July 10, 2025 • 19 mins
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What happens when artificial intelligence meets higher education? The answer might surprise you. It's not just about new technology—it's about a complete cultural transformation.
Professor Angela Virtu from American University's Kogod School of Business reveals how their Institute for Applied Artificial Intelligence is reimagining business education from the ground up. Their revolutionary approach? Infusing AI into every single course while simultaneously strengthening the human skills that machines struggle to replicate. "Knowledge has become a commodity," she explains. "The differentiator now is critical thinking and communication."
The university's strategy goes beyond simply teaching students to use AI tools. They've created a community-driven learning environment where faculty receive extensive training first—bringing in industry experts to show professors exactly how AI is transforming their respective fields. This "train the trainer" approach has been crucial for faculty buy-in, especially when redesigning courses they may have taught for decades.
As entry-level jobs disappear and middle management structures face potential collapse, American University is preparing students for a radically different professional landscape. Their focus remains on developing capabilities that AI currently struggles with: handling ambiguity, navigating chaos, and facilitating cross-functional collaboration. While many universities still debate whether AI use constitutes cheating, American University has moved forward with partnerships like Perplexity that give every business student access to enterprise-level AI tools.
Want to understand how education is evolving in the age of artificial intelligence? This conversation provides a fascinating glimpse into the future of learning—where the most valuable skills might not be what you expect.
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Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Speaker 1 (00:01):
Hey everyone.
Fascinating chat today as wedive into the world of AI and
education.
Angela, how are you?
Speaker 2 (00:09):
I'm doing well.
Thanks for having me today,Evan.
Speaker 1 (00:12):
Thanks for being here , really excited for this chat
around AI, in particular, yourrole at the Institute of Applied
AI.
We're going to learn all aboutwhat that is, what does the
Institute do and why it wascreated.
First, maybe introductions toyourself, your role as a
professor at American Universityand a little bit about your
journey.
Speaker 2 (00:33):
Great.
So again, my name is AngelaVertu.
I'm a professor in our businessschool at American University,
where I teach mainly our machinelearning, business analytics
and artificial intelligencecourses.
Before I joined academia andcame full-time, I actually
worked at a whole bunch ofstartups in the DC metro area,
where I was owning andoperationalizing all of our
(00:54):
machine learning and artificialintelligence products and tools
Fantastic.
Speaker 1 (00:59):
And what is the Institute of Applied AI?
Sounds like a fascinatingentity.
Speaker 2 (01:05):
So we just launched the Institute for Applied
Artificial Intelligence thispast spring at the university
and we have three core pillarsthat we are working on doing to
really incorporate and continueinfusing it throughout the
entire business schoolcurriculum and education through
(01:25):
learning outcomes and reallymaking sure that all of our
students get AI infused andthey're prepared for their
future careers.
The second pillar of thisinstitute is all about AI
research and then the thirdpillar is all of our business
and policy community engagementpieces.
So we're really starting to tryto branch out into the greater
DC community and even expand theAI exposure on campus, right.
(01:47):
So Kogod was one of the firstones to do this AI push.
Now we're kind of going to allthe other colleges on our campus
to make sure that all of ourstudents, regardless of if
they're necessarily a businessmajor, has that AI touch.
Speaker 1 (01:59):
Brilliant.
So you worked in both educationand business and industry.
How has your industryexperience kind of shaped the
way you're teaching AI today?
Speaker 2 (02:12):
So I think there's two key components that has
really been helpful ininfluencing our AI approach.
The first one is just industrymoves at such a rapid pace,
especially when it comes totechnologies especially when it
comes to technologies and sowe've really been able to kind
of lean into that agiledevelopment and framework and
kind of accept, hey, ai is abrand new, uncharted territory,
especially when we startapplying that to our education
(02:33):
space, but really like, let'sjust roll with it, let's go
really quick and break things.
As you know, mark Zuckerbergalways says.
So we've really been able toapproach that in that manner.
And then I think the secondthing that's been super helpful
is because I come from thatbusiness world where I kind of
know what artificialintelligence is.
I built these tools, I know howthey get adopted.
We've been able to kind of cutstudents regardless of, you know
(03:06):
, if they're going to marketingor finance or accounting or
whatever their individualdiscipline is to make sure that
they're AI literate and fluent.
Speaker 1 (03:15):
Brilliant, and one thing you've said is that AI is
more about culture thantechnology, which I spend most
of my time talking about tech onthis show.
So what do you mean by culture?
Why is it so fundamental?
Speaker 2 (03:30):
Yeah.
So I think the interesting thingabout artificial intelligence,
and more specifically the likegenerative artificial
intelligence, is that the way inwhich we interact with it is
very unintuitive.
Right, the way you actually wantto interact with these
generative AI technologies is totreat it more like a human
right.
But when you pull up on yourscreen and you just have a
little chat box, it feels weirdto speak to it like a human.
(03:55):
So there's this thing in ourbrain that's like can't quite
process that this should betalked to like an intern or like
a peer or like a colleague,instead of being like we need to
code or like what's the exactright word to use to get it to
do this thing for us.
And so I think with that justkind of design thinking, there
(04:17):
comes a much larger culturalshift that has to come from the
businesses and the organizationsto adopt it right.
It's not like we're switchingfrom Tableau to Power BI, where
you can kind of just plug thisthing in and everyone knows what
to do.
It's just a few changes ofbuttons.
It's really rewiring our brainsand kind of having the approach
that things that used to beimpossible are actually possible
(04:39):
now.
So that's why I kind of getinto it that culture shift.
Speaker 1 (04:44):
Definitely would agree with you there.
And let's talk about howschools are teaching AI
firsthand.
You can tell us, of course, butwhat can we learn on teaching
AI in academia versus trainingteams in the enterprise,
training people in business, etcetera?
Speaker 2 (05:03):
people in business, et cetera.
So what we're doing at theKogod School of Business is that
we've infused AI into everysingle class, every single
course.
That way, every single student,regardless of what their major
or minor or application is, aregoing to get these core AI
literacy skills.
And the interesting thing thatwe're doing is we're coupling
those more technical AI skillsalong with very human
(05:25):
communication skills, so all ofour students are going to be
able to talk to each other,they're going to be able to
collaborate, they're going to beable to communicate, they're
going to be able to do thosehuman things that are going to
be much, much harder toreplicate in a technological
sense.
And I think the one thingthat's been super successful
with our AI integration is we'vebeen very community driven, and
that kind of speaks back tothat culture piece a little bit,
(05:46):
where learning is a very socialatmosphere.
Right, you can't just tellpeople go do this thing on their
own.
It just doesn't work.
You need to talk, you need tointeract with each other, you
need to learn from each other asto what's going on, and so I
think that's the one thing thatbusinesses can kind of you know,
maybe take from our academicsetting.
One thing that's been super,super helpful in our approach
(06:06):
within our community is weactually had a train the trainer
experience.
So about a year and a half ago,before we said, hey, let's put
this all into our curriculum, weunderstood that if our
professors you know, theindividuals who are actually
teaching our students don't knowwhat AI is and they don't know
how to use it and they don'tknow how to use it responsibly,
it'd be really, really hard forour students to have that
(06:26):
expectation of they're going tolearn that skillset.
So we, a year and a half ago,brought in a whole bunch of
alumni and individuals inindustry.
So we brought someone in fromthe financial banking industry
to come in and kind of showcaseand demo exactly how they're
using artificial intelligencewithin their industry.
And kind of showcase and demoexactly how they're using
artificial intelligence withintheir industry.
(06:46):
And our finance team, like theirjaws, were on the floor, like
they were floored by what AIcould actually do from a finance
perspective.
We did the same thing withmarketing.
We did the same thing withaccounting, all of our
individual programs.
We brought people from industryto basically say, hey, this is
how this is completely changingour world and what that was
really able to do is get thebuy-in from the professors to
say, hey, I know I might havebeen teaching this for 20 years,
(07:08):
30 years, 40 years, butcompanies are changing today and
so having that buy-in, havingthat community, has been super,
super helpful in just learningwhat to do with this.
Speaker 1 (07:20):
Fantastic, and we're all a bit overwhelmed by the
requirement to upskill and learnnew AI skills.
It's really overwhelming,especially for younger
professionals.
What do you recommend in termsof the top AI skills younger or
older folks should be focused onright now?
Speaker 2 (07:40):
Yeah, so I think the interesting thing with this
generative AI push is thatknowledge has become a commodity
right.
It's completely at yourfingertips.
There's no longer this likehard eclipse of getting
knowledge.
It's just there and there'svast, vast, vast quantities of
it on if I was either startingschool right now or even trying
(08:07):
to upskill.
The first one is communicationright, because, as I talked
about even before, like, themore human you can speak to
these generative AI systems, themore clear your instructions
are going to be, the better yourresults will actually be at the
outcome, right.
So having really goodcommunication skills, not just
with each other but within theAI systems itself, I think is a
good piece.
And then the second piece isjust curiosity, like, can you
(08:29):
ask really good questions?
Do you have an insatiablethirst to kind of get to the
final answer, and so all of thatcombines really creates your
critical thinking.
And I think if you can siftthrough what's right, what's
wrong, and really start goingfrom is this thing possible to
building the correct thing, thatwill be that differentiator.
Speaker 1 (08:49):
That's fantastic.
And what's a big myth or twoabout AI that you wish more
people understood from readingthe press or the headlines we're
all gathering today?
Speaker 2 (09:02):
So the first one and I think this comes more from my
teacher hat than maybe mybusiness hat, but AI can be
wrong, and I think this comesmore for my teacher hot than
maybe my business hot, but AIcan be wrong and it's okay.
I have a lot of students in myvery first class and they teach
my freshmen is that they said,oh, I got this from AI, it must
be right, and they just don'teven like think about it, right.
So I think the first thing isjust test the boundaries right,
like where's one area, if you'restarting from scratch, that you
(09:25):
are an expert in Maybe it'sballet, maybe it's football,
maybe it's golf, I don't knowand have a small conversation
with the AI where you can starttesting the boundaries and
fact-checking and once youunderstand it's not always right
, come up with your system tosay, hey, does this always have
to be right?
What's the risk if it's not?
And if it is in fact incorrect,how would I maybe know about
(09:48):
that right?
So that goes back to thatcritical thinking piece.
The second thing that I thinkis a little bit of a myth, or
maybe a hope for me is I reallywant us to kind of get to a new
user experience with AI, right,I think the chat functionality
is not the best way to do iteither typing or with voice and
(10:08):
I think we're going to startseeing this new interface of how
we interact with the world ofcomputers and technology soon.
I don't know what that wouldlook like, but that, I think, is
what I'm most excited for andmaybe aspirational for.
Speaker 1 (10:23):
Oh well said, oh well said.
So, as you know, there's agrowing concern about AI
replacing white-collar jobs inparticular, especially the roles
that business students aretraining for, studying for, and
lots of entry-level jobs.
How do you prepare to competewith AI?
Speaker 2 (10:44):
or are you talking about working beside it, or both
?
So I think right now, what we'reseeing is the immediate
collapse of the first levelentry jobs.
Right, there's been lots ofconversation, lots of numbers
supporting that narrative.
I think the next stage of thatis going to be we're going to
see a collapse of the entiremiddle management structure
(11:05):
because AI can do that.
So we're going to have lots oflarge organizations that are
going to reduce and becomereally, really flat and at the
same time, the jump from ahigher education institution
into your first job is going tobe significantly widening.
Right, because now you can lookat, like KPMG, but their first
year analysts are now doing thework of years two and three
analysts that typically do thatwork.
(11:26):
So I think, as we think aboutthat preparation and the future
of work, it really comes backdown to like can you handle
messiness, can you handle thechaos that these ai systems
aren't great at just yet, andcan you do that cross-functional
collaboration right?
I think those are going to bethe two areas where, if you have
success in those domains, it'llbe harder to argue why you
(11:51):
shouldn't have that necessaryjob.
Speaker 1 (11:55):
Yeah, it's going to be an interesting one to watch.
So you're clearly moving atfast pace at American University
, but do you think universitiesare at risk of falling behind in
adopting and changing withthese tools?
What's your state of the union,as it were, for higher
education?
Speaker 2 (12:15):
So it's still very much a mixed bag, I would say.
Every single day I still haveto have conversations of why
using AI for a college studentisn't necessarily cheating.
And then when you have reportscoming out from MIT where they
did a study that you know a lotof people will synthesize is
just saying, oh like, using AIactually is like horrible for
you and it makes you not thinkand things of that nature kind
(12:36):
of just like makes thatconversation a little bit harder
.
I would say I see lots ofpromise.
So you know, obviously we'regoing to plug American
University, what we're doing atCobot and really infusing AI and
embracing AI and making all ofour students AI literate.
But there's also really goodwork going on at, like, babson
College doing the exact samestuff.
So there's pockets of hope, Iwould say, where we're really on
(12:58):
board and we understand AI isnot something we can hide from
and it's not something that wecan just kind of shove under the
rug and forget.
But at the same time, there'sthere's lots of institutions
where the conversation is stillwe're banning AI, we can't use
it, it's horrible, and a lot ofit just stems to.
It's a lot of work, right, wehave to redesign the way we
(13:23):
think of teaching.
We have to redesign ourpedagogy, we have to rethink our
assignments and the way wedeliver curriculum right, so
that student experience and theexpectations of how to work
through the learning process ischanging and there's no real
clear definitive.
This is exactly how it'ssupposed to look.
Right, your definitive.
(13:46):
This is exactly how it'ssupposed to look right.
Speaker 1 (13:47):
So it's challenging For sure, and I guess it's
questioning everything.
Everyone's questioningeverything, including their
majors.
Some evidence that computerscience majors are having a
tough time with all of the newAI coding tools on the market.
Again, those entry-level rolesare being hit.
(14:07):
Are you seeing that in terms ofchoices around majors and areas
of study based on what might ormay not happen with AI?
Speaker 2 (14:18):
So from the business school I can't speak to our
computer science numbers orenrollment too much, so I don't
know what the full metrics looklike exactly on our campus for
that.
Speaker 1 (14:30):
Yeah, well, that makes sense.
What about business and finance, where you know increasingly,
you know, learning Excel and theold school tools won't be
enough to compete.
School tools won't be enough tocompete.
How will data science and thesuite of tools that you use in
(14:51):
the future look and feeldifferent from what?
The tools that we've alllearned for, even in business
and finance, for managing thebusiness and P&L and forecasting
, et cetera, et cetera?
Speaker 2 (15:02):
Yeah, I mean we just announced a partnership with
proplexity and for the financespace in particular.
They have a really, reallyimpressive like financial
analysis tool that they'velaunched and have announced, so
we're trying to start to getinto there.
We also have an fsit lab wherewe have access to bloomberg
terminals with for our studentsto have access to.
So I would say, like the, thetooling has always been one
(15:25):
piece of the educational puzzle,right?
Because?
as you start to prepare ourstudents for industry.
Obviously it's not just whatyou know, but it's the tools and
how you actually can get thework done.
So I think we're alwaysrevisiting what that next three
to five year horizon of whattools should be, or what our
students need in terms of thosecore competencies, and horizon
(15:45):
of what tools should be or whatour students need in terms of
those core competencies, and wehave really good partnerships
with industry and we have likepanels to basically give us
feedback of.
You know, hey, actually we'reall using this thing now, or
this is the new tool or this isthe new skill set that our
students are going to beexpected to know.
But again, I just want tounderscore that our approach to
AI has always been what arethose core fundamental skills
(16:05):
that, regardless of what toolwe're using, they can then kind
of navigate their way throughthe functionality or the tooling
of it?
Speaker 1 (16:15):
Well said.
And of course, there are a lotof AI ethics landmines out there
to navigate.
How do you think about teachingstudents to build and use AI
responsibly?
Speaker 2 (16:27):
So that's throughout the entire curriculum, or we
really want them to beresponsible stewards.
So I think that comes from anunderstanding of how AI actually
works, what the limitations ofthe AI are, and that includes
some of the biases of theunderlying training materials,
include some of the biases ofthe underlying training
materials.
We have an entire businessethics class that has a lot of
(16:48):
AI incorporated into that aswell.
So I think our students are,you know, having the
conversations of, you know,examples of good AI, bad AI,
everything in between.
We have a really strongbusiness and entertainment
program where they've beentalking a lot about the
intersection between AI andentertainment.
So the whole writer's strike ayear ago now, my calendar is a
(17:11):
little questionable but, I,think a year ago, the strike,
after the strike, a lot of thathad to do with AI.
Is it okay for us to cloneactors' voices, or what about
voice actors If you can just usesomething like 11 labs to
basically do all the vocal workfor a video game or for a movie
or something along those lines?
So we have lots of room forthose conversations fantastic.
Speaker 1 (17:34):
So what are you looking uh forward to in the new
year?
Uh, school year coming up.
What's on your radar?
What are you excited about?
Speaker 2 (17:42):
we have a lot going on.
We've been working really hardthis summer.
I think the first really bigthing is we're introducing AI
learning outcomes for all of ourindividual classes and for all
of our individual programs.
So we've taken a really hardlook as to how have we
traditionally approachedlearning outcomes, what are
those core skill sets that havebeen needed, what are the
(18:03):
methodologies of how we wouldmark that skill set and
progression?
And now we're really taking afine tooth comb through what ai
skills do we need?
And of the existing skill setlike what, what changes now with
ai?
So I think we're really excitedabout the progress we've made
there.
We also this past springannounced a partnership with
perplexity, um, and so we'rereally.
(18:24):
We launched that march of ourspring semester, so about
halfway through.
So this will be, our first fullsemester where we can really
have every single student,faculty and staff within our
kogod school of business to haveaccess to enterprise level of
artificial intelligence.
So we're going to see a much,much deeper infusion of ai being
used as tutors, ai being usedas a thought partner, ai being
(18:47):
used as a learning vehicle inall of our classes this fall,
which I think is super, superexciting.
Speaker 1 (18:53):
Fantastic.
Well, it may be time for me togo back to school.
That would be a scary thought,but wonderful stuff.
Congratulations on the programand all the success onwards and
upwards.
Thanks Angela, thanks Evan.
Thanks everyone for listening,watching, sharing the episode
and check out our new TV shownow on Fox Business and
Bloomberg at techimpacttv.
(19:13):
Thanks everyone.
Hey everyone.
Fascinating chat today as wedive into the world of AI and
education.
Angela, how are you?
Speaker 2 (00:09):
I'm doing well.
Thanks for having me today,Evan.
Speaker 1 (00:12):
Thanks for being here , really excited for this chat
around AI, in particular, yourrole at the Institute of Applied
AI.
We're going to learn all aboutwhat that is, what does the
Institute do and why it wascreated.
First, maybe introductions toyourself, your role as a
professor at American Universityand a little bit about your
journey.
Speaker 2 (00:33):
Great.
So again, my name is AngelaVertu.
I'm a professor in our businessschool at American University,
where I teach mainly our machinelearning, business analytics
and artificial intelligencecourses.
Before I joined academia andcame full-time, I actually
worked at a whole bunch ofstartups in the DC metro area,
where I was owning andoperationalizing all of our
(00:54):
machine learning and artificialintelligence products and tools
Fantastic.
Speaker 1 (00:59):
And what is the Institute of Applied AI?
Sounds like a fascinatingentity.
Speaker 2 (01:05):
So we just launched the Institute for Applied
Artificial Intelligence thispast spring at the university
and we have three core pillarsthat we are working on doing to
really incorporate and continueinfusing it throughout the
entire business schoolcurriculum and education through
(01:25):
learning outcomes and reallymaking sure that all of our
students get AI infused andthey're prepared for their
future careers.
The second pillar of thisinstitute is all about AI
research and then the thirdpillar is all of our business
and policy community engagementpieces.
So we're really starting to tryto branch out into the greater
DC community and even expand theAI exposure on campus, right.
(01:47):
So Kogod was one of the firstones to do this AI push.
Now we're kind of going to allthe other colleges on our campus
to make sure that all of ourstudents, regardless of if
they're necessarily a businessmajor, has that AI touch.
Speaker 1 (01:59):
Brilliant.
So you worked in both educationand business and industry.
How has your industryexperience kind of shaped the
way you're teaching AI today?
Speaker 2 (02:12):
So I think there's two key components that has
really been helpful ininfluencing our AI approach.
The first one is just industrymoves at such a rapid pace,
especially when it comes totechnologies especially when it
comes to technologies and sowe've really been able to kind
of lean into that agiledevelopment and framework and
kind of accept, hey, ai is abrand new, uncharted territory,
especially when we startapplying that to our education
(02:33):
space, but really like, let'sjust roll with it, let's go
really quick and break things.
As you know, mark Zuckerbergalways says.
So we've really been able toapproach that in that manner.
And then I think the secondthing that's been super helpful
is because I come from thatbusiness world where I kind of
know what artificialintelligence is.
I built these tools, I know howthey get adopted.
We've been able to kind of cutstudents regardless of, you know
(03:06):
, if they're going to marketingor finance or accounting or
whatever their individualdiscipline is to make sure that
they're AI literate and fluent.
Speaker 1 (03:15):
Brilliant, and one thing you've said is that AI is
more about culture thantechnology, which I spend most
of my time talking about tech onthis show.
So what do you mean by culture?
Why is it so fundamental?
Speaker 2 (03:30):
Yeah.
So I think the interesting thingabout artificial intelligence,
and more specifically the likegenerative artificial
intelligence, is that the way inwhich we interact with it is
very unintuitive.
Right, the way you actually wantto interact with these
generative AI technologies is totreat it more like a human
right.
But when you pull up on yourscreen and you just have a
little chat box, it feels weirdto speak to it like a human.
(03:55):
So there's this thing in ourbrain that's like can't quite
process that this should betalked to like an intern or like
a peer or like a colleague,instead of being like we need to
code or like what's the exactright word to use to get it to
do this thing for us.
And so I think with that justkind of design thinking, there
(04:17):
comes a much larger culturalshift that has to come from the
businesses and the organizationsto adopt it right.
It's not like we're switchingfrom Tableau to Power BI, where
you can kind of just plug thisthing in and everyone knows what
to do.
It's just a few changes ofbuttons.
It's really rewiring our brainsand kind of having the approach
that things that used to beimpossible are actually possible
(04:39):
now.
So that's why I kind of getinto it that culture shift.
Speaker 1 (04:44):
Definitely would agree with you there.
And let's talk about howschools are teaching AI
firsthand.
You can tell us, of course, butwhat can we learn on teaching
AI in academia versus trainingteams in the enterprise,
training people in business, etcetera?
Speaker 2 (05:03):
people in business, et cetera.
So what we're doing at theKogod School of Business is that
we've infused AI into everysingle class, every single
course.
That way, every single student,regardless of what their major
or minor or application is, aregoing to get these core AI
literacy skills.
And the interesting thing thatwe're doing is we're coupling
those more technical AI skillsalong with very human
(05:25):
communication skills, so all ofour students are going to be
able to talk to each other,they're going to be able to
collaborate, they're going to beable to communicate, they're
going to be able to do thosehuman things that are going to
be much, much harder toreplicate in a technological
sense.
And I think the one thingthat's been super successful
with our AI integration is we'vebeen very community driven, and
that kind of speaks back tothat culture piece a little bit,
(05:46):
where learning is a very socialatmosphere.
Right, you can't just tellpeople go do this thing on their
own.
It just doesn't work.
You need to talk, you need tointeract with each other, you
need to learn from each other asto what's going on, and so I
think that's the one thing thatbusinesses can kind of you know,
maybe take from our academicsetting.
One thing that's been super,super helpful in our approach
(06:06):
within our community is weactually had a train the trainer
experience.
So about a year and a half ago,before we said, hey, let's put
this all into our curriculum, weunderstood that if our
professors you know, theindividuals who are actually
teaching our students don't knowwhat AI is and they don't know
how to use it and they don'tknow how to use it responsibly,
it'd be really, really hard forour students to have that
(06:26):
expectation of they're going tolearn that skillset.
So we, a year and a half ago,brought in a whole bunch of
alumni and individuals inindustry.
So we brought someone in fromthe financial banking industry
to come in and kind of showcaseand demo exactly how they're
using artificial intelligencewithin their industry.
And kind of showcase and demoexactly how they're using
artificial intelligence withintheir industry.
(06:46):
And our finance team, like theirjaws, were on the floor, like
they were floored by what AIcould actually do from a finance
perspective.
We did the same thing withmarketing.
We did the same thing withaccounting, all of our
individual programs.
We brought people from industryto basically say, hey, this is
how this is completely changingour world and what that was
really able to do is get thebuy-in from the professors to
say, hey, I know I might havebeen teaching this for 20 years,
(07:08):
30 years, 40 years, butcompanies are changing today and
so having that buy-in, havingthat community, has been super,
super helpful in just learningwhat to do with this.
Speaker 1 (07:20):
Fantastic, and we're all a bit overwhelmed by the
requirement to upskill and learnnew AI skills.
It's really overwhelming,especially for younger
professionals.
What do you recommend in termsof the top AI skills younger or
older folks should be focused onright now?
Speaker 2 (07:40):
Yeah, so I think the interesting thing with this
generative AI push is thatknowledge has become a commodity
right.
It's completely at yourfingertips.
There's no longer this likehard eclipse of getting
knowledge.
It's just there and there'svast, vast, vast quantities of
it on if I was either startingschool right now or even trying
(08:07):
to upskill.
The first one is communicationright, because, as I talked
about even before, like, themore human you can speak to
these generative AI systems, themore clear your instructions
are going to be, the better yourresults will actually be at the
outcome, right.
So having really goodcommunication skills, not just
with each other but within theAI systems itself, I think is a
good piece.
And then the second piece isjust curiosity, like, can you
(08:29):
ask really good questions?
Do you have an insatiablethirst to kind of get to the
final answer, and so all of thatcombines really creates your
critical thinking.
And I think if you can siftthrough what's right, what's
wrong, and really start goingfrom is this thing possible to
building the correct thing, thatwill be that differentiator.
Speaker 1 (08:49):
That's fantastic.
And what's a big myth or twoabout AI that you wish more
people understood from readingthe press or the headlines we're
all gathering today?
Speaker 2 (09:02):
So the first one and I think this comes more from my
teacher hat than maybe mybusiness hat, but AI can be
wrong, and I think this comesmore for my teacher hot than
maybe my business hot, but AIcan be wrong and it's okay.
I have a lot of students in myvery first class and they teach
my freshmen is that they said,oh, I got this from AI, it must
be right, and they just don'teven like think about it, right.
So I think the first thing isjust test the boundaries right,
like where's one area, if you'restarting from scratch, that you
(09:25):
are an expert in Maybe it'sballet, maybe it's football,
maybe it's golf, I don't knowand have a small conversation
with the AI where you can starttesting the boundaries and
fact-checking and once youunderstand it's not always right
, come up with your system tosay, hey, does this always have
to be right?
What's the risk if it's not?
And if it is in fact incorrect,how would I maybe know about
(09:48):
that right?
So that goes back to thatcritical thinking piece.
The second thing that I thinkis a little bit of a myth, or
maybe a hope for me is I reallywant us to kind of get to a new
user experience with AI, right,I think the chat functionality
is not the best way to do iteither typing or with voice and
(10:08):
I think we're going to startseeing this new interface of how
we interact with the world ofcomputers and technology soon.
I don't know what that wouldlook like, but that, I think, is
what I'm most excited for andmaybe aspirational for.
Speaker 1 (10:23):
Oh well said, oh well said.
So, as you know, there's agrowing concern about AI
replacing white-collar jobs inparticular, especially the roles
that business students aretraining for, studying for, and
lots of entry-level jobs.
How do you prepare to competewith AI?
Speaker 2 (10:44):
or are you talking about working beside it, or both
?
So I think right now, what we'reseeing is the immediate
collapse of the first levelentry jobs.
Right, there's been lots ofconversation, lots of numbers
supporting that narrative.
I think the next stage of thatis going to be we're going to
see a collapse of the entiremiddle management structure
(11:05):
because AI can do that.
So we're going to have lots oflarge organizations that are
going to reduce and becomereally, really flat and at the
same time, the jump from ahigher education institution
into your first job is going tobe significantly widening.
Right, because now you can lookat, like KPMG, but their first
year analysts are now doing thework of years two and three
analysts that typically do thatwork.
(11:26):
So I think, as we think aboutthat preparation and the future
of work, it really comes backdown to like can you handle
messiness, can you handle thechaos that these ai systems
aren't great at just yet, andcan you do that cross-functional
collaboration right?
I think those are going to bethe two areas where, if you have
success in those domains, it'llbe harder to argue why you
(11:51):
shouldn't have that necessaryjob.
Speaker 1 (11:55):
Yeah, it's going to be an interesting one to watch.
So you're clearly moving atfast pace at American University
, but do you think universitiesare at risk of falling behind in
adopting and changing withthese tools?
What's your state of the union,as it were, for higher
education?
Speaker 2 (12:15):
So it's still very much a mixed bag, I would say.
Every single day I still haveto have conversations of why
using AI for a college studentisn't necessarily cheating.
And then when you have reportscoming out from MIT where they
did a study that you know a lotof people will synthesize is
just saying, oh like, using AIactually is like horrible for
you and it makes you not thinkand things of that nature kind
(12:36):
of just like makes thatconversation a little bit harder
.
I would say I see lots ofpromise.
So you know, obviously we'regoing to plug American
University, what we're doing atCobot and really infusing AI and
embracing AI and making all ofour students AI literate.
But there's also really goodwork going on at, like, babson
College doing the exact samestuff.
So there's pockets of hope, Iwould say, where we're really on
(12:58):
board and we understand AI isnot something we can hide from
and it's not something that wecan just kind of shove under the
rug and forget.
But at the same time, there'sthere's lots of institutions
where the conversation is stillwe're banning AI, we can't use
it, it's horrible, and a lot ofit just stems to.
It's a lot of work, right, wehave to redesign the way we
(13:23):
think of teaching.
We have to redesign ourpedagogy, we have to rethink our
assignments and the way wedeliver curriculum right, so
that student experience and theexpectations of how to work
through the learning process ischanging and there's no real
clear definitive.
This is exactly how it'ssupposed to look.
Right, your definitive.
(13:46):
This is exactly how it'ssupposed to look right.
Speaker 1 (13:47):
So it's challenging For sure, and I guess it's
questioning everything.
Everyone's questioningeverything, including their
majors.
Some evidence that computerscience majors are having a
tough time with all of the newAI coding tools on the market.
Again, those entry-level rolesare being hit.
(14:07):
Are you seeing that in terms ofchoices around majors and areas
of study based on what might ormay not happen with AI?
Speaker 2 (14:18):
So from the business school I can't speak to our
computer science numbers orenrollment too much, so I don't
know what the full metrics looklike exactly on our campus for
that.
Speaker 1 (14:30):
Yeah, well, that makes sense.
What about business and finance, where you know increasingly,
you know, learning Excel and theold school tools won't be
enough to compete.
School tools won't be enough tocompete.
How will data science and thesuite of tools that you use in
(14:51):
the future look and feeldifferent from what?
The tools that we've alllearned for, even in business
and finance, for managing thebusiness and P&L and forecasting
, et cetera, et cetera?
Speaker 2 (15:02):
Yeah, I mean we just announced a partnership with
proplexity and for the financespace in particular.
They have a really, reallyimpressive like financial
analysis tool that they'velaunched and have announced, so
we're trying to start to getinto there.
We also have an fsit lab wherewe have access to bloomberg
terminals with for our studentsto have access to.
So I would say, like the, thetooling has always been one
(15:25):
piece of the educational puzzle,right?
Because?
as you start to prepare ourstudents for industry.
Obviously it's not just whatyou know, but it's the tools and
how you actually can get thework done.
So I think we're alwaysrevisiting what that next three
to five year horizon of whattools should be, or what our
students need in terms of thosecore competencies, and horizon
(15:45):
of what tools should be or whatour students need in terms of
those core competencies, and wehave really good partnerships
with industry and we have likepanels to basically give us
feedback of.
You know, hey, actually we'reall using this thing now, or
this is the new tool or this isthe new skill set that our
students are going to beexpected to know.
But again, I just want tounderscore that our approach to
AI has always been what arethose core fundamental skills
(16:05):
that, regardless of what toolwe're using, they can then kind
of navigate their way throughthe functionality or the tooling
of it?
Speaker 1 (16:15):
Well said.
And of course, there are a lotof AI ethics landmines out there
to navigate.
How do you think about teachingstudents to build and use AI
responsibly?
Speaker 2 (16:27):
So that's throughout the entire curriculum, or we
really want them to beresponsible stewards.
So I think that comes from anunderstanding of how AI actually
works, what the limitations ofthe AI are, and that includes
some of the biases of theunderlying training materials,
include some of the biases ofthe underlying training
materials.
We have an entire businessethics class that has a lot of
(16:48):
AI incorporated into that aswell.
So I think our students are,you know, having the
conversations of, you know,examples of good AI, bad AI,
everything in between.
We have a really strongbusiness and entertainment
program where they've beentalking a lot about the
intersection between AI andentertainment.
So the whole writer's strike ayear ago now, my calendar is a
(17:11):
little questionable but, I,think a year ago, the strike,
after the strike, a lot of thathad to do with AI.
Is it okay for us to cloneactors' voices, or what about
voice actors If you can just usesomething like 11 labs to
basically do all the vocal workfor a video game or for a movie
or something along those lines?
So we have lots of room forthose conversations fantastic.
Speaker 1 (17:34):
So what are you looking uh forward to in the new
year?
Uh, school year coming up.
What's on your radar?
What are you excited about?
Speaker 2 (17:42):
we have a lot going on.
We've been working really hardthis summer.
I think the first really bigthing is we're introducing AI
learning outcomes for all of ourindividual classes and for all
of our individual programs.
So we've taken a really hardlook as to how have we
traditionally approachedlearning outcomes, what are
those core skill sets that havebeen needed, what are the
(18:03):
methodologies of how we wouldmark that skill set and
progression?
And now we're really taking afine tooth comb through what ai
skills do we need?
And of the existing skill setlike what, what changes now with
ai?
So I think we're really excitedabout the progress we've made
there.
We also this past springannounced a partnership with
perplexity, um, and so we'rereally.
(18:24):
We launched that march of ourspring semester, so about
halfway through.
So this will be, our first fullsemester where we can really
have every single student,faculty and staff within our
kogod school of business to haveaccess to enterprise level of
artificial intelligence.
So we're going to see a much,much deeper infusion of ai being
used as tutors, ai being usedas a thought partner, ai being
(18:47):
used as a learning vehicle inall of our classes this fall,
which I think is super, superexciting.
Speaker 1 (18:53):
Fantastic.
Well, it may be time for me togo back to school.
That would be a scary thought,but wonderful stuff.
Congratulations on the programand all the success onwards and
upwards.
Thanks Angela, thanks Evan.
Thanks everyone for listening,watching, sharing the episode
and check out our new TV shownow on Fox Business and
Bloomberg at techimpacttv.
(19:13):
Thanks everyone.
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