
And it's just going to create so many competing signals that a lot of people are justlike, fuck it.
I'm not listening to any of you.
People already don't trust doctors.
People already don't trust medical institutions.
People already don't trust the authorities in this space.
(10:30):
And we have doctors who are supposed to be authorities saying, I don't trust this, but I'mgoing to have to use this because I know that in order for me to stay alive in the
business world and be able to do the things that I need to do at scale, I have to havethese things in place.
And it's incredibly dangerous.
It's incredibly
misguided, it's ineffective from a costing perspective in terms of going through and usingthese tools to make these things faster.
(10:52):
AI is going to help us do a lot of things much, much quicker, including fucking up.
We're going to fuck up quicker and at scale.
And we're going to go, that was great.
It only cost us, you know, the earth in the process because we're going to burn everythingup.
Yeah.
I mean, you mentioned cost a couple times there.
If in the end, the goal here is to reduce the cost of American health care, okay, there'sa case to be made.
(11:15):
There's no way that's gonna be the end result.
They're gonna argue that this costs more and that's why all of a sudden your costs need togo up, which is why insurance premiums need to go up.
This is not going to solve that problem.
And just to your point about the doctors themselves, mean, according to this article,nearly half of physicians surveyed.
47 % ranked increased oversight as the number one regulatory action that needs to happen.
So again, now we're bringing in more people to oversee the AI that humans have been doingfor a really long time pretty badly already.
(11:44):
So do we really need robots to also do it badly?
Well, not just that, you mentioned a really salient point and that's the idea of havinginsurance companies involved in this and the point of using AI.
So the point of using AI is not to make things cheaper.
The point of using AI is to not do anything other than make things faster.
(12:05):
That's all it's really meant to do.
It's meant to shortcut these pieces so you can execute things quicker and go much quicker.
And I guarantee you, insurance companies are going to use it to deny your claims faster.
because they're going to use it to go through, scrape this bit of information, understandthese things in context and say, now I don't need someone to go through and read these
charts.
I can say no fast because they're going to use keyword searches and indexing functions andeverything else.
(12:26):
And they're going to stick these things together and then hope people don't look too hard.
And we're not exactly in a position right now as consumers and as citizens where we'regoing to have the US government try to help us and protect us.
These are things that are just going to fall apart.
of now hiring jobs up in the federal government.
(12:50):
Right.
I mean, the government is not, the current administration does not want the government totry to help consumers.
They want the administration to enable businesses to be able to do more business likethings.
And we already know that businesses in general, especially corporations, you know, aresociopathic.
they're, they're to extract money from you and pull in.
And I'm not saying that businesses are the problem here.
(13:12):
I'm saying that our adoption of a technology that we don't understand at scale, at rate,
going into actually critical infrastructure, your body, and being said, now we're going tostart making decisions based upon this, and then punch it into a database, and then hope
for the best in the future, is probably not a great way to work on health.
(13:33):
I think, I mean, you guys hit on a couple of points where, you know, the healthcare systemin America is for sure for profit, right?
And they make money on it.
And even in the business I'm in AI is the buzzword that executives are hearing too, right?
I have been told, get AI into our systems.
(13:55):
I don't know what that means.
They don't know what that means.
And it, you know,
I always hesitated and was like, I'm not going to put AI into our product, but I'll put AIinto the backend part of it and make lives easier for us.
But at the end of the day, you know, Jeremy, you said make healthcare cheaper.
way.
(14:15):
Jason's right.
It's going to be faster and prices won't go down.
Their cost of doing business is going to go down and they're just going to keep moreprofits.
But where are they going to choose to put that AI?
Because some executive in the healthcare system is going, Hey,
put AI into the system, put AI into the system.
And you've got people who don't know what they're doing putting it in where it doesn'tbelong or where it's not necessary, where it's dangerous, where it could cause so many
(14:42):
problems.
like on top of all the other things that Jason's talking about, like it could be a hugeclusterfuck with AI all over the place where it shouldn't be.
Well, and can imagine a scenario too where, you know, right now when you go to the doctor,you fill out the intake form and list out all the symptoms you've had.
That's essentially what we're doing now with WebMD.
So now I'm doing it in my doctor's lobby while I'm waiting to be seen, probably on sometablet that's going to be telling AI, these are my symptoms.
(15:05):
And the doctor is going to basically validate what the decision AI came up with ratherthan using the, you know, the brain they have that they developed from all those many
years of community college sitting next to Jason.
And,
And now my diagnosis is coming from Dr.
Google.
And I would hope that's not the end result.
But in a push to do more faster to reduce cost, I see that as a pretty likely endingscenario here.
(15:34):
Yeah, and that we also have to take into consideration is that using AI to get informationand to do to diagnose treatments, I mean, all these pieces, it's not necessarily a bad
thing.
I mean, doctors today use Google and they use research magazines and they use industrytrade publications to go through and try to understand what medical journals are saying
(15:58):
nowadays.
These are all things that they're already doing, and they're already using the Google todo this.
It's the summarization of this information and putting these things into these augment orthese really generative AI capabilities to go through and actually give you a generative
response before it becomes scary.
And it's not necessarily that it's going to be entirely wrong or any worse than what wehave today.
(16:21):
It's just that it's going to be harder to point the finger and say who to blame.
Because if I go through and I misdiagnosed somebody and I give them the wrong drug and itcauses vasodilation and they pass out and they crash their car on the way home from the
doctor's office and kill somebody, who's at fault?
(16:43):
Because is it the AI?
Is it the doctor?
Is it the person driving the car?
Who is really to blame for all these pieces?
And we don't know yet.
And it's the accountability factor and the fact that there really is no accountabilitylane in this.
And there's no way to reverse engineer some of the AI pieces that come out of it and someof the information that it gives you.
And most people wouldn't even know how to do it.
And that's the scary part is that these things are, they're just way outside of our zoneof control.
(17:08):
I, doctors don't move fast.
Like they don't change their opinions quickly.
They tend to move slowly.
They're moving fast on AI and they're moving fast on AI because there is a economic reasonand incentive for them to do that.
But also all the tools out there.
that are in the medical industry are making this shift towards AI capabilities as well,because they're trying to get rid of their back end developers.
(17:31):
They're trying to get rid of the people that actually do data entry.
So we're just handing more and more of these things over without looking at what thecontrolling functions are going to be over time.
As the signals go up and the data gets more polluted, what you're going to wind up with ismore noise.
And the signal to noise ratio
(17:51):
is the really, really big thing.
So we have a ton of noise coming in.
We don't know how to decipher it and turn it into a signal that says, this is what youshould do.
AI is supposed to help us with that.
But the way that we're implementing it and instrumenting it, it's going to make it worsebecause we're not putting filters on those signals.
Those signals are rapid firing coming towards us and they're just turning into noise.
(18:17):
And then we're relying on these experts to try to tune these things down.
And don't think they were equipped for it.
I mean, I'll be honest.
My, my, old air force physician that worked on me as a kid when I had allergies or thetime that I like blew my ankle out, like if you told that dude, Hey, talk to this robot
and have you tell you what's going on.
I'd get a fuck you kid as he's smoking a cigarette and blowing smoke in my face from myallergy discussion.
(18:41):
But he's also the guy that probably would have done the best job treating me for myallergies compared to how things are today, because he actually would taken the time to do
a test and run through these things.
And not just said.
denied because your healthcare doesn't support these pieces based upon some arbitraryinformation that we extracted in these layers.
It just makes things harder and people are going to give up and they're going to not try.
And then I'm like, I don't care.
(19:03):
I'm going to go take ginseng and ginger and hope that I live.
So that's, yeah, okay.
That's exactly what I wanted to go next with this is desperately clinging to any glimmerof hope in this.
What do we do, right?
What's the solution?
And to me, I wonder, you know, are the naturopaths out there chomping at the bit becausethis means people are going to want the more, you know, a holistic approach to healthcare.
(19:26):
They're going to want the hour with their doctor to talk about their diet and what they'redoing differently and what's going on.
Does, does this shift us more into hippie mode where we suddenly, where we're a littleless reliant on
the traditional medical system and starting to look for alternatives because we don'ttrust the robots that they're using.
Yeah, so my end is an MD and I've had a couple of discussions about with him about, youknow, how do you feel about AI to generate diagnoses or feeding this information?
(19:53):
And he goes, well, I mean, we've been using it to some degree for a long time anyways,whether it's, you know, the naturopathic side or the actual medical doctor side.
And looking at these bits of information and understanding these things doesn'tnecessarily mean you're not going to get good outcomes.
It all depends on who's probing the system, inputting information.
I think what it's a false dichotomy to think that it's one or the other.
(20:19):
think the reality is it's going to be an amalgamation of these pieces.
And the net result is that it could be good in the end, but it's going to hurt along theway.
mean, we all work out and we go and lift heavy things and then we feel like shit after it.
because we're tired and that's part of the process.
(20:39):
Part of the process is breaking things down so you can actually get better, stronger andfaster.
This AI is like all of us being forced to do like the Batan Death March together on thisparticular area.
And you're going to be sore whether you like it or not.
You didn't volunteer for it, but you're on board.
So pack your fucking trail mix and get your boots on because we're going.
(21:01):
And this is what's happening.
And
Along the way, you're either going to figure out a way to adapt and make these pieces workand get stronger, or you're going to fall off the trail and you're going to become a
casualty in this process.
And I think there will be a lot of casualties along the way and who owns that and who isaccountable for that.
(21:22):
Everyone's just going to go, sorry.
Certainly not the insurance companies.
Has nothing to with them.
I agree with you a hundred percent.
I have, I have put a few models in place at work that, you know, augmented humans or made,or made humans super humans to some extent.
And you're not kidding.
(21:43):
Like you are absolutely right.
The people who can't go on that march fall off and die.
Like it's, I've seen it at very, very small scale.
But I totally believe you, like, that's the way it's gonna be.
All right, well, since we've solved that global crisis, let's move on to my duh moment.
(22:03):
You mentioned working out, Jason, and that just reminds me, you know, a few days ago I wasin one of my slumps, you know, when you live with depression, that's kind of part of the
deal.
And so you start, you know, when it comes to everything in your life, you're like, oh,what's the point?
Everything's pointless.
I'm not doing this anymore.
And so I'm considering the amount of time I'm spending in the gym and, you know,
(22:23):
There's some days I look in the mirror and I'm like, Oh, hey, this is working.
This is all right.
And then there's some days I'm like, what a waste of time.
Yeah.
Disgusting.
And so I got curious and started looking through, you know, the data that is automaticallytracked with my workout tool.
I use fit bottom.
I'm a big fan of the thing.
It's not a sponsor, although there should be.
And I just was curious, like, what, what is it collecting about me?
What does it know?
(22:44):
Is this doing anything for me?
And so not only do I see an incredibly consistent streak over a number of weeks, I'm like,wow, I've never worked out that much that consistently in my entire life.
That's incredible.
But it also, they have this number and you know, it's, one of these numbers where you takeit with a grain of salt, but they take all of your data and they gather how much stronger
you've gotten over the course of, of using the app.
(23:05):
And they have this arbitrary number and, and they say on their scale of zero to a hundred,most users of their app should be at about a 50.
And so when I started, according to this calculation, it shows that my numbers were downin the 30, know, weak as a bird.
And so now it's up around 60.
(23:25):
And I just thought like, well, that's incredible.
Like I'm, I'm twice as strong as when I started this little adventure in October.
And it just hit me over the head with something that Zach, you and I have talked about onthe show forever.
And that I've always been incredibly miserably bad at, which is tracking things.
I'm not a details person.
It's the kind of thing that drives me crazy.
(23:46):
I will track something for about four minutes and then I'll get bored and give up on it.
But it reminded me of the value of doing that if there's a way to do it.
Like to have this little robot in my pocket for the last four months calculating how muchbetter I'm getting made me go, okay, I don't have to question this anymore.
Like the proof is in my hand, I'm doing it.
(24:07):
And so it just made me curious, you know,
as someone who struggles to track things if it's not done automatically, what do you guysdo to track the things in your lives that you're trying to improve?
Zach, I'll let you go first on this one.
Well, I don't think we have enough time to go through all that, I do.
(24:28):
have.
I didn't, I am.
I actually, took a shower right before this, so like you can't see it, but like I don'thave my Apple watch which tracks things and my whoop that tracks things and my aura ring
and my bed that tracks things.
I mean, these are all just like the general things I wear every day.
Yeah.
I know.
Like I feel like I should be making gang times with my.
(24:50):
I know, that's what we're doing over here.
but you know, I also, you know, I also track like, you know, it's just a habit.
Like, you know, I use my fitness pal just because I like it.
You know, it's got good, macro that you can track with it and things like that.
And it's a good catalog of, of things of, of food there.
(25:12):
But I also track a lot of, I mean, I work in data, so like, I'm just, just a super bigfan.
So whenever I see anything that I want to track, I don't know, it's just about discipline.
I.
You know, I look over and I see Jaco's book, like, and you know, the initials good.
And I'm okay, it's going to suck to track all this stuff.
And I just get down with it.
I've got so many spreadsheets and so many things and you know, my better half calls me anerd.
(25:39):
And, you know, she says it in a, a negative way.
I think it's a positive thing because I like to do that stuff.
So I don't know.
It's just part of my culture.
It's part of my DNA.
I don't know.
I love looking at that data and looking at.
You the changes, but like the things you're talking about, like, know, you, gotta becareful what you're looking at.
(26:00):
Like if you look one day to the next, there's going be nothing.
Even if you look one week to the next, you'll probably see nothing.
Like you need to, you need to understand that in order to see those differences, you'vegot to be consistent and have that months and months and months worth of data in there to
see the changes.
You know, like it's not up and down like.
(26:21):
volatile stock market or something like that on different days.
But I don't know.
That's just how I do it.
just have tons of, I automate it wherever I possibly can.
And I've, it is sad.
have a bunch of code that automates a lot of data tracking, but a lot of it's manual,right?
You just have to punch the things in.
(26:41):
Yeah.
Which gets measured gets changed if you don't measure a thing your ability to change it isIrrelevant because you have no way to understand it So if you're not going to record it,
you're not doing the thing So Jeremy this app that you had that said you are stronger.
What signaling what signal messages was it based in that office?
(27:02):
have to imagine that it's measuring the amount of weight that I'm lifting in any givensession, session after session.
Yeah, yeah, it's like how many reps, how much weight over the course of a period of time.
I'm sure if I looked back, I was lifting probably half of what I'm lifting now, that's,I'm inferring in their description that that's how they come up with that data.
(27:23):
And is that strength a one rep max?
Is that 10 rep max?
Is it supersets?
Like, these are arbitrary things.
And to have something tell you that and arbitrarily say you're 50 % stronger.
They're all point in time snapshots of things that you've done over a certain period oftime.
(27:43):
So it's nice because it shows progress.
Now, what it also does is it encourages you to keep going with the application so that youkeep paying for it.
And whether you actually pay out of pocket or you are the data itself, it's a differentstory.
But at the end of the day, it's about do I feel like I'm improving?
Do I feel like I'm getting better and having a hard having something that says I am a harddata asset says here's how.
(28:07):
makes all of us want to keep going.
So like I've always been fairly strong.
And I ripped my distal bicep tendon off in 2021.
And during that period of time, my deadlift was about 495 to 505.
Ripped my distal bicep tendon off, came back six months later, was working out.
(28:28):
And now my deadlift was like under 400.
So I've had to take time to rebuild those things, put those things back together, getmyself
Strong again, but I also went during that time for 295 to the 205 and then back to 245 soNow my deadlift is about 455 which is about 45 pound about 40 to 50 pounds off of what it
(28:50):
used to be when I was heavier But am I stronger now?
like Maybe if you look at it as a relative ratio of what my weight was before how thosepieces go through I'm certainly my cardiovascular improvements have occurred then I can do
a lot more pull-ups and I can do a lot more other things but
Strength is a relative term and it's nebulous because it's on a definition.
It's defined in context, the thing that you're trying to look at.
(29:14):
So measuring those things over time is the only way you can figure out if this shit'sworth it or not.
And by the way, if you're looking to not feel bad when you work out, no.
I mean,
Neatie basically, from a philosophical perspective, said that the experience of humanityis suffering.
(29:37):
So in order for you to improve and get better, you're going to have to suffer for a periodof time to make those things better.
Diamonds happen because you put them under, you put coal under extreme pressure.
So you can be happy coal that's not meant to do anything, or you can be a diamond gettingshaped into something better.
But at the end of the day, does that matter to you?
Do you give a fuck?
Like, do you care whether or not these things pan out?
(29:58):
And that's an individual thing.
And you're going to have to figure that every person has to figure that out forthemselves.
What the value is of this and what the real meaning behind it is.
And nobody is going to be able to give that to you.
You're going to have to figure that out for yourself.
And talking about this in the context of depression and going, what am I doing?
What's the meaning behind this?
I find that when I go to work out, if I just go, there is no meaning to any of this.
(30:18):
I'm just putting myself through suffering makes it much easier for me to just go and dothe thing.
And then come back and look at it later on and go, all right, it doesn't matter whether ornot anything's better or not.
I decided I committed myself to go and do this.
I'm going to go and make it happen because I'm a stubborn asshole.
And I think if other people take stubborn asshole approaches, just going and doing thesethings and then looking at the results at the end, that's when you actually see the real
(30:42):
value in the benefit.
And if you set your goal as I want to be X amounts stronger over this period of time, no,because there are physical and physiological things that might change.
You could break something, could get wrecked.
But that's not it.
If your real goals should be, I showed up.
I showed up this period of time.
I tried these things.
(31:03):
And part of that is that data tracking.
I tracked my data.
That's a showing up piece.
And showing up consistently, trying to do those things and measuring them at the end willgive you motivation to keep showing up and doing the shitty thing.
Yeah, and in the end, that is it, right?
Like my goal is not to weigh X, it's not to bench X, it is literally to show up every dayand do the thing as much as I possibly can.
(31:25):
But when the darkness comes and everything feels pointless to a point that it is kind of,I don't like to use the word crippling, I just can't think of a better word, but it just,
it's this very, it shuts me down.
And so it was encouraging for me, and we talked a little bit about this on another episodeabout like the...
million points of data that all these things gather to give you this arbitrary number thatyou're supposed to mean something to you.
(31:49):
So like the aura ring and how my readiness score, like what the hell's readiness?
I don't know, but if it says I'm at 90, let's go.
I don't know what that means, but I'm pretty ready.
And there are some days when it says I'm at 90 and I feel like it's at 60.
And I'm like, well, I don't believe you, you're wrong.
But it was just, it was a cool thing that I needed from an external point of view to gosomething, something is measuring progress in a positive direction.
(32:12):
whether my, whether I'm
actually have, you know, or double my strength that I was in October.
I don't know.
But this arbitrary tracker says that I'm in a better place than I was then.
And it's because of the fact that my goal is to show up every day.
And so that was what I needed from an external point of view, because I know that for alot of my life, I've depended on this doesn't feel right.
(32:33):
This doesn't feel like it's doing it.
My feeling about this isn't pushing me in the right direction.
Sometimes I need that number that says, no, you're fine.
Like it might feel like it sucks right now, but it's actually working.
So just keep going.
So that I think in the end, no matter what path you're on, tracking it will help you havethe external data that tells you, yes, this is working.
(32:56):
So that was, that was just sort of the duh aha moment that I had that I thought was worthsharing in case anyone else struggles like I do to pay attention to those terrible
details.
Well, this brings up a really good point.
So there's this common thought process of, you know, change your thinking from don't workharder, work smarter.
(33:16):
No, work harder.
Motivate smarter.
Do things smarter that keep you doing hard work, because if your entire goal is that I'm Idon't want to work as much as I'm going to do something smart, I'm going to make things
peel off.
No.
Like find other shit to do, put things in that place.
(33:39):
Don't stop working hard, working hard.
mean, even if it's a mental health thing, like sometimes the working hard part when you'rehaving a rough day is it is hard for me to get out of bed and go take a shower.
Like that's a thing.
And you should be proud when you're like, I'm going to fight entropy and the universe'sdecision to, you know, essentially annihilate me and turn me back into the stardust from
(34:02):
which I came.
If you just make all of these small little tiny things, little tiny incrementalexistential crises that you're going to deal with.
Perfect.
Do that.
Make them small, measurable, repeatable, attainable.
All those things are great.
But be smart with how you motivate yourself.
Don't beat the shit out of yourself.
Like, I'm going to do better if I keep beating myself up.
(34:25):
Like, no, you're probably not.
You're probably going to do better if you get proper rest.
And that's one of those things that people don't take into account.
Like they go through, I'm going to work harder.
Great, how are you gonna rest harder?
Well, you're not.
I mean, that's part of the motivation factor.
How do you do those things, prioritize those pieces and put them in?
And that's the whole point is like, if you're gonna have an existential crisis, make itthis big, make it a little tiny, make it a little tiny existential crisis that you can get
(34:51):
to the other side of.
Don't set yourself up with big existential crises of not knowing if you're valuable, ifyou have good worth, what am I doing?
No, just make the little tiny thing.
And sometimes you can go, all right,
I lost this existential crisis battle.
I'll get the next one.
Just change the model.
I'll put it into really, I'll put it into a way that I think about it occasionally whenI'm in those dark moments.
(35:15):
So I work out, it's who I am.
It's what I do.
I do hard things on purpose so that when the things that I don't expect that are hard comealong, I know I can do hard things.
But when I'm in that dark place and I'm thinking about, I want to go to the gym.
have to go to the gym.
I want to go to the gym.
I think about it when I take a dump.
(35:36):
I don't think I don't want to my ass.
Like you just wiped your ass, And so you just go to the gym, right?
You do the things that you need to do, put it into that small term.
So when you're like, I don't want to go to the gym, just think that in your head.
I got to wipe my ass too.
And then you'll go to the gym.
to defend myself a little bit here, it wasn't a moment of, don't want to go to the gym.
(35:58):
was an overall, what's the meaning of it all?
This stupid thing I do sucks.
right.
you are, even in those moments where you're like, what's the purpose of life?
You're still gonna wipe your ass, aren't you?
Right.
Well, and I like, I'm sure this is, I know this has been said millions of times, but MarkManson is the one that drilled it into my head in a way that was effective.
He's just like, the whole concept of you can look at it as life is pointless.
(36:23):
So what's the point?
This sucks or life is pointless.
Cool.
That means nothing matters and I can do whatever I want.
This is amazing.
So it's, totally just a perspective shift of like, when you're in that place, maybemeaning this is meaninglessness is exactly what you need it to be.
Nihilism can be very, very freeing.
And if you just take that approach to things and just go, all right, none of this mattersanything until I'm going to give it meaning and purpose.
(36:48):
Great.
Give it your meaning and purpose and say, is what it is today.
Well, cool.
We solved the problem.
We fixed that one.
I don't know about the whole AI thing.
We'll figure that out down the road as how many of us are left when this is all done.
I suspect Skynet's going to fix that problem for us.
Probably.
But that's gonna do it for this episode.
Thanks so much for sticking around.
If you have gotten any value out of this and you know someone who would also benefit fromhearing it, please share this with them.
(37:11):
There are links to do so at our website, thefitmess.com.
But that's it for this week.
Jason, Zach, thanks so much for being here.
And you, the listener, thanks for being here.
We'll be back in about a week with a brand new episode at thefitmess.com.
Thanks for listening.
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