Future IT Considerations for Federal and State IT
Carahsoft's Government Innovation Exchange Keynote explored tech trends, challenges, and opportunities for federal and state agencies.
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And Gordon Bitco with the Information Technology Industry Council, I'm going to
ask each of
our panelists to just introduce themselves really briefly.
And then to, by way of introduction, just to talk for a few minutes about what
are some
of the key challenges that you've learned over the last few years?
You've all been doing government IT in one way or another.
Some of you still are.
What are those big challenges?
So, Cashant, why don't we start with you since you're your closest?
Sure.
Thank you, Gordon.
Hi, everyone.
Cuz she's Pandia.
I am the Chief Technology Officer for Internal Revenue Service.
Hi, good afternoon.
Karen Howard.
I'm the Director of the Office of Online Services with the Internal Revenue
Service.
Hello, I'm Owen Casey.
I, formerly with government and DOD, but I came out a year and a half ago to be
the VP
of Cybersecurity Strategy and Product Development at OWN.
All right.
Thank you.
And I'm back with you again.
Andrew Nielsen.
I'm the Director of the Government and Wide IT Accessibility Program that sits
within the
Office of Government and Wide Policy at GSA.
And I'm also representing kind of a sub office, the Office of Technology Policy
So, my colleagues who also work and provide guidance in identity and credential
ing and
access management, cloud center optimization and emerging technologies.
Great.
Thanks, Andrew.
And so, why don't we actually start that first question with you.
What are the couple of key lessons that you've really learned over the last few
years?
Yeah, I think, you know, on my, you know, more narrow perspective on
accessibility, you
know, I kind of, we talked a little bit about it this morning as part of the
customer experience
panel.
But more and more, of course, more and more of our services are moving to the
digital
sphere.
And so, I think, you know, certainly a trend that we're seeing with the advent
of, and
development of low code, no code environments, that obviously the advent of
artificial intelligence,
generative AI, just more and more customization, more technologies, specialized
technologies
for specific line items of business.
And so, I think, you know, we're seeing that.
We'll see only more of that as we make better and more intelligent use of gener
ative AI's
and as they get better.
And so, you know, along with that, you know, of course, the challenges.
I won't speak to all of them.
But the challenges that come with that in making sure that we are making
intelligent
use of those and that we're safeguarding privacy, we're safeguarding the
security of our applications
and our digital services.
And then again, maybe Naramine, again, on my accessibility focus, ensuring that
as we
-- and I think there's probably a question later.
I'm skipping ahead to the question on innovation.
But as we innovate, that we don't leave people behind, and that, again, on my
accessibility
focus, that we need to ensure the legitimacy of our government, the services
that we provide
by ensuring inclusion and ensuring that we meet the needs of all of the public,
the citizens
of the U.S.
So, yeah, sorry.
>> No, no, great, Andrew.
I think all super helpful.
I'll note, you know, not just the eclipse but an earthquake going on here at
the same
time, too.
So, we're full-futures, full services.
Oh, and same question to you to start with.
You know, what are the key lessons over the last few years that you've really
taken away?
>> So, I have to balance innovation and security.
So I came from a background of dealing with security breaches and investigation
, but moved
into more of a proactive state.
But trying to translate, I think, some of the lessons we've learned from the
past -- from
the past, I think there's been a lot of good discussion today about data being
so critical
now in everything that we do, and making effective use of that, and doing it in
a more
speedy manner, we have to keep pace with the changes in technology and the
advances that
are coming with stronger analytics and more advanced AI, but balancing that
with proactive
security from the outset.
And so I come in with that integration of the innovation and the protection.
We can't just let the data go ahead of us and try and catch up.
We will not catch up.
I can guarantee it.
>> Yeah, for sure.
I think that's a great point.
And Karen, I'd like your thoughts as well.
But one of the themes that we just got from both folks is the importance of
people in
all of this.
And given your role, I'm sure you've got some thoughts there as well.
>> Sure.
I think one of the things that I think we're really starting to understand is
the importance
of user experience design in the design and putting that first, letting that
drive the
design of products, the design and the needs of the business so that then the
technology
follows behind what's learned in the UX research and the data that helps us
understand that.
I think that's one of the things that you're seeing a really good focus on now
that you
didn't before.
Typically, UX was kind of an afterthought.
It's like, oh, now that we've designed this, now let's get designers to look at
it.
And it was about colors of call to action button.
And now it's really about partnering with our IT partners and making sure UX
design is
in the forefront of development.
And not an afterthought.
I think the other thing that these two gentlemen have already really spoken to
is data and
data-driven decisions and data that supports business cases.
Sometimes we think we know what our users want and what our customers want.
But using data to kind of validate or help us understand anomalies that we can
address
in design.
And I would end with saying that letting business needs and business problems
and business use
case drive technology solutions and not going for technology and then looking
to retrofit
it into the business.
Yeah, I think that's a great lesson because I'd certainly like to get your key
lessons
from the last few years as well.
So I'm going to add on a spin to that around that point.
You've got obviously the IRS tons of data.
And how do you think about those exact issues?
We've got all this data.
We've got these really challenging use cases for Americans who expect certain
behaviors
on the IRS.
And so how do you balance those?
Yeah.
No, data certainly is and we have more than our fair share of it.
Over the last couple of years what we have really observed and the pandemic hit
this
home is that we need to find better, more intuitive ways to engage with our
taxpayers.
And our taxpayers in turn want to engage with us in a similar manner.
Perhaps you've seen these unfortunate pictures of us having volumes of paper
stacked in our
cafeterias and all over our IRS campuses.
We have really focused on digital transformation.
So digital transformation, we cannot stop paper from coming in.
However, we can convert paper and digitize it and digital transformation has
been a pioneer
of a program for us.
However, what we observed is while we were converting our paper to digital
images internally,
our people were printing them out.
Of course they were.
Because in order for them to get access to the data and if it wasn't
necessarily the
highest degree of accuracy, so they're printing out all the paper, we were
digitally transforming
at our doorsteps.
We then realized that the reason they were printing this out is because they
needed to
key in the data manually into the systems.
Our focus then shifted to not just converting them to digital format but really
honing in
on extracting the data and feeding it downstream to our systems so that our
people are focused
on running the necessary analytics, doing all the work that is required to
assist taxpayers
versus printing out and punching in that same data that we were collecting.
Yeah, I think that's a great example that highlights Karen's point about
understanding
the business case and really knowing what the technology is for.
But at the same time, it also highlights one of the challenges I always had in
these
transformations is the people and the cultural aspect of they're used to doing
something
the same way for so long or you as a federal agency have compliance
requirements where
you have to do things a certain way or the agency's made a risk management
decision to
do things a certain way.
And so Karen, if I could go back to you, how do you deal with changing that
environment?
Well, I think when it comes to changing an environment where you've got a lot
of legacy
practices and comfort in doing things the same way, you've got to really find
the win-win
for the employees or the people doing the work.
I think part of it is going to involve upskilling and how it adds value to
their role sometimes
to their bank account.
Wouldn't that be nice?
Just giving them more skills and showing them the benefit.
Also making them a part of the solution.
I think when you talk about change management, first of all, you've got to make
sure the
business is ready so there's business readiness or organizational readiness and
then it's
really making them part of the decisions around what you're planning to do and
getting their
feedback along the way, giving them ownership in the change and also showing
them the benefit
to them.
Not everyone will grasp that and be excited about it, but most people will and
then the
outliers, you know, you handle those in the best way you know how and help them
find their
happy place.
But one of the things I can say, change management, it's easy to say and it's
hard to do.
And I think organizations need to understand where they are from a cultural
standpoint
in the maturity for change and begin to implement change based on that.
Some organizations are ready for it and some organizations need to move at a
slower pace.
But when it comes to change management, if you build it, they will come, does
not apply,
especially when you have a lot of legacy employees.
You've got to figure out how to make it affect them in a positive way.
Yeah, thanks, just to follow up on that and, Andrew, I'm going to go to you
with this
question.
How do you balance that change management challenge with the potential of all
these emerging technologies,
which I would imagine when it comes to accessibility, have the potential for
huge benefits, right?
AI can really transform a lot of the challenges that we have in access and
accessibility.
Yeah, yeah, I mean, particularly with regard to artificial intelligence, gener
ative AI,
maybe narrowing in on that world of accessibility and then broadening.
There has been some argument in our little world of accessibility that AI will
just solve
all of our problems.
AI as an assistive technology can just help anyone with a disability regardless
of the
type of disability.
When it comes to interacting in the digital sphere, we don't need to worry
about making
our stuff accessible anymore because you could just use AI as an assistive
technology and
then that fixes everything.
And then, by the way, it's also, that's to our benefit because it costs too
much and
it's just too much effort and there's too much cognitive load.
I have to train people to know how to make their stuff accessible.
And that's just kind of wrong-headed in the first place.
It's subscribed to the model of looking at an individual and their differences
as differences
when not recognizing that differences are really dependent on environment and
context.
And especially in our broad human experience, everyone has differences and when
it comes
to disabilities, rather than relying on somebody to fix their difference, we
should adapt our
environment.
We should adapt our context to meet the needs of individuals and that can go
for any type
of difference.
And so there is still fantastic promise.
I'm more excited about the use of AI on the intent, on that side, on that
really side of
development, whether it's development of a process or development of technology
, and
using AI to help as a copilot, if you will, or a tutor or a partner, I want to
do a thing
I might not know how and so help me do that thing.
And so, again, with what we're talking about, low code, no code environments or
a developer
who knows all of the bells and whistles but just doesn't know accessibility,
that is a
very positive, I think, a positive development we can look forward to.
And then expanding that out to other spheres outside of just accessibility,
there's so
much more where it's applicable.
Not only when I'm looking to meet the needs of individuals with disabilities,
but when
I'm looking to meet broad customer needs, again, in the digital sphere, to
better understand
that I don't know everyone's circumstances or all of their needs, but I can use
AI to
inform that and to broaden my context and to rely on that rather than only on
my knowledge.
Great.
That's, I think, a really helpful set of insights into the ways that AI can
help.
But when there's a flip side, AI introduces threats, changes the threat
landscape.
So I'm sure you've got some thoughts about how we should be trying to
incorporate that
into our understanding of the threat environment.
Well, I think there's the traditional threats just applied to the new
technology which we
have the disruption by adversaries.
But I think one other factor that we have to consider is bias.
And this is something that came up in roundtable discussions, what we also see
in across sectors
is the potential for some of the training that's been done or even just the
data that's available,
introducing certain biases.
So if you think of, in a hospital setting, doctors are being approached by
pharmaceutical
companies to promote a particular prescription, that's then setting a trend, a
historical
trend that could ultimately bias any automation that we have to help with
prescription management,
prescription efficiencies.
So we have to, I think, be careful of the risks that are unintended of the use
of the
technology also.
And one of the things that I think pulls us all together is if we have humans
in the loop
for sure who are able to more quickly, if you think about the speed of
iteration that
we now can achieve with this technology of getting, it's the Uda loop from, I
guess,
the military context but applied here, we're talking about observe, orient,
decide, and
act.
We can do that more quickly now and make adjustments and see problems more
quickly and adapt.
I think that that's some of the potential that I see where we can avoid some of
the problems,
we can be more proactive and avoid some of the problems from a security, a bias
perspective
and perhaps come up with better solutions in the long run.
So we're not getting rid of people is what you're saying.
I think that's given.
So because I think that aligns really well with one of the use cases we were
talking
about outside around how you're looking at helping the IRS workforce with AI
tools,
not replacing them.
Correct.
Yes.
We are being very cautious, naturally so, about how we leverage the
technologies.
AI is quite prevalent and what people equate AI to is chat GPT.
I mean, that is what is typically known.
However, we want to be much more deliberate about how we apply it.
And we're being cautious on how we apply it for external facing.
We want to be very, very careful of how our taxpayers engage with us and
leveraging AI
and we don't want to create those hallucinations or have any misleading
information.
If we were focused on or populate our data models with scour the internet for
any and
all tax related questions, somebody on Reddit might say you don't need to pay
taxes and
all of a sudden when a taxpayer asks if I should or not, that's the answer that
pops
up.
We're looking more internally and there are a plethora of opportunities
internal to IRS
on how we can apply AI.
For example, we have a legacy or I would say an aging workforce that is leaving
and they
have been very accustomed to reviewing manuals that are physical, that are
paper and they're
looking across these lengthy and thick workbooks on how to apply or how to
evaluate or how to
assess.
However, as the newer generation comes in, they are much more open to and
wanting the
digital equivalent of it.
But the volume of data contained, however, hasn't changed.
In fact, it's done nothing but grow.
How can we assist our internal employees to not have to figure out which page
to look
for and we are applying AI against that?
Convert our internal information and make it more conversational so that our
internal
employees are able to simply ask a question, to go and find that information
rather than
have to figure out which book contains what part of the tax law.
I'm disappointed to hear that Reddit is not in the favor too of a source.
I might have to sell my stock.
That's a great example though of how do you use technology to actually drive
change in
the organization.
So I'm going to go back around and ask each of you that question, Karen,
starting with
what's the thing where you think there's the best opportunity for technology
and your
workforce together to be transformative in that way?
I think if we can leverage technology to address business problems, customer
problems,
user problems, and to bring efficiency in addressing those either from a
customer facing
perspective or behind the scenes from an operational perspective.
If we can look at, you know, to, because she's point using artificial
intelligence to help
us with a fine anomalies or to fine patterns that help us identify scams and
schemes which
is, you know, really a big thing right now and usually is around tax filing
times.
We can use it to find pain points in arduous processes that take a long time
and help eliminate
those.
I think if we can leverage platforms, workflow management to really identify
bottlenecks and
workflow and really hold people accountable.
I think right now with a lot of manual processes in place and not knowing where
the black
holes are when we're waiting for a response or looking to understand where a
document
that, you know, it's going to drive a business decision or a action is located.
There's just so much if you just look at what's causing problems in the
organization and focus
on those and that is serving the team, making your employees involved in what
are your biggest
pain points if they say it's, you know, procurement or hiring or onboarding
employees and kind
of mapping that out in a value stream way and then saying, okay, how can we
leverage
technology to do some of this stuff?
That's where technology begins to pay off.
And again, like I said before, that is using business needs to drive technology
and not
the other way around.
Great, can we maybe afterwards just have a purely intellectual conversation
about how
you're using models to find scams and tax filings?
We absolutely can.
Just hypothetical, like I said.
Oh, and same question over to you.
I'd really like to just continue that.
I completely agree, Karen.
And I'm happy to say I had a very positive experience with the IRS and working
with
someone who knew a lot of the systems in place.
And I think what we really have a potential for here is to take some of those,
we might
call it a pain point, but I also can think of this as finding the things that
makes us
successful and amplifying those across the organization.
So it's using the historical successes or the factors that contribute to
success historically
and amplifying that with the technology to help people across our organizations
be successful.
Andrew?
Yeah, I think, you know, broadening it.
Remember my comments on specific to accessibility.
While there again, just some fantastic, I think, things to look forward to
using advancing
technologies, AI, to help us as partners, as mentors, as co-pilots, to make our
content
and our digital tools and services accessible to people.
I think another thing to look forward to is that while, in some cases, it may
also be
perceived as a threat, but the hyper-customization of my experience as a
customer, especially
in the digital sphere.
I think most of us are accustomed to seeing custom ads and maybe get a little
bit worried
that they're overhearing, my computer's overhearing, my conversation, how did
you know I was talking
about that earlier?
And so there's some advanced algorithms, but there also, and so we need to be
concerned
about privacy and security, but there's also a great opportunity for hyper-
customers.
More relying on cues that you provide as a user or as a customer to customize
your experience
and to choose your own experience, if you will.
And so I think, again, technology will only continue to quicken our pace and
our ability
to adjust and to provide new technologies that's only going to increase,
especially with AI.
And I think, again, more and more, we'll be able to customize our experience to
our needs
and excited about that.
So Andrew, just to stick with that comment for a second, because I think that
the hyper-customization
thing is certainly really fascinating in government.
It's something that we all see and experience in our own personal uses of
technology.
Can government policy, can government compliance, can government regulation
keep up with the
ability to do things like that?
You look at how long it takes an executive order to come out or guidance to
come out
from OMB to agencies, and it can be years from the time that it's discussed
until it's
in place.
Yeah, I think that there is still room for that.
I mean, of course, that can be hard.
I think a starting point, I think, first of all, let's not start from scratch.
Let's rely on best practices.
Let's rely on design systems, for instance.
The agencies, hopefully, are all using the US Web Design System for your web
presence.
Start there, and then customize on top of that.
So start with what you have.
Don't necessarily start from scratch.
Build on best practices.
Yes, absolutely, I think our pace will still be slower in government as we
adapt regulation
and law and rely on our legislators to do that as well.
So I don't know that I have a silver bullet answer.
There will be some lag.
But I think that there is still a lot of room based on a lot of really great
work and tools
that we have available.
Yeah, I don't think anybody expects government technology to be the same as
what it is at
home.
We'd like that, right?
But if we can converge, right, if those things can get closer.
And Karen, one of the things that you said about the role of some of these
technologies
in the procurement process, I think, is that the core of trying to do that
better and smarter
and faster.
So I don't know if that's something that IRS has started to think about yet.
We have, and probably because she can probably speak to this better than I can.
I know with the funding, the influx of funding from the Inflation Reduction Act
, we are addressing
a lot of the historic, iconic processes that we all know and love.
But I do want to speak to one thing.
I always function on the mindset of there are some things you can't control or
that
are going to be what they're going to be.
What are the things that I can control?
So when we talk about customization, part of that is personalization.
So really looking at one of the things that I really have worked hard on with
my IT partners
are online account.
And how do we make that so people are getting more of what they want after they
authenticate?
So to answer your question, I really think that to this point, there is still
room to
grow.
But we can continue to look at the things we can impact while we wait for the
wheels
of government to continue to turn and we continue to educate ourselves,
leveraging our industry
partners in the private sector to know what's coming and to be ready.
Is she, did you have more to talk about procurement?
Absolutely.
First of all, we have a lot of witnesses who did hear Owen say he had a
pleasant experience
with the IRS.
So procurement is one of those areas that we have found that we can apply
intelligence
against to expedite how we procure and how we deliver, how we award contracts.
In fact, we have, to Karen's earlier points, we really are targeting business
cases.
And when we talk about business cases, we're saying what can we do to help
improve our
internal business users to do their jobs better, but also our customers as a
whole, all of
the taxpayers, ourselves included.
It is looking beyond technology and thinking about what problem exists and how
can we apply
technology to solve it versus saying here's a technology, now let's go find the
problem.
The procurement one is really interesting one.
We have a procurement office where individuals were spending hours and hours,
if not longer
than that, and perhaps days scouring the right websites to determine whether or
not a vendor
we are going to engage with is tax compliant.
And if they're not tax compliant, we naturally can't engage with you.
And this would be a manual effort.
People would go on websites and do research.
We applied intelligence against it, and now we've cut down from multiple days
to minutes,
five minutes currently to find whether or not a vendor is tax compliant.
That's a real case example of how fast we can now perhaps determine whether
somebody's
qualified or not.
That's some of the really quick use case.
So that's our internal team that's focused on that we've been thinking about
how to solve
for.
The other one is again, all of us, the taxpayers.
When you file a tax return today, it gets submitted, it gets processed within
hours.
However, if you have to amend a tax return, if you had to modify it, it takes
months.
And the reason for that is because when it gets modified, somebody internal to
IRS has
to evaluate your tax return to your new amended return and make a judgment call
on whether
or not this is something that needs further scrutiny or it should pass muster.
What we are doing is applying intelligence to say you don't have to look at
everything.
Here are the biggest discrepancies.
So you really have a decision to make on these three focus areas.
Now it's cut down the time that our internal representatives spend on
evaluating the whole
form versus the three most typical or the three most questionable areas.
And now it's just their judgment.
I'm going to pick amongst the three versus spending days and evaluating one by
one between
the two.
You would think that there would be a self-selection rate that companies that
are not tax compliant
aren't going to look to do business with the government, with the IRS in
particular.
But apparently that's a bad assumption.
So I'm glad to know that you guys check that.
Oh, and from the outside, what does modernized procurement look like?
How is technology helping?
I was hearing some of this and was thinking the modernization and some of these
efficiencies
are to be encouraged.
But the data that we're using as we move into some of these modernized
capabilities and
we can talk about sales force here, the lessons that we've learned from the
past about securing
that data, having continuity of operations as we move forward with that new
technology
and new solution, we have to translate.
And we're running behind in terms of our ability to do that.
So I think one of the key factors that I would say is as we move to these
solutions,
we don't forget the lessons that we learned from failures in the past.
And just keep in mind, for example, the lessons that I learned in my dealing
with insider
threat and APT threats, the zero trust approach has to be applied in these new
environments
as well.
And that's very data centric.
It's least privilege access management.
It's making sure that people who have access to data, they need it.
It's not broadly accessible.
And that we're monitoring some of the activities so that we, if we do see a
problem of somebody
doing something that they shouldn't in that environment, we're aware of it and
we can
be proactive.
And that applies also to the automation and the AI where auditability, I think,
is something
that we've lost our -- we've kind of lost the threat a little bit in these new
environments.
Automability of AI applications is critical.
To be able to figure out, when you do make a decision, if it's comparing two
tax returns,
that decision can be tracked back through some of the processing that led to it
so that
it's not just a black box and potentially a liability if somebody then made the
wrong
decision.
Do you think the -- something like auditability, though, depends on the use
case and the particular
risk.
Clearly, taxpayers are going to be very upset if their filings are wrong
because of an
AI.
But there are other cases where government agencies and others can use AI where
the impact is
different, right?
I'd say kind of going back to the keynote with a speaker, Nataka, was talking
about some
of the innovations.
We can use technology to help, but I don't think that there are many situations
where
we won't, at some point, want to -- or need to explain to a lawyer how that
decision was
made.
And we can't just say that the AI told me to do it.
So auditability is going to come in once it's medical malpractice.
It's maybe in the higher risk.
It will be more necessary and more detailed.
But if we can't at least explain to some degree how the decision was aided by
the technology,
we're opening ourselves to the problems.
I just had a Megan flashback.
Did you all see the movie Megan?
But the AI went -- oh, so I digress.
Okay.
I saw the trailer for it.
And the accountability was they didn't know because the AI did it, and they
didn't know
what it was doing.
And so you just kind of brought that back to my mind.
That's a scary thought.
There it is.
Yeah.
So I want to be respectful of time, but I did want to get into that point just
a little
bit more because one of the issues that -- break when it comes up in settings
like this is
how do you balance those new additional government requirements?
Some people might call them compliance, but whatever we call them, with the
desire to
move quickly on the technologies, to innovate, to compete with other nation-
state adversaries,
all of those things.
And it's a balancing act.
So I don't know -- let me start with you if you've got thoughts on how to do
that.
Well, I'll just remind you of mine, the one who asked Taka how he got the ATO
process down
to two or three weeks because I was in the DOD and I couldn't figure out how to
get it
done faster.
So it's a problem, but obviously Taka has solved it, so go ask him.
No, it's something we have to strive for, and I think one of the key factors is
a forum
like this where we can share solutions and figure out how to do better.
So I'm glad that we're -- thank you for the opportunity to join you, and I hope
we can
learn more after.
Yeah, Andrew?
Yeah, you know, I made a comment earlier about safeguarding or protecting the
legitimacy of
our government.
And I think that there's just some acknowledgement for us bureaucrats that we
rely on, we need
some of that red tape.
And that is, again, to safeguard to the legitimacy of our government.
And so, yes, there is a balance.
We absolutely want to innovate.
We want to make things easier.
We want to make things quicker, but we also need to slow down sometimes and
make sure that
we are compliant, that we're complying with the law, conforming to technical
standards
for whether it's security or for accessibility, and that is necessary.
And I think that we can also look forward to technologies that can help us
navigate that
more easily.
And so, yes, there, again, still will be a lag, but a necessary one.
And we still can look for ways to improve those.
And our challenge, of course, is, again, as bureaucrats to determine what red
tape can
I eliminate and what needs to stay and for what reasons.
And that's our job.
Great.
Thanks, Karen.
Yeah, I think that no one expects us to move at the pace that industry does,
private
sector, because we have more to lose.
We have more threat that has a more radical implication if those cyber surfaces
are, you
know, attacked.
So I think while we do have the desire to move fast, and I think we can move
faster by learning
from industry, seeing, letting them, you know, run with and learning from them
in events
like this, learning what not to do, what to do, what lessons learned.
But also, I like the idea of test and learn, you know, piloting MVPs.
And let's try a little bit and let's learn, let's dip our toe in the water and
see what
happens and then scale up as we get comfort as legislation changes.
And actually using those tests to drive changes in legislation and increase
compliance.
I think the risk for government far exceeds, especially with the IRS, what
would be tolerated
for a, you know, private sector organization.
I mean, how many times have you all received letters where there was a data
breach and
you get a subscription to monitor and life's good?
So if IRS sent you one of those, we would be tired and feathered on the steps
of the
White House.
So we just don't have the tolerance, but we can learn and we can test and grow.
Well, I did get one of those from OPM once upon a time.
I did just think we just let them.
I just let some people being tired and feathered in congressional hearings.
Yeah.
No, I, so Karen is absolutely right.
Our primary responsibility is to protect all of your data, all of our data.
Really we see about two and a half billion unauthorized attempts against us,
two and a
half billion.
We're talking about multiple millions a day.
And these are bad actors who are trying to access information that they know we
possess.
So we are extremely careful.
We are very risk averse and naturally so because we have a very big
responsibility.
However, there are two things that were said here is the approach that we've
taken.
One is exactly what Karen said.
Let's try it out.
Let's do it on a smaller scale.
We don't have to do this for everyone all at once.
You know, of a population of 400 million, we have over 200 million that are
paying taxes.
We don't have to target and find a solution for applied technology that
addresses the
needs of 200 million.
Perhaps we look at 100,000 and testing out those waters.
The other thing is what Owen said, there is a great opportunity to engage with
all of
you, with our other partners, other agencies, and learn how they're doing it.
One of my areas of responsibilities that I've now started to expand on is not
just containing
it within the United States, but frequently speaking with the tax agencies of
UK, Australia,
Canada, the ones who also have a similar scale and size of ours, how are they
addressing
some of these challenges while keeping that risk at bay and keeping it minimal
at best,
because we don't have that luxury to, again, be the one that sends out the
letter that
tells you that we're going to help you now monitor your credit for the next 12
months.
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