October 29, 2024 • 52 mins
How is 5G powering the use of AI to revolutionize life-saving solutions? Malcolm sits with T-Mobile for Business CMO Mo Katibeh, 3AM Innovations COO Ryan Litt, and the University of Miami Miller School of Medicine's Dr. Azizi Seixas to find out in this special episode of Revisionist History. Brought to you in partnership with T-Mobile for Business, and recorded live from the Mobile World Congress in Las Vegas.
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Speaker 1 (00:15):
Pushkin. This episode is a paid partnership with T Mobile
for Business. Hello, Hello, Malcolm Glawel. Here today. I wanted
to share a very special conversation I had recently hosted
by my good friends at T Mobile for Business about
(00:37):
how AI is changing our world. My guests are oh Kataba,
the CMO of T Mobile for Business, doctor Azizi Satias,
chair of the Department of Informatics and Health Data Science
at the University of Lammy Miller School of Medicine, and
Ryan Litt, COO and co founder of three AM Innovations.
Speaker 2 (00:58):
MO.
Speaker 1 (00:59):
I know from years ago when we had a fascinating
conversation about five G when that technology was in its infancy.
Ryan is from Buffalo and we shared a deep affection
for the Buffalo Bills. And as Easy as will soon
be obvious is Jamaica, which of course is the surest
way to my heart. Anyway, we talked about some really
(01:19):
cool applications of AI and five G and the way
really smart people like Ryan and as Easy are using
these technologies to solve some pretty hard and fascinating problems.
(01:40):
Thank you. Hey everyone, we're all wearing our Should we
just put our I know this is a podcast. 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 se converse converse. Yeah,
very so we're all representing the brand I think very
effective to here. So we're here to talk about AI
(02:03):
and five G. But what we're really here to talk
about is something much simpler and more important than that,
is problem. So, right, 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.
Speaker 3 (02:26):
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 smoke, falling debris,
(02:52):
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.
Speaker 1 (03:03):
Yeah, wait, before we go on. Tell us a little bit,
but how how is it you landed in this particular world?
Why is it you're thinking about this problem of the
disorientation of the of the firefighter.
Speaker 3 (03:16):
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 firefighter, the fire itself moved faster, so they
(03:39):
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. And when was this go ahead?
Two thousand and nine. Yeah, And to make matters worse,
there was nobody inside. They were just unsure. And so
(04:02):
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 race. No slide against
the radio either, But all of us are here because
technology is flush in many other places and our belief
as they deserve to have it too.
Speaker 1 (04:18):
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.
Speaker 3 (04:30):
Yeah, So I mean that event was in two thousand
and nine. We officially started in twenty seventeen, 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,
(04:53):
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 twenty seventeen, technology seemed
(05:17):
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
(05:38):
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
(05:58):
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, 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.
Speaker 1 (06:15):
This is all super interesting, and I want to come
back in more detail after we've gone down the pen
a little bit. But one thing I wanted to talk
to you 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
(06:37):
there was no existing system in place that would allow
you to easily track that person. Correct. Yeah, And is
it because of the the Is it because the fire
had destroyed any kind of infrastructure that might make that possible,
or is it just I mean was why is what's
particularly hard about about tracking someone in a in the
(07:01):
middle of a burning building?
Speaker 3 (07:06):
Well, circumstantially, it wasn't necessarily the case that comms are
necessarily completely blown out. 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
(07:27):
a large structure like we're in now, in a small
structure in a suburban area, in remote areas and wild
land fires and such, right, And it has to work
on all of those places in order to work for
a firefighter, because the modern firefighter experiences so much right, so,
you know, chasing those problems fundamentally difficult, a lot of data,
a lot of error, right, and you know you push
(07:52):
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.
Speaker 1 (08:06):
Yeah, well, I want you to respond to Ryan. And
I'm curious whether did you when you when you when
you started on this road, did you imagine you'll be
having conversations with people like Ryan.
Speaker 2 (08:19):
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 TE Mobile for business perspective,
how can we take this incredible best in the nation
(08:41):
five G network and how can we harness some very
specific capabilities to bring to life a solution that serves
the first responder community? And you know, companies like Ryan's
three a M. And just a few weeks ago now
we launched what we call TE Priority, which brings not
(09:04):
just the network which has forty percent 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,
(09:25):
which is, hey, can we create the 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 bump if you will, a commercial user off
(09:46):
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
(10:07):
congestion can be a current, you know, like a trained
rail ment or a massive natural disaster, et cetera, that
we can essentially give up to one hundred percent of
the network over to the first responders so that they
can save lives.
Speaker 1 (10:22):
Yeah, I want to return to that, but I want
to talk a little bit too. As easy you are
tell us what you tell us your title of your job.
Speaker 4 (10:31):
So I currently serve as an interim chair for the
Department of informatics and health data science, and I'm the
phone and 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 from multiple jobs.
Speaker 1 (10:50):
And yes, this is at the University.
Speaker 4 (10:53):
Of It is at the University of Mine. But you're
a doctor by I'm PhD. I'm a clinical psychologist. But
I lead many off the efforts at the university to
lead digital transformation. And so I was recruited from an
another large institution when I was at NYU School of
Medicine to lead this effort at the University of Miami.
(11:17):
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
are not familiar, the global surth represents eighty percent of
(11:38):
the world's population, yet as a euphemism, they're oftentimes seen
as the poorest, less resource, 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
(12:01):
deprived communities throughout Florida and then use it as a
model to pre really do this in the global South.
Speaker 1 (12:09):
You at what point during your career did you realize
what you wanted to do is use technology to solve problems.
I mean, you have a PhD in clinical psychology. You're
not looking at AI and five G when you're doing
a PhD.
Speaker 4 (12:23):
Well, you know, so, great question. So when I realized
that technology was important was when I realized that many
of the most vexing health care challenges that we saw
in my own family, my grandmother who raised me, and
we realized that there was just significant lack of resources.
(12:45):
She had insurance, but what we saw was a significant
gap in the continuity of care. And extrapolate in her
experience to what I see when I go to barbershops,
beauty sulments, 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 on mortar
(13:07):
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,
(13:31):
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 provide us. And
so technology became the means by which it would allow
(13:52):
us to really extend our tentacles into places beyond that
we thought were unimaginable.
Speaker 1 (13:59):
It gives a specific example, yeah, of a moment where
you realized, oh, this is a NOTT we can only
crack with technology.
Speaker 4 (14:07):
Yes, So we created our own remote health monitor and
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
(14:29):
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 our study, and because of HIPPO compliance,
I can't say her name, but we'll call her Miss Jones.
Miss Jones is a sixty year old African American woman
lives in Brooklyn, and we call her Miss Jones. Such
(14:53):
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 monitor and solution, knowing very well
(15:14):
that it can be used for people. It's oftentimes said
that since twenty sixteen, you're about one hundred and forty
million emergency department visits and they are about sixty percent
of global deaths that can be attributed to non communicable
diseases like cardive metabolic health. And what are the biggest
drivers of that? No healthcare right and people don't have access.
(15:40):
So when we went to someone like Miss Jones and
what we've seen beer 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 said, no, nothing is wrong.
You're trying to evade pain your rent. And she's like, no,
(16:02):
there's something wrong with you. You need to change something.
And she was part of our study and we have
as part of our remote health monitoring solution and air
quality device and she was able to use that to
show to her landlord that there is something significantly wrong
in terms of mold. And so look at this. Many
of us live in environments that we just trust that
(16:25):
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.
(16:47):
That's just one Examplar is another example as well, and
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 print outs on our lab
work and we don't know what they mean.
Speaker 1 (17:02):
Let's be real and.
Speaker 4 (17:05):
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,
(17:25):
has three kids, so she was 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
(17:48):
to do by wearing one of our rings, she called
us angry. She said, doctor Sashas your device is waking
me up every ten 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. These lady
oxygen levels were dropping below eighty percent critical. So what
(18:10):
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 should have left her kids orphans. This is what
(18:31):
we've seen black and brown families all the time. It's
not just a healthcare issue. She had healthcare, but are
we able to connect the dots and we believe through
technology we can have a physical in ABox to do
with her.
Speaker 1 (18:43):
I want to come back to Riteah the same question.
Let's talk about the technology here. Yeah, you gave her
a ring. Yeah, like a describe this?
Speaker 4 (18:53):
Yeah, I mean yeah, 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
their circuitur system your heart. What ends up happening in
(19:14):
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
CARDI pullman Rey coupling, because your watch doesn't do that
(19:34):
because you 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.
Speaker 1 (19:44):
So this ring, is this an off the shelf thing
or something you.
Speaker 4 (19:48):
We're trying to get it off the shelf, but it's
more of a medical device. And there 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.
Speaker 1 (20:00):
So you wear this ring and then it's connected to what.
Speaker 4 (20:04):
It's connected to a cell phone that we provide, so
it's tether. So when you fall asleep, you hit start
and it starts to measure. It can measure if you're
at risk for sleep apnel. It can measure if you
have significant oxygen you know, desaturation lowering the levels and.
Speaker 1 (20:23):
That data is coming back.
Speaker 4 (20:25):
Yes, so that data comes back to the command center
that we are able to see.
Speaker 1 (20:30):
Which is at the University of Mind, which is.
Speaker 4 (20:32):
At Yes in our group at the University of Miami.
Speaker 1 (20:34):
And how many patients do you have on for example.
Speaker 4 (20:37):
Yes, So right now we're piloting this in our research studies.
So we have fifteen hundred 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
(20:57):
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 you know, supporting force. So we work with the
largest free clinic in the state of Florida.
Speaker 1 (21:17):
We'll be right back with more from the panel. We're
back with more Cattaba, Doctor as Easy, Satious and Ryan Lydd.
(21:38):
So walk us through how you use technology to answer
those questions.
Speaker 3 (21:43):
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 compliment, not complicate. Right, So if
there's something that's already available, if there are tools that
(22:05):
are already there, can we listen to those tools so
that it can feel, seemed like 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, five
G and software and these sorts of things start to
you know, form because it makes sense to do. We've
(22:27):
thought a lot about bioindicators, like doctors 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 is the stressor it's such a high
stress environment that we need the technology to get to
(22:51):
a point where it can actually give us that accuracy
when we need it and not tell us after the
cardiac rent 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.
(23:11):
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. I 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
(23:33):
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. Thankfully, everything was all clear, nobody got hurt.
We went back to the station and I asked him, hey, Chief,
(23:55):
have you taught yourself over the years to listen to
two conversations at the same time? And he's like nah,
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.
Speaker 1 (24:08):
Oh, and that's so fascinating.
Speaker 3 (24:10):
Yeah, And the thought process was coming home, driving back
to our headquarters in Buffalo is a bit of a drive.
I thought, computers don't have yours, Right, What about the
idea of opening up a phone and allowing the phone
to listen to as many conversations as maybe happening at
any given time, and maybe take tay a little further.
Instead of just listening for intensity, we can actually listen
(24:31):
to that conversation and interpret it. And that was literally
the dawn of us starting to use AI. And you know,
when we think about other tools, what other tools do
we have that can fundamentally bring that?
Speaker 1 (24:42):
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 things going on. And you're saying, we could
have AI listen to all of those conversations simultaneously and
(25:02):
do what exactly prioritize them, summarize them. How does the
AI interface with the human decision? Yeah?
Speaker 3 (25:10):
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
firefighters at risk of a loss of life, so mayda
(25:30):
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. In a we have a
software interface, of course, and the chief will see someone
(25:51):
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.
Speaker 1 (25:58):
So the chief's looking at his phone or is he.
Speaker 3 (26:00):
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.
Speaker 1 (26:07):
In real time. The tablet is ranking everybody and prioritizing
the person who is in most distress or under the
most stress.
Speaker 3 (26:14):
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 sensors, all the networks,
(26:35):
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.
Speaker 1 (26:48):
Then well, I'm listening to these two Ryan and as
Easy 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
(27:09):
a cheerleader? Are you an instigator? Are you? Are you
the person who helps them? There must obstacles. I mean,
you're changing the way people do business, and I'm curious
this team will play a role in kind of how
would you characterize what.
Speaker 2 (27:24):
You yes your partnership at the end of the day.
What we love to do is to visit with business
customers on 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
(27:46):
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 in three AM 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
(28:07):
trying to give the chief wherever's doing command and control
of that specific situation. How can we leverage both devices
where 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's that information coming back? Using the devices for things
(28:29):
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
(28:50):
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 three AM 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
(29:12):
to support everything that's happening there. It's the number one thing.
Speaker 1 (29:16):
What DOESPI mean by the way?
Speaker 3 (29:18):
Application programming interface?
Speaker 2 (29:20):
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.
Speaker 1 (29:43):
So you make that we have this complicated thing situation
happening and at various moments we want to use as
many resources as possible to answer very specific and problems,
and you're divert you're making sure the necessary network resources
go to the right place at the right time.
Speaker 2 (30:03):
Exactly all of these at at the heart of it's
setting aside, the technology is ways of suring 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 you know, this clinical
health that scale, no matter where you happen to be
(30:25):
in America is available for them to be able to
do that thing.
Speaker 1 (30:29):
I read this study recently, a couple weeks ago, maybe
no lesson it, so 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 the doctor all by himself does a diagnosis
and they're like seventy two percent, right. Arm number two
(30:50):
is doctor plus AI and it was seventy seven. Arm
number three was AI alone and it was ninety two.
And the conclusion 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
(31:10):
do you get pushed back? 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?
Speaker 4 (31:21):
I can comment on that. So I know that study
very well because there are some of my colleagues who
did that work really so so here here's in terms
of pushback, definitely, and I think what in healthcare one
of the things that we get pushed back around is
our own data privacy security. That is huge, particularly for
(31:41):
information technology departments. But what we have done, because we
know that 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
(32:03):
size 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.
Speaker 1 (32:13):
Broadishday that you're talking about clinicians.
Speaker 4 (32:16):
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
(32:40):
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 off retreats, focusing on the problem, trying to understand
what their pain points are, and then have the technology
(33:01):
come second, or have the technology come last.
Speaker 1 (33:04):
Give me an example of what someone's pain point might be.
What's what's an objection you?
Speaker 4 (33:09):
Yeah, So, for example, digital literacy, some provide us 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 we're not
saying that they shouldn't do that. But I think some
(33:30):
of them have a form of technophobia as well. And
by digital literacy, I'm talking you know, they may feel
as if they don't know or they may not be
as fascile in working some of the technology. So we
really peer it down, you know, for them, and I
think some of the technology I think some pushback as well.
I think many people, especially in the community that we serve,
(33:52):
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 ninety
two percent of the US population, particularly low income folks,
actually have a smartphone or some form of mobile device. No,
(34:14):
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 provide us ask those
questions as well. And I think this is why having
(34:35):
very robust secure environments is important time. So similar to
what we do, especially with the mailbox, we have about
seven or sold 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
(34:57):
Walmart version because typically when you look at remote health
monitoring solutions are very expensive and quite proprietory. We want
providers and we want provide us and patients to be
empowered that 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 to those data. So
(35:18):
those are some of the pushbacks that we've experienced.
Speaker 1 (35:20):
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.
Speaker 4 (35:30):
Yeah.
Speaker 3 (35:30):
Hate the way things are, but hate change probably even more.
That's they're saying, not mine. I brow. 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
(35:52):
know the kids that are bringing 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 wanted 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 right, well, great, I like this idea,
(36:14):
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
(36:35):
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 as security.
(36:56):
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 PERSPECTI it helps
accuracy to go actually up.
Speaker 1 (37:11):
But when you go out on someone from three am
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?
Speaker 3 (37:29):
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 fourth of July and it was hundreds
(37:50):
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
(38:13):
those objections.
Speaker 1 (38:14):
All these innovations have multiple constituencies, right right. I wonder
if you can sort of appine 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?
Speaker 2 (38:34):
Right?
Speaker 1 (38:34):
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.
Speaker 2 (38:47):
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 consumers or is it their end consumer that
they're trying to solve the problem and then designing the
(39:10):
solution to meet that meet that need. Going back to
your AI study example just a few minutes ago, like
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 you know,
doctor Azezy and Ryan is individuals that looked at the
(39:34):
industries in which they were working and thought there is
a better way. I don't care how our industry has
done it before, and can I build something that drives
that outcome?
Speaker 3 (39:45):
I mean with.
Speaker 2 (39:45):
Doctor as easy clinical studies invariably have been at a
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
(40:08):
to gather 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,
(40:28):
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.
Speaker 1 (40:48):
Two to ask questions. We're sadly running a time, but
two ask questions for both of you. I'm curious about
how you measure success. So you ran, you've given this
marvelous tool to people in very high stressed situations, and
intuitively we would say you've made you made their the
(41:11):
job of the of fighting the fire better easier. But
how do you know 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 that the magnitude
of the impact you're having.
Speaker 3 (41:31):
It'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
(41:51):
a major event. It was actually a marathon, so there
are a lot of medical issues people that go into
cardiac arrest and over exhaustion, and there were code blues,
which means this person is critical. If we don't get
to the hospital immediately, they will likely die. And immediately
they go the tool And to your question, is you
(42:11):
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.
Speaker 1 (42:22):
So what is instance the tool selling is putting the
code blues at the top.
Speaker 3 (42:26):
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, ISP two, that's where they're going to go.
But instead they're all the way three blocks down, and
now that you've made that assignment, it's going to take
them three blocks to get to the patient. By the
(42:48):
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, no, ISP three, you turn around.
I literally watched them and they coach them back and
that incident command to look to me goes. Your tool
has been instrumental today. So those are those moments where
we saved a life.
Speaker 1 (43:05):
Precision, the precision with which you can you can allocate
resources to the problem is greater here, right, yeah.
Speaker 3 (43:13):
So in those moments, those are those things that that
sort of matter, right And to your question though, on
how do we, you know, 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
(43:36):
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 pose 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, you know, things of that.
Speaker 1 (43:56):
Back it becomes a learning tool. Then. Yes, in addition
to real to its real time importance, it has a
kind of retrospective importance that you can leverage that data
to kind of figure out how to do a better job.
Speaker 3 (44:06):
The big piece that I think will triage into a
ZAS is that our greatest goal here is a safe
first responder. Is a safe society is or 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 sixty one years of age.
Cardiac arrest being a big driver. Cancer is really crawling
(44:28):
up there though, and we have all 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 a diseas he's talking about, Hey, you've
spent one thousand hours in that facility that has now
been discovered to contain carcinogens. Now the medical practitioner can
(44:49):
do things on a preventative care standpoint so that we
can get ahead of that and make sure that firefighters
live along in healthy life. So to me, that is
that ultimate goal.
Speaker 1 (44:59):
It's easy. I'm almost more interested in you responding to
what Moe was saying about decentralization and why that's I
think that's actually a lovely place to 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
(45:21):
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 high So talk a little bit.
This is what you've managed to do to You've now
(45:42):
decentralized the collection of medical information from people and the
conduct of studies. What does that mean for fairness and society,
for the quality of the data we're collecting, for the
way people perceive the medical care system. It's a big deal.
Speaker 4 (45:58):
It's huge. That's a great question, thanks for asking. We
believe that most of healthcare occurs outside of the brick
on more to healthcare, and what would often happen is
that we would get these findings that are artifacts. So
for example, if you go to you know, your provide
and your blood pressure is high, are you considered hypertensive
(46:21):
or is it just artifactual? Right because of the fact
that you know, people are stressful and the like. What
we're thinking, 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,
(46:42):
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 know 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
(47:05):
blood work that we are collecting. What does this mean.
It means that we can anticipate what comes next or
even before it happens. But from a fearness standpoint, this
allows us to really get into all crevices, all the areas,
all underserved communities that were left by the wayside. So
(47:25):
for us metrics or success, I've never led us study
where the recruitment has been so great. And this is
the this is why, you know, one of the biggest
journal science learned about what we were doing and wanted
us to document that because typically when people innovate, the
innovate for the haves and have mores. We fundamentally believe
that if we innovate for the have nots, that it
(47:48):
will allow us to scale much better and it will
have far more rich and more applicability. So from an
ethics and an equitable standpoint, so that's why we dubbed
what we call health tequity. 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
(48:09):
nexus of equity and technology, that we could exacerbate health
care issues or it could be cure. We could mend it,
and we're 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
(48:31):
Alzheimer's disease six to ten years before age of onset.
We're providing virtual reality solutions to black on brought black
on Brown moms who have notoriously been known to have
a huge epidemic in maternal mental health. At Maternal Health,
we're providing that to a slew of folks. We're reaching
out and providing it to over three thousand kids in
(48:52):
the state of Florida because sixty eight percent of families
don't live near a licensed mental health practitioner. And we're
also building the next generation of technologies and healthcare provide
us so that we know can have a provider, we
can listen because typically when you go to your provider,
what are they doing. They're writing notes and there's no
(49:13):
eye contact.
Speaker 1 (49:14):
No.
Speaker 4 (49:15):
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 human way, and that's
what it will allow us to do.
Speaker 1 (49:28):
So that's how we.
Speaker 4 (49:29):
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
(49:53):
of healthcare through technology.
Speaker 1 (49:55):
That's our thesis. Yeah, that's really beautiful.
Speaker 3 (49:58):
Thanks.
Speaker 1 (49:59):
I will say just one last note. The whole time
you guys were talking, I was having these kinds of
absurd fantasies about how I, as I am a parent
of two girls, how I could use both of your
technologies to uh helicopter parent. I give them a wearable,
(50:21):
they would monitor everything. I'd be listening to all their conversations.
And I just walk around with Ryan with one of
your with one of your tablets, and every they were
just like highlight if there's ever any kind of problem.
But this has been absolutely fascinating. I don't I feel
we could have gone on and on and on for
another hour. But I think what you've done is just
(50:43):
given us a little glimpse into how human ingenuity is
using technology in utterly unexpected ways. And I think that's
it's a it'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
(51:10):
this special episode brought to you by T Mobile for Business.
Special thanks to our guests Mokattaba, T Mobile for Businesses
Chief Marketing Officer, Ryan Litt, chief operating Officer and co
founder three A M Innovations, and doctor Azizi Satius, Chair
of the Department of Informatics and Health Data Science at
(51:30):
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
nadafh Haffrey. Editing by Karen Schakerji mastering by Sarah Buguer.
Special thanks to Lou Carloso for on site recording. Our
(51:51):
executive producer is Jacob Smith. I'm Malcolm Lappa eight
Pushkin. This episode is a paid partnership with T Mobile
for Business. Hello, Hello, Malcolm Glawel. Here today. I wanted
to share a very special conversation I had recently hosted
by my good friends at T Mobile for Business about
(00:37):
how AI is changing our world. My guests are oh Kataba,
the CMO of T Mobile for Business, doctor Azizi Satias,
chair of the Department of Informatics and Health Data Science
at the University of Lammy Miller School of Medicine, and
Ryan Litt, COO and co founder of three AM Innovations.
Speaker 2 (00:58):
MO.
Speaker 1 (00:59):
I know from years ago when we had a fascinating
conversation about five G when that technology was in its infancy.
Ryan is from Buffalo and we shared a deep affection
for the Buffalo Bills. And as Easy as will soon
be obvious is Jamaica, which of course is the surest
way to my heart. Anyway, we talked about some really
(01:19):
cool applications of AI and five G and the way
really smart people like Ryan and as Easy are using
these technologies to solve some pretty hard and fascinating problems.
(01:40):
Thank you. Hey everyone, we're all wearing our Should we
just put our I know this is a podcast. 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 se converse converse. Yeah,
very so we're all representing the brand I think very
effective to here. So we're here to talk about AI
(02:03):
and five G. But what we're really here to talk
about is something much simpler and more important than that,
is problem. So, right, 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.
Speaker 3 (02:26):
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 smoke, falling debris,
(02:52):
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.
Speaker 1 (03:03):
Yeah, wait, before we go on. Tell us a little bit,
but how how is it you landed in this particular world?
Why is it you're thinking about this problem of the
disorientation of the of the firefighter.
Speaker 3 (03:16):
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 firefighter, the fire itself moved faster, so they
(03:39):
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. And when was this go ahead?
Two thousand and nine. Yeah, And to make matters worse,
there was nobody inside. They were just unsure. And so
(04:02):
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 race. No slide against
the radio either, But all of us are here because
technology is flush in many other places and our belief
as they deserve to have it too.
Speaker 1 (04:18):
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.
Speaker 3 (04:30):
Yeah, So I mean that event was in two thousand
and nine. We officially started in twenty seventeen, 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,
(04:53):
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 twenty seventeen, technology seemed
(05:17):
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
(05:38):
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
(05:58):
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, 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.
Speaker 1 (06:15):
This is all super interesting, and I want to come
back in more detail after we've gone down the pen
a little bit. But one thing I wanted to talk
to you 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
(06:37):
there was no existing system in place that would allow
you to easily track that person. Correct. Yeah, And is
it because of the the Is it because the fire
had destroyed any kind of infrastructure that might make that possible,
or is it just I mean was why is what's
particularly hard about about tracking someone in a in the
(07:01):
middle of a burning building?
Speaker 3 (07:06):
Well, circumstantially, it wasn't necessarily the case that comms are
necessarily completely blown out. 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
(07:27):
a large structure like we're in now, in a small
structure in a suburban area, in remote areas and wild
land fires and such, right, And it has to work
on all of those places in order to work for
a firefighter, because the modern firefighter experiences so much right, so,
you know, chasing those problems fundamentally difficult, a lot of data,
a lot of error, right, and you know you push
(07:52):
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.
Speaker 1 (08:06):
Yeah, well, I want you to respond to Ryan. And
I'm curious whether did you when you when you when
you started on this road, did you imagine you'll be
having conversations with people like Ryan.
Speaker 2 (08:19):
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 TE Mobile for business perspective,
how can we take this incredible best in the nation
(08:41):
five G network and how can we harness some very
specific capabilities to bring to life a solution that serves
the first responder community? And you know, companies like Ryan's
three a M. And just a few weeks ago now
we launched what we call TE Priority, which brings not
(09:04):
just the network which has forty percent 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,
(09:25):
which is, hey, can we create the 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 bump if you will, a commercial user off
(09:46):
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
(10:07):
congestion can be a current, you know, like a trained
rail ment or a massive natural disaster, et cetera, that
we can essentially give up to one hundred percent of
the network over to the first responders so that they
can save lives.
Speaker 1 (10:22):
Yeah, I want to return to that, but I want
to talk a little bit too. As easy you are
tell us what you tell us your title of your job.
Speaker 4 (10:31):
So I currently serve as an interim chair for the
Department of informatics and health data science, and I'm the
phone and 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 from multiple jobs.
Speaker 1 (10:50):
And yes, this is at the University.
Speaker 4 (10:53):
Of It is at the University of Mine. But you're
a doctor by I'm PhD. I'm a clinical psychologist. But
I lead many off the efforts at the university to
lead digital transformation. And so I was recruited from an
another large institution when I was at NYU School of
Medicine to lead this effort at the University of Miami.
(11:17):
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
are not familiar, the global surth represents eighty percent of
(11:38):
the world's population, yet as a euphemism, they're oftentimes seen
as the poorest, less resource, 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
(12:01):
deprived communities throughout Florida and then use it as a
model to pre really do this in the global South.
Speaker 1 (12:09):
You at what point during your career did you realize
what you wanted to do is use technology to solve problems.
I mean, you have a PhD in clinical psychology. You're
not looking at AI and five G when you're doing
a PhD.
Speaker 4 (12:23):
Well, you know, so, great question. So when I realized
that technology was important was when I realized that many
of the most vexing health care challenges that we saw
in my own family, my grandmother who raised me, and
we realized that there was just significant lack of resources.
(12:45):
She had insurance, but what we saw was a significant
gap in the continuity of care. And extrapolate in her
experience to what I see when I go to barbershops,
beauty sulments, 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 on mortar
(13:07):
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,
(13:31):
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 provide us. And
so technology became the means by which it would allow
(13:52):
us to really extend our tentacles into places beyond that
we thought were unimaginable.
Speaker 1 (13:59):
It gives a specific example, yeah, of a moment where
you realized, oh, this is a NOTT we can only
crack with technology.
Speaker 4 (14:07):
Yes, So we created our own remote health monitor and
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
(14:29):
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 our study, and because of HIPPO compliance,
I can't say her name, but we'll call her Miss Jones.
Miss Jones is a sixty year old African American woman
lives in Brooklyn, and we call her Miss Jones. Such
(14:53):
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 monitor and solution, knowing very well
(15:14):
that it can be used for people. It's oftentimes said
that since twenty sixteen, you're about one hundred and forty
million emergency department visits and they are about sixty percent
of global deaths that can be attributed to non communicable
diseases like cardive metabolic health. And what are the biggest
drivers of that? No healthcare right and people don't have access.
(15:40):
So when we went to someone like Miss Jones and
what we've seen beer 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 said, no, nothing is wrong.
You're trying to evade pain your rent. And she's like, no,
(16:02):
there's something wrong with you. You need to change something.
And she was part of our study and we have
as part of our remote health monitoring solution and air
quality device and she was able to use that to
show to her landlord that there is something significantly wrong
in terms of mold. And so look at this. Many
of us live in environments that we just trust that
(16:25):
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.
(16:47):
That's just one Examplar is another example as well, and
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 print outs on our lab
work and we don't know what they mean.
Speaker 1 (17:02):
Let's be real and.
Speaker 4 (17:05):
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,
(17:25):
has three kids, so she was 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
(17:48):
to do by wearing one of our rings, she called
us angry. She said, doctor Sashas your device is waking
me up every ten 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. These lady
oxygen levels were dropping below eighty percent critical. So what
(18:10):
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 should have left her kids orphans. This is what
(18:31):
we've seen black and brown families all the time. It's
not just a healthcare issue. She had healthcare, but are
we able to connect the dots and we believe through
technology we can have a physical in ABox to do
with her.
Speaker 1 (18:43):
I want to come back to Riteah the same question.
Let's talk about the technology here. Yeah, you gave her
a ring. Yeah, like a describe this?
Speaker 4 (18:53):
Yeah, I mean yeah, 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
their circuitur system your heart. What ends up happening in
(19:14):
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
CARDI pullman Rey coupling, because your watch doesn't do that
(19:34):
because you 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.
Speaker 1 (19:44):
So this ring, is this an off the shelf thing
or something you.
Speaker 4 (19:48):
We're trying to get it off the shelf, but it's
more of a medical device. And there 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.
Speaker 1 (20:00):
So you wear this ring and then it's connected to what.
Speaker 4 (20:04):
It's connected to a cell phone that we provide, so
it's tether. So when you fall asleep, you hit start
and it starts to measure. It can measure if you're
at risk for sleep apnel. It can measure if you
have significant oxygen you know, desaturation lowering the levels and.
Speaker 1 (20:23):
That data is coming back.
Speaker 4 (20:25):
Yes, so that data comes back to the command center
that we are able to see.
Speaker 1 (20:30):
Which is at the University of Mind, which is.
Speaker 4 (20:32):
At Yes in our group at the University of Miami.
Speaker 1 (20:34):
And how many patients do you have on for example.
Speaker 4 (20:37):
Yes, So right now we're piloting this in our research studies.
So we have fifteen hundred 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
(20:57):
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 you know, supporting force. So we work with the
largest free clinic in the state of Florida.
Speaker 1 (21:17):
We'll be right back with more from the panel. We're
back with more Cattaba, Doctor as Easy, Satious and Ryan Lydd.
(21:38):
So walk us through how you use technology to answer
those questions.
Speaker 3 (21:43):
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 compliment, not complicate. Right, So if
there's something that's already available, if there are tools that
(22:05):
are already there, can we listen to those tools so
that it can feel, seemed like 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, five
G and software and these sorts of things start to
you know, form because it makes sense to do. We've
(22:27):
thought a lot about bioindicators, like doctors 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 is the stressor it's such a high
stress environment that we need the technology to get to
(22:51):
a point where it can actually give us that accuracy
when we need it and not tell us after the
cardiac rent 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.
(23:11):
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. I 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
(23:33):
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. Thankfully, everything was all clear, nobody got hurt.
We went back to the station and I asked him, hey, Chief,
(23:55):
have you taught yourself over the years to listen to
two conversations at the same time? And he's like nah,
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.
Speaker 1 (24:08):
Oh, and that's so fascinating.
Speaker 3 (24:10):
Yeah, And the thought process was coming home, driving back
to our headquarters in Buffalo is a bit of a drive.
I thought, computers don't have yours, Right, What about the
idea of opening up a phone and allowing the phone
to listen to as many conversations as maybe happening at
any given time, and maybe take tay a little further.
Instead of just listening for intensity, we can actually listen
(24:31):
to that conversation and interpret it. And that was literally
the dawn of us starting to use AI. And you know,
when we think about other tools, what other tools do
we have that can fundamentally bring that?
Speaker 1 (24:42):
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 things going on. And you're saying, we could
have AI listen to all of those conversations simultaneously and
(25:02):
do what exactly prioritize them, summarize them. How does the
AI interface with the human decision? Yeah?
Speaker 3 (25:10):
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
firefighters at risk of a loss of life, so mayda
(25:30):
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. In a we have a
software interface, of course, and the chief will see someone
(25:51):
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.
Speaker 1 (25:58):
So the chief's looking at his phone or is he.
Speaker 3 (26:00):
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.
Speaker 1 (26:07):
In real time. The tablet is ranking everybody and prioritizing
the person who is in most distress or under the
most stress.
Speaker 3 (26:14):
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 sensors, all the networks,
(26:35):
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.
Speaker 1 (26:48):
Then well, I'm listening to these two Ryan and as
Easy 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
(27:09):
a cheerleader? Are you an instigator? Are you? Are you
the person who helps them? There must obstacles. I mean,
you're changing the way people do business, and I'm curious
this team will play a role in kind of how
would you characterize what.
Speaker 2 (27:24):
You yes your partnership at the end of the day.
What we love to do is to visit with business
customers on 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
(27:46):
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 in three AM 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
(28:07):
trying to give the chief wherever's doing command and control
of that specific situation. How can we leverage both devices
where 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's that information coming back? Using the devices for things
(28:29):
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
(28:50):
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 three AM 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
(29:12):
to support everything that's happening there. It's the number one thing.
Speaker 1 (29:16):
What DOESPI mean by the way?
Speaker 3 (29:18):
Application programming interface?
Speaker 2 (29:20):
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.
Speaker 1 (29:43):
So you make that we have this complicated thing situation
happening and at various moments we want to use as
many resources as possible to answer very specific and problems,
and you're divert you're making sure the necessary network resources
go to the right place at the right time.
Speaker 2 (30:03):
Exactly all of these at at the heart of it's
setting aside, the technology is ways of suring 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 you know, this clinical
health that scale, no matter where you happen to be
(30:25):
in America is available for them to be able to
do that thing.
Speaker 1 (30:29):
I read this study recently, a couple weeks ago, maybe
no lesson it, so 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 the doctor all by himself does a diagnosis
and they're like seventy two percent, right. Arm number two
(30:50):
is doctor plus AI and it was seventy seven. Arm
number three was AI alone and it was ninety two.
And the conclusion 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
(31:10):
do you get pushed back? 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?
Speaker 4 (31:21):
I can comment on that. So I know that study
very well because there are some of my colleagues who
did that work really so so here here's in terms
of pushback, definitely, and I think what in healthcare one
of the things that we get pushed back around is
our own data privacy security. That is huge, particularly for
(31:41):
information technology departments. But what we have done, because we
know that 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
(32:03):
size 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.
Speaker 1 (32:13):
Broadishday that you're talking about clinicians.
Speaker 4 (32:16):
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
(32:40):
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 off retreats, focusing on the problem, trying to understand
what their pain points are, and then have the technology
(33:01):
come second, or have the technology come last.
Speaker 1 (33:04):
Give me an example of what someone's pain point might be.
What's what's an objection you?
Speaker 4 (33:09):
Yeah, So, for example, digital literacy, some provide us 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 we're not
saying that they shouldn't do that. But I think some
(33:30):
of them have a form of technophobia as well. And
by digital literacy, I'm talking you know, they may feel
as if they don't know or they may not be
as fascile in working some of the technology. So we
really peer it down, you know, for them, and I
think some of the technology I think some pushback as well.
I think many people, especially in the community that we serve,
(33:52):
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 ninety
two percent of the US population, particularly low income folks,
actually have a smartphone or some form of mobile device. No,
(34:14):
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 provide us ask those
questions as well. And I think this is why having
(34:35):
very robust secure environments is important time. So similar to
what we do, especially with the mailbox, we have about
seven or sold 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
(34:57):
Walmart version because typically when you look at remote health
monitoring solutions are very expensive and quite proprietory. We want
providers and we want provide us and patients to be
empowered that 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 to those data. So
(35:18):
those are some of the pushbacks that we've experienced.
Speaker 1 (35:20):
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.
Speaker 4 (35:30):
Yeah.
Speaker 3 (35:30):
Hate the way things are, but hate change probably even more.
That's they're saying, not mine. I brow. 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
(35:52):
know the kids that are bringing 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 wanted 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 right, well, great, I like this idea,
(36:14):
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
(36:35):
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 as security.
(36:56):
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 PERSPECTI it helps
accuracy to go actually up.
Speaker 1 (37:11):
But when you go out on someone from three am
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?
Speaker 3 (37:29):
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 fourth of July and it was hundreds
(37:50):
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
(38:13):
those objections.
Speaker 1 (38:14):
All these innovations have multiple constituencies, right right. I wonder
if you can sort of appine 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?
Speaker 2 (38:34):
Right?
Speaker 1 (38:34):
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.
Speaker 2 (38:47):
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 consumers or is it their end consumer that
they're trying to solve the problem and then designing the
(39:10):
solution to meet that meet that need. Going back to
your AI study example just a few minutes ago, like
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 you know,
doctor Azezy and Ryan is individuals that looked at the
(39:34):
industries in which they were working and thought there is
a better way. I don't care how our industry has
done it before, and can I build something that drives
that outcome?
Speaker 3 (39:45):
I mean with.
Speaker 2 (39:45):
Doctor as easy clinical studies invariably have been at a
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
(40:08):
to gather 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,
(40:28):
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.
Speaker 1 (40:48):
Two to ask questions. We're sadly running a time, but
two ask questions for both of you. I'm curious about
how you measure success. So you ran, you've given this
marvelous tool to people in very high stressed situations, and
intuitively we would say you've made you made their the
(41:11):
job of the of fighting the fire better easier. But
how do you know 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 that the magnitude
of the impact you're having.
Speaker 3 (41:31):
It'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
(41:51):
a major event. It was actually a marathon, so there
are a lot of medical issues people that go into
cardiac arrest and over exhaustion, and there were code blues,
which means this person is critical. If we don't get
to the hospital immediately, they will likely die. And immediately
they go the tool And to your question, is you
(42:11):
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.
Speaker 1 (42:22):
So what is instance the tool selling is putting the
code blues at the top.
Speaker 3 (42:26):
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, ISP two, that's where they're going to go.
But instead they're all the way three blocks down, and
now that you've made that assignment, it's going to take
them three blocks to get to the patient. By the
(42:48):
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, no, ISP three, you turn around.
I literally watched them and they coach them back and
that incident command to look to me goes. Your tool
has been instrumental today. So those are those moments where
we saved a life.
Speaker 1 (43:05):
Precision, the precision with which you can you can allocate
resources to the problem is greater here, right, yeah.
Speaker 3 (43:13):
So in those moments, those are those things that that
sort of matter, right And to your question though, on
how do we, you know, 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
(43:36):
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 pose 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, you know, things of that.
Speaker 1 (43:56):
Back it becomes a learning tool. Then. Yes, in addition
to real to its real time importance, it has a
kind of retrospective importance that you can leverage that data
to kind of figure out how to do a better job.
Speaker 3 (44:06):
The big piece that I think will triage into a
ZAS is that our greatest goal here is a safe
first responder. Is a safe society is or 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 sixty one years of age.
Cardiac arrest being a big driver. Cancer is really crawling
(44:28):
up there though, and we have all 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 a diseas he's talking about, Hey, you've
spent one thousand hours in that facility that has now
been discovered to contain carcinogens. Now the medical practitioner can
(44:49):
do things on a preventative care standpoint so that we
can get ahead of that and make sure that firefighters
live along in healthy life. So to me, that is
that ultimate goal.
Speaker 1 (44:59):
It's easy. I'm almost more interested in you responding to
what Moe was saying about decentralization and why that's I
think that's actually a lovely place to 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
(45:21):
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 high So talk a little bit.
This is what you've managed to do to You've now
(45:42):
decentralized the collection of medical information from people and the
conduct of studies. What does that mean for fairness and society,
for the quality of the data we're collecting, for the
way people perceive the medical care system. It's a big deal.
Speaker 4 (45:58):
It's huge. That's a great question, thanks for asking. We
believe that most of healthcare occurs outside of the brick
on more to healthcare, and what would often happen is
that we would get these findings that are artifacts. So
for example, if you go to you know, your provide
and your blood pressure is high, are you considered hypertensive
(46:21):
or is it just artifactual? Right because of the fact
that you know, people are stressful and the like. What
we're thinking, 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,
(46:42):
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 know 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
(47:05):
blood work that we are collecting. What does this mean.
It means that we can anticipate what comes next or
even before it happens. But from a fearness standpoint, this
allows us to really get into all crevices, all the areas,
all underserved communities that were left by the wayside. So
(47:25):
for us metrics or success, I've never led us study
where the recruitment has been so great. And this is
the this is why, you know, one of the biggest
journal science learned about what we were doing and wanted
us to document that because typically when people innovate, the
innovate for the haves and have mores. We fundamentally believe
that if we innovate for the have nots, that it
(47:48):
will allow us to scale much better and it will
have far more rich and more applicability. So from an
ethics and an equitable standpoint, so that's why we dubbed
what we call health tequity. 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
(48:09):
nexus of equity and technology, that we could exacerbate health
care issues or it could be cure. We could mend it,
and we're 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
(48:31):
Alzheimer's disease six to ten years before age of onset.
We're providing virtual reality solutions to black on brought black
on Brown moms who have notoriously been known to have
a huge epidemic in maternal mental health. At Maternal Health,
we're providing that to a slew of folks. We're reaching
out and providing it to over three thousand kids in
(48:52):
the state of Florida because sixty eight percent of families
don't live near a licensed mental health practitioner. And we're
also building the next generation of technologies and healthcare provide
us so that we know can have a provider, we
can listen because typically when you go to your provider,
what are they doing. They're writing notes and there's no
(49:13):
eye contact.
Speaker 1 (49:14):
No.
Speaker 4 (49:15):
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 human way, and that's
what it will allow us to do.
Speaker 1 (49:28):
So that's how we.
Speaker 4 (49:29):
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
(49:53):
of healthcare through technology.
Speaker 1 (49:55):
That's our thesis. Yeah, that's really beautiful.
Speaker 3 (49:58):
Thanks.
Speaker 1 (49:59):
I will say just one last note. The whole time
you guys were talking, I was having these kinds of
absurd fantasies about how I, as I am a parent
of two girls, how I could use both of your
technologies to uh helicopter parent. I give them a wearable,
(50:21):
they would monitor everything. I'd be listening to all their conversations.
And I just walk around with Ryan with one of
your with one of your tablets, and every they were
just like highlight if there's ever any kind of problem.
But this has been absolutely fascinating. I don't I feel
we could have gone on and on and on for
another hour. But I think what you've done is just
(50:43):
given us a little glimpse into how human ingenuity is
using technology in utterly unexpected ways. And I think that's
it's a it'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
(51:10):
this special episode brought to you by T Mobile for Business.
Special thanks to our guests Mokattaba, T Mobile for Businesses
Chief Marketing Officer, Ryan Litt, chief operating Officer and co
founder three A M Innovations, and doctor Azizi Satius, Chair
of the Department of Informatics and Health Data Science at
(51:30):
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
nadafh Haffrey. Editing by Karen Schakerji mastering by Sarah Buguer.
Special thanks to Lou Carloso for on site recording. Our
(51:51):
executive producer is Jacob Smith. I'm Malcolm Lappa eight
Host
Malcolm Gladwell
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