May 28, 2025 • 42 mins
When you hear "artificial intelligence," what comes to mind? Fear of job loss? Sci-fi robots? Or the promise of innovation? In this episode, we explore how AI is already transforming public safety — from predictive policing to streamlined emergency response — and tackle the big questions about ethics, trust, and change management.
🎯 What We Cover:
- How AI is changing emergency response and 911 operations
- Overcoming resistance to change in high-stakes environments
- Microsoft's new AiRS (Advanced Incident Response System)
- Why connectivity is critical for AI systems to work in real-time
- Real client success stories from early AI adopters
- The truth about AI replacing humans vs. enhancing capabilities
- Freeing up officers to focus on what they love: investigation and critical thinking
🎙️ Expert Panel:
- Christopher Blake Carver - Director of Market Development, Hexagon Safety, Infrastructure & Geospatial (Former NENA 911 Association)
- Sai Narain - Director of Technology Strategy, State & Local Government, Public Safety & Justice, Microsoft
- Kevin Fernandes - Chief Revenue Officer, Dejero
- Ivy Cuervo (Host) - Director of Brand & Communications, Dejero
🚨 Critical for Public Safety:
At the heart of AI innovation is connectivity — ensuring AI-powered tools can respond in real-time during life-or-death situations. Discover how Dejero and Microsoft are partnering to close the information gap and push technology to the edge.
🔗 Useful Links:
Learn about Dejero's public safety solutions: https://www.dejero.com/industry/public-safety
Book a demo: https://www.dejero.com/contact-sales
Mark as Played
Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
(00:02):
Let's use AI to actually identify
what really great new things we can dowith the capability that AI brings us.
You know, examples include betterorganization of queues of calls
coming in to 911.Handling when a 911 center goes down,
what do we do for that first hour orso before we get our backup up,
especially if it's a disasterthat impacts our nearby 911 center
(00:26):
where our calls normally go?Well, now we live in a world
where an AI attendant can at least handlethat call in the meantime.
I see huge potential there.
Everything from like, you know,maybe first responder wellness, to,
you know, accountabilityas people are responding to incidents,
to bringing the right informationand surfacing up the right information
at the right time.
I see there's a lot more sensorsthat are going to go out there
(00:47):
in our world,as IoT devices are going to increase.
When that happens, guess what's critical?
Connectivity and synthesizingthat information to make that available.
When I say
artificial intelligence,what's the first thing that comes to mind?
(01:11):
Is it the excitement of opportunity?
The fear of job loss?
Or maybe a vision of sci-firobots taking over?
Whatever it is, AI have sparkeda conversation like no other.
There is a lot to unpack,especially when it comes to public safety,
a critical service,
but one that also has a reputationof being slow to embrace change.
(01:33):
Welcome to Critical Connections, a podcastthat features the stories of the people
and companies helping to keep ourcommunities connected, informed and safe.
Today, we're going to explorehow AI is already playing a role in public
safety, from predictive policy
models to streaming emergency response.
But it's also raising important questionsabout ethics, trust and transformation.
(01:58):
At the heart of all of this innovationis connectivity, something that ensures AI
powered tools can respond in real time,especially in life or death situations.
Lots to talk about today.
Joining me now is Christopher Blake Carver,the Director of Market Development
at Hexagon Safety,Infrastructure and Geospatial.
(02:19):
He also spent several years with NENA,the 911 Association.
Welcome, Chris.
Hello and thanks for having me here
It's great to, great to be a part of this exciting conversation.
Also joining me is Sai Narain.
He works at Microsoftas a Director of Technology Strategy.
A big part of his job is workingclosely with state and local governments,
(02:41):
helping them accelerate innovationthrough technology.
One of his specialties is PublicSafety and Justice.
I'm very excited to have you heretoday, Sai.
Thanks for having me, appreciate it.
And finally, my colleague at Dejero,
Kevin Fernandes, a familiar face to many.
He leads Dejero’s global sales teamas the Chief Revenue Officer.
(03:01):
Hi, Kevin.
Hey Ivy, and hey Sai and Chris.
Privileged to be here and listening in,
and working with you guys on this.
Okay, let's start with
this exercise right off the top.
You've all got
a variety of work and life experiencein tech and emergency response.
When you hear artificial intelligence,what comes
(03:22):
what comes to mind?
Yeah, sure.
So AI is an opportunitymore than anything.
It's a transformative opportunityto enhance how we do our jobs,
no matter whatyour role is in public safety.
Now, the reality is, is thatthat can be scary.
Nobody likes change.
I once had a doctor tell me on a plane,the only person in the entire world
(03:43):
that actually likeschange is a baby with a wet diaper.
And I think that's true.
It's especially truewhen it comes, you know, to public safety.
But what AI also is,is not everything changing,
you know,and the analogy that I spoke of with
our Dejero friendsbefore was, in the 1920s,
the American Fire Service switched overfrom having their fire trucks drawn
(04:05):
by horses to having to be motorizedand attached to, you know, at the time,
gasoline or even steam powered trucksto get where they were going.
Yes, that was unbelievably hard,especially
for firefighters that had come to lovethe horses that served them.
And the fire stationswere designed for these horses.
They had haylofts. We had a wholeecosystem built around that.
(04:28):
But it
changed. Didn't change overnight,took a period of time,
took a period of adjustment, and we ended upimproving public safety dramatically.
Response times were lowered,costs were lowered,
the whole entire operationwas made a little bit better,
but in most other ways,it was still the same.
It was still firefightersdragging hose going into firehouses.
(04:50):
It was still the response looked the same.
The dispatching looked the same.
Everything else looked the same.
So it's this unbelievable combinationof transformative,
yet same. And that, although maybesome might find it to be limiting,
is actually inspiring, because it meanswe can do some amazing, great things,
but the whole world doesn'thave to be different tomorrow.
(05:11):
And it allows us to feela little more comfortable
with moving forward and exploringsome of the possibilities inherent
in any technology evolution, including AI.
Really interesting.
Sai, I'm going to get you to jump in here.Obviously,
we see Microsoft Copilot as sort of,you know,
how it's moving forwardwith AI in its application.
But of course,there's lots more to to see
(05:34):
what will come out of that.
What comes to mindwhen you think about AI?
Yeah. I think AI is not new.
I think to Christopher's point, like it's–
There is a ton of opportunity.
I look at AI as an opportunity as well.
Over the years, we're all used toAI in different ways, shapes, or form.
We all have probably now, mobile devices.
We probably do our banking from it.
We probably pick our favorite restaurantto go eat.
(05:56):
We probably book our tickets from our mobilephones.
I mean, email spam filtering.
I mean, all this is AI in differentways, and shapes or form.
it's become a big hot conversation topicsince generative
AI has gained so much traction and newsthat this idea of AI generating content
has all of a sudden createdthis mass awareness of AI.
But AI is not new, and we are all using AIin some way, shape, or form.
(06:18):
And I think, what what's different here,
as we talk about publicsafety, is applying AI,
to be a meaningful and as youmentioned the word, "copilot," as an assist.
It's this idea of nowlooking at AI differently
and using the best of our abilitiesor natural intelligence, and combining
(06:39):
that with artificial intelligenceto be able to do our work better.
Right? And that's reallywhat we're talking about.
So AI for me is not new.
It's different.
And it's certainly, to Christopher's point,it's it's transformative
and it's change.
How about you yourself, Kevin,what are your thoughts on AI
and you know, it's applications?
(06:59):
Yeah, I think
working at Dejero, Ivy,for all these years and focusing on
customers or putting technologyin front of customers that aren't techies,
right?
And looking at and saying,how how can we offer value?
Whether it's connectivityor something else to that customer base?
When I look at AI along those lines,I look at it as
(07:23):
trying to describe it as somethingthat's very common to the average person,
which is it's just another search engine.And it's a different way to interact
with that search engine that offers
a whole bunch of unique opportunitiesthat I think will be disruptive.
But when people look at, and to Sai'spoint of AI in some form or another,
(07:44):
being around for for a long time,this is just an evolution of that.
I see it the exact same way.
I think it's an evolution that will beprobably a little bit more disruptive
because of how much
more capability it has.
But if you boil it down to kind of,at least in my mind, the simplest form,
it's a way of an assistantthat has that is a better search
(08:06):
engine than you have today.
And, at least for me, it sounds lessscary when you say it that way.
Yeah.
I mean,I think that all of you, in some ways,
you know,we're all referring to the promise of AI,
but also the transformationthat it is going to,
and it's already happening.
But I think, you know, change management
is certainly one of the challengesto how that will unfold.
(08:28):
You know, public safety agenciesoften operate in high stakes environments
where traditionand reliability are critical.
Chris, how do you approach then,
fostering trust in AI within that kind of environment?
So I think it's actuallya two part process.
I think half ofit is exactly what Kevin just said.
(08:49):
It's framing what you're doing in a waythat connects it
to something that we already do.
And Sai mentioned it as well.
You know, AI is already being used.
You know, we
we did a survey here at Hexagona couple of weeks ago on LinkedIn, and 85%
of the people said they were either usingor looking forward to using AI
and not not to not to kind of totease the folks that completed the survey,
(09:12):
but I got a chuckle out of it,
because the reality is that 100% ofthe people are already using AI.
You know, unless they live somewhere completely disconnected from the grid,
have never used a banking app,have never made an airline reservation,
have never gone to dinneror anything like that right?
So I think the better that we frame it inthe first place
as something that's an enhancementof something we're already doing.
(09:34):
I think that's part of the puzzle.
But there's another piece too. I hadthe opportunity, the unbelievable pleasure
of being an attendee at the National Emergency
Number Association's Standards and Best Practices
Conference and Critical IssuesForum last week in Clearwater, Florida.
And at that event, the CIF focusedfor two days on AI and public safety.
(09:54):
And it was one of those great eventswhere your mind is just blown constantly.
And one of the the constant themes
was, the blend of looking at itas something we already do,
but also taking a step backand not just using AI to repaint the room.
Let's use AI to actually identifywhat really great
(10:15):
new things we can do with the capabilitythat AI brings us.
You know, examples include betterorganization of queues of calls
coming in to 911. Handlingwhen a 911 center goes down,
what do we do for that first hour orso before we get our backup up?
Especially if it's a disasterthat impacts our nearby 911 center
(10:37):
where our calls normally go?Well, now we live in a world
where an AI attendant can at least handlethat call in the meantime.
Or, if my 911 centeronly has five dispatchers able
to answer calls, and I'm getting 100 callsbecause of the severity of a major event.
And when we connect the factthat it's leveraging something
(10:58):
we already do,plus the power of it to solve problems
that we can't currently solve,and just have to throw up our hands.
Well that to me, is where the really exciting
innovation comes,and we transform the conversation
about a transformative technology from,oh, how is this going to work?,
what are we going to do?,to what are the possibilities and power and potential
(11:20):
that can help make people's lives betterand our organizations more effective?
What are you hearing, Sai, about trust in AI?
You know, you work for a companythat is certainly bringing
an offering to the market.
What what are you hearing from your side?
You know, II kind of agree with Christopher's point.
Like, early communication and framingis such a key aspect of sort of
just change management with AI, right?
(11:41):
I also look at training and adoption,establishing
you know, a leadership perspectivewithin organizations as to how
AI is being used or, and needs to be usedor adopted within the organization,
and creating an iterative feedback loop.
You know, AI, just like any other technology,
you know, that you implementwithin an organization,
(12:02):
there's a lot of testing that, you know,is going to be part of that whole process.
And I think with AI, a lot more testing,
a lot more iterative, a lot more feedbackloops are required.
And so, you know, what I'm hearing isthere is a massive promise, right?
I think we need to go from the art of
possible to the art of the practical and,and sort of
(12:22):
put out scenarios, put out opportunitieswhere we can start now
as opposed to just keep thinkingabout what's possible in the future.
Because unless we start on that journeyand start making iterative steps towards
that journey,
we're not going to eventually get thereor, you know, again, North Star is north that
you just never get there eventually,but you kind of keep progressing, right?
(12:42):
So, for me, I think it's all aboutframing, communicating, being iterative
and setting clear expectationsas to what you want AI to do and not to do,
and where do you want it to play a role.
And and keeping that human elementin the middle of all this and making sure
that we're not diminishing the valueof natural intelligence and the human
in the middle of it, because at the endof the day, it's about how humans use AI.
(13:05):
It's not about how AI works with humans.
It's about how humans use AI.
That's just been a theme of AI conversationsfor public safety now for months
and maybe even years, is that it isnot a replacement for the human.
In fact, the human interaction isrequired to make AI reach its potential,
just like the reverse of that is true.
(13:26):
And when you start thinking abouthallucinations and biases and things like that,
that can enter an AI model,it's more important than ever.
We just can't throw up our hands and say,oh AI is going to do it.
Then we're not going to be anywherebetter than we are today.
But Sai, to your point, if we leverage the human talent and
ingenuity and innovation and then support itwith a technology backbone
(13:49):
that ensures that it's available for us to use,like what we're talking about with Dejero,
then we can really reach someamazing heights.
Yeah, that's great.
I mean, what I was going to mention was,So AI is really a
there's there's the art of the possible,but nothing's possible
if it doesn't have any internetconnection.
Kevin, do you want to jump inwith your thoughts on that?
(14:11):
Yeah. It's obviously,
it's something of a focus area
that we pay a lot of attention to.
And really, from from our perspective,
and we don't know where the future's
going to lie in terms of distributed compute.
But Ivy, to your point, and to make all these systems work,
(14:31):
there has to be typically, the ability to have reliable connectivity
to connect to all that computein the Cloud that allows you to run those
AI modelsand get smarter and learn and train
all, all the different modelsand actors properly in the field.
So I'm not one to
to predict
(14:51):
how much of that's going to gointo the field with expensive high-end
compute boxes or lots of the high-endexpensive compute boxes versus
maybe a lower-end type of devicethat has more connectivity
and relies on kind of a central core
to do most of the computing.Regardless of which way it goes,
it's not going to be all the wayto the left or all the way to the right,
(15:14):
which means connectivity is goingto be key in making all this work.
So the way we look atit is without that that ability
to connect to that Edge,that Edge is kind of dead on,
it's dead on arrival, right?
There's there's nothing, it can actually do or function or update,
if it doesn't have the abilityto, to dial
(15:37):
home, stay connected and transfer.
Especially when we talk about the newer applications,
especially in fire and policing, it'sa lot of video-centric types uploading.
And when you talk about connectivity,you guys know that uploading video
is a pretty intensive effort,especially if you need it real-time.
(15:59):
So connectivity will,I think, will persist to be a challenge
and we're happy to do our partto, to try to minimize
the challengesas AI applications continue to adapt.
This is really interesting,because we're talking
sort of about the adoptionor the understanding
in the early days of AI.
Sai,
you're the Director of TechnologyStrategy at Microsoft,
(16:22):
where the flagship AI product is Microsoft365 Copilot.
You and I talked previously,and you had mentioned to me how Microsoft
employees themselves were gettingyou know, used to Copilot.
Can you take us through that momentand how you navigated it?
Like, what are some of the best practicesthat helped
with the understanding of whatthis actually means?
(16:45):
I think the number one best practice,I would say, is giving access
to the tools and technologies.
I think one thing Microsoft did reallywell is, is rolled out the tools to,
sort of that they had their rings or,or loops of users as they roll this out.
And I think one of the things they didbest was not wait for an over-
exhaustive training,not wait for an over-exhaustive,
(17:06):
setting up this massive,like, learning practice
before they put the tools out thereto the users.
Because, you know, a lot of timeswhen you give something to the users
and the users start playing with it,they look at it
from a very different perspective
than when they take a courseand use that same tool.
And I think that was somethingthat was fantastic.
Is that early adopters andputting the tools out in front of people.
(17:29):
Then came the training,
then came the adoption, then camethe communities of practice.
And now we've got everything from,gosh, iterative
feedback loops to office hoursto communities of practice.
We have– what do you call it likea champions group within the organization.
And so these are all critical waysin which, you know, users
(17:51):
within the organization, within Microsoft,for example, are able to,
you know, constantly iterateand evolve with their AI skills.
You know, it's funny, like I say thisall the time, I spent 18 years of my
schooling life and then followed that upwith four years of engineering
and then went to, you know,a couple of years of grad for engineering.
And I studied engineering throughoutto learn how AI works eventually,
(18:13):
and here I am in the last two yearslearning English
so I can prompt betterand I can talk to AI in a better way.
So it's almost like,the term engineering, obviously
prompt engineeringis a big aspect of all of this.
And so I feel like, AI hasdefinitely changed that conversation a lot.
Right?
So even a company as large as Microsoft,we're constantly looking at, hey,
(18:35):
what are the best prompts?
What are different ways
in which you can interact withAI to get the best out of it?
On a, you know, on a variety of places.
And it's changing as the modelsare evolving, as reasoning evolves,
as, you know, morecompanies are putting out more models,
as Microsoft is startingto pick up on a lot of this
and, and, you know, integratethat into their technology.
(18:56):
The framing is also changing.
So it's again, it's an iterative journey.
It's not a one and done model.
It's not like, here's a book, go read AI.
I mean, some technologies are like that.
Go, here's a book,go read this stuff and go use it.
AI is more of a conversation.
It's a little bit of a dance, right?
It takes two.
Yeah I mean, and I've also heard from peoplewho are engineers and are programmers
(19:19):
who are saying,"Hey, it's okay if AI takes over my job,
because then I get to do something elsethat helps to advance the company,
and it helps to advance new waysand new efficiencies."
It's not meant to sayor to have that fear.
Chris, you do a lot of public speaking,and you've
talked a lot about,sort of "Best Buy Syndrome."
(19:40):
Can you unpack that for us?
With apologies to all of the chiefsout there that I may have accused
of suffering from it,
"Best Buy Syndrome" is that is the thoughtthat if I just go buy
the newest, greatest, biggest,most amazing, awesomest
looking new technology,then all my problems will be solved
and everything is great.
And the way I describe that is it'ssort of like building three more floors
(20:02):
on top of a house with a bad foundation.Whether it's technology
or whether it's operations or whateverit is, our organizations
are first most essentiallymade up of humans.
And whether it's CAD,whether it's records,
whether it's a mobile product,whether it's AI, whether it's
a networking solutionthat allows us to guarantee connectivity,
(20:23):
or whether it's the Office 365 productthat we use for everything from,
you know, PowerPoints to, to,to writing reports.
All of those are only as goodas the folks that use them.
And and there is no– I have not seen yeta technology that can take
an organization that is sufferingand make it all of a sudden amazing.
But I have seen an organizationthat is suffering,
(20:46):
that has addressed its challenges, whetherthat's staffing or funding or community
engagement or internal leadershipand supervision and management,
then use technology to go frombeing maybe middle-of-the-road
to being an unbelievablyeffective group of professionals.
And that really is the journeythat I think,
you know, we as vendors need to understandthat we're supporting
(21:09):
and, you know,and it begs important conversations.
It begs a sales processthat isn't just show up
and you take an orderand then you walk out the door and,
you know, it begs a long-term relationshipwith your vendor
the same way you're going to have
to have to have a long-term relationshipwith AI and anything else
in this industry.None of it is is one and done.
(21:29):
So, you know, and I think it's interestingthat AI,
even though it's this newfangled, amazingpart– and Machine Learning the same way,
this new, amazing part of our ecosystem,it really falls back on the same
tried and true historical processes
that have guided change in organizationaldevelopment since minute one.
(21:50):
Yeah.
Can I comment on that, Christopher?
Like,I think you raised a really good point.
What's interesting is a lot of peopletreat this like just another tool, right?
AI is not just another tool.
You have to approach it as a strategy.
It is a strategythat you have to look at it.
What is your operational strategy,
from a public safetyand justice perspective? Like,
you know, businessstrategy, operations strategy.
(22:13):
Then there's a technology and
a data strategy that's associated with it.You know, how is your data set up?
How is the technology ecosystem set up?
Then you look at the user experience andhow does this interact with those users?
Then you lookat the organizational culture.
Where does it sit in the organizationthat you have today,
and how does that culture need to improveand evolve?
(22:35):
And all this is, you know, will only workif there's
some sort of a governance frameworkor structure within the organization.
So I think looking at AI ratherthan by the shiniest tool and implement it,
you have to look at it
as sort of building that foundationand a strategy within the organization.
The tools will continue to evolve,
but the strategy isis key to that organizational use,
(22:59):
right? So it's a great point.
Oh, I love that.
It absolutely is a strategy because it's
at the end of the day,you have to ask yourself,
as an organization,what is the best way to do this?
And when you're dealing with public safety
where you're now, you'retalking about dollars from taxpayers.
It's even dicier
because everybody's first to say,you know, is this really a priority?
(23:20):
So I think this isan interesting conversation,
that we're taking,that is taking us into a different area.
Kevin, I want you to jump in here becauseyou lead the global sales team with Dejero,
so you work with a variety of clientsand early adopters are rockstars
who are willing to take those risksand embrace technology.
(23:41):
Can you think of a couple of client success stories
that you want to share?
I think it ties really nicely into wherewe're going in this conversation.
Three different examples.
The first one is our internal use of it.
Where I firmly believewe have one of the best support
teams in in public safety.
(24:03):
And to Chris's point, it's not we're
we're not in a world where we sell a boxand and just leave.
We have to support them throughout whatever incidences or challenges
they have.
We're looking at AI to make sure that that support team
is well equippedwith all the latest information to be able to
on, you know, in real-time, bring up
articles and support, or installation
(24:25):
instructions, anything that we've doneand got a database on,
have it ready at the fingertipsso they don't have to go searching for it.
So they can thenfocus on the actual incident and helping
typically, you know, a personthat's calling in the middle of something
pretty, pretty challenging, having,
making sure that their equipment's workingand they're,
they've got the informationat their fingertips.
(24:46):
So internally, that's that's one of them.
Outside of public safety,the one I can think of is our broadcast
the media companies, our partnersthat are looking at closed captioning.
That's something that's kind of lowhanging fruit that, that they can go off
and do.And I see a lot of innovation there.
And then finally,on the public safety side,
I would say
(25:07):
it's moving a little bit slowerbecause of all the regulations
and the life-saving aspects of it.
But what really excites meis the, the folks out in, Central Pierce
County who decided to create a ubiquitous network
so all their applications can work acrossLMR, satellite, cellular
and helping them enablethat kind of groundwork foundation
(25:30):
that I'm really excited
to see how that then gets usedfor all the applications in the field.
That's really,really exciting to us.
And, and like I said,disruptive and transformative
as, as we've been talking about.
We end up siloed
oftentimes in public safety.We kind of do our thing
and then we don't for whatever reason,we don't engage and talk about it.
(25:51):
Events like that, that networkconstruction
are so profound to share
as best practices across the industryso that I mean, we can become a little
AI inspired ourselvesand become a learning model,
right? We can–
and that's just historically somethingthat public safety has always needed to do
(26:13):
just a little bit better.
There is nothing sadder than an agencyor a vendor, quite honestly,
repeating a mistake that their neighboralready learned not to do.
That wastes time,
it kills trust, and it just creates
an unnecessary level of stress and traumafor the public,
for the people were supposed to serve.
If I go outand do something that doesn't work, only
(26:34):
because I never botheredto ask my neighbor
how it did, you know,how it worked when they tried it.
So that sounds really excitingabout Central Pierce,
Kevin, that is the kind of stuffthat I think we're going to see.
I think there's going to beso many lessons learned from the
from this, this round of wildfiresin California, along that route.
Right?
And and someday soon,I think we're going to see
(26:55):
predictive analyticsaround anticipated disasters.
Unfortunately,we see more and more of them.
Sadly, all the time.
And we all know, especially those of uson this, on this webinar,
the impact of that on public safety,the impact of that on public
safety technology, and being able to planfor that and accommodate that and have,
you know, be ready to go with thingslike those types of networks.
(27:15):
Really powerful stuff.
I'm glad you shared that, Kevin.That's really cool.
I think I brought it up earlierin the conversation
that one of the fears that we hearfrom people often when AI is
part of the conversation, is,am I going to lose my job?
And as you all know,you know, people won't be replaced by AI,
but they will be replacedby someone who uses it.
Chris, can you take us through thata little bit more?
(27:38):
Yeah, sure.
The firefighters are still here.
Fire truck maybe no longer pulled,
hasn't been pulled by horsesfor a long, long time.
But we still need folksto do those jobs.
Now, what jobs did go away?
I assume everybody on here has never gottenin an elevator with an operator.
So there's some jobs,
you know, there's some things that maybe will.
I don't think we do
(27:59):
anybody any serviceby saying that everything
is going to be exactly the same forever.
I don't think that's realistic, whetheryou're talking about AI or anything else.
But to your point,if we know how to use the tool,
if we become valuable,whether we know how to use CAD
or we know how to use AI,or we know how to use a radio,
or we know how to use
Copilot or any of these other systemsthat we're talking about,
(28:19):
it makes us more valuable.
It makes us more essential,you know, to the operation.
So I would encourage anyone in publicsafety, you know, find the training.
There's so many free coursesavailable online.
There's so many classes you can go take.
And no one knows everything about this.
They really don't.
We are all learning as we goand being a part of that
(28:40):
and being engaged in that will help youestablish yourself in your organization
and in your future path to operate in an AI enhanced world.
So, you know, be the firefighter.
Don't be the horse.
You know?
I mean, that's that's reallywhat I would say in that case.
Sai or Kevin,what are some of the exciting examples
you've seen where AI has enhanced or,you know, we're starting
(29:04):
to see the potential of it enhancinghuman capability rather than replacing it?
Gosh, I mean everythingfrom transcription to
translation, like Kevin talkeda little bit about closed captioning.
I think, you know,we live in a global society.
They've got peoplewho are calling into the 911 system
with multiple languages as they speak.
And, you know, I see there's massivepotential for AI to play a great role
(29:29):
in like the ability to real-timetranscript and translate conversations.
Obviously, predictive
modeling is a huge area.
I also look at, you know, areas like,
you know, synthesizinglarge pieces of information.
So we went from this era of like,tons of data to information.
(29:50):
And then now I think we're at a pointwhere we now have a ton of information.
How do we go from informationto intelligence, right?
And I think AI has
got a massive potential as sort of likeintelligence synthesizing. Varying pieces
of information, creating correlations,figuring out pulses and signals from that.
Right?
I see huge potential there.
Everything from like,you know, maybe first responder wellness,
(30:12):
to you know, accountabilityas people are responding to incidents,
to bringing the right informationand surfacing up the right information
at the right time,
you know?
Listening to ten different radio channelsis not what we're built for as humans.
Although, you know, our first respondersdo a phenomenal job at,
and keeping pulse of everythingthat's coming at them.
(30:33):
I see there's a lot more sensorsthat are going to go out there.
In our world,as IoT devices are going to increase.
When that happens, guess what's critical?
Connectivity and synthesizingthat information to make that available.
So I see a lot of promisein those areas with AI.
I know companies are already working onthat.
And I see I'm going to I think we'regoing to see more and more organizations
(30:56):
starting to look at how AI playsa critical role in these areas.
Kevin,anything you want to add like to that?
No, I’m
by far the lightweight when it comes tobeing out in the field in public safety
compared to you, Sai, and Chris.
But I've yet to meet a chief, firefighter, or police officer that says,
finally, I get to write my reportof the day and and sit here and do that.
(31:19):
Right?
So, to your point, Sai, like,those are the
the easy things that enhance,
not only the well-being of the officer,but enhances the service
that's provided and, and have them focuson the things that only they can do.
Right?
And I mean, I joke aroundwe we have internal meetings now
(31:40):
let alone within public safetyand anything like that where there's
AI notetakers that,that are now competing.
They have multiple AI notetakerson a video call.
So all that stuff is, is highly usefuland even moreso
when it comes to being out in the fieldwhere lives are at stake
(32:00):
and, and people are challengedwith real-life
challenges thatthat involve public safety. So.
Yeah. I mean, I've stopped taking, like,look at this.
Like, hands are free.We're having a conversation.
This is interactive and engagingand we're actually focused on being human,
as opposed to looking down at a penin a paper and just constantly writing
(32:22):
when we're talking to other people.
I feel like that in itself.
Like I've been using Copilotfor the last couple of years.
I don't remember taking any notesin any meetings.
I do draw and other things.That doesn't change,
but that's part of change management.
I think it's made me more humanas I'm talking to people
because I'm able to look them in the eyeand have that conversation, you know.
Yeah.
Right.
Yeah, it definitely helps enhancesother skill sets and
(32:44):
yeah, notetaking again,
you you didn't get towhere you are at Microsoft
because you wrote good notes, right?
It's it's all the other featuresand all the other things that, that,
that come through thatallow you to do that. So.
Well before we say goodbye,
I wanted to just hear a bitfrom all of you:
You know, we talk about the promise of AIin public safety.
(33:06):
And I think, Chris,you've touched a little bit, in regards
to how we can break this downfrom automating and supporting processes
that humans shouldn't be doing anyways,especially when agencies like, you know,
are already facing crisis of staffing.
Talk to us a little bit about that,and then we'll jump over to Sai.
(33:27):
So, I mean, it's it's a world
of promise in terms of any new technologywhen it comes in.
But there's another example too thatI think is important,
almost as importantas the as the fire trucks and the horses.
And that was the idea of CAD itself.It's Computer Assisted Dispatching.
CAD was introduced in the late 1960sand has been gradually, slowly perfected,
(33:49):
I think, over the years as vendorslike my own have gotten, you know,
better and better at deploying solutions
that match the needsof their customers.
Yet ultimately, it's a balance.
It's a balance of what people needand what technology is able to provide,
and the willingness of people
to be engaged in the processto ensure that product works.
And that same model will serve us well,
(34:12):
in my opinion, in the evolutionand implementation
of AI, Machine Learning,and all these other solutions as well.
So my my closing messageto anybody on this
topic is (34:22):
we've done it before.
This is a skill set that we have.
This is an understanding we have.
It's maybe in a different way.
You know, I didn't even have a smartphone20 years ago.
Now, you know, you get anxiousif you don't have it, but that's okay.
And we can evolve and we can growand we can learn
and we can deploy these things.
(34:44):
And Sai said it earlier perfectly.
It's not perfect.
It's never going to be perfect.
And that's okay too.
So we've done it before. We can do it.
Let's be inspiredand hopeful about how we can use it.
And the last thing I'll say isno one does this alone.
Absolutely not.
Whether it's your partner agencies,whether it's your vendor,
(35:04):
if you're if you have vendorsthat you cannot get on the phone
when you have a challenge,
If I can't, you know, and I knowDejero is one that is this way,
that is effectively communicativewith your your customers because of the,
you know, it's just the nature of the company,the essential need of that technology.
Then that's a vendor
you should probably–If it's not that way,
(35:24):
that's probably a relationshipyou should look to
you know, reexaminebecause nobody wants to build the future
with somebody that they can't talk toand collaborate with and exchange ideas.
So there, that'd be my closing word.
Thanks!
Sai, Microsoft recentlylaunched the Advanced incident
Response System (AiRS). Chris, you mentionedno one does this alone.
(35:44):
Dejero is a partner in this project.
Can you help us understandwhat AiRS is a little bit more
and how Microsoftis pushing to the Edge? Sure.
I think over the years, we've always hada vehicle program within Microsoft.
It's got to be a tactical vehicle program.
It's evolvedover the last, I think, ten years or so.
In its latest iterationthis year, it's now being rebranded
(36:07):
as Advanced incident Response System.
The idea–I know Hexagon is a partner of that.
And Dejero is a critical componentof that with connectivity.
You know, it all boils down to pushing
compute and pushing a lot of intelligenceto the Edge.
The Edge meaningwhere the first responders are,
right?
Traditional comms is always relianton the dispatch center
(36:28):
or emergency operations center
or some sort of a centralized placewhere everything's coming from.
I think with as more data is becomingavailable, like we talked about earlier,
there is a need for more distributeddecision making.
And part of that distributed decisionmaking is that incident commander
or the individualwho is responding to that incident.
Up on the top of the vehicle, you'll seea plethora of communication choices.
(36:51):
If you look in here,you want to come take a look?
It no longer requires an 18 wheeler or a 36 wheeler.
It's not the size of the vehicle; it's the size of what capability exists within that vehicle.
Could be something as little as a little SUV or what have you, right?
So the AiRs program is intended to push a lot of the compute
(37:12):
and the capabilities to the Edge where first responders are
responding. And sure, there's a component of Edge AI in it as well.
The idea that, hey,
if there's absolutely no connectivity,can we do some basic things?
But connectivityis a critical component of that.
I know that's where Dejero playsa huge role and that partnership
with Dejero is aroundproviding that critical connectivity,
(37:33):
bringing all those layers of connectivityto the Edge where you're able
to run dispatch systemslike the products of Hexagon or others.
As well as intelligence, you know, integrating AI into
that is another layer that, you know,obviously, we're talking about now.
So, if anyone wants to check it out,it's
aka.ms/microsoftairs. That's the URL.
(37:56):
And I think, you know,there's a lot of promise.
We have a partnership now with Darley,which is a vehicle manufacturer,
vehicle outfitter, you know?And they're able to now
for any organization,any public safety entity
who wants to build out these vehicles,we're able to bring Darley
and Dejero and all our partners togetherand build those out.
(38:17):
So, our role is primarily in showingwhat's possible,
but it's also showing the art of the now,not just the art of the possible.
Right?
Really interesting.Kevin, I want you to join in.
Dejero is a partner with Microsofton closing this information gap.
And it's also important to knowthat connectivity is critical for AI
and we mentioned it today. Today.
(38:38):
In order for it to interoperate.
Kevin, diga little bit deeper on that for us.
Yeah
it's exactlywhat Chris and Sai have been saying.
I think there's no way that you look at
how much effort it takes
to get an application up and runningand make it seamless for the user.
There's no way one company does that.
(38:58):
And I think if one company triesto attack all problems at the same time,
they actually get nowhereand don't create that ecosystem
that Sai was mentioning.
So we're thrilled to be partneredwith Hexagon, partnered with Microsoft to
to contributeour small puzzle piece to the equation,
which is an important smallpuzzle piece of critical connectivity.
(39:19):
So by keeping people connected and lettingthe applications do their thing,
it puts the userin the best possible position.
And when we talk about connectivity, it's,
it's it's kind of interestingbecause it's it's not just a computer
talking to a Cloud andand running that. It's connectivity of
(39:39):
just what Sai mentioned– chief talking tohis people in the field
staying connected, staying safe,being able to anticipate what's happening
and using those applications,whether it's AI enabled, video enhanced,
whatever it is, to makethe right decisions at the right time.
So we're allbut I think, an interesting puzzle piece
(40:02):
to the whole scenario. But,
you won't definitely see the picture
if you don't bring in the Hexagons,the Microsofts,
and all the other applicationsto make it work.
Final
rapid fire response here for you all.
What one piece of advice or insightwould you give to public
safety professionals or organizationsconsidering adopting AI?
(40:23):
We're going to start with you, Sai.
Oh, get started now.
Don't wait for someone elseto tell you when to get started.
I mean, doesn't mean you go downloadyour favorite AI tool and start using it.
That's not what I mean.
What I mean is just get startedworking towards that strategy.
Whether you know, and pull people withinyour organization that are like-minded.
And if you don't find enough within yourorganization, find your neighbors,
(40:45):
collect a force of individuals and talkto, you know,
companies like oursto help you in that process.
Just get started now. I wouldthat's what I would say.
How about yourself, Christopher?
Find a tiger teaminside your organization.
Find three peopleand get together once in a while.
Go to lunch. Go to breakfast.
I don't care how you do it,
but just get a few different mindswrapped around this issue
(41:08):
and then slowly expandthat to involve your stakeholders
and agencies you serve,and your vendors,
and build out your approach toto not just AI,
but I think with the amountof technological advancement
we have in the industry right now,
I think that's the approach to do withall of it. It's no
no one person can do it alone.
No one vendor can do it alone.
And if we have at leasta few more people engaged in the process,
(41:31):
we dramatically increase
in my opinion,the likelihood that we'll be successful.
Kevin, you get the last word. Oh, geez.
I would say I would appealto the individual first in
the sense that if you step back at it,get curious about what it's
what AI's capabilities are.
Use it instead of Google or whatever
your chat or whateveryour search engine is, for you personally.
(41:51):
Play around with it, figure it out.
It becomes less scary to thenallow you to tackle the bigger integration
challenges of, okay, how do I deploy thisacross a public safety
scenario or, or station?That is maybe a little daunting to begin with
as an individual, so sort of build upthat that confidence and curiosity.
(42:11):
Well, thank you all.
Thank you.
Christopher,
Sai, and Kevin. As we've explored today,the promise of AI in public
safety is both profound and complex.
What role do you think AI should play inmaking our community safer?
We'd love to hear your thoughts.
Leave a comment underneath this videofor more about Dejero, Hexagon, or Microsoft.
Of course, we'll have a storythat will be along with this podcast.
(42:35):
And if you want any other information,head to dejero.com.
See you soon.
Let's use AI to actually identify
what really great new things we can dowith the capability that AI brings us.
You know, examples include betterorganization of queues of calls
coming in to 911.Handling when a 911 center goes down,
what do we do for that first hour orso before we get our backup up,
especially if it's a disasterthat impacts our nearby 911 center
(00:26):
where our calls normally go?Well, now we live in a world
where an AI attendant can at least handlethat call in the meantime.
I see huge potential there.
Everything from like, you know,maybe first responder wellness, to,
you know, accountabilityas people are responding to incidents,
to bringing the right informationand surfacing up the right information
at the right time.
I see there's a lot more sensorsthat are going to go out there
(00:47):
in our world,as IoT devices are going to increase.
When that happens, guess what's critical?
Connectivity and synthesizingthat information to make that available.
When I say
artificial intelligence,what's the first thing that comes to mind?
(01:11):
Is it the excitement of opportunity?
The fear of job loss?
Or maybe a vision of sci-firobots taking over?
Whatever it is, AI have sparkeda conversation like no other.
There is a lot to unpack,especially when it comes to public safety,
a critical service,
but one that also has a reputationof being slow to embrace change.
(01:33):
Welcome to Critical Connections, a podcastthat features the stories of the people
and companies helping to keep ourcommunities connected, informed and safe.
Today, we're going to explorehow AI is already playing a role in public
safety, from predictive policy
models to streaming emergency response.
But it's also raising important questionsabout ethics, trust and transformation.
(01:58):
At the heart of all of this innovationis connectivity, something that ensures AI
powered tools can respond in real time,especially in life or death situations.
Lots to talk about today.
Joining me now is Christopher Blake Carver,the Director of Market Development
at Hexagon Safety,Infrastructure and Geospatial.
(02:19):
He also spent several years with NENA,the 911 Association.
Welcome, Chris.
Hello and thanks for having me here
It's great to, great to be a part of this exciting conversation.
Also joining me is Sai Narain.
He works at Microsoftas a Director of Technology Strategy.
A big part of his job is workingclosely with state and local governments,
(02:41):
helping them accelerate innovationthrough technology.
One of his specialties is PublicSafety and Justice.
I'm very excited to have you heretoday, Sai.
Thanks for having me, appreciate it.
And finally, my colleague at Dejero,
Kevin Fernandes, a familiar face to many.
He leads Dejero’s global sales teamas the Chief Revenue Officer.
(03:01):
Hi, Kevin.
Hey Ivy, and hey Sai and Chris.
Privileged to be here and listening in,
and working with you guys on this.
Okay, let's start with
this exercise right off the top.
You've all got
a variety of work and life experiencein tech and emergency response.
When you hear artificial intelligence,what comes
(03:22):
what comes to mind?
Yeah, sure.
So AI is an opportunitymore than anything.
It's a transformative opportunityto enhance how we do our jobs,
no matter whatyour role is in public safety.
Now, the reality is, is thatthat can be scary.
Nobody likes change.
I once had a doctor tell me on a plane,the only person in the entire world
(03:43):
that actually likeschange is a baby with a wet diaper.
And I think that's true.
It's especially truewhen it comes, you know, to public safety.
But what AI also is,is not everything changing,
you know,and the analogy that I spoke of with
our Dejero friendsbefore was, in the 1920s,
the American Fire Service switched overfrom having their fire trucks drawn
(04:05):
by horses to having to be motorizedand attached to, you know, at the time,
gasoline or even steam powered trucksto get where they were going.
Yes, that was unbelievably hard,especially
for firefighters that had come to lovethe horses that served them.
And the fire stationswere designed for these horses.
They had haylofts. We had a wholeecosystem built around that.
(04:28):
But it
changed. Didn't change overnight,took a period of time,
took a period of adjustment, and we ended upimproving public safety dramatically.
Response times were lowered,costs were lowered,
the whole entire operationwas made a little bit better,
but in most other ways,it was still the same.
It was still firefightersdragging hose going into firehouses.
(04:50):
It was still the response looked the same.
The dispatching looked the same.
Everything else looked the same.
So it's this unbelievable combinationof transformative,
yet same. And that, although maybesome might find it to be limiting,
is actually inspiring, because it meanswe can do some amazing, great things,
but the whole world doesn'thave to be different tomorrow.
(05:11):
And it allows us to feela little more comfortable
with moving forward and exploringsome of the possibilities inherent
in any technology evolution, including AI.
Really interesting.
Sai, I'm going to get you to jump in here.Obviously,
we see Microsoft Copilot as sort of,you know,
how it's moving forwardwith AI in its application.
But of course,there's lots more to to see
(05:34):
what will come out of that.
What comes to mindwhen you think about AI?
Yeah. I think AI is not new.
I think to Christopher's point, like it's–
There is a ton of opportunity.
I look at AI as an opportunity as well.
Over the years, we're all used toAI in different ways, shapes, or form.
We all have probably now, mobile devices.
We probably do our banking from it.
We probably pick our favorite restaurantto go eat.
(05:56):
We probably book our tickets from our mobilephones.
I mean, email spam filtering.
I mean, all this is AI in differentways, and shapes or form.
it's become a big hot conversation topicsince generative
AI has gained so much traction and newsthat this idea of AI generating content
has all of a sudden createdthis mass awareness of AI.
But AI is not new, and we are all using AIin some way, shape, or form.
(06:18):
And I think, what what's different here,
as we talk about publicsafety, is applying AI,
to be a meaningful and as youmentioned the word, "copilot," as an assist.
It's this idea of nowlooking at AI differently
and using the best of our abilitiesor natural intelligence, and combining
(06:39):
that with artificial intelligenceto be able to do our work better.
Right? And that's reallywhat we're talking about.
So AI for me is not new.
It's different.
And it's certainly, to Christopher's point,it's it's transformative
and it's change.
How about you yourself, Kevin,what are your thoughts on AI
and you know, it's applications?
(06:59):
Yeah, I think
working at Dejero, Ivy,for all these years and focusing on
customers or putting technologyin front of customers that aren't techies,
right?
And looking at and saying,how how can we offer value?
Whether it's connectivityor something else to that customer base?
When I look at AI along those lines,I look at it as
(07:23):
trying to describe it as somethingthat's very common to the average person,
which is it's just another search engine.And it's a different way to interact
with that search engine that offers
a whole bunch of unique opportunitiesthat I think will be disruptive.
But when people look at, and to Sai'spoint of AI in some form or another,
(07:44):
being around for for a long time,this is just an evolution of that.
I see it the exact same way.
I think it's an evolution that will beprobably a little bit more disruptive
because of how much
more capability it has.
But if you boil it down to kind of,at least in my mind, the simplest form,
it's a way of an assistantthat has that is a better search
(08:06):
engine than you have today.
And, at least for me, it sounds lessscary when you say it that way.
Yeah.
I mean,I think that all of you, in some ways,
you know,we're all referring to the promise of AI,
but also the transformationthat it is going to,
and it's already happening.
But I think, you know, change management
is certainly one of the challengesto how that will unfold.
(08:28):
You know, public safety agenciesoften operate in high stakes environments
where traditionand reliability are critical.
Chris, how do you approach then,
fostering trust in AI within that kind of environment?
So I think it's actuallya two part process.
I think half ofit is exactly what Kevin just said.
(08:49):
It's framing what you're doing in a waythat connects it
to something that we already do.
And Sai mentioned it as well.
You know, AI is already being used.
You know, we
we did a survey here at Hexagona couple of weeks ago on LinkedIn, and 85%
of the people said they were either usingor looking forward to using AI
and not not to not to kind of totease the folks that completed the survey,
(09:12):
but I got a chuckle out of it,
because the reality is that 100% ofthe people are already using AI.
You know, unless they live somewhere completely disconnected from the grid,
have never used a banking app,have never made an airline reservation,
have never gone to dinneror anything like that right?
So I think the better that we frame it inthe first place
as something that's an enhancementof something we're already doing.
(09:34):
I think that's part of the puzzle.
But there's another piece too. I hadthe opportunity, the unbelievable pleasure
of being an attendee at the National Emergency
Number Association's Standards and Best Practices
Conference and Critical IssuesForum last week in Clearwater, Florida.
And at that event, the CIF focusedfor two days on AI and public safety.
(09:54):
And it was one of those great eventswhere your mind is just blown constantly.
And one of the the constant themes
was, the blend of looking at itas something we already do,
but also taking a step backand not just using AI to repaint the room.
Let's use AI to actually identifywhat really great
(10:15):
new things we can do with the capabilitythat AI brings us.
You know, examples include betterorganization of queues of calls
coming in to 911. Handlingwhen a 911 center goes down,
what do we do for that first hour orso before we get our backup up?
Especially if it's a disasterthat impacts our nearby 911 center
(10:37):
where our calls normally go?Well, now we live in a world
where an AI attendant can at least handlethat call in the meantime.
Or, if my 911 centeronly has five dispatchers able
to answer calls, and I'm getting 100 callsbecause of the severity of a major event.
And when we connect the factthat it's leveraging something
(10:58):
we already do,plus the power of it to solve problems
that we can't currently solve,and just have to throw up our hands.
Well that to me, is where the really exciting
innovation comes,and we transform the conversation
about a transformative technology from,oh, how is this going to work?,
what are we going to do?,to what are the possibilities and power and potential
(11:20):
that can help make people's lives betterand our organizations more effective?
What are you hearing, Sai, about trust in AI?
You know, you work for a companythat is certainly bringing
an offering to the market.
What what are you hearing from your side?
You know, II kind of agree with Christopher's point.
Like, early communication and framingis such a key aspect of sort of
just change management with AI, right?
(11:41):
I also look at training and adoption,establishing
you know, a leadership perspectivewithin organizations as to how
AI is being used or, and needs to be usedor adopted within the organization,
and creating an iterative feedback loop.
You know, AI, just like any other technology,
you know, that you implementwithin an organization,
(12:02):
there's a lot of testing that, you know,is going to be part of that whole process.
And I think with AI, a lot more testing,
a lot more iterative, a lot more feedbackloops are required.
And so, you know, what I'm hearing isthere is a massive promise, right?
I think we need to go from the art of
possible to the art of the practical and,and sort of
(12:22):
put out scenarios, put out opportunitieswhere we can start now
as opposed to just keep thinkingabout what's possible in the future.
Because unless we start on that journeyand start making iterative steps towards
that journey,
we're not going to eventually get thereor, you know, again, North Star is north that
you just never get there eventually,but you kind of keep progressing, right?
(12:42):
So, for me, I think it's all aboutframing, communicating, being iterative
and setting clear expectationsas to what you want AI to do and not to do,
and where do you want it to play a role.
And and keeping that human elementin the middle of all this and making sure
that we're not diminishing the valueof natural intelligence and the human
in the middle of it, because at the endof the day, it's about how humans use AI.
(13:05):
It's not about how AI works with humans.
It's about how humans use AI.
That's just been a theme of AI conversationsfor public safety now for months
and maybe even years, is that it isnot a replacement for the human.
In fact, the human interaction isrequired to make AI reach its potential,
just like the reverse of that is true.
(13:26):
And when you start thinking abouthallucinations and biases and things like that,
that can enter an AI model,it's more important than ever.
We just can't throw up our hands and say,oh AI is going to do it.
Then we're not going to be anywherebetter than we are today.
But Sai, to your point, if we leverage the human talent and
ingenuity and innovation and then support itwith a technology backbone
(13:49):
that ensures that it's available for us to use,like what we're talking about with Dejero,
then we can really reach someamazing heights.
Yeah, that's great.
I mean, what I was going to mention was,So AI is really a
there's there's the art of the possible,but nothing's possible
if it doesn't have any internetconnection.
Kevin, do you want to jump inwith your thoughts on that?
(14:11):
Yeah. It's obviously,
it's something of a focus area
that we pay a lot of attention to.
And really, from from our perspective,
and we don't know where the future's
going to lie in terms of distributed compute.
But Ivy, to your point, and to make all these systems work,
(14:31):
there has to be typically, the ability to have reliable connectivity
to connect to all that computein the Cloud that allows you to run those
AI modelsand get smarter and learn and train
all, all the different modelsand actors properly in the field.
So I'm not one to
to predict
(14:51):
how much of that's going to gointo the field with expensive high-end
compute boxes or lots of the high-endexpensive compute boxes versus
maybe a lower-end type of devicethat has more connectivity
and relies on kind of a central core
to do most of the computing.Regardless of which way it goes,
it's not going to be all the wayto the left or all the way to the right,
(15:14):
which means connectivity is goingto be key in making all this work.
So the way we look atit is without that that ability
to connect to that Edge,that Edge is kind of dead on,
it's dead on arrival, right?
There's there's nothing, it can actually do or function or update,
if it doesn't have the abilityto, to dial
(15:37):
home, stay connected and transfer.
Especially when we talk about the newer applications,
especially in fire and policing, it'sa lot of video-centric types uploading.
And when you talk about connectivity,you guys know that uploading video
is a pretty intensive effort,especially if you need it real-time.
(15:59):
So connectivity will,I think, will persist to be a challenge
and we're happy to do our partto, to try to minimize
the challengesas AI applications continue to adapt.
This is really interesting,because we're talking
sort of about the adoptionor the understanding
in the early days of AI.
Sai,
you're the Director of TechnologyStrategy at Microsoft,
(16:22):
where the flagship AI product is Microsoft365 Copilot.
You and I talked previously,and you had mentioned to me how Microsoft
employees themselves were gettingyou know, used to Copilot.
Can you take us through that momentand how you navigated it?
Like, what are some of the best practicesthat helped
with the understanding of whatthis actually means?
(16:45):
I think the number one best practice,I would say, is giving access
to the tools and technologies.
I think one thing Microsoft did reallywell is, is rolled out the tools to,
sort of that they had their rings or,or loops of users as they roll this out.
And I think one of the things they didbest was not wait for an over-
exhaustive training,not wait for an over-exhaustive,
(17:06):
setting up this massive,like, learning practice
before they put the tools out thereto the users.
Because, you know, a lot of timeswhen you give something to the users
and the users start playing with it,they look at it
from a very different perspective
than when they take a courseand use that same tool.
And I think that was somethingthat was fantastic.
Is that early adopters andputting the tools out in front of people.
(17:29):
Then came the training,
then came the adoption, then camethe communities of practice.
And now we've got everything from,gosh, iterative
feedback loops to office hoursto communities of practice.
We have– what do you call it likea champions group within the organization.
And so these are all critical waysin which, you know, users
(17:51):
within the organization, within Microsoft,for example, are able to,
you know, constantly iterateand evolve with their AI skills.
You know, it's funny, like I say thisall the time, I spent 18 years of my
schooling life and then followed that upwith four years of engineering
and then went to, you know,a couple of years of grad for engineering.
And I studied engineering throughoutto learn how AI works eventually,
(18:13):
and here I am in the last two yearslearning English
so I can prompt betterand I can talk to AI in a better way.
So it's almost like,the term engineering, obviously
prompt engineeringis a big aspect of all of this.
And so I feel like, AI hasdefinitely changed that conversation a lot.
Right?
So even a company as large as Microsoft,we're constantly looking at, hey,
(18:35):
what are the best prompts?
What are different ways
in which you can interact withAI to get the best out of it?
On a, you know, on a variety of places.
And it's changing as the modelsare evolving, as reasoning evolves,
as, you know, morecompanies are putting out more models,
as Microsoft is startingto pick up on a lot of this
and, and, you know, integratethat into their technology.
(18:56):
The framing is also changing.
So it's again, it's an iterative journey.
It's not a one and done model.
It's not like, here's a book, go read AI.
I mean, some technologies are like that.
Go, here's a book,go read this stuff and go use it.
AI is more of a conversation.
It's a little bit of a dance, right?
It takes two.
Yeah I mean, and I've also heard from peoplewho are engineers and are programmers
(19:19):
who are saying,"Hey, it's okay if AI takes over my job,
because then I get to do something elsethat helps to advance the company,
and it helps to advance new waysand new efficiencies."
It's not meant to sayor to have that fear.
Chris, you do a lot of public speaking,and you've
talked a lot about,sort of "Best Buy Syndrome."
(19:40):
Can you unpack that for us?
With apologies to all of the chiefsout there that I may have accused
of suffering from it,
"Best Buy Syndrome" is that is the thoughtthat if I just go buy
the newest, greatest, biggest,most amazing, awesomest
looking new technology,then all my problems will be solved
and everything is great.
And the way I describe that is it'ssort of like building three more floors
(20:02):
on top of a house with a bad foundation.Whether it's technology
or whether it's operations or whateverit is, our organizations
are first most essentiallymade up of humans.
And whether it's CAD,whether it's records,
whether it's a mobile product,whether it's AI, whether it's
a networking solutionthat allows us to guarantee connectivity,
(20:23):
or whether it's the Office 365 productthat we use for everything from,
you know, PowerPoints to, to,to writing reports.
All of those are only as goodas the folks that use them.
And and there is no– I have not seen yeta technology that can take
an organization that is sufferingand make it all of a sudden amazing.
But I have seen an organizationthat is suffering,
(20:46):
that has addressed its challenges, whetherthat's staffing or funding or community
engagement or internal leadershipand supervision and management,
then use technology to go frombeing maybe middle-of-the-road
to being an unbelievablyeffective group of professionals.
And that really is the journeythat I think,
you know, we as vendors need to understandthat we're supporting
(21:09):
and, you know,and it begs important conversations.
It begs a sales processthat isn't just show up
and you take an orderand then you walk out the door and,
you know, it begs a long-term relationshipwith your vendor
the same way you're going to have
to have to have a long-term relationshipwith AI and anything else
in this industry.None of it is is one and done.
(21:29):
So, you know, and I think it's interestingthat AI,
even though it's this newfangled, amazingpart– and Machine Learning the same way,
this new, amazing part of our ecosystem,it really falls back on the same
tried and true historical processes
that have guided change in organizationaldevelopment since minute one.
(21:50):
Yeah.
Can I comment on that, Christopher?
Like,I think you raised a really good point.
What's interesting is a lot of peopletreat this like just another tool, right?
AI is not just another tool.
You have to approach it as a strategy.
It is a strategythat you have to look at it.
What is your operational strategy,
from a public safetyand justice perspective? Like,
you know, businessstrategy, operations strategy.
(22:13):
Then there's a technology and
a data strategy that's associated with it.You know, how is your data set up?
How is the technology ecosystem set up?
Then you look at the user experience andhow does this interact with those users?
Then you lookat the organizational culture.
Where does it sit in the organizationthat you have today,
and how does that culture need to improveand evolve?
(22:35):
And all this is, you know, will only workif there's
some sort of a governance frameworkor structure within the organization.
So I think looking at AI ratherthan by the shiniest tool and implement it,
you have to look at it
as sort of building that foundationand a strategy within the organization.
The tools will continue to evolve,
but the strategy isis key to that organizational use,
(22:59):
right? So it's a great point.
Oh, I love that.
It absolutely is a strategy because it's
at the end of the day,you have to ask yourself,
as an organization,what is the best way to do this?
And when you're dealing with public safety
where you're now, you'retalking about dollars from taxpayers.
It's even dicier
because everybody's first to say,you know, is this really a priority?
(23:20):
So I think this isan interesting conversation,
that we're taking,that is taking us into a different area.
Kevin, I want you to jump in here becauseyou lead the global sales team with Dejero,
so you work with a variety of clientsand early adopters are rockstars
who are willing to take those risksand embrace technology.
(23:41):
Can you think of a couple of client success stories
that you want to share?
I think it ties really nicely into wherewe're going in this conversation.
Three different examples.
The first one is our internal use of it.
Where I firmly believewe have one of the best support
teams in in public safety.
(24:03):
And to Chris's point, it's not we're
we're not in a world where we sell a boxand and just leave.
We have to support them throughout whatever incidences or challenges
they have.
We're looking at AI to make sure that that support team
is well equippedwith all the latest information to be able to
on, you know, in real-time, bring up
articles and support, or installation
(24:25):
instructions, anything that we've doneand got a database on,
have it ready at the fingertipsso they don't have to go searching for it.
So they can thenfocus on the actual incident and helping
typically, you know, a personthat's calling in the middle of something
pretty, pretty challenging, having,
making sure that their equipment's workingand they're,
they've got the informationat their fingertips.
(24:46):
So internally, that's that's one of them.
Outside of public safety,the one I can think of is our broadcast
the media companies, our partnersthat are looking at closed captioning.
That's something that's kind of lowhanging fruit that, that they can go off
and do.And I see a lot of innovation there.
And then finally,on the public safety side,
I would say
(25:07):
it's moving a little bit slowerbecause of all the regulations
and the life-saving aspects of it.
But what really excites meis the, the folks out in, Central Pierce
County who decided to create a ubiquitous network
so all their applications can work acrossLMR, satellite, cellular
and helping them enablethat kind of groundwork foundation
(25:30):
that I'm really excited
to see how that then gets usedfor all the applications in the field.
That's really,really exciting to us.
And, and like I said,disruptive and transformative
as, as we've been talking about.
We end up siloed
oftentimes in public safety.We kind of do our thing
and then we don't for whatever reason,we don't engage and talk about it.
(25:51):
Events like that, that networkconstruction
are so profound to share
as best practices across the industryso that I mean, we can become a little
AI inspired ourselvesand become a learning model,
right? We can–
and that's just historically somethingthat public safety has always needed to do
(26:13):
just a little bit better.
There is nothing sadder than an agencyor a vendor, quite honestly,
repeating a mistake that their neighboralready learned not to do.
That wastes time,
it kills trust, and it just creates
an unnecessary level of stress and traumafor the public,
for the people were supposed to serve.
If I go outand do something that doesn't work, only
(26:34):
because I never botheredto ask my neighbor
how it did, you know,how it worked when they tried it.
So that sounds really excitingabout Central Pierce,
Kevin, that is the kind of stuffthat I think we're going to see.
I think there's going to beso many lessons learned from the
from this, this round of wildfiresin California, along that route.
Right?
And and someday soon,I think we're going to see
(26:55):
predictive analyticsaround anticipated disasters.
Unfortunately,we see more and more of them.
Sadly, all the time.
And we all know, especially those of uson this, on this webinar,
the impact of that on public safety,the impact of that on public
safety technology, and being able to planfor that and accommodate that and have,
you know, be ready to go with thingslike those types of networks.
(27:15):
Really powerful stuff.
I'm glad you shared that, Kevin.That's really cool.
I think I brought it up earlierin the conversation
that one of the fears that we hearfrom people often when AI is
part of the conversation, is,am I going to lose my job?
And as you all know,you know, people won't be replaced by AI,
but they will be replacedby someone who uses it.
Chris, can you take us through thata little bit more?
(27:38):
Yeah, sure.
The firefighters are still here.
Fire truck maybe no longer pulled,
hasn't been pulled by horsesfor a long, long time.
But we still need folksto do those jobs.
Now, what jobs did go away?
I assume everybody on here has never gottenin an elevator with an operator.
So there's some jobs,
you know, there's some things that maybe will.
I don't think we do
(27:59):
anybody any serviceby saying that everything
is going to be exactly the same forever.
I don't think that's realistic, whetheryou're talking about AI or anything else.
But to your point,if we know how to use the tool,
if we become valuable,whether we know how to use CAD
or we know how to use AI,or we know how to use a radio,
or we know how to use
Copilot or any of these other systemsthat we're talking about,
(28:19):
it makes us more valuable.
It makes us more essential,you know, to the operation.
So I would encourage anyone in publicsafety, you know, find the training.
There's so many free coursesavailable online.
There's so many classes you can go take.
And no one knows everything about this.
They really don't.
We are all learning as we goand being a part of that
(28:40):
and being engaged in that will help youestablish yourself in your organization
and in your future path to operate in an AI enhanced world.
So, you know, be the firefighter.
Don't be the horse.
You know?
I mean, that's that's reallywhat I would say in that case.
Sai or Kevin,what are some of the exciting examples
you've seen where AI has enhanced or,you know, we're starting
(29:04):
to see the potential of it enhancinghuman capability rather than replacing it?
Gosh, I mean everythingfrom transcription to
translation, like Kevin talkeda little bit about closed captioning.
I think, you know,we live in a global society.
They've got peoplewho are calling into the 911 system
with multiple languages as they speak.
And, you know, I see there's massivepotential for AI to play a great role
(29:29):
in like the ability to real-timetranscript and translate conversations.
Obviously, predictive
modeling is a huge area.
I also look at, you know, areas like,
you know, synthesizinglarge pieces of information.
So we went from this era of like,tons of data to information.
(29:50):
And then now I think we're at a pointwhere we now have a ton of information.
How do we go from informationto intelligence, right?
And I think AI has
got a massive potential as sort of likeintelligence synthesizing. Varying pieces
of information, creating correlations,figuring out pulses and signals from that.
Right?
I see huge potential there.
Everything from like,you know, maybe first responder wellness,
(30:12):
to you know, accountabilityas people are responding to incidents,
to bringing the right informationand surfacing up the right information
at the right time,
you know?
Listening to ten different radio channelsis not what we're built for as humans.
Although, you know, our first respondersdo a phenomenal job at,
and keeping pulse of everythingthat's coming at them.
(30:33):
I see there's a lot more sensorsthat are going to go out there.
In our world,as IoT devices are going to increase.
When that happens, guess what's critical?
Connectivity and synthesizingthat information to make that available.
So I see a lot of promisein those areas with AI.
I know companies are already working onthat.
And I see I'm going to I think we'regoing to see more and more organizations
(30:56):
starting to look at how AI playsa critical role in these areas.
Kevin,anything you want to add like to that?
No, I’m
by far the lightweight when it comes tobeing out in the field in public safety
compared to you, Sai, and Chris.
But I've yet to meet a chief, firefighter, or police officer that says,
finally, I get to write my reportof the day and and sit here and do that.
(31:19):
Right?
So, to your point, Sai, like,those are the
the easy things that enhance,
not only the well-being of the officer,but enhances the service
that's provided and, and have them focuson the things that only they can do.
Right?
And I mean, I joke aroundwe we have internal meetings now
(31:40):
let alone within public safetyand anything like that where there's
AI notetakers that,that are now competing.
They have multiple AI notetakerson a video call.
So all that stuff is, is highly usefuland even moreso
when it comes to being out in the fieldwhere lives are at stake
(32:00):
and, and people are challengedwith real-life
challenges thatthat involve public safety. So.
Yeah. I mean, I've stopped taking, like,look at this.
Like, hands are free.We're having a conversation.
This is interactive and engagingand we're actually focused on being human,
as opposed to looking down at a penin a paper and just constantly writing
(32:22):
when we're talking to other people.
I feel like that in itself.
Like I've been using Copilotfor the last couple of years.
I don't remember taking any notesin any meetings.
I do draw and other things.That doesn't change,
but that's part of change management.
I think it's made me more humanas I'm talking to people
because I'm able to look them in the eyeand have that conversation, you know.
Yeah.
Right.
Yeah, it definitely helps enhancesother skill sets and
(32:44):
yeah, notetaking again,
you you didn't get towhere you are at Microsoft
because you wrote good notes, right?
It's it's all the other featuresand all the other things that, that,
that come through thatallow you to do that. So.
Well before we say goodbye,
I wanted to just hear a bitfrom all of you:
You know, we talk about the promise of AIin public safety.
(33:06):
And I think, Chris,you've touched a little bit, in regards
to how we can break this downfrom automating and supporting processes
that humans shouldn't be doing anyways,especially when agencies like, you know,
are already facing crisis of staffing.
Talk to us a little bit about that,and then we'll jump over to Sai.
(33:27):
So, I mean, it's it's a world
of promise in terms of any new technologywhen it comes in.
But there's another example too thatI think is important,
almost as importantas the as the fire trucks and the horses.
And that was the idea of CAD itself.It's Computer Assisted Dispatching.
CAD was introduced in the late 1960sand has been gradually, slowly perfected,
(33:49):
I think, over the years as vendorslike my own have gotten, you know,
better and better at deploying solutions
that match the needsof their customers.
Yet ultimately, it's a balance.
It's a balance of what people needand what technology is able to provide,
and the willingness of people
to be engaged in the processto ensure that product works.
And that same model will serve us well,
(34:12):
in my opinion, in the evolutionand implementation
of AI, Machine Learning,and all these other solutions as well.
So my my closing messageto anybody on this
topic is (34:22):
we've done it before.
This is a skill set that we have.
This is an understanding we have.
It's maybe in a different way.
You know, I didn't even have a smartphone20 years ago.
Now, you know, you get anxiousif you don't have it, but that's okay.
And we can evolve and we can growand we can learn
and we can deploy these things.
(34:44):
And Sai said it earlier perfectly.
It's not perfect.
It's never going to be perfect.
And that's okay too.
So we've done it before. We can do it.
Let's be inspiredand hopeful about how we can use it.
And the last thing I'll say isno one does this alone.
Absolutely not.
Whether it's your partner agencies,whether it's your vendor,
(35:04):
if you're if you have vendorsthat you cannot get on the phone
when you have a challenge,
If I can't, you know, and I knowDejero is one that is this way,
that is effectively communicativewith your your customers because of the,
you know, it's just the nature of the company,the essential need of that technology.
Then that's a vendor
you should probably–If it's not that way,
(35:24):
that's probably a relationshipyou should look to
you know, reexaminebecause nobody wants to build the future
with somebody that they can't talk toand collaborate with and exchange ideas.
So there, that'd be my closing word.
Thanks!
Sai, Microsoft recentlylaunched the Advanced incident
Response System (AiRS). Chris, you mentionedno one does this alone.
(35:44):
Dejero is a partner in this project.
Can you help us understandwhat AiRS is a little bit more
and how Microsoftis pushing to the Edge? Sure.
I think over the years, we've always hada vehicle program within Microsoft.
It's got to be a tactical vehicle program.
It's evolvedover the last, I think, ten years or so.
In its latest iterationthis year, it's now being rebranded
(36:07):
as Advanced incident Response System.
The idea–I know Hexagon is a partner of that.
And Dejero is a critical componentof that with connectivity.
You know, it all boils down to pushing
compute and pushing a lot of intelligenceto the Edge.
The Edge meaningwhere the first responders are,
right?
Traditional comms is always relianton the dispatch center
(36:28):
or emergency operations center
or some sort of a centralized placewhere everything's coming from.
I think with as more data is becomingavailable, like we talked about earlier,
there is a need for more distributeddecision making.
And part of that distributed decisionmaking is that incident commander
or the individualwho is responding to that incident.
Up on the top of the vehicle, you'll seea plethora of communication choices.
(36:51):
If you look in here,you want to come take a look?
It no longer requires an 18 wheeler or a 36 wheeler.
It's not the size of the vehicle; it's the size of what capability exists within that vehicle.
Could be something as little as a little SUV or what have you, right?
So the AiRs program is intended to push a lot of the compute
(37:12):
and the capabilities to the Edge where first responders are
responding. And sure, there's a component of Edge AI in it as well.
The idea that, hey,
if there's absolutely no connectivity,can we do some basic things?
But connectivityis a critical component of that.
I know that's where Dejero playsa huge role and that partnership
with Dejero is aroundproviding that critical connectivity,
(37:33):
bringing all those layers of connectivityto the Edge where you're able
to run dispatch systemslike the products of Hexagon or others.
As well as intelligence, you know, integrating AI into
that is another layer that, you know,obviously, we're talking about now.
So, if anyone wants to check it out,it's
aka.ms/microsoftairs. That's the URL.
(37:56):
And I think, you know,there's a lot of promise.
We have a partnership now with Darley,which is a vehicle manufacturer,
vehicle outfitter, you know?And they're able to now
for any organization,any public safety entity
who wants to build out these vehicles,we're able to bring Darley
and Dejero and all our partners togetherand build those out.
(38:17):
So, our role is primarily in showingwhat's possible,
but it's also showing the art of the now,not just the art of the possible.
Right?
Really interesting.Kevin, I want you to join in.
Dejero is a partner with Microsofton closing this information gap.
And it's also important to knowthat connectivity is critical for AI
and we mentioned it today. Today.
(38:38):
In order for it to interoperate.
Kevin, diga little bit deeper on that for us.
Yeah
it's exactlywhat Chris and Sai have been saying.
I think there's no way that you look at
how much effort it takes
to get an application up and runningand make it seamless for the user.
There's no way one company does that.
(38:58):
And I think if one company triesto attack all problems at the same time,
they actually get nowhereand don't create that ecosystem
that Sai was mentioning.
So we're thrilled to be partneredwith Hexagon, partnered with Microsoft to
to contributeour small puzzle piece to the equation,
which is an important smallpuzzle piece of critical connectivity.
(39:19):
So by keeping people connected and lettingthe applications do their thing,
it puts the userin the best possible position.
And when we talk about connectivity, it's,
it's it's kind of interestingbecause it's it's not just a computer
talking to a Cloud andand running that. It's connectivity of
(39:39):
just what Sai mentioned– chief talking tohis people in the field
staying connected, staying safe,being able to anticipate what's happening
and using those applications,whether it's AI enabled, video enhanced,
whatever it is, to makethe right decisions at the right time.
So we're allbut I think, an interesting puzzle piece
(40:02):
to the whole scenario. But,
you won't definitely see the picture
if you don't bring in the Hexagons,the Microsofts,
and all the other applicationsto make it work.
Final
rapid fire response here for you all.
What one piece of advice or insightwould you give to public
safety professionals or organizationsconsidering adopting AI?
(40:23):
We're going to start with you, Sai.
Oh, get started now.
Don't wait for someone elseto tell you when to get started.
I mean, doesn't mean you go downloadyour favorite AI tool and start using it.
That's not what I mean.
What I mean is just get startedworking towards that strategy.
Whether you know, and pull people withinyour organization that are like-minded.
And if you don't find enough within yourorganization, find your neighbors,
(40:45):
collect a force of individuals and talkto, you know,
companies like oursto help you in that process.
Just get started now. I wouldthat's what I would say.
How about yourself, Christopher?
Find a tiger teaminside your organization.
Find three peopleand get together once in a while.
Go to lunch. Go to breakfast.
I don't care how you do it,
but just get a few different mindswrapped around this issue
(41:08):
and then slowly expandthat to involve your stakeholders
and agencies you serve,and your vendors,
and build out your approach toto not just AI,
but I think with the amountof technological advancement
we have in the industry right now,
I think that's the approach to do withall of it. It's no
no one person can do it alone.
No one vendor can do it alone.
And if we have at leasta few more people engaged in the process,
(41:31):
we dramatically increase
in my opinion,the likelihood that we'll be successful.
Kevin, you get the last word. Oh, geez.
I would say I would appealto the individual first in
the sense that if you step back at it,get curious about what it's
what AI's capabilities are.
Use it instead of Google or whatever
your chat or whateveryour search engine is, for you personally.
(41:51):
Play around with it, figure it out.
It becomes less scary to thenallow you to tackle the bigger integration
challenges of, okay, how do I deploy thisacross a public safety
scenario or, or station?That is maybe a little daunting to begin with
as an individual, so sort of build upthat that confidence and curiosity.
(42:11):
Well, thank you all.
Thank you.
Christopher,
Sai, and Kevin. As we've explored today,the promise of AI in public
safety is both profound and complex.
What role do you think AI should play inmaking our community safer?
We'd love to hear your thoughts.
Leave a comment underneath this videofor more about Dejero, Hexagon, or Microsoft.
Of course, we'll have a storythat will be along with this podcast.
(42:35):
And if you want any other information,head to dejero.com.
See you soon.
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