Exploring Life-Saving AI Tech with T-Mobile for Business

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This episode is a paid partnership with T-Mobile for Business.

Hello, hello, Malcolm Gladwell here.

Today, I wanted to share a very special conversation I had recently, hosted by my good friends at T-Mobile for Business, about how AI is changing our world.

My guests are Mo Cadaba, the CMO of T-Mobile for Business, Dr.

Azizi Seychis, Chair of the Department of Informatics and Health Data Science at the University of Miami Miller School of Medicine, and Ryan Litt,

COO and co-founder of 3AM Innovations.

Mo, I know, from years ago when we had a fascinating conversation about 5G when that technology was in its infancy.

Ryan is from Buffalo, and we shared a deep affection for the Buffalo Bills.

And Azizi, as will soon be obvious, is Jamaican.

which of course is the surest way to my heart.

Anyway, we talked about some really cool applications of AI and 5G and the way really smart people like Ryan and Azizi are using these technologies to solve some pretty hard and fascinating problems.

Thank you.

Hey everyone, we're all wearing our,

should we just put our, I know this is a podcast and you can't see it, but we're all wearing T-Mobile sneakers right now.

I see two of us have got the Air Forces and then the others.

Converse.

Converse high tops.

So we're all representing the brand, I think, very effectively here.

So we're here to talk about AI and 5G, but what we're really here to talk about is something much simpler and more important than that, and that is problem solving.

All of you guys are people who basically solve problems for a living.

And I wanted to start there.

And maybe, Ryan, you could kick us off.

Tell us a little bit about what you do, but then tell us about the problem you're trying to solve.

Sure.

So

when we think about emergency events and really at the majority of the world, the primary tool set that firefighters use is a radio to communicate their status to the outside operation.

And I'm sure we can all imagine, however, you know, winding hallways, dense forests,

black black smoke, falling debris.

Pretty reasonable to expect that people can become disoriented.

They can be a bit confused.

And the issue for a firefighter is when they're confused, inherently, so is the rest of the operation.

Yeah.

Wait, before you go on, tell us a little bit about how is it you landed in this particular world?

Why is it that you're thinking about this problem of the disorientation of

the firefighter?

Well, you know, ultimately when there's confusion, it ultimately leads to injury and sometimes death.

So the true inspiration to our origin is in Buffalo, New York.

There was a convenience store that was on fire.

And, you know, upon arrival, firefighters quickly got to trying to put out the fire, but

the fire itself moved faster.

So they had to call an evacuation, pull everybody out, but they were unsure if everybody got out.

So they assigned a team to go sweep the facility to try to rescue anybody remaining.

and unfortunately the structure collapsed over top of them and killed them both.

When was this?

Go ahead.

2009.

Yeah.

And to make matters worse, there was nobody inside.

They were just unsure.

And so for us, it's no slight against them, but we just feel like they deserve better tools.

There has to be more than what they have, that radio.

No slight against the radio either.

But all of us are here because technology is flush in many other places, and our belief is they deserve to have it too.

Tell us how that company starts.

Does it arise out of that particular incident or I'm just curious about how you kind of evolved to the point where you were looking for solutions to that problem?

Yeah, so I mean that event was in 2009.

We officially started in 2017.

So there's a time and distance between those two things.

My co-founder Patrick is a volunteer firefighter.

And he was constantly educated that if career firefighters, which to be clear for everybody, they are getting paid and work as a firefighter every day, but volunteers typically have a day job and then they get called to an emergency event in the middle of it.

So the message was: if the career people can make mistakes, we're definitely going to be prone to making mistakes.

So let's learn from this.

And so Patrick kind of lived with that for years in education and felt, come on, I got this iPhone in my pocket.

There's got to be something more.

And finally, by 2017, technology seemed to go in a place that made sense, And he had to find a partner to help him do it.

And that's why we ended up pursuing it from there.

So our original intent was to build technology to

help them in these emergency events.

The hard part, though, is an emergency is inherently chaotic, unpredictable, right?

And all of a sudden we think, okay, we're just going to repurpose technology that already exists and afford it to the fire service.

Instead, we're at the edge of technology actually pushing on capabilities that, according to colleagues and people that we worked with in NASA and DHS didn't exist.

So for example, like tracking someone's location when they are GPS denied, you know, helping communication to be shared when you are communication denied.

It turned out that not many people around the world were doing it and at which point we said, uh-oh, this is going to be a lot more of a difficult endeavor than we had anticipated.

So that's the origin of why we're here.

Is there

This is all super interesting and I want to come back in more detail after we've gone down the panel a little bit.

But one thing I wanted to

talk about just a little bit so we understand this.

When you have a kind of fire that's out of control,

the specific issue that you were trying to solve is that once someone, a firefighter, entered the facility, you lost track of where that person was.

Right.

And there was no existing system in place that would allow you to easily track that person.

100% correct.

Yeah.

And is it because of the

is it because because the fire had destroyed any kind of infrastructure that might make that possible?

Or is it just I mean, why was

why is what's particularly hard about

tracking someone in a in the middle of a of a burning building?

Well, circumstantially, it wasn't necessarily the case that comms are necessarily completely blown out.

Not not always the case, because sometimes the radio system continues to function.

There are so many dynamics to the situation that for you to give someone a tool that you say universally will help you is a very precarious undertaking, right?

You have to handle in a large structure like we're in now, in a small structure in a suburban area, in remote areas, and wildland fires and such, right?

And it has to work in all of those places in order to work for a firefighter because the modern firefighter experience is so much, right?

So, you know, chasing those problems fundamentally difficult.

A lot of data, a lot of

error, right?

And

you push hard to make sure that it's purpose-built.

So I think this is where the AI portion of our discussions makes sense, right?

It can help to interpret a lot of inputs and give us some simple surfacings and understandings that we can leverage from there.

Yeah.

Mo, I want you to respond to Ryan.

And I'm curious whether Did you, when you when you started on this road, did you imagine you'd be having conversations with people like Ryan?

I was certainly hopeful.

Being able to serve the first responder community

is such an important undertaking, you know, every single day to protect you and me, our families, our communities.

And, you know, from a T-Mobile for Business perspective, how can we take this incredible best in the nation 5G network and how can we harness some very specific capabilities to bring to life a solution that serves the first responder community and companies like Ryan's 3AM.

And just a few weeks ago now, we launched what we call T-Priority,

which brings not just the network,

which has 40% more capacity, which means more firefighters and police and EMS showing up at a location are able to get on the network and do what they need to do.

But then something that we call a slice, which is really a fancy technology term, which is, hey, can we create a traffic cop, if you will,

a capability that as first responders are getting on the network, that not only gives them the access to the network, priority access and then preemption access to essentially, you know, bump, if you will, a commercial user off of the network, and that's been around for four, five, six, seven years at this point.

But can we give them the ability then to manage that traffic and dynamically allocate the amount of capacity on the network to the first responders so that in these sorts of scenarios where

extreme congestion can be occurring, you know, like a train derailment or a massive natural disaster, et cetera, that we can essentially give up to 100% of the network over to the first responders responders so that they can save lives.

Oh, wow.

Yeah.

I want to return to that, but I want to talk a little bit too Azizi.

You are, tell us what you,

tell us your title, your job.

So I currently serve as the interim chair for the Department of Informatics and Health Data Science, and I'm the founding director of the Media and Innovation Lab.

And I co-lead a sleep on circadian science, and I lead population health informatics.

So not to be funny, but as a Jamaican, we're known for multiple jobs.

This is at the University of Miami.

It is at the University of Miami.

But you're a doctor by training.

I'm a PhD.

I'm a clinical psychologist, but I lead many of the efforts at the university to lead digital transformation.

And so, I was recruited from

another large institution when I was at NYU School of Medicine to lead this effort at the University of Miami.

And the reason why it's important is because the University of Miami really serves as the academic epicenter of the Southeast, particularly in Florida.

And Miami in particular is really considered the gateway to the Global South.

For those of you who are not familiar, the Global South represents 80% of the world's population, yet as a euphemism, they're oftentimes seen as the poorest, less resourced, particularly in healthcare.

And so I was brought to lead that effort to create models that would be able to serve not just South Florida, but how it could be translated to similar socio-economic deprived communities throughout Florida and then use it as a model to really do this in the global south.

Yeah.

At what point during your career did you realize that what you wanted to do was use technology to solve problems?

I mean, you have a PhD in clinical psychology.

You're not looking at AI and 5G when you're doing a PhD.

Well you know so great question.

So when I realized that technology was important

was when I realized that many of the most vexing healthcare challenges that we saw in my own family, my grandmother who raised me, and we realized that there was just significant lack of resources.

She had insurance, but what we saw was a significant gap in the continuity of care.

And extrapolating her experience to what I see when I go to barber shops, beauty salons, and faith-based organizations, because we're one of those folks who we like to be in the community, that we don't believe in this sterile brick and mortar healthcare because we believe healthcare needs to be more.

And what we found out was that in order for us to meet the challenges that our nation and our globe sees, that we either need to train a whole lot more healthcare practitioners, which we still need to do, but that was not going to be sufficient to close that gap in good time.

So what we realized was that technology, though it is not a panacea that can cure all, was going to be the means by which we were going to be able to, one, provide the care that so many people desperately need, but also to provide adjunctive and supportive and augmentive care to healthcare providers.

And so technology became the means by which it would allow us to really extend our tentacles into places beyond that we thought were unimaginable.

Give us a specific example of a moment where you realized, oh, this is a nut we can only crack with technology.

Yeah, so we created our own remote health monitoring solution called the mailbox.

And we were funded to do some really novel research looking at cardiovascular health in urban and rural areas.

And so, like most scientists, we don't care about, you know, accolades per se.

We just wanted to do the work and we did the work.

And then COVID happened.

And we went into someone's home because we would typically send out technicians.

And I remember because she's part of a study and because of HIPAA compliance, I can't say her name.

But we'll call her Miss Jones.

Miss Jones is a 60-year-old African-American woman, lives in Brooklyn.

And we called her and said, Ms.

Jones, such and such will be coming down there to do the study.

And she said, hey, honey, you ain't coming here at all, because I ain't trying to get the Rona.

And that allowed us to realize

that how can we flip it?

And that's what really spurred us into action quickly to create a remote health monitoring solution, knowing very well that it can be used for people.

It's oftentimes said that since 2016, 2016, there are about 140 million emergency department visits.

And there are about 60%

of global deaths that can be attributed to non-communicable diseases like cardiometabolic health.

And what are the biggest drivers of that?

No health care.

Right?

And people don't have access.

So when we went to someone like Ms.

Jones and what we've seen bear out in our studies and what we've seen, we've seen another woman who she lives in government housing in Florida, and she would always go to her landlord because she had these respiratory illnesses.

And the landlord will push her aside and say, no, nothing is wrong.

You're trying to evade paying your rent.

And she's like, no, there's something wrong with me.

You need to change something.

And she was part of our study.

And we have as part of our remote health monitoring solution an air quality device.

And she was able to use that to show to her landlord that there was something significantly wrong in terms of mold.

And And so look at this.

Many of us live in environments that we just trust that it has the right environment, it has everything.

Even if you have healthcare.

And what we want to be able to do is to put a wearable on the environment, put a wearable on individuals, and it is facilitated through technology so that we can quantify, so that we can show and prove, so that we can further empower our patients.

That's just one example.

There's another example as well.

Another woman who lives in a rural area in Florida and went to the physician like most of us and we get all of these printouts on our lab work and we don't know what they mean.

Let's be real.

And I'm not to knock on my colleagues, but you will be very lucky if someone goes through with you what each measurement means.

Right?

So this is what happened.

This woman went to her provider and the provider said, I think something is up with your heart.

Something is up with your heart.

Now, this is a woman who works two jobs, has three kids.

So she's like, what should I do?

Well, you should go ahead and see a cardiologist.

Didn't provide the necessary handoff at all.

And so here is it that we dropped the ball as a community.

That this lady just went off and just said, well, I guess something is wrong with my heart.

You know, we'll see.

I'll go to the ER, which is why we have so many ER visits.

And so what she was able to do by wearing one of our rings, she called us angry she said dr.

Seishas your device is waking me up every 10 minutes I don't want to be part of your study anymore when we looked at our command center and we saw what was happening this lady oxygen levels were dropping below 80 percent

Critical.

So what we ended up doing, we said, you know what, we don't care about health care and insurance right now.

We have a study physician.

We connected her and she was able to see a cardiologist in no time.

She called us crying, saying thank you very much because if she hadn't gotten that intervention, she probably would have died and she would have left her kids orphans.

This is what we see in black and brown families all the time.

It's not just a health care issue.

She had health care.

But how are we able to connect the dots?

And we believe through technology, we can have a physical in a box to do that.

I want to come back to Ryan, same question.

Let's talk about the technology here.

Yeah.

You gave her a a ring.

Yeah.

Like a,

describe this.

Yeah, I mean,

I mean, I have the ring here, but it's a ring that measures what we call cardiopulmonary coupling, big terms.

Here's what it means.

Typically, what happens is your respiratory system, your lungs, operate in conjunction with your circulatory system, your heart.

What ends up happening in between that physiology is so many things and that's where we believe many of the illnesses that get undetected, that's where they surface, and they surface mostly in your sleep.

So, you will never feel those symptoms at all.

So, what we were able to do through the ring, measuring cardiopulmonary coupling, because your watch doesn't do that, because your watch only measures one or the other.

We're able to measure the two, and we're able to measure how the two interact and connect with each other.

So, this ring, is this an off-the-shelf thing or something you gotta do?

We're trying to get it off-the-shelf, but it's it's more of a

medical device.

And dare I say, it's not this, any other, but it's not as expensive as others.

We've worked with some other proprietary.

It is not as expensive.

So you wear this ring, and then it's connected to what?

It's connected to

a cell phone that we provide.

So it's tethered.

So when you fall asleep, you hit start and it starts to measure.

It can measure if you're at risk for sleep apnea.

It can measure if you have significant oxygen desaturation, lowering the levels and all that.

And that data is coming back?

Yes, so that data comes back to the command center that we are able to see.

Which is at the University of Miami.

Which is at, yes, in our group at the University of Miami.

And how many patients do you have on, for example?

Yeah, so right now we're piloting this in a research study.

So we have 1,500 participants, African American and Hispanics in urban and rural areas.

And we've partnered with community health centers, federally qualified health centers.

Oftentimes, academic centers are the ones who are the ones who wave the flag of technology.

What we said at the University of Miami is that we have to do more, that it is our vocation and it is our mission to really be that

supporting force.

So we work with the largest free clinic in the state of Florida.

We'll be right back with more from the panel.

In today's super competitive business environment, the edge goes to those who push harder, move faster, and level up every tool in their arsenal.

T-Mobile knows all about that.

They're now the best network, according to the experts at OOCLA Speed Test, and they're using that network to launch Super Mobile, the first and only business plan to combine intelligent performance, built-in security, and seamless satellite coverage.

With Supermobile, your performance, security, and coverage are supercharged.

With a network that adapts in real time, your business stays operating at peak capacity even in times of high demand.

With built-in security on the first nationwide 5G advanced network, you keep private data private for you, your team, your clients.

And with seamless coverage from the world's largest satellite-to-mobile constellation, your whole team can text and stay updated even when they're off the grid.

That's your business, supercharged.

Learn more at supermobile.com.

Seamless coverage with compatible devices in most outdoor areas in the U.S.

where you can see the sky.

Best network based on analysis by OOCLA of Speed Test Intelligence Data 1H 2025.

We're back with Mo Cadaba, Dr.

Azizi Seychis, and Ryan Lid.

So walk us through how you use technology

to answer those questions.

I think that the place that we start, and as some of us in technology, because myself, you know, probably more of a technologist, it's to start with the person first,

right?

To observe, to understand, and then augment.

But ideally, we always say complement, not complicate.

So if there's something that's already available, if there are tools that are already there, can we listen to those tools?

So that it can feel seamless to the first responder.

The last thing we want them to do is be playing with new tech and buttons and other things to make their jobs even more complex.

So, we sought to make a more integrative solution, which therefore, you know, 5G and software and these sorts of things start to

form because it makes sense to do.

We've thought a lot about bioindicators, like the doctor's talking about.

Cardiac arrest is still one of the greatest killers in the fire service.

Detecting blood oxygen levels would be amazing because if we could capture those things as a precursor, we could draw those individuals out before it's too late.

The hard part is the stressor, it's such a high-stress environment that we need the technology to get to a point where it can actually give us that accuracy when we need it and not tell us after the cardiac arrest has already happened, oh, you know, this person's about to have one.

So for us, we look at interfacing with other technology, but inevitably what got interesting is phones had a role to play, right?

And in a couple of different ways, one of which is the compute, all the things that phones can do for all of us in our daily lives.

Those are great assets and tools for the fire service.

Right now they literally have that radio I explained before and rarely much else.

So an example,

again, we're human-centric, so we stay with people, we embed in fire stations.

And I was following a fire chief, and the alarms went off and we went off to an emergency event.

And I watched him as he pulled out two radios, turned each one to a different channel, placed them against his ears, and looked up at the event and proceeded to manage it.

Manage it, in other words, keep it safe, you know, mitigate the emergency, right?

Thankfully, everything was all clear, nobody got hurt.

We went back to the station, and I asked him, Hey, Chief, have you taught yourself over the years to listen to two conversations at the same time?

And he's like, no.

He's like, the intensity draws my attention.

So he listens for the intensity of the voice to say, this might be something, it's time for me to listen.

Oh,

that's fascinating.

Yeah, and the thought process was coming home, driving back to our headquarters in Buffalo.

It was a bit of a drive.

I thought, computers don't have ears, right?

What about the idea of opening up a phone?

and allowing the phone to listen to as many conversations as may be happening at any given time and maybe take it a little further.

Instead of just listening for intensity, we can actually listen to that conversation and interpret it.

And that was literally the dawn of us starting to use AI.

And when we think about other tools, what other tool do we have that can fundamentally bring that to some of the things?

So just so I understand, we're at a complex fire scene.

We have multiple firefighters, multiple people talking on radios.

The guy in charge has got to make sense, has to coordinate all the things going on.

And you're saying we could have AI listen to all of those conversations simultaneously and do what exactly?

Prioritize them, them, summarize them?

How does the AI interface with

the human decision maker?

Yeah, so the nice part is you can teach it for what you want to listen for.

So a lot of times there are operative words of concern that are communicated.

They want to know when certain indicators happen.

But let's be honest, the real thing that most people are looking for is when the firefighter is under duress, when the firefighter is at risk of a loss of life.

So Mayday and these types of situations are pretty consistent.

So the way we think about it is we take the communication standard operating procedure.

How do people communicate officially through these radio systems?

When do we know it's bad?

Let's teach the AI to listen for that.

And then that way we rise to the top.

We have a software interface, of course, and the chief will see someone just said something that is of concern.

They turn red, they glow, we show them where they're located, and then the chief can take it from there.

So the chief's looking at his phone, or is he?

So the chief is actually looking at a tablet.

A tablet.

Just because you want a little bit more surface area to kind of be able to.

In real time, the tablet is tracking everybody and prioritizing the person who is in most distress or under the most stress.

Yes.

And then the other nice part with the phone, because of the amount of data that's available, we can localize people in three-dimensional space.

So we can actually show where they exist in the world, but inside even a given structure and with height considered.

So that's where we fuse these things together.

So we use some of the capabilities inside the phone, all the the sensors, all the networks, and we can say, hey, this person's up here.

Oh, by the way, through the AI, they said something that you need to know about.

So now we can really localize this is where that person exists.

And then from there, they can decide what they want to do.

Mo, I'm listening to these, to Ryan and Azizi, and I'm seeing, so here are people in very specific

corners of the world taking these technologies and making, doing very, very practical things with it.

I'm curious how does T-Mobile interact in this are you are you a cheerleader are you an instigator are you

Are you the person who helps them there must you must learn obstacles?

I mean you're changing the way people do business I'm curious does T-Mobile play a role in kind of how would you characterize what you

your partnership

at the end of the day What we love to do is to visit with business customers on what out what what's your challenge?

Like, what is the heart of what you're trying to accomplish with your solution, your product, your service?

And how can we build capabilities in and around our network that really support that?

So as an example,

and I can touch on both of the use cases that have come up in the last few minutes, but talking about Ryan and 3 a.m.

for just a moment.

I love the conversation really oriented around, hey, as you think about your platform and the situational awareness that you're trying to give the chief or whoever is doing command and control of that specific situation, how can we leverage both devices, whether it's wearables that give you insights if a person can't even talk, perhaps smoke inhalation and they've fallen.

And okay, now I need to know, hey, they're not moving.

How is that information coming back?

Using the devices for things like both near-field communications and barometric pressure, which has been in the phones for six, seven years again at this point, that lets you know, hey, not only the X and Y axis of where they are, but how many floors up on a building are they, which is incredibly important for firefighters.

And then over time, we're also going to be enabling API access into the network.

We've announced this, it's coming out in the near future, which will allow the 3AM platform to enhance all of the capabilities they already have around things like even more precise location, quality of service.

Hey, I'm in the building, it's burning, I need to dial up the network resources to support everything that's happening there.

It's the number one thing.

What does API mean, by the way?

Application programming interface.

Thank you very much.

It's basically, in plain English, a way of building a door so that someone else's platform can come knock on the door, the door is opened, and we give them very specific capabilities on things that they can do with network resourcing in real time.

Quality of service, location, application support.

It's

a distribution.

We have this complicated thing, situation happening, and at various moments we want to use as many resources as possible to answer very specific problems.

And

you're making sure the necessary network resources go to the right place at the right time.

Exactly.

All of these, at the heart of it, setting aside the technology, is ways of ensuring that you're diverting or allocating the right amount of resources to a given use case so that the

first responder or the doctor or the mobile network that's enabling this clinical health at scale, no matter where you happen to be in America, is available for them to be able to do that thing.

I read this study recently, a couple weeks ago.

Maybe no less than it.

Some of you may have seen it.

It was some study

talking about an AI diagnostic tool for doctors.

Did you guys see this?

And it's like

arm number one was a doctor all by himself does a diagnosis, and they're like 72% right.

Arm number two is

doctor plus AI, and it was 77.

Arm number three was AI alone, and it was 92.

And the conclusion of the study was we gave doctors these tools, and most of the time they didn't want to use them.

So I'm curious about that problem in your worlds.

When do you get pushback?

Are you sure that you've given a marvelous suite of tools to people out

in these fields?

Do they use them?

Is there a roadblock there?

And if so, what do you think?

I can comment on that.

So I know that study very well because there are some of my colleagues who did that work.

Oh, really?

Yeah.

So

here's, in terms of pushback, definitely, and I think in healthcare, one of the things that we get pushback around is around data, privacy, security.

That is huge, particularly for

information technology departments.

But what we have done, because we know that there is going to be some, this is disruptive technology, and we have to be able to better socialize it, we have led an entire year of what we call innovation retreats at the University of Miami so that we can give it to them in bite-sized format format so that they understand that it's not just focused on the technology, but how is it that we can actually help to solve what they're doing.

And so when we broaden it.

But it's they that you're talking about, clinicians?

Clinicians, and not just clinicians, because I think when you're talking about healthcare, let me just kind of deconstruct.

Behind that provider, you have administrative staff, billing, you know, scheduling, all of those people who are critical to ensure the operations.

And particularly some of those operations are very mundane and very time-consuming and it collects a lot of data.

And therefore, as a result, it can lead to a tremendous amount of error.

So what we're trying to do and what we did was to lead this digital innovation transformation set of retreats, focusing on the problem, trying to understand what their pain points are, and then have the technology come second or have the technology come last.

Give me an example of what someone's pain point might be.

What's an objection you would get?

Yeah, so for example,

digital literacy.

Some providers

unfortunately are stuck in their ways.

They believe that they want to feel and touch the patient as they should.

And we're not saying what we're proposing is we're not saying that they shouldn't do that.

But I think some of them have a form of technophobia as well.

And And by digital literacy, I'm talking, you know, they may feel as if they don't know or they may not be as facile in working some of the technology.

So we really pair it down, you know, for them.

And I think that's some of the technology.

I think some pushback as well.

I think many people, especially in the community that we serve, many people believe, and it's an important issue, that access is a huge issue for their patients.

So they may say, well, my patient doesn't have a cell phone.

And I'm like, we push back and said, actually, the Pew says 92%

of the US population, particularly low-income folks, actually have a smartphone or some form of mobile device.

Now, it's a different thing.

when we're talking about do they know how to use it?

Do they know how to optimally use it as well?

And this is what we do as well.

We provide training to patients as well as to how to use it as well.

So those are some of the unique pushbacks.

And then obviously data.

Where do my data go?

And providers ask those questions as well.

And I think this is is why having very robust, secure environments is important.

And so similar to what we do, especially with the mailbox, we have about seven or so devices that they were not built to communicate with each other.

So, you know, the API is another thing, and we call it handshakes, you know.

And what we try to do is we said we wanted to create a remote health monitoring solution that's like the Walmart version.

Because typically when you look at remote health monitoring solutions, they're very expensive and quite proprietary.

We want providers and we want providers and patients to be empowered that you can bring your own device, whatever device you have, as long as it actually has the necessary API connectivity, then we'll be able to collect those data.

So those are some of the pushbacks that we have experienced.

Ryan, do you,

surely this must be, I mean, you're entering a field that has been

fighting virus in the same way for a very, very long time.

Yeah.

Hate the way things are, but hate change probably even more.

That's their saying, not mine, I promise.

The first place that it started was absolutely social media.

The biggest fear in the fire service about even bringing a phone into the mix, or let's call it a smart device, is the propensity to share this information publicly.

But the reality was, I reminded them when you go to a supermarket, you know, the kids that are ringing up your groceries, that's a Windows computer, but they're not cruising around on social media.

We can configure the device to only do the thing you want it to do.

So we can take advantage of the capability.

So that was the first obstacle.

And now that we deal with AI, the big one is hallucination and inaccuracy, naturally.

Well, great, I like this idea, but what happens if it's wrong?

And I think to quote

a chief that I work with at the Philadelphia Fire Department, he actually wrote his thesis on leveraging AI in the Philadelphia Fire Department and beyond.

And his argument was decision support, not to make the decisions for you, not to ask it and you shall receive and just do what it says.

Have it go retrieve the things that you need, right?

And so this concept of augmented retrieval, giving it domain-specific knowledge.

Here is something about what you're dealing with.

Let me go find the best information and present it to you so that you can decide from there.

I think those bits are the essential.

And then lastly, absolutely for all of us, is security.

So the nice part is Microsoft and some of these groups have made sort of enterprise contained AIs.

So we're not dispersing this throughout some central knowledge.

This is specific to the fire department, which in our perspective helps accuracy to go actually up.

But when you go out on a, someone from 3 a.m.

goes out on a sales call, you go and visit a fire department somewhere, and you say,

we have this whole set of ideas to solve some problems for you.

You have your conversation with the chief who you've never talked to before.

What does the chief say?

The chief is immediately, any single time it has to do with safety of their firefighters, they're obviously compelled to listen.

The hard part, I think, really is how much change is this going to bring to my organization?

In other words, how much friction is me implementing this technology going to bring?

And so one of my proudest moments, which sounds super innocuous, we did the 4th of July, and it was hundreds of people, and they all forgot they had the device.

And I was super happy, right?

Because it became invisible.

And if we can do that,

you know, the obstacles are sort of overcome, right?

So the idea of automation and streamlining all of this contextually, just put the smart thing in your pocket, don't worry about anything else, that's our fundamental goal.

And that's the way that we overcome those objections.

All these innovations have multiple constituencies.

Right.

Right.

And

Mo, I wonder if you can sort of opine on this.

This must be a kind of perennial issue for

anyone who's like T-Mobile, who is driving innovation, is to ask yourself, who's the customer here?

Do you have these,

do you face this kind of tension between

who, is it important to clarify who we're serving with this innovation before you go down the road towards pushing the innovation?

It really goes back to,

if you will, selling through curiosity.

Meaning, when you're sitting down with the customer, you're trying to understand what it is that they're trying to accomplish.

And is it for their employees?

Is it business to business to consumer?

So is it to their end consumer that they're trying to solve the problem?

And then designing the solution to meet that need.

Going back to your AI study example just a few minutes ago,

this is what I love about what we're here today to celebrate is unconventional thinking, which inherently is

what is to the left of me here today with Dr.

Azizi and Ryan is individuals that looked at the industries in which they were working and thought, there's a better way.

I don't care how our industry has done it before, and can I build something that drives that outcome?

I mean, with Dr.

Azizi,

clinical studies invariably have been at some central location.

And what that means is that

marginalized groups, underserved groups, were being underserved.

And so the problem statement was, hey, can we bring together low-cost medical devices, stitch them together with a connectivity solution, which then in real time will send that information back?

One, so that we can learn more on how to better serve these groups, but in the case of

the cardiac patient that you were talking about a little bit ago,

also save lives.

So that's the heart of it for me is I love, love, love visiting with businesses that are thinking unconventionally, innovatively, and then how can we build something with them to drive the outcome, which may be the business or in this case is the end person that's part of the clinical trial.

Yeah.

Two last questions.

We're sadly running out of time, but two last questions are both of you.

I'm curious about how you measure success.

So you've, Ryan, you've given this marvelous tool to people in very high stress situations and intuitively we would say

you've made

the job

of fighting the fire better, easier.

But

how do you know that's true, A?

And how do you know how much you've improved?

I mean, do you actively go out and collect

data or feedback or something from the field to understand

the magnitude of the impact you're having?

That's a great question.

And I get really fired up because competitors or people in the space throw vanity metrics around.

And they try to tell first responders this is how much time and how many lives they're going to save.

And that's a ridiculous concept.

It's all relative, right?

So to your question, you know, for example, I was at a major event.

It was actually a marathon.

So there are a lot of medical issues.

People that go into cardiac arrest and overexhaustion, and there were code blues, which means this person is critical.

If we don't get them to hospital immediately, they will likely die.

And immediately they go, the tool.

And to your question, is you brought up earlier about screens and distraction.

We are infinitely obsessed with that.

The reason why I think automation and AI is interesting is because it can be in the background and there when you need it.

That's how we view it.

So wait, is this instance?

The tool is putting the code blues at the top.

Well, so they're putting it up.

Code blue gets called in.

They immediately look at their people on the map.

And typically, they would have emergency resources that are assigned to specific areas for an event and you would just say okay send you know ISP2 that's where they're gonna go but instead they're all the way three blocks down and now that you've made that assignment it's gonna take them three blocks to get to the patient by the time you get there oxygen's been denied from the brain for too long and we've lost the patient right so instead they say no no no ISP3 you turn around I literally watch them and they coach them back and that incident commander looked to me and goes your tool has been instrumental today so those are those moments moments where we saved a life.

The precision with which

you can allocate resources to the problem is greater here.

Right.

Yeah.

So in those moments, those are those things that sort of matter, right?

And to your question though, on how do we

sort of bring it back to people to show them the impact it's driving.

Again, I think usage creates value.

The more you use it, the more it's valuable to you.

Why?

Because we actually document all data for all events forever.

And then what you can do is you can scrub through it and go back in time from years ago and say, what happened at exactly the three-minute mark on this particular event?

You can pause it almost like the matrix and spin it around and look at it, look at all the information that was presented.

And that becomes mission critical for evolving your best practices,

things of that nature.

It becomes a learning tool then.

Yes.

In addition to its real-time importance, it has a kind of retrospective importance that you you can leverage that data to kind of figure out how to do a better job.

And the big piece that I think will triage into Aziz is that our greatest goal here is a safe first responder, you know, is a safe society, is our safe communities.

If we keep them safe, the rest of us are in a much better position.

The sad part is the average life expectancy of a firefighter is 61 years of age.

Cardiac arrest being a big driver, cancer is really crawling up there, though.

And we have a lot of other terminal diseases that come later in life, right?

So our goal is over time throughout your career, because we capture all of this data and because we could cross-reference with medical professionals exactly as Azizi's talking about, hey, you spent 1,000 hours in that facility that has now been discovered to contain carcinogens.

Now the medical practitioner can do things on a preventative care standpoint so that we can get ahead of that and make sure that firefighters live a long and healthy life, you know?

So to me, that is that ultimate goal.

Azizi, I'm almost more interested in you responding to what Mo was saying about decentralization and why that's, I think that's actually a lovely place to

end this conversation.

Because it does strike me, as I've listened to both of you, that

there is something, there is a real revolution here

in the way data is being collected and used and how we're learning from it.

But the decentralization piece

has a kind of social and

almost political importance, right?

It's like it's something higher.

So talk a little bit, this is what you've managed to do.

You've now decentralized the collection of medical information from people and the conduct of studies.

What does that mean for fairness in society, for the quality of the data we're collecting, for the way people perceive the medical care system?

It's a big deal.

It's huge.

That's a great question.

Thanks for asking.

We believe that most of healthcare occurs outside of the brick and mortar healthcare.

And what would oftentimes happen is that we would get these findings that are artifacts.

So for example, if you go to, you know, you're providing your blood pressure is high,

are you considered hypertensive or is it just artifactual, right?

Because of the fact that, you know, people are stressful and the like.

What we know we're doing is that we are actually connecting the dots in between visits.

What we call real world data.

We want to study the human being in the wild, not in some kind of artificial setting.

And that allows us to be more fair, but it also allows us to be far-reaching as well.

Why?

One of the things that I hadn't shared, and I'll share this now, is that at the end of this, we're going to be creating digital twins of each person.

What does that mean?

We can know exactly what someone's biological algorithm is based on sensing data as well as blood work that we're collecting.

What does this mean?

It means that we can anticipate what comes next or even before it happens.

But from a fairness standpoint, this allows us to really get into all crevices, all the areas, all underserved communities that were left by the wayside.

So for us, metrics of success, I've never led a study where the recruitment has been so great.

And

this is why, you know, one of the biggest journals, Science, learned about what we were doing and wanted us to document that.

Because typically, when people innovate, they innovate for the haves and the have-mores.

We fundamentally believe that if we innovate for the have-nots, that it will allow us to scale much better and it will have far more reach and more applicability.

So, from an ethics and an equitable standpoint, so that's why we dubbed what we call health technique, right?

We've been talking about this with the American Art Association.

It's a real deal, though,

that we believe that at the intersection, at the nexus of equity and technology, that we could exacerbate healthcare issues or it could be cured, we could mend it.

And we are saying that we want to be the ones.

And so for us, here's what we're doing already.

We're screening people for Alzheimer's disease much earlier using augmented reality, where we can determine if someone is going to get Alzheimer's disease six to ten years before age age of onset.

We're providing virtual reality solutions to

black and brown moms who have notoriously been known to have a huge epidemic in maternal mental health and maternal health.

We're providing that to a slew of folks.

We're reaching out and providing it to over 3,000 kids in the state of Florida because 68% of families don't live near a licensed mental health practitioner.

And we're also building the next generation of technologists and healthcare providers so that we know can have a provider who can listen.

Because typically when you go to your provider, what are they doing?

They're writing notes and there's no eye contact.

Now we can use AI and ambient technology to capture all of those data so that your provider can be with you more in a more

human way.

And that's what it will allow us to do.

So that's how we measure metrics of success.

And I think that's where the ethics lies as well.

Restoring the humanity in medicine.

Oftentimes, people think that when you use technology, that it actually effaces the human.

What we're trying to do is that we believe that technology can allow us to make healthcare more human again.

Restoring the soul and reclaiming the soul of healthcare through technology.

That's our thesis.

Yeah.

That's really beautiful.

Thanks.

I will say, just on one last note,

the whole time you guys were talking, I was having these kinds of absurd

fantasies about how I, I am a parent of two girls, how I could use both of your technologies to helicopter parent my

I'd give them a wearable that would monitor everything.

I'd be listening to all their conversations, and I'd just walk around with Ryan with

one of your

tablets, and they would just like highlight if there's ever any kind of problem.

But

this has been absolutely fascinating.

I feel we could have gone on and on and on for another hour, but I think what you've done is just given us a little glimpse into how human ingenuity is using technology in utterly unexpected ways.

And I think that's it's a that's it's a beautiful story that needs to be told and I'm glad we're telling it.

Thank you.

Thank you.

Thank you.

Thank you.

Thanks for listening to this special episode brought to you by T-Mobile for Business.

Special thanks to our guests, Mo Cadaba, T-Mobile for Business's Chief Marketing Officer, Ryan Litt,

Chief Operating Officer and Co-Founder 3AM Innovations, and Dr.

Azizi Seychis.

Chair of the Department of Informatics and Health Data Science at the University of Miami School of Medicine.

And special thanks to the entire production crew at iHeartMedia.

This episode was produced by Nina Bird Lawrence with Lucy Sullivan and Ben Nadaf Haffrey.

Editing by Karen Shikurji, mastering by Sarah Bruguer.

Special thanks to Lou Carloso for on-site recording.

Our executive producer is Jacob Smith.

I'm Malcolm Glabo.

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