E018 – AI or Not – Renee Wynn and Pamela Isom - AI or Not

Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Pamela Isom (00:17):
This podcast is for informational purposes only.
Personal views and opinionsexpressed by our podcast guests
are their own and not legaladvice, neither health tax, nor
professional nor officialstatements by their
organizations.
Guest views may not be those ofthe host host.

(00:51):
Hello and welcome to AI or Not,the podcast where business
leaders from around the globeshare wisdom and insights that
are needed now to address issuesand guide success in your
artificial intelligence anddigital transformation journey.
I am Pamela Isom and I'm yourpodcast host, and we have a
special guest with us todayRenee Wynn.
Renee is an independent boarddirector.

(01:13):
She's a former NASA CIO.
She also was at the EPA.
We met during her tenure,during your tenure at NASA, and
I'm so happy that we havemaintained our relationship.
I really am.
You're a strong leader.
You're a good role model.

(01:34):
I appreciate you.
You're a digital transformationleader, and I know you because
of your excellence incybersecurity.
So there's more that I couldsay, but I'll let you tell your
story.
So, Renee, welcome to AI or Not.

Renee Wynn (01:51):
Pamela, it's great to see you and it's great to be
here with you today and thanksso much for asking and I'm so
glad we have been able to stayin touch through all of these
years and for the listeners toknow you and I actually never
worked together, we just ran inthe same circles.
I think a hidden secret in theIT world in the United States

(02:12):
government is a lot of folks arevery well connected with each
other across all the agencies,even if you've never worked with
them.
And I love that about beingpart of the IT community in the
US government because you werealways a phone call away from
help and you, pamela, put on themap working at Department of

(02:35):
Energy, sort of an AIorganization, which was
wonderful that DOE did that andput you at the helm to really
capitalize on your amazingcareer.
And what a great way for you toend your career in the federal
government as you move to thisnext phase.
So thank you very much.
So for the listeners, a littlebit about me.
I always like to tell peoplewhat's the job of the NASA CIO,

(02:59):
and it's quite simply this youdeliver IT services across the
globe and off the globe.
The CIO's organization doesprovide some services to
International Space Station, andthe other part is is I led the
effort to overhaul NASA'scybersecurity posture across the

(03:21):
globe and off the globe, andNASA still operates in Russia
today, which is always a bit ofa surprise to everybody, but
there was a few months ago botha launch and a return of an
American astronaut on the Soyuzcapsule out of Russia.
So in many ways, I think spaceis a great human connector and

(03:45):
if you're always talking, thenyou have a chance to resolve
conflict, which is my great hopewith the political and
geopolitical situations that aregoing on around the globe today
, the ones that are obviously inthe news every day.
But there's some that are goingon that don't make the news
every day, that are just as hardon the people there.
So that's what I did at NASA,and I also have people forget

(04:09):
and I actually forget too,because it was a while ago and
that was I had about 25 years ofmy career, was at the
Environmental Protection Agencyand I came from mission.
And a warning to all yourlisteners if you complain a
little too much about your ITservices, you could end up in an

(04:29):
IT organization.
So, having offered a fewobservations.
That is when I made the switchfrom mission delivery, program
delivery at EPA to being thedeputy CIO at EPA Because, like,
okay, well, she certainly seemsto understand it and maybe

(04:52):
she'll bring her mission heartto delivering those services.
And what's really funny is thatone.
I learned how hard it wasbecause so complicated and it's
so complicated and it's largelydriven by people, as you know.
But the other part about movingand shifting there is the pace

(05:12):
of the work and, boy, once I gotcomfortable with the pace, I
loved the chaos and the pace ofoperations.
It wears you out, as you know,but it can be really fun because
you can make a big differencein mission and delivery and you
get to solve some problems,sometimes at 2 and 4 am, and

(05:35):
that's okay because you and yourpeople realize that you're
critical to mission delivery andit's always good to be reminded
of that.
So that's a little bit about meand how I came into the IT
world and a warning to folks ifthey complain too much, they may
end up with a job somethingenough, do something about it.

So that's that's yeah, and so and it's also funny
, I find it I find it a littlecomical that you said the the

(06:14):
operations, that you love thepace and chaos of operations.
Okay, so I liked it earlier inmy career, I loved it and that's
what I did.
Right, that's starting out inmy career.
And then I moved into theinnovation realm and so I don't
know if I really liked theoperations, but I know that I
always felt this sense ofaccomplishment because you're

(06:36):
carrying the brunt of theorganization.
It's the operations crew that'skeeping the organization
running.
So I appreciate the value ofbeing in operations, but I don't
know if I always like the paceand the chaos.

Renee Wynn (06:52):
But you switching into innovation from operations.
You have this greatunderstanding and compassion and
empathy for operations and how,frankly, to deliver innovation
in a way where folks arereceptive and it actually fits
in the organization.
I've had a number ofconversations not everybody on

(07:13):
the innovation side that was, ohwell, just go do this and you
think You're like what Exactly?
You know you have a networkthat's across the globe and a
hiccup could be very problematic, so that's why you have
development environments to goplay and production and

(07:35):
environments are far more useful, but you got to figure some
things out in these complexenvironments.
So, yay, I know that you took acommon sense approach to
innovation and I think it's.
The reason you did is justhaving that experience in the
chaos of operation.
So that's great.

Well, thank you, and that's probably good for
people that are listening.
So, as you're looking at, whenwe're trying to figure out, like
, how are we going about dealingwith things that are going on
today and trying to get back tosome of the fundamentals, or
even those that are just gettinggoing, we have to remember that
if you're going to be a stronginnovator, you may want to look

(08:11):
at transitioning to differentroles within the department so
that you get some experienceright, and vice versa.
So, when they switch roles,that's really helpful.
I think you're right about that, though I believe that that's
probably how and why I have thetemperament that I had as an
innovator.
I believe that's a goodassertion.

(08:32):
But I want to thank you foryour work and I want to thank
you for the things that you havedone.
I sincerely, more than yourealize, appreciate it.
So I'd like to take time nowand talk about governance, ai
governance particularly.
I'm curious as to yourperspectives on, you know, are
there things that we could bedoing to make our lives and

(08:57):
business leaders' lives easier,like, are there things?

Renee Wynn (09:01):
we should be thinking about.
I think that's absolutely right.
So AI governance first.
When you say the wordgovernance, most people their
eyes just glaze right over.
Well, I'm going to use a NASAexample and then I'm going to
get into the AI governancebecause I'd like to set the
stage of why governance matters.
So an element of governance atNASA was the Agency Program

(09:24):
Management Council, apmc Makesure I got the letters right
there.
And James Webb Space Telescopecame through the APMC and every
line of business or line ofmission within NASA, including
mission support, sat at thetable so I'm speaking for myself

(09:45):
sat at the table to review thatprogram, to ensure that program
would be successful.
And in many ways you have toalso say that success is the
reputation.
When you're paid by taxpayermoney, that reputational stakes
and that success stakes, I think, go higher.

(10:08):
And, nasa being rather iconicagency, people are always
looking at what they do andmistakes are important to make
and you have to create anenvironment that allows for
mistakes.
But you also have to learn fromthose mistakes and integrate
those into what you do so thaton the day of lunch we're about

(10:30):
as mistake-free as you can get.

Yeah, right, like in your case, lunch means lunch.

Renee Wynn (10:36):
Yeah, it's like, yeah, we're leaving the
atmosphere and let's go, yeah,and so I bring that to light,
because people have a tendencyto say governance is bureaucracy
.
Yeah, and there are cases andin fact a lot of the cases where
governance has become too muchbureaucracy.
And so it's important to assesson a regular basis your

(10:56):
governance processes and can youmove them with the right
friction, with the rightfriction?
Friction is good.
You want to bring the rightfriction to the process so you
don't go too soon or you don'tgo too late and you want to get
the right voices at the table.
So, with AI governance, part ofthat process is to do the due

(11:19):
diligence on AI.
How are you going to use it?
You need to have a purpose.
It's not just a cool, shinything because AI could wreck
your business.
It's touching your data.
It's bringing data potentiallyfrom outside your organization
and bringing that into yourorganization.

(11:40):
So there's a big trust piecewith AI and can you believe what
it's producing?
At the other end?
And I always like to say well,let's go to the basics first
with AI, and what processesautomated processes already do

(12:01):
you have that you could bring AIto?
So you already know the process.
You know I was thinkingworkflow charts.
You know, back there, when youhad the little drawing tools to
do that which I loved, and then-I remember those Were yours,
the green ones, yep.
Yep, you know, make the boxes inthat Well trained me to think

(12:24):
that way.
And then I loved when the bigApple Macs came out and you
could draw them instead of withthe tools, instead of having to
write them and then erase andthen write and erase.
Then take a look at what you'vegot and say, well, how can AI
help us with our alreadydigitized processes?

(12:48):
It's a great place to start andwhat you can do through
governance processes you askacross your enterprise, and so
for me, I always think of theNASA enterprise.
So, in science, what have yougot already processed and how
can this AI help you Missionsupport, hr, it, my organization

(13:09):
procurement and then bringforward those that you serve to
be part of the due diligence,the governance process, and then
begin deploying it where youare best able.
And there's a whole piece toinfrastructure with AI, and so
that's where you're going toturn for most CIOs within their
own organization and make surethat your organization is ready

(13:33):
to start on a few AI projects asyou figure out best how to
capture AI for productivity andcontinue to keep your
organization thriving.

Mm-hmm, I agree with that.
I have this excitement, but Ihave this concern that People
and business business more sothan individual consumers.
I have two concerns.
One I feel like consumers areforced to speak up.

(14:11):
Speak out because things arehappening, and forced upon us
that if we don't, we're justgoing to get run over, and what
I'm getting to is AI tools andprivacy and protection of our

(14:33):
data.
I'm getting to all of thatbecause of the way that these
tools are being rolled out.
So we got tools that are numberone.
There's just like this influxof tools.
You don't know which one tochoose from.
You're like, okay, I want touse AI.
So this is.
This forces you to almost goback and think what is your,
what is your mission intent,because there are so many tools.

(14:53):
So that's number one is I'mconcerned as a consumer that I'm
not sure I'm being considered,but my other concern along those
lines is the tools aren'treally tested.
So not only is there an influxof tools I don't think that
they're I'm not making a blanketstatement that they're not

(15:15):
being tested but I feel likethey're leaning on us to do the
testing and quality assurancewithout informing us that, hey,
we are releasing a version thatis a test version only.
So please don't try to makebusiness decisions with this
tool because it isn't there yet.
We don't know that until westart seeing hallucinations and

(15:38):
wild outcomes and then we gettold.
So I have those two concerns andI want consumers to be
empowered.
So my take on it is back to twothings again.
One, the ethics board, so thegovernance boards.
Going back to the discussionaround ethics, are we too far

(15:59):
removed?
I mean we should be out therewith the consumers.
We should be out there withthose stakeholders in the
organization, understanding whatthey're going through, seeing,
feeling, knowing what they'regoing through so that they are
empowered and so that theleaders are proactive.
I don't know if that's going ontoday.

(16:21):
I want to push that more.

Renee Wynn (16:26):
I think that's right and part of that governance
process, as you pointed out, isthis ethics and business values
versus business value, and I'llcall it mission value.
Both you and I are government.
We called it mission, businessvalue and I'll call it mission
value.
Both you and I are government,we called it mission.
So let's separate the missionpurpose and begin with the

(16:47):
ethics and the business values.
One again part of the governanceprocess, and this is the due
diligence part of it.
So you've got to have yourethics folks and your
cybersecurity, supply chain riskmanagement folks, your supply
chain, you know, maybe othersupply chain expertise besides

(17:11):
cybersecurity sit at the tableas well as, I think, some other
capabilities at the table toreally evaluate what were the
ethics, what are the ethics ofour organization in bringing
this in?
United States government?
The privacy piece is definedfor us by law, which is great.

(17:31):
It's defined for manybusinesses.
You have the healthcareprofessions because they've got
the HIPAA privacy laws, so youcan go to, as part of the ethics
, the laws that govern how youneed to operate.
So any publicly traded company,they have a list of compliance
laws that they have to do.
Well, those ought to getcompared, you know, be part of

(17:55):
this ethics review, businessvalues review, that you do so
once you've identified a tool,an AI tool that you think works
with your ethics, the matchingof it.
Where was it trained?
Right, right An example theCIOs were all together and we

(18:15):
got a briefing on the ethics ofAI, and so this would have been
eight, nine years ago, and thewoman who spoke did her research
and got her PhD out of Harvardand looked at the results of the
ethics associated with facialrecognition.

(18:39):
So a complex thing to do, butit's only one aspect of what AI
can do to you.
And you and I, pam, as femalesmost of the time would not have
been recognized by these earlyfacial recognition models as

(18:59):
humans, because the models hadbeen trained on the internet and
most of the images out therethat were training them and this
is before Taylor Swift's bigexplosion and Beyonce's big you
know they are GDP.
Those two create blips,positive blips, in gross

(19:23):
domestic production in somecountries when they go visit.
So when I say they are aphenomenon, they are a
phenomenon.

This is pre-them.

Renee Wynn (19:32):
So most of the images were male and
predominantly white male.
So when those models started toget applied to female faces
different skin tones and colorsit could not recognize it as
human.
So can you imagine if youhadn't done the research right
and brought that in to rely onit or even test it?

(19:55):
You would have been, I hope,curious about your outcomes and
then go back and figure it out.
So, in this day and age, doyour research first so that when
you start in on your duediligence on a particular AI
provider I'm not going tomention any names that'll narrow

(20:16):
down what you're going to haveto focus on.
So that's the ethics side, andthen the business values.
How do you speak in yourorganization?
Right, and you want your tool,frankly, to mirror, or begin to
mirror, the language of and themethod by which you communicate

(20:37):
in your organization, becausepeople are going to start to
think of this thing as asentient being and therefore
you've got to raise and alignthe LLM that you're using on
your AI to match your businessvalues, so it begins to speak
the way you expect it to speak,because you and I know when

(21:00):
somebody is in a influentialposition in an organization and
they're in a cranky mood.
Most of the people around themfeel that cranky mood Right?
So your AI is in a cranky moodthat day or always displays
abrupt language, right?
That's going to start topermeate and affect the culture

(21:22):
of your organization.
So these are hard issues thatwe're bringing up, but they are
so key to the output andproductivity that you can gain.
And again, this goes back togovernance and frankly, I put it
free, it's governance, but it'salso having the right team
really doing the research on themodel, the large language model

(21:45):
or the product provider thatyou want to bring in to your
organization.
And these aren't easy, but theyare fun, right?
I mean, isn't doing hard fun?

hard fun For some people like me or used to be, I
don't know, I need things easynowadays.
But yeah, no, no, I agree withyou.
I like what you said and Ithink it is governance and it is
looking at that whole supplychain.
So governance is going to seeto it that we're looking across
the supply chain, that we'reevaluating what our supply chain
is for the AI models also, theintegrity of our supply chain.

(22:25):
It seems like that there's anopportunity for this
conversation really is turninginto a governance conversation.
It seems like there's anopportunity to strengthen the
governance playbook and thatwe're starting to highlight some
of those things that we shouldconsider deeper today than one

(22:48):
might be used to in traditionaldigital transformation projects.
Now, when you're saying whatyou're saying, I thought about
democratizing AI.
I know that it's important thatin order for I said earlier
that we want the ethics teamsand the governance teams to
understand what's happening inthe environment.

(23:09):
So, in order to do so maybe notnecessarily the board of
directors, but maybe someone'sgot to get out there and be with
the ones on the ground right,someone's got to understand and
make sure that all thecommunications is like it should
be and that we're consistent inour communications.
Then you also mentioned acommon vernacular, so that
business values are trulyunderstood.

(23:32):
So democratizing AI, then, isanother area that I think we
need to pay attention to,because we want the AI tools to
be accessible, and we want themto be accessible to all, not
just a group of people that'ssitting over here, and so that's
a tough issue to address, butthat's going to help build that

(23:55):
culture that we're talking about.
So, when you mentioned cultureearlier and working that culture
and dealing with the culturedynamics, I think that one thing
we have to think about is whatdoes democratizing AI really
mean, and what does it mean tomake it accessible to all,
because it's not good enough tojust say, ok, ok, the tool is

(24:17):
available.
That's not good enough, right?
So we got to make sure that isaccessible to all.
That is understandable.
Maybe they look at what are theproper tools?
How do we assess the tools?
How do we go about guidingpeople on how to use the tools?
So that's something that Ithink effective governance needs

(24:38):
to start to pay attention toand also look at the different
generations.
I'm not sure we're looking atthe generation.
So I had a situation a couple ofweeks ago and it's a client and
they wanted to use the toolthat they're using and they said
AI keeps popping up.

(24:58):
And I was like how do you knowthat it's AI?
Well, it just keeps popping upon my phone.
And I was like, okay, she'slike can you help me with this?
Because I don't have time todeal with it right now, because
I'm just trying to send amessage to somebody, and clearly
it was someone that wasn'tfamiliar with how to use some of

(25:19):
the other capabilities, but sheknew it was an AI chatbot
that's what it was, no doubt.
And so she was like I don'twant to use it.
I don't want to use it.
I think there needs to be moreattention paid to all
generations.
What do you think about that?

Renee Wynn (25:34):
Well, I think that's absolutely right and I'm going
to sort of distill this downwith any tool and, in particular
, ai, so let's talkorganizationally first and then
let's talk personally.
You have to do the training andhaving delivered that training
and I'm confident, pamela,you've delivered that training
People are like I don't want totake the training, just let me
dive in.
And for those folks that tookthe time to do the training and

(26:00):
we would provide entry levelmaybe we'll call it the college
level, the 101, up to thegraduate degrees of training for
various types of tool, and wewould do it in person and you
can do the on-demand videos.
Training is so key with AI Toyour point.
One is so people recognize ifyou've allowed this to be in

(26:25):
your everyday usage, well, let'ssay, in the email system, so
that people and what's going tohappen out of it, and so this is
where training becomes reallycritical and that way people
know how best to use it, theyunderstand that they are

(26:47):
training it and you cancoordinate off in your
organization.
So you're just training themodel that you're using in your
organization, not the global one.
We'll call it that.
So that's one side of the iseducation and training.
Well, it's much easier to speakabout and attempt to deliver in
an organization than it is inour personal lives.

(27:09):
We know across the globe thereis a difference of access to the
internet, and that differencein the internet access is a
difference of understandingwhat's going on with AI.
I'm just going to stay focusedon that.
And so if you come into contactwith AI for the first time and

(27:34):
you've not been able to do somereading on it or watch videos on
it or anything you know on thepersonal side, it could be
frightening for some and it'llbe energizing for others.
And out in our regular everydaylives, this is harder.
This is harder to get thetraining and if you rely on the

(27:56):
news, you're going to see thatit's only you know, depending on
your news source.
There's the one that's writingfear, fear, fear.
And then there's always a setof people that are in the media
that are writing do the research, but implore them to spread the
word and share with others tosay please do your research or

(28:28):
you be an advocate for that.
You know, offer educational tipsand stuff like that, because I
don't know how we're going toreach every person and let's
just make it in the UnitedStates, and I'll just narrow it
down to the state of Virginia,I'm not going to be able to do
it and that spectrum ofunderstanding of AI is in the

(28:49):
state of Virginia, just like itis in every state, and so there
is this responsibility to getpeople to pay attention and get
educated, and that's part of thedemocratizing the AI is
understanding what it is, whatit can do for you and what the
dangers are associated with it.
So and it's hard, this, I meanthis is easy for you and I to

(29:11):
talk to, because many times withIT, the methods for doing
something people process andtools yeah, okay, that's it.
But getting to the people,getting to an education level,
getting that people movementside is so hard to do that.
And AI is just bright, neonlight, screaming or saying to us

(29:37):
pay attention and get ready tolearn.

Exactly.
I believe that one of my otherguests or he said to me and
where they're going right, sohelp us reach and connect, and

(30:06):
then I have a follow-up.
You started to talk Mars and AI, so tell me more about this
Mars and AI.

Renee Wynn (30:14):
Yeah, so AI has been around for decades.
So AI has been around fordecades.
What we're seeing right now isAI at anyone's fingertips with a
computer or a mobile phone,because there's more people that
use mobile phones every daythan they do computers.
I'm a both person, and so NASAput AI on Mars in 2003.

(30:54):
So the rovers that are up thereas much as we might want to
imagine there's somebody downhere, just like they do with AI
and this learning and relearningon being on Mars, learning
about the terrain and how toadjust the terrain, just in
simple movement.
Recently, in 2020, nasa put thefirst ever helicopter on Mars.
Ingenuity was the name and itwent on the Perseverance launch

(31:17):
in 2020.
Perseverance was the rover.

You know I had a little bit to do with that,
right, you did tell me aboutthat, because of Spectrum,
because of Spectrum, yep, I hadno idea, yeah.

Renee Wynn (31:31):
So yes, spectrum management is a huge issue in
the IT world.
When you're flying, whetheryou're flying in an airplane or
in a spaceship, whether you'recommunicating, our whole
communications, radio systemsand all of that all have this
spectrum and that's just a wholeother topic in and of itself.
So AI are on these vehicles tohelp them learn, help them

(31:54):
advance science and help themoperate autonomously.
And it's a great thing becauseit's a long communication
timeframe from Earth to Mars andthen a lot of the it depends
upon solar access and stuff, andso Mars does have dark periods.
So communication is a challenge, if at all, if there isn't any

(32:18):
communication, and so AI isreally helpful to advance
missions in space.
In particular, we've beentalking about Mars, and since
2003, it's been there.
It just happens to be explodingacross Earth.
I like to remind people it'sEarth 1.0, and there is no 2.0
yet designated.
So I would also advocate thatwe should probably be treating

(32:41):
current Earth 1.0, mother Earth,a little bit better, because we
still don't have an option forall of us billions of people to
go somewhere else just yet.

Not yet.
Huh, no, not yet.
What's your take on generativeAI?
Since you're mentioning Marsand AI, what's generative AI?
Is it being updated or what'shappening.

Renee Wynn (33:04):
Absolutely.
You know, generative AI has thename generative, right.
It's like you and I, sometimesright, if I touch something hot
and it's red, then the next timeI see something red, I'm not
going to go reach right into itand do that, and so it's very
much a requirement, I think, ifyou're operating in harsh

(33:28):
environments and environmentsthat are incredibly remote and
Mars is a harsh environment andit is incredibly remote.
It doesn't seem like it becauseyou can look at images from it
every day, but it's a long wayaway from this planet.
But one of the things I reallylike about generative AI and the
application of AI is in thehealth field.

(33:50):
So one remote medicine andthere's remote medicine going on
ever since we had InternationalSpace Station, because the
astronauts' health is monitoredon a regular basis.
So you've got remote healthcare on Space Station.
We're seeing now across theglobe, and especially after

(34:10):
COVID, a lot more tools at theready for doctors and nurses to
work with us you and I, frankly,from home, and so this is where
I think AI is going to beincredibly helpful, as ethical
adoption of it happens in themedical field.

(34:32):
So if you're a rural doctor andyou're accustomed to a spectrum
of illnesses because of yourpopulation and somebody walks in
with an illness and you've doneall the testing and you've
concluded it's none of thethings that you thought about.
Well, this is where the AItools in healthcare can really
begin to help you, because youcould go to them with the

(34:56):
symptoms.
I wouldn't put the patient'sname in there, but you might
have to put information aboutgender and age and ethnicity,
because those do have a factorin disease susceptibility.
So for Black women, there is atype of breast cancer that is

(35:17):
incredibly aggressive thatyou're not seeing in general in
white women.
So here in this diagnosis case,right, understanding ethnicity
and race matters, because itcould be pretty potent what you
have, and so this is where theAI part can help with these

(35:37):
diagnosis, when you're hittingsomething that's particularly
unusual or you're just notaccustomed to seeing it, and so
I think it's got some realbenefits.

I was hearing the relationship between space and
remote monitoring of ourastronauts and for monitoring
their health, and then how thatalso parlayed into using AI to

(36:11):
diagnose and for remote care onearth.
Is that did I?
Okay, so, absolutely?
Is that right?
Okay, so, absolutely?
Did it start there?
Did it start with the space?
And then we started to modelthat remote health care and all
that from what happened with ourastronauts.
Is that you?

Renee Wynn (36:31):
know that's an interesting question, Pam.
I've never looked into this.
Space technology is part of it.
Space technology is part of it.
There's several elements of amobile phone that is technology
that was developed for space usethat is now used across the
planet in carrying a mobilephone, and there's all sorts of
technology in our daily livesthat become that.

(36:53):
But I never actually looked atthe correlation associated with
astronaut remote medicalmonitoring and how that may have
helped inform and lay thegroundwork for across Earth
remote medical providing.

(37:15):
I haven't looked into that, sothat'll be something for your
listeners and it'll certainly besome homework for me.

Okay, what I'd like to do is maybe have a follow-up
conversation with you, becauseI'd like to talk some more about
AI readiness and we kind of didthroughout this whole
discussion, but there were a fewmore things that we probably
could go into.
I know you had mentioned thequantum resistant encryption, so
what I'd like to do is give youtime to share your words of

(37:50):
wisdom and any other experienceswith us before we have to
depart here.
And then I wanted to remind usthat we want to pay attention to
technical debt.
So, in the traditional digitaltransformation system, lifecycle
AI development work you want tothink about that in the
governance realm and in the AIworld in particular, because you

(38:15):
cannot let the technical debtmount up.
You need to address that debtas soon as possible.
And then sometimes it's notcalled technical debt.
You know it's called ML debt orAI debt, but let's deal with
that technical debt, let'sunderstand what it is and let's
start to get our arms around.

(38:36):
What's going to remain.
That's the debt.
What's going to remain when itcomes to an issue that we're
going to set aside and deal withlater, or residual risk, right,
what is that?
And are we going back andmaking sure that we are
addressing these matters andthat we are monitoring things.
So, from a governanceperspective, we want to be sure

(38:57):
that we pay attention to thatand reflect back on the fact
that that has always been a partof our system development and
product development life cycle,and let's not let that go by the
wayside, especially today.
So now I'm going to give overto you.

Renee Wynn (39:13):
So, pamela, let's for our next conversation.
Let's talk about modernization,emerging tech which is quantum,
and AI can continue andadvancing the mission.
Yeah, you know, those are allall intertwined in all of that.
As we close out, I do want tothank you for the invitation to
talk to you.
It's always a treat to see you,my friend, and as we leave it

(39:35):
and we're going to talk aboutemerging tech and we've talked
today about AI and thegovernance, all in all, in
advancing anything within anorganization and within society,
it comes down to people.
Are the people ready to adaptand adopt, and are the people

(39:56):
ready to listen and be part ofit?
And what are you doing abouthelping people get ready for
change?

And I think that pretty much sums up this
conversation.
I'll add one more thing, andthat is be brave, get out of
yourself, just get out ofyourself, don't overthink it and
take the risk.
I think I want us to do more ofthat.
I want us to do exactly likewhat you said.
What you said is remember thepeople, so remember the human

(40:29):
side, and I think that that's soimportant because that's
missing, so you can be brave andtake care of people Absolutely.
Yeah, yeah, all right.
Well, it's great to talk to you.

All Episodes

E018 – AI or Not – Renee Wynn and Pamela Isom

Episode Transcript

Popular Podcasts

Bookmarked by Reese's Book Club

On Purpose with Jay Shetty

Dateline NBC