December 2, 2025 • 55 mins
On this episode of the Sell Me This Podcast, host Keith Daser talks with Dr. Stella Lee. The conversation explores how organizations can build real AI literacy, why policy matters more than ever, and what it takes to prepare people for a future shaped by intelligent technology.
Dr. Lee breaks down the difference between understanding AI in theory and using it responsibly in practice. She shares insights on how schools, businesses, and governments can approach education and policy with clarity, intention, and long-term thinking. They also discuss how leaders can empower teams with the skills and confidence needed to work alongside AI in meaningful ways.
Whether you are designing learning programs, shaping policy, or navigating AI adoption inside your organization, this episode delivers a practical perspective from one of the field’s most trusted voices.
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If you believe you deserve more from your technology partnerships – connect with the team at:
https://www.deliverdigital.ca/?utm_source=videodescription&utm_id=youtube
Sell Me This Podcast is brought to you by the team at Deliver Digital, a Calgary-based consulting organization that guides progressive companies through the selection, implementation, and governance of key technology partnerships. Their work is transforming the technology solution and software provider landscape by helping organizations reduce costs and duplication, enhance vendor alignment, and establish sustainable operating models that empower digital progress.
This episode of the Sell Me This Podcast was expertly edited, filmed, and produced by Laila Hobbs and Bretten Roissl of Social Launch Labs, who deliver top-tier storytelling and technical excellence. A special thanks to the entire team for their dedication to crafting compelling content that engages, connects, and inspires.
Find the team at Social Launch Labs at:
www.sociallaunchlabs.com
Sell Me This Podcast is brought to you by the team at Deliver Digital, a Calgary-based consulting organization that guides progressive companies through the selection, implementation, and governance of key technology partnerships. Their work is transforming the technology solution and software provider landscape by helping organizations reduce costs and duplication, enhance vendor alignment, and establish sustainable operating models that empower digital progress.
If you believe you deserve more from your technology partnerships – connect with the team at:
www.deliverdigital.ca
This episode of Sell Me This Podcast was expertly edited, filmed, and produced by Laila Hobbs and Bretten Roissl of Social Launch Labs, who deliver top-tier storytelling and technical excellence. A special thanks to the entire team for their dedication to crafting compelling content that engages, connects, and inspires.
Find the team at Social Launch Labs at:
www.sociallaunchlabs.com
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
SPEAKER_02 (00:00):
I think everybody needs to get involved and first
have a baseline understandingand to have that voice out there
to shape actively on how thistechnology is going to develop
and impact us.
SPEAKER_00 (00:20):
Welcome to another episode of Sell Me This Podcast.
This week I am incrediblyexcited to welcome our guest,
Dr.
Stella Lee.
Stella and I dive into anincredibly exciting conversation
around education, aroundgovernment policy and AI, and
around what business leaders cando to make meaningful steps in
implementing these technologiesin their business.
I hope you enjoy.
(00:41):
So welcome to another episode ofSell Me This Podcast.
Today I'm incredibly excited tohave our guest, Dr.
Stella Lee.
I promise it's the only timethat I'll mention the doctor off
the bat for formalities.
Thank you.
I have been looking forward tothis episode for a while.
You and I met um at an untappeduh energy AI summit.
Um, probably about a month ortwo ago, and and I was blown
(01:05):
away by everything that youshared.
It was immediately clear to methat we were um we saw the world
in a similar way, and so thankyou for agreeing to be on the
show.
SPEAKER_02 (01:13):
Thanks for having me.
SPEAKER_00 (01:14):
Um for our listeners, um, I'd love to just
jump right into things.
And if you could give maybe aquick introduction of who you
are, um the the work that youdo, and um we maybe we can start
there.
SPEAKER_02 (01:25):
Okay, um I'm Stella.
I run a boutique, as I like tocall it, consulting firm.
It's it's me and a couple ofstaff uh called Paradox
Learning, and it's based inCalgary.
I work, um, oh gosh, I done somany different projects from
NGOs like the United Nations togovernments like Yukon
(01:46):
government to small, mediumenterprise organizations, uh
primarily in digital learningand education tech space.
Um these days it's all about AI,so I happen to also have a
background in that, so I do allthe consulting in that in that
way.
I came from an academicbackground, so I don't know if
(02:06):
you know this, but I wastraining as a painter.
I did not and a designer.
So um, and I kind of find my wayinto um computer science, so I I
have a BFA and I end up gettinga PhD in computer science.
And so I was an academic and Ilike to call myself a now
reformed academic turnconsultant.
SPEAKER_00 (02:26):
Yeah, you've you've recovered from the academic side
of things.
SPEAKER_02 (02:29):
Almost.
SPEAKER_00 (02:30):
And so you I actually didn't know that you
were a painter, but we we haveum It's my love for art.
I know we have our tradition onthe show where where uh you know
the guest gets to pick theartwork behind us.
SPEAKER_02 (02:41):
I love that.
Yeah.
SPEAKER_00 (02:42):
And so can you tell us about this piece?
SPEAKER_02 (02:44):
Like I I'm I'm blissfully ignorant on a lot of
art stuff, but um I don'tactually know this piece, but I
just was drawing I I my love isactually in in modern or
contemporary art, so anything20th century or kind of late
19th century onwards.
So I really love um abstract, umbold, kind of um very expressive
(03:07):
kind of strokes and colors andjust essentially pushing the
limit of what we call art,right?
SPEAKER_00 (03:14):
So I love it, and and and I love the combination
as well, and I'm sure it givesyou a really interesting
perspective of having that thatartistic and creative side along
with the the more digitaltechnology side from your comp
sci um studies.
How do those things blendtogether?
And I imagine it gives you areally interesting view of the
world.
SPEAKER_02 (03:33):
Yeah, to me, I I always I I don't see them as two
separate things.
Like to me, knowledge it's onething.
And it's just merely, dependingon what you study, give you a
different lens, if you will, oflooking at the world, right?
Art and design give me, youknow, an understanding of what a
(03:53):
creative process is like.
Uh what's design thinking, it'swhat we actually study in art
school back in the days.
It just packages it in a newterm, and now they're taught at
business uh business schools.
Um with computer science, Ithink it gives you more of a
logical uh thinking behind thator or um more critical thinking,
which I would argue art alsogives you that.
(04:14):
Um so to me it's just um givingme a different perspective and
and not necessarily umseparately, right?
SPEAKER_00 (04:25):
That m that makes sense to me.
And so when you think about thethe way that technology is going
right now, and it sounds like alot of the work that you do is
consulting um how organizationsadopt and and really um
strategize around some of thetechnology shifts that are
happening.
SPEAKER_01 (04:39):
Yeah.
SPEAKER_00 (04:40):
Um how much does creativity um play a role when
you think about the directionthat technology is going and the
the things that AI and some ofthese new technologies unlock?
SPEAKER_02 (04:52):
So, okay, can I can I share something else before
that?
100%.
I always want to challengepeople when they say I'm not
creative.
You know, people say that.
And I think we look atcreativity in such a
conventional way.
Um by that I mean people think,oh, I cannot draw, I cannot
sing, I cannot dance.
(05:13):
But if you look at us as kids,we didn't think that way.
Somehow we were educated out ofour creativity.
Because like as kids, we alldraw, we all sing, we all dance
pretty um, not veryself-consciously.
You just enjoy it because it'sso um inherently human.
(05:34):
It's it's to express ourselves.
If you look at um the caves inself-of-frice, the the cave
painting, like that thousands ofyears old, people inherently
wanted to express in indifferent shapes and and forms.
So to me, I think it's in all ofus that we have creativity, but
(05:54):
we don't necessarily think aboutum the things that we do are
creative because we were soembedded in what conventionally
are called creative pursuits.
And so I think it actuallymanifests in so many different
ways in in business, in in in inin the way we work, in
(06:14):
consulting, in teaching, inlearning.
Um, even just you know, notfollowing, like you can be
creative commuting by not takingyour conventional route, by by
challenging you know, normalassumptions about things.
I think to me that's creativity.
It doesn't have to be, you know,creating a piece of work.
(06:36):
It it could be just thinking outof the box or or just
questioning things and and notalways how things have been
done.
SPEAKER_00 (06:44):
I I think and I'd never really thought about it
that way, but you know, we um wewere talking about right before
the show.
I have a you know almostthree-year-old daughter, and
most mornings, you know, I Ithink this morning and it's out
of season, and we're recordingthis right now in October.
She woke up and we could hearher in her bed in her crib
singing jingle bells at the topat the top of her lungs.
Um but you know, she lovesdrawing, she loves singing,
(07:07):
yeah.
Um dancing and all all of likeall of those creative
expressions, and it's notnecessarily uh you know what
you'd hang in a museum.
Yeah.
SPEAKER_02 (07:17):
And and it's not it doesn't have to be, right?
I think that's just the wholepoint.
It's like in in business, evenum one of the things I always
encourage people is well looklook beyond what you're doing in
your own domain, right?
Like what's happening in yourindustry.
It's important to look at yourcompetitors, but it's also
important to look at somethingcompletely different.
Like what's what's happening intransportation, for example.
(07:39):
Just lots of innovation in inthat.
Uh what's what's happening in infinance, what's happening in
government.
Like it's just so much uminnovation and and so many ways
of doing things differently youcan learn and incorporate into
your own thing.
SPEAKER_00 (07:54):
And so there was a really interesting book, and I'm
not sure if you read it, and II'm actually now forgetting the
title, but it's really aroundthat idea of generalization.
Um and they they studied a lotof top-tier athletes.
SPEAKER_01 (08:04):
Oh, okay.
SPEAKER_00 (08:06):
It's called range.
Um range, okay.
And so they studied a lot oftop-tier athletes, and um
there's this narrative right nowthat exists like if I want to be
the best golfer in the world, Ihave to follow the Tiger Woods
story, and I have to start whenI'm four years old, and I have
to golf twelve hours a day, etc.
etc.
And so they they wanted to putsome science around it and also
(08:27):
debunk that kind of 10,000 hoursmyth.
SPEAKER_02 (08:30):
Oh yes, mock and clightwell.
SPEAKER_00 (08:32):
Yeah, and and so they actually um did a study,
and the the statistically thebest way to become a high
performing athlete is actuallynot to specialize in it at a
young age.
And they found that thelearnings, whether it be pattern
recognition, muscle memory, etc.
etcetera, of doing a whole bunchof different things um and kind
(08:53):
of doing them to the 80%, gaveyou a much better likelihood of
actually exceeding as aprofessional athlete rather than
um the I'm doing this every day,all day, just because it gave
you that range and it gave youthe ability to see patterns and
things in a different way.
SPEAKER_02 (09:09):
Yeah, I think it's also aligned with the research
that we need recovery time,right?
Also, um I I think that's a lotof research on that to say,
well, if you step back, if yougive yourself a break, if you do
something differently, which isalso a creative way of doing
things, is to you know, if youcan step back and and not get so
(09:32):
caught up into uh thinking thesame problem, uh it it actually
gives you a fresh perspectiveand also give you a brain to to
hang back and and makeconnections and see patterns.
SPEAKER_00 (09:45):
Super interesting.
I and I agree.
And so do you think that there'sbecause I feel like there's been
this perpetual push forproductivity.
Yeah.
And so do you think that thatpush of productivity comes at
the expense of some of thecreativity?
SPEAKER_02 (10:00):
I think that's also a very North American thinking
as well, in terms of where youhave to be productive all the
time.
Um like I love like for example,in France, like they are
fearlessly protective of of thefree time, right?
Like they they outlaw um it it'sillegal for employers to send
you emails aft outside your workhours.
(10:23):
And um I try to practice thattoo, by the way.
I think it's a very healthyboundary.
But I think it's it's a it'slike everything else that needs
to be a balance.
Yet we we need to be productive,but I think it gets this there's
a point of um diminishing returnuh when you push so much, then
you're actuallycounterproductive.
(10:43):
Or if you're not giving peoplespace.
It's like like Amazons andGoogle have these uh pet
projects, right?
They give people space to thinkand create.
Uh Amazon wants dozens ofhackathons internally, and and
that's perhaps not directlyconnected to what they're
(11:04):
building, uh products that areprofitable, but it's giving
space for for the employees tostep back and look at things
more laterally and morecross-functionally.
So I think you know, some of thecompanies get it, and that's why
they are implementing these umthese activities, these
incentives for people to becreative, to for people to have
(11:25):
space to think.
And and also I think creativityuh stems from uh talking to
people that uh perhaps have it,you know, you don't interact
with all the time, perhaps umthink uh differently, but even
disagree with your way ofthinking.
I think f I think conflict or orfriction also creates a new way
(11:45):
of thinking.
Because if you're just you knowuh hanging out with people that
think the same way, you have,you know, what echo chamber
effects, you have group think,you're not coming up with new
things because you are allreinforcing the same ideas.
SPEAKER_00 (12:00):
Yeah.
And so if you think about, andI'm gonna bring this back to
technology for a few seconds,you know, I I agree 100% with
what you're saying around theimportance of conflict, and I
recognize that there's humor inthe statement of saying I agree
100% with the conflict side ofthings.
But now we have these modelsthat are coming out from a
(12:20):
technology and an AI perspectivethat for lack of a better word
are very agreeable.
SPEAKER_02 (12:25):
Um are you talking about chatbots that always say
you're brilliant stuff?
SPEAKER_00 (12:32):
Um like uh you know, I I I put some stuff into Chat
GBT and uh, you know, I get Icome out of there feeling like a
million bucks that everything Isay is right.
Um, you know, my my view iscorrect.
And uh you know, this is uh it'sperfect, you know.
I think that if I ever need anego boost, but but if you think
about the the power of conflictand the the power of you know
people, you know, a term that umI've heard used and I love being
(12:55):
anti-fragile, the fact that youneed to have some of that
friction.
What r risks do you start to seewhen everything you say is
right?
SPEAKER_02 (13:03):
Oh, logs.
But but by the way, you couldask your chatbot to be more
stern with you.
You you could request that.
And it's you can tune it.
Yeah.
Actually, I I just read a like Ihad a quick glance this morning.
I haven't kind of dig too deepinto this study.
They they say if you're rude toyour chatbot, it gives you
better outcomes.
(13:23):
Really?
I don't want to encourage that.
But um but yeah, I uh agree withyou.
Um there's some studies about umif you, you know, what would
happen if you always get suchpositive reinforcement with no
criticism or no boundary, if youwill.
(13:44):
I think it's good to getpositive reinforcement, I think,
to a degree, but you don't wantthat degree to be delusional,
you know, like you don't wantpeople just to say, I'm great,
because I I was listening to apodcast, I think it was hard
forked.
And they say, I tested withchatbot, and I say, Am I am I
the top one person, you know,most intelligent person in the
(14:07):
world?
And then he said, and I askedthat with a sentence full of
mistakes and typos.
And then chatbot was stupid,like, yes, you are like one of
the top 1% most intelligent,brilliant person in in the
world.
So, so that's you know, yeah,that's not good.
And people would believe in it,right?
I think if if you think aboutum, you know, all the conspiracy
(14:30):
theories out there, people wouldbelieve in it without critical
thinking.
People is gonna buy into likethink I am, I am the best thing.
Um I I think it it's hugelydangerous, not just on that
front, but the fact that we aretaking these AI output um
without critically breaking itdown and and evaluate them.
(14:54):
I think that's a bigger problem,not just the fact that you think
you know you're being reinforcedpositively all the time.
I think it's just a general oflike just taking it as it is
without questioning it.
SPEAKER_00 (15:06):
So you you probably have a very interesting lens on
how people are actually using AIright now.
And so I think that um you know,from my exposure, like there's a
lot of people that um are on thevery front end, which is like
the consumer chat GBT userswe'll call it, which um and then
there's a lot of very kind ofscientific elements, but but how
(15:27):
do like from your perspectiveand the work that you're doing,
how are people actively adoptingAI right now?
SPEAKER_02 (15:35):
I think there's a lot of interest.
I I think people are kind of apiecemeal testing and trying
things out.
Um AI, gen AI definitely uh uhhas gone mainstream.
I even hear people talking abouttheir farmers market, like
everyday conversations now,right?
It's even three years ago, youdon't you don't hear that.
(15:58):
Um and so many it it it concernsme a little bit because it's
almost like people wouldcasually say, Oh, my AI said
that, my AI did that, um withwithout um without giving any um
reference, without giving anyconstraint.
Um I I think people are using ita lot of them are using it for
(16:23):
information seeking, if youwill.
It's it's almost like a Googlereplacement.
Surprisingly, less people areusing it like a therapist.
You think there's gonna be a lotof people doing that, but
there's actually less, but morefor information seeking.
And um and I think that's that'sa good thing because it's much
more natural, more, more, moreum targeted.
(16:44):
It's if you use it well, if youknow how to craft the prompt
critically and iteratively, Ithink it it actually is a very
good tool.
Um I don't necessarily think itsaves me time or or people's
time in general.
Um if you use it well, itactually takes some time, right?
Like as you know, it's you don'ttrust the first output.
(17:06):
I never trust the first output.
I'm like, okay, break this downto me.
How do you come to thisconclusion?
Give me references on that.
And the references half the timeis not right, it's it's
outdated, that some of them theydon't even exist.
So so it takes time, but I thinkpeople start understanding that
now.
I think it helps that thetechnology is also building that
(17:27):
in.
Um now it's several iterationsago that it ChatGPT didn't give
you uh uh references, it didn'tgive you citations.
You have to perhaps ask for it.
Now it it kind of give it toyou.
And just this morning I was umasking ChatGPT one thing, and
it's actually um going throughthe thinking steps and it's
(17:48):
telling me what it's thinkingand say, okay, this is
interesting.
I'm gonna look here first, andthen I'm gonna look at this
source, I'm gonna come by thosetwo, and I'll give give you an
average of the percentage.
So you kinda see that, and sothe technology is also you know
making it more obvious or moreuh accessible for you to
(18:11):
understand it.
So I think people are startbuilding that critical thinking
skills in their interaction withit.
Um I still think we haven'tquite um um realized the the
full potentials of what we cando with with these kind of
technologies, especially withgen AI and and AI in general is
a a different conversation.
SPEAKER_00 (18:33):
And and so I I recognize that this is a a
moving target and that there'sno clear answer.
But what are some of thoseopportunities?
Because I like going back tocreativity, yeah, I think that
it's such a functional rewiringof how we think about um what
technology can do.
Um that that I think people arereally outside of the like I'll
(18:54):
call it like the chat GPT magictricks, yeah.
Um struggling to see how doesthis actually apply in what I do
day-to-day.
SPEAKER_02 (19:02):
Yeah, I I think um honestly use cases is still
emerging because the technologychanges so quickly, right?
Um but the full potential ormore promising potentials, I
would say, um, is in looking atmore um bigger patterns or or
(19:25):
different patterns, right?
The patterns that we um it it'snot obvious to to humans.
Um and and looking at really uhhuge amount of data across
multiple uh sources, likelooking at globally, like the
global trends.
I I think is a good way of of oflooking at uh using uh genai to
(19:48):
say, well, um in terms ofmigration pattern, for example,
or climate change or or uh uh uhtalent development across across
the globe, right?
Like education, for example.
Uh what are some emerging uhneeds of the next generation?
Um how can we allocate thatresources adequately or or
(20:11):
equitably?
So I think those are hugeopportunities in in making,
looking at patterns, but alsonot so much uh even a
prediction, but uh help usbetter inform in creating
policies, in allocatingresources, in um uh addressing
some of the tougher questionslike you know, you've it's it's
(20:33):
about uh you know, equitableaccess.
What does that mean, right?
How how does data help us um youknow get better insights, but
then to uh for us to make betterpolicies out of it?
So I think those areopportunities.
And education is just oneexample.
It's it's the one that closestto my heart.
So I I like to see that uhhappening more and more.
SPEAKER_00 (20:55):
And so is that how you'd classify a lot of your
work today in the educationspace more so than anything?
Like is that where most of theheavy lift is today?
SPEAKER_02 (21:04):
Yeah, mostly education, it's the umbrella
term.
Um of course it's the K3 12 anduniversity, the more formal
education, which I do a fair bitof work in.
Um I also um work withgovernments in what we call the
workforce development, uh talentuh attraction and retention and
(21:27):
secession planning, which isbasically um in in in a changing
conversation about the futurework and the changing uh work
task and and displacement withAI.
How can we better equip peopleuh for the very, very uncertain
future?
Uh so with uh organization isit's it's about how do you build
(21:49):
that AI literacy and and AI umfluency.
Uh but with organization alsolike how do you use AI so people
trust it, people don't feeldisplaced, um, people don't feel
um disempowered.
And so a lot of my work is aboutsupporting that kind of
(22:10):
adoption.
Yeah.
SPEAKER_00 (22:11):
So I I do want to come back a little bit later to
the the conversation around AIand the future of work and and
what it means from a talent anda workforce perspective.
But I I want to stay on the ideaof government for two seconds,
which um you know, at a verysimple lens, like w what role do
you see government needing toplay as these technologies and
(22:32):
these tools evolve?
SPEAKER_02 (22:34):
At the national level or international level?
SPEAKER_00 (22:37):
Um let's say both.
SPEAKER_02 (22:39):
Okay.
Um you don't ask easy questions,do you?
SPEAKER_00 (22:44):
This is the softball free zone.
SPEAKER_02 (22:46):
Yeah.
Um I think nationally I am quitecritical about the Canadian
government.
Because I I I call it tough lovebecause I care because I'm
Canadian.
I live here.
I want us to be uh competitiveglobally.
I I think we can do more.
I I I think we definitely needpolicies.
(23:07):
We still don't have an AI policylike the EU has the first AI EU
act, and along with that,there's so many things, right?
Like they were leading with umGDP out to start with, so they
have a good base to build on topof that.
And and one of the mandates nowin EU is every organization have
(23:31):
to equip the staff with AIliteracy training.
Like every single organization.
That's amazing.
Yeah, I know.
Um same with um, I thinkSingapore has a mandate to train
all the students, to teach allthe students with AI literacy
skills.
Finland has been leading thatfor some time uh with free AI
(23:52):
literacy education um forcitizen, right?
And I haven't seen anything likethat here.
And it's challenging too becauseeducation is the provincial
matter.
And so federally it's hard tokind of have the two-tier
system, right?
And how do you mandate somethingthat essentially is a provincial
(24:13):
matter?
And then that's the traditionaleducation, but there's also
citizen education that I I'dlike to see more of here.
Um LATC government to alsoencourage more on the AI
ecosystem in general, like forcompanies to to experiment.
I know that we're working veryhard on growing a startup
(24:34):
culture, but I think it shouldnot just be startups.
I think it needs to be everyone.
SPEAKER_00 (24:40):
You're you're speaking my language here, and
it's it's one of my pet peeves.
And I I you know we're fortunateto be in Calgary where I think
that there is a very uhinteresting and exciting, you
know, startup community that'sreally starting to flourish.
But the there's a narrative thatI keep hearing that's really
alarming, which is a lot ofthese, you know, very innovative
organizations are having to goelsewhere to not develop their
(25:01):
product but find their firstcustomers.
SPEAKER_02 (25:03):
And once they get some success, they left, right?
Like because they got bought,they got merged, they need to
move you know locations, yeah.
SPEAKER_00 (25:10):
And they st they still need somewhere to sell
their stuff.
And like without some of theselarger, more established
organizations trialing some ofthese innovative technologies,
whether they be AI or whetherthey be some sort of new and
novel way to um solve problem X,if if we're having to go to the
states to find our firstcustomers or to the EU, then
(25:32):
inevitably you create pathwaysout for your IP, for your
people, for your organizations.
Yeah.
And we just don't create thatecosystem at home here.
And it just becomes aself-fulfilling prophecy.
Sorry, you've got me on a soap.
Oh no, no, no.
SPEAKER_02 (25:44):
It's it's and it's not the first time, like if you
look at the whole techdevelopment through through the
past couple of decades, it's thesame story.
Yeah.
Like we had some success storieslocally, and they hire
disappeared or or they care gotbought out and they moved to the
states, or they moved to Europe,or they fail, like RIM.
(26:07):
And it's it's it's it's sad,right?
And and so we don't I mean uhand again, I think focusing on
startup it's great, but I thinkit really needs to be from the
ground app for for for all typesof organization.
And if you look at the Canadianum uh business uh ecosystem, we
(26:30):
don't have multinationals as aswe like not as many of them,
right?
Ninety some percent of companiesare small medium enterprises.
So we need to support them.
We need to focus on that.
SPEAKER_00 (26:45):
And and this is where like and I'm I'm curious
on your perspective on this.
I think that some of the digitaltools that are coming out create
an incredible opportunity to torethink about how we compete and
to rethink about how we we uhcompete on the global scale.
SPEAKER_02 (27:00):
Are you thinking about a one-person unicorn
conversation?
Maybe.
Yeah.
SPEAKER_00 (27:05):
Well, so what's your perspective?
And then maybe for ourlisteners, um what is the one
percent one person unicornconversation?
SPEAKER_02 (27:12):
Oh, the the idea that now with AI tools, you
don't need multiple personrunning a startup and and still
make the the unicorn status.
Unicorn is what?
Is it um 10 billion?
I thought it was a billion.
Oh, is it one billion?
Okay, it's maybe one billion.
SPEAKER_00 (27:29):
I can't I can't I can't get numbers that large.
We'll fact check ourselvesafterwards.
It's yeah.
SPEAKER_02 (27:34):
Yeah, I think I think it it's it's um that
number is it's large.
It's large.
So basically, the premise isthat instead of having a team of
a a larger team of peoplebuilding a company to to to get
to that stage that's value at agazillion dollars, now you only
need one person.
(27:55):
Or maybe three, I don't know.
But uh so it the idea is itwould drastically reduce your
number of manpower to build acompany.
Yeah.
SPEAKER_00 (28:05):
And so I think you segued me perfectly back into
the conversation that um I Ikind of tabled earlier, which
was, you know, what impacts doesAI have on on the workforce,
right?
And so you know, if if we'reable to create a billion dollars
in value um or economic valuewith one person, um, you know,
maybe there's this Schenger Lawstate where every single person
(28:27):
has a billion-dollar company,but I think the the realistic
scenario is probably muchdifferent than that.
What do you foresee happening?
Um, and maybe I'll break it downinto kind of short, medium, and
long term, um, around some ofthese challenges um or
opportunities that might comefrom what's happening in AI
right now?
SPEAKER_02 (28:47):
Yeah, I agree.
I think it's not gonna be likeevery other street would have a
one-person Unicorn.
Um I it does create moreopportunities, I think, for
organizations to experiment toperhaps um uh my my I hope it
(29:08):
will level the playing field alittle bit more because some of
the even the tools that areavailable now, um you you need
money to buy them before, right?
You need money to hire a team tobuild a platform.
Now you can just pay for a$20monthly subscription.
You can have a platform.
And it's it's pretty amazingthat um, you know, AI can help
(29:33):
you build some of the the um thetechnologies behind what you
need to build your company.
So I I hope that means uh peoplethat have less means can start
companies, people that have agood idea or young graduates,
like like our very nice uhproducer here.
SPEAKER_00 (29:53):
Yeah, Zach and Zach right over here.
SPEAKER_02 (29:56):
Yeah, over here.
Um Young graduates.
That's what also give themalternatives to full-time
employment in light of the AIconversation about displacing
jobs and the increaseddifficulties in in looking for
particularly entry-level work,right?
As you know, um a lot of the AIdisplace jobs that are more
(30:20):
entry-level.
Um and and so maybe it wouldencourage people to say here's
an alternative pathway.
Uh and and from thatperspective, I hope that helps,
especially with the Canadianeconomy.
I I think um it's it's alreadybeen known that it's it's
difficult to get into a field.
Uh if you talk to new Canadianscoming here with foreign
(30:43):
credentials, it's it'snotoriously difficult to get
into a professional field thatneeds credentialing.
Um it's hard for younggraduates, it's also difficult
for um people that are on theother end of the career, right?
Like you're uh in terms ofpeople that are older and and
wanted to change, I think thatwould also help them as well.
(31:04):
And and as you know, Canadian,uh, we have an aging population
here.
SPEAKER_00 (31:08):
So well, because I was gonna ask the flip end of
the conversation there, which isum sure there's some short-term
economic value potentially bybeing able to create more with
less.
SPEAKER_01 (31:17):
Yeah.
SPEAKER_00 (31:18):
But what happens when we start to have a gap on
the front end of our workforce?
And um, I'll use a really kindof crude example from like
traditional consulting firms.
SPEAKER_01 (31:28):
Yeah, yeah.
SPEAKER_00 (31:29):
And so um a lot of the like very traditional, like
we'll say like kind of big 4Sconsulting firms have a very
scientific model that says, youknow, a hundred people in, um,
whittle down to 50, whittle downto 25, and out of X amount of
people, we get one seniorpartner 25 years from now.
And so they they have a veryspecific calculus.
But what happens when you knowyou don't get that experience on
(31:52):
the way up the chain?
SPEAKER_02 (31:53):
Oh, I know you have to build a talent pipeline,
right?
Like if you've never done like abasics, how do you know what it
takes to to run an office?
How do you know the the basicsof accounting or if you haven't
done the grunt work?
Like, how do you how do you be agood manager?
Like you don't know what it whatit took.
I oh it it it's a huge concern.
I don't agree with that.
I don't think they shoulddisplace uh the entry-level
(32:16):
workers as well.
I I I mean it's it's it's a hugequestion, as you know.
Um that's uh it's it's stillchanging.
Like, for example, I think wasit IBM that lay off a bunch of
people and then six months laterthey rehire them back.
And and so I don't thinkcompanies even know.
I think they react to economicincentives, and then when it no
(32:39):
longer works for them, they haveto like pivot.
So I am watching that spaceclosely.
I am not convinced getting ridof the entry-level work, it's
the solution.
I I do think we need to redesignwork.
I I do think we need to rethinkum in in terms of breaking down
(33:00):
uh work task in instead of jobtitles, right?
Like what does it mean to be ajunior accountant, a a junior um
uh business person, like otherentry-level work.
Perhaps we need to um you knowthink about okay, this this
there is AI involved, but uh AIhas so many problems right now
(33:25):
that human needs to be the onethat's overseeing it, it needs
to be the one reviewing thework, and and along with that,
perhaps AI can teach theentry-level workers how to be um
how to improve and build thecareer pathways.
I I think that should be the wayto go.
SPEAKER_00 (33:44):
Yeah, and I I I agree once again with this idea
that things need to befunctionally reimagined.
And going back once again to theidea of creativity really being
the superpower, yeah.
Um, you know, our organizationalstructures of today are very
much designed and built aroundthis idea of, you know, the
assembly line of people, right?
SPEAKER_02 (34:04):
How do we how do we produce I know a lot we haven't
changed since the 19th century,did we?
SPEAKER_00 (34:09):
And and so we you kind of have this, you know, for
better lack of a better, apyramid.
SPEAKER_01 (34:13):
Right.
SPEAKER_00 (34:13):
Um or or whatever shape you want to um to call it.
But it's it's a very kind ofcommand and control type
organizational design.
And I think that the theopportunity to reimagine what
that looks like, not just froman execution of work, but from a
quality of life, from a spacefor creativity, space to enjoy.
(34:34):
Like I think that there's thisum you know, pot of gold at the
end of the rainbow that comesfrom some of these technologies
if we can take that leap.
SPEAKER_02 (34:44):
Yeah, and also I think it gets back to our early
conversation about governmenttoo, right?
We need regulations, we needincentives, like and and
internationally too.
I I think um there needs to besome regulatory bodies that work
together, um, because it it cutsacross every industry, but it
(35:05):
also cuts across the world,right?
It's it doesn't happen justhere, it doesn't happen just in
North Korea, it it happenseverywhere.
And so I I think um having agovernment governmental role,
you know, in in in kind of helpshaping that, I I think that's
critical.
SPEAKER_00 (35:25):
So how much and and you might not have a lens into
this, but how muchcross-governmental collaboration
are you seeing?
Like is it um you know everycountry for themselves right
now, um, or are you seeingstarting to see more
collaboration in terms of howpeople are piecing these um
policies um et cetera, together?
SPEAKER_02 (35:42):
I I see a bit of both.
I definitely see the eachcountry its own kind of, you
know, and and with differentagendas.
I I think it's definitely likethe the new neoclear race, if
you will.
Um China is putting major, majoreffort in in building AI
(36:04):
superpower and incentivizedifferent provinces and
different counties and and atthat level of government to to
build out AI.
Um same with so many, likeEurope, it's just announced big
incentives for you know bigfunding.
I mean, EU in general, it'salways been very collaborative
(36:25):
within the European Union, whichmakes sense to them, you know, a
clusters of countriesgeographically close to each
other.
And and so they they could beleading in in that sense in
terms of regulations, they theyhave been.
Um places like I've seen um, youknow, like the United Nations
(36:46):
types of NGOs been doing some ofthat work.
Uh UNESCO, UNICEF been doingsome of um and also um OCED has
like a new.
I'm not sure if I'm familiarwith that.
So it's kind of like the thedeveloped country um research
(37:06):
arms or policy making.
So they also have an AI literacythat's kind of a a combination
of different country expertsthat come together and look at.
I see my logo work being donewith the AI literacy, or or what
does it mean to be AI literaryor digital literary or AI
fluent?
So there's a lot morecollaborative work being done
(37:28):
across countries in that sense.
Uh in terms of policies, I don'tknow.
I I tend to monitor a fewcountries just to see what
they're doing.
Like UK is doing great policywork.
They they have uh AI uh usecases, libraries that you can
look into, and and and I haven'tseen that in in in Canada yet.
SPEAKER_00 (37:50):
That's very interesting.
So you you've mentioned the termAI literacy a handful of times.
Yeah, and I know in previousprevious conversations that you
and I have had, you know, therethere's a really important
distinction between the idea ofAI literacy and AI fluency.
Um can you walk me through alittle bit of your your thoughts
on both of those uh thosepoints?
SPEAKER_02 (38:12):
Yeah, I mean some of it is I think it's a spectrum,
right?
It's it's uh a finer definition.
I think literacy, it's kind ofyour basics, your your
foundation building, if youwill.
It's it's just think aboutliteracy.
What what is basic literacy,right?
You can read, you can, you cando numbers, you can you can have
(38:32):
critical thinking skills, youcan identify you know, you can
tell truth from fiction, allthat stuff, right?
Um and uh you can you can youcan you can you can communicate
well, um all of that it's it'sbasic literacy.
So if you translate that intoAI, by the way, I think it's a
continuum of digital literacy.
I think AI it's so new, so wedifferentiate that from
(38:56):
traditional computer sciencetech technologies, but I think
eventually it's gonna fall intojust tech.
Um AI um is a tech, it's this abit of a joke about that to say,
oh, it's it's AI until it's notnew and shiny, and then it's
just regular tech, right?
And so I think it's a continuumof what we've been building for
(39:19):
like the past 20 years of whatwe call digital literacy.
Um so translating that frombasic literacy is you know, you
you need to understand thetechnology.
What what what is AI?
It's not one thing, it's a it'sa collection of different
techniques.
Um the definition changes overtime, and AI um, you know,
(39:43):
there's different domains withinthat.
Uh just different ways of doingAI, just your gen AI, there's
predictive AI, just robotics,and a whack of different fields
together.
So people need to have a generalunderstanding, right?
You need to have a generalunderstanding of how data works
with what AI.
How does how does that impact AImodels and output?
(40:06):
You need to understand criticalthinking skills, you need to
understand how creativity, youknow, uh the relationship
between creativity and AI.
You need to understand uh whatare some use cases in AI, you
need to understand the ethicalconcerns, which is another topic
that we can talk for anotherhour, Keith.
(40:26):
Um But fluency really it's it'suh to me at least is another
step of because you think aboutspeaking a language.
I can speak uh French.
Am I fluent in it?
SPEAKER_01 (40:42):
No.
SPEAKER_02 (40:43):
So there's a there's a a difference in mastery, I
think.
Right.
Um so fluency is yeah, you canuh perhaps teach these concepts
to other people.
Uh you could uh drive policies,uh, you could impact change in
in light of uh AI developmentand advancement.
So fluency it's it's that uhthat mastery level that you can
(41:07):
actually um uh help uh shape thefield.
It doesn't necessarily need tobe technical, you could be
someone that understanding umlimitations of AI and the risks,
and so you can shape policy thatway from a more sociological
perspective.
Um so by me advocating AIliteracy and fluency, it doesn't
(41:31):
mean everybody need to be a datascientist.
It doesn't mean everybody needsto start building AI models, but
I think everybody needs to getinvolved and first have a
baseline understanding and tohave that voice out there to
shape actively on how thistechnology is gonna develop and
(41:53):
impact us.
SPEAKER_00 (41:54):
So whose responsibility do you think it
is to make sure that we havethat level of well, we'll start
at the baseline literacy umacross a population?
SPEAKER_02 (42:06):
So who's responsibility before for basic
literacy?
Government, right?
Because we have education, wehave compulsory education, and
and so I think government needto take the lead to start with
that.
Um as you know, we as humanbeings are are not very
self-motivated or disciplined inin any shape and form.
(42:29):
Speaking for myself here, butbut I think um there needs to be
um uh some structure in place,if you will, to to help guide us
and also to help us understandwhy we need it so much, right?
SPEAKER_00 (42:47):
Yeah.
Well, and even if I think backto bring it to a kind of a maybe
a more digestible analogy, theone of the biggest things that
kind of separated people back inthe you know, the before time, I
don't know, 1800s, 1700s, etc.
etcetera, um was the ability toread, the ability to write.
(43:09):
Right, yeah.
Um and and not to be able tocode, but the ability to just
read a book.
And and the the knowledge gapand the knowledge boost that
came from being able to do that,all of a sudden you gave way
more power to people, you wereyou gave way more power to um
you know different thought, etc.
etc.
And the ability for nations,areas, regions, geographies to
(43:33):
compete really came from theability to educate their um
their population.
Don't don't you think and seethis as an imperative to just be
competitive at a at a baseeconomic level?
SPEAKER_02 (43:45):
Absolutely.
Oh, a hundred percent.
I mean, government is just thefirst step, right?
Um from a capitalisticdemographic society perspective,
we also need that as a um acompetitive advantage and also
as um it's something that youyou need to do so you're not
(44:06):
being excluded or or leftbehind.
So think about if you don't readhow much of information is being
left out for you.
So if you don't understand AI,it's increasingly embedded in
everything we do in in our inour houses, right?
It's all the AI embedded devicesas well.
(44:26):
So you don't want to be left outof the society.
So I think there's also personalinterest involved.
It's also I think the communityalso needs to take on some
responsibilities as as um ascommunities.
I think that needs to be uh um acommunity level education, uh
(44:47):
support in in understanding anddeveloping that literacy.
I I think of course school, butalso society, um nonprofit
organizations, like so.
I guess my response is everyoneat different levels needs to be
uh take up that responsibilityof of developing the literacy
(45:07):
for AI.
SPEAKER_00 (45:09):
I love that, and that makes complete sense.
Libraries.
Yeah.
SPEAKER_02 (45:12):
I mean, like they they play a major role in
information literacy, right?
So it's a natural extension tobe advocating and supporting AI
literacy at at the librarylevel.
SPEAKER_00 (45:24):
I think so.
And the the infrastructure isthere already.
Yeah, exactly.
SPEAKER_02 (45:27):
Everyone has a gathering place.
SPEAKER_00 (45:30):
So I I love it.
So so if we think about umturning the corner to you know
very practically if I'm abusiness leader, if I run a um
$20 million um mid-cap uh oiland gas company.
SPEAKER_02 (45:47):
I thought I was gonna say, I thought you are a
business leader.
SPEAKER_00 (45:50):
I guess I guess I don't have to pretend that much.
Exactly.
And maybe I'll I'll kind oftransport it.
I I feel like I know enough tobe dangerous in this space.
I feel like I still haveinfinity questions, but um
there's a lot of people that Italk to that are just so
overwhelmed about where to getstarted.
And so they I know.
Yeah they know that it'simportant.
SPEAKER_01 (46:12):
Yep.
SPEAKER_00 (46:12):
They know that it's something that that has to be
part of their business strategy,yeah, but have zero clue of
where to get started when itcomes to taking the first step
on this journey.
So from your perspective, whatdo they do?
SPEAKER_02 (46:29):
I completely understand that.
Um even as someone who actuallyhas a com-site background, I
feel overwhelmed all the time.
Like literally every day youwake up, there's this 10 stories
about AI, right?
It's it's it's overwhelming.
(46:50):
But I think um the impetus isyou have to get started
somewhere, and it's never toolate.
I I I really dislike thenarrative out there sometimes.
You hear it's like if youhaven't used AI, it's too late.
I'm like, no, like that is not agood place to start in terms of
(47:12):
encouraging people to try.
Um so I think it's never toolate.
It's you know, start at anytime.
But it doesn't have to be a bigthing.
I I it doesn't have the mediahyped up so much about AI, so
it's this mystical, almost likegodlike being, which isn't.
It's it's a tool, right?
It's a tech it's a technique,it's a platform.
(47:34):
Yeah, it's it's it's somethingthat's it's it's pretty it's a
pretty big deal, but it doesn'thave to be.
And it doesn't have to beingested in one goal.
It you can start by taking alittle bite here, a little bite
there, and um and start withjust one thing.
(47:55):
And I would start with what isit that like from a business
perspective?
I I work with businesses uh onthat, and I always say, well,
start with your your businessneeds.
Like, you know, what what whatare what are something that you
you're um dealing with that arethat are a bit of a a pin point
for you?
Like what is something that it'sa bottleneck or or or where are
(48:18):
the opportunities you're tryingto like seek out?
Where where do you want to growyour company?
What do you think um theseopportunities are or where are
something that's holding youback?
Like what are some problemsyou're dealing with from a
business perspective, right?
So start there.
I don't start with AI.
I I start with like what'swhat's your own use cases and
and and start thinking about,okay, you've it's um for
(48:43):
example, uh customer complaints,you get lots of them from uh
your your call centers.
Uh it's it's it's becoming aproblem.
So start there and look at whatAI tools, platforms, technology
can help with that and starttesting that.
Start investigating into maybe Itry this one tool and see if
(49:08):
that helps and use it in a in avery um in a in a creative
experimental pilot kind of way.
Say let's implement this for sixmonths, let's try it out, let's
have put a small team together,um, you know, test it and and
and make sure you measure you'veif it works, right?
(49:30):
And and that's all there is toit.
You don't have to start withthis big implementation of AI in
every department.
You don't have to start witheverybody need to be up and
running with, you know, aninternal AI that's it's built,
it's massive, that thateverything needs to be checked.
Um it's it's just with that thatalready gets you started.
(49:53):
And there's no two ways aboutit.
You need to start playing, youneed to start like testing, you
need to start uh shopping andlooking at tools or or you
whether you build it internallyor you work with an external
vendor, you start kind oftesting things and and get
demos, get people to to try itout and get some feedback.
SPEAKER_00 (50:12):
So as people get started, do they need different
people around them?
Do they need like if if you wereto think of the a demographic of
someone that helps organizationsget through this?
Did does the um soft skills ofthis person change?
Um or the the things that theybring to these leaders?
(50:33):
Like w what are some of thoseskills that are needed to help
organizations through this?
SPEAKER_02 (50:38):
Yeah, I think you definitely need different
business departments to worktogether.
I think it's one um I think it'sa unique thing about AI.
It's sometimes when youimplement a piece of tech in a
past, you can you can just havetwo or three departments and
that's it.
And I I AI cuts across so manydepartments.
You f you need to workcommunications department,
(50:59):
right?
Because you need to communicatethis, you know, how does this
being done, how is it affectingpeople, what are some risk
associated with that.
So you might have to work withlegal, you might have to work
with um L and D for training andand and and and upskilling
people, you probably need towork with procurement, you you
(51:21):
know, so so I think um I thinkif anything else, the soft
skills is even more importantnow because you have to work
with so many different groupsand you have to to manage and
negotiate relationships and makesure that everybody has a say
and everybody can bring a youknow a pr a piece of the AI lens
to this project.
(51:41):
So um so if anything else, Ithink it's even more important
about teamwork, aboutcommunications, about empathy,
right?
Because we we work with uh andcultural awareness.
I think that's becoming andculture doesn't just mean
countries, but also likedifferent subcultures within the
organization.
(52:01):
Uh like, you know, the IT teamshave their own culture, HR has
their own culture, even tounderstand how to make sure you
communicate so they understood,you know, the language, the
share language, if you will.
Um so so those are all the softskills that um perhaps we need
to about game a little bit more.
SPEAKER_00 (52:21):
I that makes complete sense to me.
So um you and I could keeptalking for probably three or
four more hours.
SPEAKER_02 (52:27):
Are we getting a signal now to stop talking?
SPEAKER_00 (52:30):
I don't I don't know.
I like I said, I I think that uhI I have one thing that I want
to end with, which is you know,if you have kind of some final
thoughts around maybe theopportunity um that's in in
front of us as as businessleaders, as a society, um, from
AI and from some of thesetechnologies that are going to
be game-changing, um, you know,what thought would you want to
(52:53):
leave people with?
SPEAKER_02 (52:57):
Wow.
So many.
SPEAKER_00 (53:00):
You gotta pick one.
SPEAKER_02 (53:01):
Okay.
Um I think don't be scared byAI, but also don't get bought
into the hype.
I think looking like go into itwith a a balanced lens.
There's gonna be opportunities,but there's also limitations and
(53:24):
and challenges and and thingsthat are risky.
So um so think about that andand make sure you do it in in a
way that's responsible, in a waythat's transparent, in a way
that you know, don't get caughtup in the efficiency game.
Think about impact, think aboutopportunities.
SPEAKER_00 (53:47):
I love it.
And so I'm sure people comingfrom this conversation will have
just as many questions as I did,and probably even more for you.
SPEAKER_02 (53:55):
I have more questions than answers,
honestly.
SPEAKER_00 (53:58):
I if people wanted to get in touch with you, is
there a way, um the best way todo that if they want to learn
more about you around the workyou're doing in Paradox?
Um, what's the best way?
SPEAKER_02 (54:07):
Um so my website is paradoxlearning.com, and you can
email me at Stella atParadoxLearning.com.
I am fairly active on LinkedInas well.
My LinkedIn handle is a StellaL, or just search my name.
I think um you should be able toget to me.
Uh I'm always happy to have aconversation.
(54:29):
I'd love to like I say I havemore questions to have answers
for.
So uh I love hearing otherpeople's perspectives as well.
So yeah.
SPEAKER_00 (54:39):
Fantastic.
This has been an absolutepleasure.
Thank you so much for taking thetime to come with us.
Thank you.
SPEAKER_02 (54:43):
It's a great conversation.
Thanks for having me.
SPEAKER_00 (54:46):
And I I feel like there's a part two in our
future, but this is this hasbeen fantastic.
So thank you so much today.
SPEAKER_02 (54:51):
Thanks, Keith.
SPEAKER_00 (54:53):
If you've made it this far, like and subscribe on
YouTube or follow and leave areview on your favorite
podcasting platform so you don'tmiss any future episodes.
I think everybody needs to get involved and first
have a baseline understandingand to have that voice out there
to shape actively on how thistechnology is going to develop
and impact us.
SPEAKER_00 (00:20):
Welcome to another episode of Sell Me This Podcast.
This week I am incrediblyexcited to welcome our guest,
Dr.
Stella Lee.
Stella and I dive into anincredibly exciting conversation
around education, aroundgovernment policy and AI, and
around what business leaders cando to make meaningful steps in
implementing these technologiesin their business.
I hope you enjoy.
(00:41):
So welcome to another episode ofSell Me This Podcast.
Today I'm incredibly excited tohave our guest, Dr.
Stella Lee.
I promise it's the only timethat I'll mention the doctor off
the bat for formalities.
Thank you.
I have been looking forward tothis episode for a while.
You and I met um at an untappeduh energy AI summit.
Um, probably about a month ortwo ago, and and I was blown
(01:05):
away by everything that youshared.
It was immediately clear to methat we were um we saw the world
in a similar way, and so thankyou for agreeing to be on the
show.
SPEAKER_02 (01:13):
Thanks for having me.
SPEAKER_00 (01:14):
Um for our listeners, um, I'd love to just
jump right into things.
And if you could give maybe aquick introduction of who you
are, um the the work that youdo, and um we maybe we can start
there.
SPEAKER_02 (01:25):
Okay, um I'm Stella.
I run a boutique, as I like tocall it, consulting firm.
It's it's me and a couple ofstaff uh called Paradox
Learning, and it's based inCalgary.
I work, um, oh gosh, I done somany different projects from
NGOs like the United Nations togovernments like Yukon
(01:46):
government to small, mediumenterprise organizations, uh
primarily in digital learningand education tech space.
Um these days it's all about AI,so I happen to also have a
background in that, so I do allthe consulting in that in that
way.
I came from an academicbackground, so I don't know if
(02:06):
you know this, but I wastraining as a painter.
I did not and a designer.
So um, and I kind of find my wayinto um computer science, so I I
have a BFA and I end up gettinga PhD in computer science.
And so I was an academic and Ilike to call myself a now
reformed academic turnconsultant.
SPEAKER_00 (02:26):
Yeah, you've you've recovered from the academic side
of things.
SPEAKER_02 (02:29):
Almost.
SPEAKER_00 (02:30):
And so you I actually didn't know that you
were a painter, but we we haveum It's my love for art.
I know we have our tradition onthe show where where uh you know
the guest gets to pick theartwork behind us.
SPEAKER_02 (02:41):
I love that.
Yeah.
SPEAKER_00 (02:42):
And so can you tell us about this piece?
SPEAKER_02 (02:44):
Like I I'm I'm blissfully ignorant on a lot of
art stuff, but um I don'tactually know this piece, but I
just was drawing I I my love isactually in in modern or
contemporary art, so anything20th century or kind of late
19th century onwards.
So I really love um abstract, umbold, kind of um very expressive
(03:07):
kind of strokes and colors andjust essentially pushing the
limit of what we call art,right?
SPEAKER_00 (03:14):
So I love it, and and and I love the combination
as well, and I'm sure it givesyou a really interesting
perspective of having that thatartistic and creative side along
with the the more digitaltechnology side from your comp
sci um studies.
How do those things blendtogether?
And I imagine it gives you areally interesting view of the
world.
SPEAKER_02 (03:33):
Yeah, to me, I I always I I don't see them as two
separate things.
Like to me, knowledge it's onething.
And it's just merely, dependingon what you study, give you a
different lens, if you will, oflooking at the world, right?
Art and design give me, youknow, an understanding of what a
(03:53):
creative process is like.
Uh what's design thinking, it'swhat we actually study in art
school back in the days.
It just packages it in a newterm, and now they're taught at
business uh business schools.
Um with computer science, Ithink it gives you more of a
logical uh thinking behind thator or um more critical thinking,
which I would argue art alsogives you that.
(04:14):
Um so to me it's just um givingme a different perspective and
and not necessarily umseparately, right?
SPEAKER_00 (04:25):
That m that makes sense to me.
And so when you think about thethe way that technology is going
right now, and it sounds like alot of the work that you do is
consulting um how organizationsadopt and and really um
strategize around some of thetechnology shifts that are
happening.
SPEAKER_01 (04:39):
Yeah.
SPEAKER_00 (04:40):
Um how much does creativity um play a role when
you think about the directionthat technology is going and the
the things that AI and some ofthese new technologies unlock?
SPEAKER_02 (04:52):
So, okay, can I can I share something else before
that?
100%.
I always want to challengepeople when they say I'm not
creative.
You know, people say that.
And I think we look atcreativity in such a
conventional way.
Um by that I mean people think,oh, I cannot draw, I cannot
sing, I cannot dance.
(05:13):
But if you look at us as kids,we didn't think that way.
Somehow we were educated out ofour creativity.
Because like as kids, we alldraw, we all sing, we all dance
pretty um, not veryself-consciously.
You just enjoy it because it'sso um inherently human.
(05:34):
It's it's to express ourselves.
If you look at um the caves inself-of-frice, the the cave
painting, like that thousands ofyears old, people inherently
wanted to express in indifferent shapes and and forms.
So to me, I think it's in all ofus that we have creativity, but
(05:54):
we don't necessarily think aboutum the things that we do are
creative because we were soembedded in what conventionally
are called creative pursuits.
And so I think it actuallymanifests in so many different
ways in in business, in in in inin the way we work, in
(06:14):
consulting, in teaching, inlearning.
Um, even just you know, notfollowing, like you can be
creative commuting by not takingyour conventional route, by by
challenging you know, normalassumptions about things.
I think to me that's creativity.
It doesn't have to be, you know,creating a piece of work.
(06:36):
It it could be just thinking outof the box or or just
questioning things and and notalways how things have been
done.
SPEAKER_00 (06:44):
I I think and I'd never really thought about it
that way, but you know, we um wewere talking about right before
the show.
I have a you know almostthree-year-old daughter, and
most mornings, you know, I Ithink this morning and it's out
of season, and we're recordingthis right now in October.
She woke up and we could hearher in her bed in her crib
singing jingle bells at the topat the top of her lungs.
Um but you know, she lovesdrawing, she loves singing,
(07:07):
yeah.
Um dancing and all all of likeall of those creative
expressions, and it's notnecessarily uh you know what
you'd hang in a museum.
Yeah.
SPEAKER_02 (07:17):
And and it's not it doesn't have to be, right?
I think that's just the wholepoint.
It's like in in business, evenum one of the things I always
encourage people is well looklook beyond what you're doing in
your own domain, right?
Like what's happening in yourindustry.
It's important to look at yourcompetitors, but it's also
important to look at somethingcompletely different.
Like what's what's happening intransportation, for example.
(07:39):
Just lots of innovation in inthat.
Uh what's what's happening in infinance, what's happening in
government.
Like it's just so much uminnovation and and so many ways
of doing things differently youcan learn and incorporate into
your own thing.
SPEAKER_00 (07:54):
And so there was a really interesting book, and I'm
not sure if you read it, and II'm actually now forgetting the
title, but it's really aroundthat idea of generalization.
Um and they they studied a lotof top-tier athletes.
SPEAKER_01 (08:04):
Oh, okay.
SPEAKER_00 (08:06):
It's called range.
Um range, okay.
And so they studied a lot oftop-tier athletes, and um
there's this narrative right nowthat exists like if I want to be
the best golfer in the world, Ihave to follow the Tiger Woods
story, and I have to start whenI'm four years old, and I have
to golf twelve hours a day, etc.
etc.
And so they they wanted to putsome science around it and also
(08:27):
debunk that kind of 10,000 hoursmyth.
SPEAKER_02 (08:30):
Oh yes, mock and clightwell.
SPEAKER_00 (08:32):
Yeah, and and so they actually um did a study,
and the the statistically thebest way to become a high
performing athlete is actuallynot to specialize in it at a
young age.
And they found that thelearnings, whether it be pattern
recognition, muscle memory, etc.
etcetera, of doing a whole bunchof different things um and kind
(08:53):
of doing them to the 80%, gaveyou a much better likelihood of
actually exceeding as aprofessional athlete rather than
um the I'm doing this every day,all day, just because it gave
you that range and it gave youthe ability to see patterns and
things in a different way.
SPEAKER_02 (09:09):
Yeah, I think it's also aligned with the research
that we need recovery time,right?
Also, um I I think that's a lotof research on that to say,
well, if you step back, if yougive yourself a break, if you do
something differently, which isalso a creative way of doing
things, is to you know, if youcan step back and and not get so
(09:32):
caught up into uh thinking thesame problem, uh it it actually
gives you a fresh perspectiveand also give you a brain to to
hang back and and makeconnections and see patterns.
SPEAKER_00 (09:45):
Super interesting.
I and I agree.
And so do you think that there'sbecause I feel like there's been
this perpetual push forproductivity.
Yeah.
And so do you think that thatpush of productivity comes at
the expense of some of thecreativity?
SPEAKER_02 (10:00):
I think that's also a very North American thinking
as well, in terms of where youhave to be productive all the
time.
Um like I love like for example,in France, like they are
fearlessly protective of of thefree time, right?
Like they they outlaw um it it'sillegal for employers to send
you emails aft outside your workhours.
(10:23):
And um I try to practice thattoo, by the way.
I think it's a very healthyboundary.
But I think it's it's a it'slike everything else that needs
to be a balance.
Yet we we need to be productive,but I think it gets this there's
a point of um diminishing returnuh when you push so much, then
you're actuallycounterproductive.
(10:43):
Or if you're not giving peoplespace.
It's like like Amazons andGoogle have these uh pet
projects, right?
They give people space to thinkand create.
Uh Amazon wants dozens ofhackathons internally, and and
that's perhaps not directlyconnected to what they're
(11:04):
building, uh products that areprofitable, but it's giving
space for for the employees tostep back and look at things
more laterally and morecross-functionally.
So I think you know, some of thecompanies get it, and that's why
they are implementing these umthese activities, these
incentives for people to becreative, to for people to have
(11:25):
space to think.
And and also I think creativityuh stems from uh talking to
people that uh perhaps have it,you know, you don't interact
with all the time, perhaps umthink uh differently, but even
disagree with your way ofthinking.
I think f I think conflict or orfriction also creates a new way
(11:45):
of thinking.
Because if you're just you knowuh hanging out with people that
think the same way, you have,you know, what echo chamber
effects, you have group think,you're not coming up with new
things because you are allreinforcing the same ideas.
SPEAKER_00 (12:00):
Yeah.
And so if you think about, andI'm gonna bring this back to
technology for a few seconds,you know, I I agree 100% with
what you're saying around theimportance of conflict, and I
recognize that there's humor inthe statement of saying I agree
100% with the conflict side ofthings.
But now we have these modelsthat are coming out from a
(12:20):
technology and an AI perspectivethat for lack of a better word
are very agreeable.
SPEAKER_02 (12:25):
Um are you talking about chatbots that always say
you're brilliant stuff?
SPEAKER_00 (12:32):
Um like uh you know, I I I put some stuff into Chat
GBT and uh, you know, I get Icome out of there feeling like a
million bucks that everything Isay is right.
Um, you know, my my view iscorrect.
And uh you know, this is uh it'sperfect, you know.
I think that if I ever need anego boost, but but if you think
about the the power of conflictand the the power of you know
people, you know, a term that umI've heard used and I love being
(12:55):
anti-fragile, the fact that youneed to have some of that
friction.
What r risks do you start to seewhen everything you say is
right?
SPEAKER_02 (13:03):
Oh, logs.
But but by the way, you couldask your chatbot to be more
stern with you.
You you could request that.
And it's you can tune it.
Yeah.
Actually, I I just read a like Ihad a quick glance this morning.
I haven't kind of dig too deepinto this study.
They they say if you're rude toyour chatbot, it gives you
better outcomes.
(13:23):
Really?
I don't want to encourage that.
But um but yeah, I uh agree withyou.
Um there's some studies about umif you, you know, what would
happen if you always get suchpositive reinforcement with no
criticism or no boundary, if youwill.
(13:44):
I think it's good to getpositive reinforcement, I think,
to a degree, but you don't wantthat degree to be delusional,
you know, like you don't wantpeople just to say, I'm great,
because I I was listening to apodcast, I think it was hard
forked.
And they say, I tested withchatbot, and I say, Am I am I
the top one person, you know,most intelligent person in the
(14:07):
world?
And then he said, and I askedthat with a sentence full of
mistakes and typos.
And then chatbot was stupid,like, yes, you are like one of
the top 1% most intelligent,brilliant person in in the
world.
So, so that's you know, yeah,that's not good.
And people would believe in it,right?
I think if if you think aboutum, you know, all the conspiracy
(14:30):
theories out there, people wouldbelieve in it without critical
thinking.
People is gonna buy into likethink I am, I am the best thing.
Um I I think it it's hugelydangerous, not just on that
front, but the fact that we aretaking these AI output um
without critically breaking itdown and and evaluate them.
(14:54):
I think that's a bigger problem,not just the fact that you think
you know you're being reinforcedpositively all the time.
I think it's just a general oflike just taking it as it is
without questioning it.
SPEAKER_00 (15:06):
So you you probably have a very interesting lens on
how people are actually using AIright now.
And so I think that um you know,from my exposure, like there's a
lot of people that um are on thevery front end, which is like
the consumer chat GBT userswe'll call it, which um and then
there's a lot of very kind ofscientific elements, but but how
(15:27):
do like from your perspectiveand the work that you're doing,
how are people actively adoptingAI right now?
SPEAKER_02 (15:35):
I think there's a lot of interest.
I I think people are kind of apiecemeal testing and trying
things out.
Um AI, gen AI definitely uh uhhas gone mainstream.
I even hear people talking abouttheir farmers market, like
everyday conversations now,right?
It's even three years ago, youdon't you don't hear that.
(15:58):
Um and so many it it it concernsme a little bit because it's
almost like people wouldcasually say, Oh, my AI said
that, my AI did that, um withwithout um without giving any um
reference, without giving anyconstraint.
Um I I think people are using ita lot of them are using it for
(16:23):
information seeking, if youwill.
It's it's almost like a Googlereplacement.
Surprisingly, less people areusing it like a therapist.
You think there's gonna be a lotof people doing that, but
there's actually less, but morefor information seeking.
And um and I think that's that'sa good thing because it's much
more natural, more, more, moreum targeted.
(16:44):
It's if you use it well, if youknow how to craft the prompt
critically and iteratively, Ithink it it actually is a very
good tool.
Um I don't necessarily think itsaves me time or or people's
time in general.
Um if you use it well, itactually takes some time, right?
Like as you know, it's you don'ttrust the first output.
(17:06):
I never trust the first output.
I'm like, okay, break this downto me.
How do you come to thisconclusion?
Give me references on that.
And the references half the timeis not right, it's it's
outdated, that some of them theydon't even exist.
So so it takes time, but I thinkpeople start understanding that
now.
I think it helps that thetechnology is also building that
(17:27):
in.
Um now it's several iterationsago that it ChatGPT didn't give
you uh uh references, it didn'tgive you citations.
You have to perhaps ask for it.
Now it it kind of give it toyou.
And just this morning I was umasking ChatGPT one thing, and
it's actually um going throughthe thinking steps and it's
(17:48):
telling me what it's thinkingand say, okay, this is
interesting.
I'm gonna look here first, andthen I'm gonna look at this
source, I'm gonna come by thosetwo, and I'll give give you an
average of the percentage.
So you kinda see that, and sothe technology is also you know
making it more obvious or moreuh accessible for you to
(18:11):
understand it.
So I think people are startbuilding that critical thinking
skills in their interaction withit.
Um I still think we haven'tquite um um realized the the
full potentials of what we cando with with these kind of
technologies, especially withgen AI and and AI in general is
a a different conversation.
SPEAKER_00 (18:33):
And and so I I recognize that this is a a
moving target and that there'sno clear answer.
But what are some of thoseopportunities?
Because I like going back tocreativity, yeah, I think that
it's such a functional rewiringof how we think about um what
technology can do.
Um that that I think people arereally outside of the like I'll
(18:54):
call it like the chat GPT magictricks, yeah.
Um struggling to see how doesthis actually apply in what I do
day-to-day.
SPEAKER_02 (19:02):
Yeah, I I think um honestly use cases is still
emerging because the technologychanges so quickly, right?
Um but the full potential ormore promising potentials, I
would say, um, is in looking atmore um bigger patterns or or
(19:25):
different patterns, right?
The patterns that we um it it'snot obvious to to humans.
Um and and looking at really uhhuge amount of data across
multiple uh sources, likelooking at globally, like the
global trends.
I I think is a good way of of oflooking at uh using uh genai to
(19:48):
say, well, um in terms ofmigration pattern, for example,
or climate change or or uh uh uhtalent development across across
the globe, right?
Like education, for example.
Uh what are some emerging uhneeds of the next generation?
Um how can we allocate thatresources adequately or or
(20:11):
equitably?
So I think those are hugeopportunities in in making,
looking at patterns, but alsonot so much uh even a
prediction, but uh help usbetter inform in creating
policies, in allocatingresources, in um uh addressing
some of the tougher questionslike you know, you've it's it's
(20:33):
about uh you know, equitableaccess.
What does that mean, right?
How how does data help us um youknow get better insights, but
then to uh for us to make betterpolicies out of it?
So I think those areopportunities.
And education is just oneexample.
It's it's the one that closestto my heart.
So I I like to see that uhhappening more and more.
SPEAKER_00 (20:55):
And so is that how you'd classify a lot of your
work today in the educationspace more so than anything?
Like is that where most of theheavy lift is today?
SPEAKER_02 (21:04):
Yeah, mostly education, it's the umbrella
term.
Um of course it's the K3 12 anduniversity, the more formal
education, which I do a fair bitof work in.
Um I also um work withgovernments in what we call the
workforce development, uh talentuh attraction and retention and
(21:27):
secession planning, which isbasically um in in in a changing
conversation about the futurework and the changing uh work
task and and displacement withAI.
How can we better equip peopleuh for the very, very uncertain
future?
Uh so with uh organization isit's it's about how do you build
(21:49):
that AI literacy and and AI umfluency.
Uh but with organization alsolike how do you use AI so people
trust it, people don't feeldisplaced, um, people don't feel
um disempowered.
And so a lot of my work is aboutsupporting that kind of
(22:10):
adoption.
Yeah.
SPEAKER_00 (22:11):
So I I do want to come back a little bit later to
the the conversation around AIand the future of work and and
what it means from a talent anda workforce perspective.
But I I want to stay on the ideaof government for two seconds,
which um you know, at a verysimple lens, like w what role do
you see government needing toplay as these technologies and
(22:32):
these tools evolve?
SPEAKER_02 (22:34):
At the national level or international level?
SPEAKER_00 (22:37):
Um let's say both.
SPEAKER_02 (22:39):
Okay.
Um you don't ask easy questions,do you?
SPEAKER_00 (22:44):
This is the softball free zone.
SPEAKER_02 (22:46):
Yeah.
Um I think nationally I am quitecritical about the Canadian
government.
Because I I I call it tough lovebecause I care because I'm
Canadian.
I live here.
I want us to be uh competitiveglobally.
I I think we can do more.
I I I think we definitely needpolicies.
(23:07):
We still don't have an AI policylike the EU has the first AI EU
act, and along with that,there's so many things, right?
Like they were leading with umGDP out to start with, so they
have a good base to build on topof that.
And and one of the mandates nowin EU is every organization have
(23:31):
to equip the staff with AIliteracy training.
Like every single organization.
That's amazing.
Yeah, I know.
Um same with um, I thinkSingapore has a mandate to train
all the students, to teach allthe students with AI literacy
skills.
Finland has been leading thatfor some time uh with free AI
(23:52):
literacy education um forcitizen, right?
And I haven't seen anything likethat here.
And it's challenging too becauseeducation is the provincial
matter.
And so federally it's hard tokind of have the two-tier
system, right?
And how do you mandate somethingthat essentially is a provincial
(24:13):
matter?
And then that's the traditionaleducation, but there's also
citizen education that I I'dlike to see more of here.
Um LATC government to alsoencourage more on the AI
ecosystem in general, like forcompanies to to experiment.
I know that we're working veryhard on growing a startup
(24:34):
culture, but I think it shouldnot just be startups.
I think it needs to be everyone.
SPEAKER_00 (24:40):
You're you're speaking my language here, and
it's it's one of my pet peeves.
And I I you know we're fortunateto be in Calgary where I think
that there is a very uhinteresting and exciting, you
know, startup community that'sreally starting to flourish.
But the there's a narrative thatI keep hearing that's really
alarming, which is a lot ofthese, you know, very innovative
organizations are having to goelsewhere to not develop their
(25:01):
product but find their firstcustomers.
SPEAKER_02 (25:03):
And once they get some success, they left, right?
Like because they got bought,they got merged, they need to
move you know locations, yeah.
SPEAKER_00 (25:10):
And they st they still need somewhere to sell
their stuff.
And like without some of theselarger, more established
organizations trialing some ofthese innovative technologies,
whether they be AI or whetherthey be some sort of new and
novel way to um solve problem X,if if we're having to go to the
states to find our firstcustomers or to the EU, then
(25:32):
inevitably you create pathwaysout for your IP, for your
people, for your organizations.
Yeah.
And we just don't create thatecosystem at home here.
And it just becomes aself-fulfilling prophecy.
Sorry, you've got me on a soap.
Oh no, no, no.
SPEAKER_02 (25:44):
It's it's and it's not the first time, like if you
look at the whole techdevelopment through through the
past couple of decades, it's thesame story.
Yeah.
Like we had some success storieslocally, and they hire
disappeared or or they care gotbought out and they moved to the
states, or they moved to Europe,or they fail, like RIM.
(26:07):
And it's it's it's it's sad,right?
And and so we don't I mean uhand again, I think focusing on
startup it's great, but I thinkit really needs to be from the
ground app for for for all typesof organization.
And if you look at the Canadianum uh business uh ecosystem, we
(26:30):
don't have multinationals as aswe like not as many of them,
right?
Ninety some percent of companiesare small medium enterprises.
So we need to support them.
We need to focus on that.
SPEAKER_00 (26:45):
And and this is where like and I'm I'm curious
on your perspective on this.
I think that some of the digitaltools that are coming out create
an incredible opportunity to torethink about how we compete and
to rethink about how we we uhcompete on the global scale.
SPEAKER_02 (27:00):
Are you thinking about a one-person unicorn
conversation?
Maybe.
Yeah.
SPEAKER_00 (27:05):
Well, so what's your perspective?
And then maybe for ourlisteners, um what is the one
percent one person unicornconversation?
SPEAKER_02 (27:12):
Oh, the the idea that now with AI tools, you
don't need multiple personrunning a startup and and still
make the the unicorn status.
Unicorn is what?
Is it um 10 billion?
I thought it was a billion.
Oh, is it one billion?
Okay, it's maybe one billion.
SPEAKER_00 (27:29):
I can't I can't I can't get numbers that large.
We'll fact check ourselvesafterwards.
It's yeah.
SPEAKER_02 (27:34):
Yeah, I think I think it it's it's um that
number is it's large.
It's large.
So basically, the premise isthat instead of having a team of
a a larger team of peoplebuilding a company to to to get
to that stage that's value at agazillion dollars, now you only
need one person.
(27:55):
Or maybe three, I don't know.
But uh so it the idea is itwould drastically reduce your
number of manpower to build acompany.
Yeah.
SPEAKER_00 (28:05):
And so I think you segued me perfectly back into
the conversation that um I Ikind of tabled earlier, which
was, you know, what impacts doesAI have on on the workforce,
right?
And so you know, if if we'reable to create a billion dollars
in value um or economic valuewith one person, um, you know,
maybe there's this Schenger Lawstate where every single person
(28:27):
has a billion-dollar company,but I think the the realistic
scenario is probably muchdifferent than that.
What do you foresee happening?
Um, and maybe I'll break it downinto kind of short, medium, and
long term, um, around some ofthese challenges um or
opportunities that might comefrom what's happening in AI
right now?
SPEAKER_02 (28:47):
Yeah, I agree.
I think it's not gonna be likeevery other street would have a
one-person Unicorn.
Um I it does create moreopportunities, I think, for
organizations to experiment toperhaps um uh my my I hope it
(29:08):
will level the playing field alittle bit more because some of
the even the tools that areavailable now, um you you need
money to buy them before, right?
You need money to hire a team tobuild a platform.
Now you can just pay for a$20monthly subscription.
You can have a platform.
And it's it's pretty amazingthat um, you know, AI can help
(29:33):
you build some of the the um thetechnologies behind what you
need to build your company.
So I I hope that means uh peoplethat have less means can start
companies, people that have agood idea or young graduates,
like like our very nice uhproducer here.
SPEAKER_00 (29:53):
Yeah, Zach and Zach right over here.
SPEAKER_02 (29:56):
Yeah, over here.
Um Young graduates.
That's what also give themalternatives to full-time
employment in light of the AIconversation about displacing
jobs and the increaseddifficulties in in looking for
particularly entry-level work,right?
As you know, um a lot of the AIdisplace jobs that are more
(30:20):
entry-level.
Um and and so maybe it wouldencourage people to say here's
an alternative pathway.
Uh and and from thatperspective, I hope that helps,
especially with the Canadianeconomy.
I I think um it's it's alreadybeen known that it's it's
difficult to get into a field.
Uh if you talk to new Canadianscoming here with foreign
(30:43):
credentials, it's it'snotoriously difficult to get
into a professional field thatneeds credentialing.
Um it's hard for younggraduates, it's also difficult
for um people that are on theother end of the career, right?
Like you're uh in terms ofpeople that are older and and
wanted to change, I think thatwould also help them as well.
(31:04):
And and as you know, Canadian,uh, we have an aging population
here.
SPEAKER_00 (31:08):
So well, because I was gonna ask the flip end of
the conversation there, which isum sure there's some short-term
economic value potentially bybeing able to create more with
less.
SPEAKER_01 (31:17):
Yeah.
SPEAKER_00 (31:18):
But what happens when we start to have a gap on
the front end of our workforce?
And um, I'll use a really kindof crude example from like
traditional consulting firms.
SPEAKER_01 (31:28):
Yeah, yeah.
SPEAKER_00 (31:29):
And so um a lot of the like very traditional, like
we'll say like kind of big 4Sconsulting firms have a very
scientific model that says, youknow, a hundred people in, um,
whittle down to 50, whittle downto 25, and out of X amount of
people, we get one seniorpartner 25 years from now.
And so they they have a veryspecific calculus.
But what happens when you knowyou don't get that experience on
(31:52):
the way up the chain?
SPEAKER_02 (31:53):
Oh, I know you have to build a talent pipeline,
right?
Like if you've never done like abasics, how do you know what it
takes to to run an office?
How do you know the the basicsof accounting or if you haven't
done the grunt work?
Like, how do you how do you be agood manager?
Like you don't know what it whatit took.
I oh it it it's a huge concern.
I don't agree with that.
I don't think they shoulddisplace uh the entry-level
(32:16):
workers as well.
I I I mean it's it's it's a hugequestion, as you know.
Um that's uh it's it's stillchanging.
Like, for example, I think wasit IBM that lay off a bunch of
people and then six months laterthey rehire them back.
And and so I don't thinkcompanies even know.
I think they react to economicincentives, and then when it no
(32:39):
longer works for them, they haveto like pivot.
So I am watching that spaceclosely.
I am not convinced getting ridof the entry-level work, it's
the solution.
I I do think we need to redesignwork.
I I do think we need to rethinkum in in terms of breaking down
(33:00):
uh work task in instead of jobtitles, right?
Like what does it mean to be ajunior accountant, a a junior um
uh business person, like otherentry-level work.
Perhaps we need to um you knowthink about okay, this this
there is AI involved, but uh AIhas so many problems right now
(33:25):
that human needs to be the onethat's overseeing it, it needs
to be the one reviewing thework, and and along with that,
perhaps AI can teach theentry-level workers how to be um
how to improve and build thecareer pathways.
I I think that should be the wayto go.
SPEAKER_00 (33:44):
Yeah, and I I I agree once again with this idea
that things need to befunctionally reimagined.
And going back once again to theidea of creativity really being
the superpower, yeah.
Um, you know, our organizationalstructures of today are very
much designed and built aroundthis idea of, you know, the
assembly line of people, right?
SPEAKER_02 (34:04):
How do we how do we produce I know a lot we haven't
changed since the 19th century,did we?
SPEAKER_00 (34:09):
And and so we you kind of have this, you know, for
better lack of a better, apyramid.
SPEAKER_01 (34:13):
Right.
SPEAKER_00 (34:13):
Um or or whatever shape you want to um to call it.
But it's it's a very kind ofcommand and control type
organizational design.
And I think that the theopportunity to reimagine what
that looks like, not just froman execution of work, but from a
quality of life, from a spacefor creativity, space to enjoy.
(34:34):
Like I think that there's thisum you know, pot of gold at the
end of the rainbow that comesfrom some of these technologies
if we can take that leap.
SPEAKER_02 (34:44):
Yeah, and also I think it gets back to our early
conversation about governmenttoo, right?
We need regulations, we needincentives, like and and
internationally too.
I I think um there needs to besome regulatory bodies that work
together, um, because it it cutsacross every industry, but it
(35:05):
also cuts across the world,right?
It's it doesn't happen justhere, it doesn't happen just in
North Korea, it it happenseverywhere.
And so I I think um having agovernment governmental role,
you know, in in in kind of helpshaping that, I I think that's
critical.
SPEAKER_00 (35:25):
So how much and and you might not have a lens into
this, but how muchcross-governmental collaboration
are you seeing?
Like is it um you know everycountry for themselves right
now, um, or are you seeingstarting to see more
collaboration in terms of howpeople are piecing these um
policies um et cetera, together?
SPEAKER_02 (35:42):
I I see a bit of both.
I definitely see the eachcountry its own kind of, you
know, and and with differentagendas.
I I think it's definitely likethe the new neoclear race, if
you will.
Um China is putting major, majoreffort in in building AI
(36:04):
superpower and incentivizedifferent provinces and
different counties and and atthat level of government to to
build out AI.
Um same with so many, likeEurope, it's just announced big
incentives for you know bigfunding.
I mean, EU in general, it'salways been very collaborative
(36:25):
within the European Union, whichmakes sense to them, you know, a
clusters of countriesgeographically close to each
other.
And and so they they could beleading in in that sense in
terms of regulations, they theyhave been.
Um places like I've seen um, youknow, like the United Nations
(36:46):
types of NGOs been doing some ofthat work.
Uh UNESCO, UNICEF been doingsome of um and also um OCED has
like a new.
I'm not sure if I'm familiarwith that.
So it's kind of like the thedeveloped country um research
(37:06):
arms or policy making.
So they also have an AI literacythat's kind of a a combination
of different country expertsthat come together and look at.
I see my logo work being donewith the AI literacy, or or what
does it mean to be AI literaryor digital literary or AI
fluent?
So there's a lot morecollaborative work being done
(37:28):
across countries in that sense.
Uh in terms of policies, I don'tknow.
I I tend to monitor a fewcountries just to see what
they're doing.
Like UK is doing great policywork.
They they have uh AI uh usecases, libraries that you can
look into, and and and I haven'tseen that in in in Canada yet.
SPEAKER_00 (37:50):
That's very interesting.
So you you've mentioned the termAI literacy a handful of times.
Yeah, and I know in previousprevious conversations that you
and I have had, you know, therethere's a really important
distinction between the idea ofAI literacy and AI fluency.
Um can you walk me through alittle bit of your your thoughts
on both of those uh thosepoints?
SPEAKER_02 (38:12):
Yeah, I mean some of it is I think it's a spectrum,
right?
It's it's uh a finer definition.
I think literacy, it's kind ofyour basics, your your
foundation building, if youwill.
It's it's just think aboutliteracy.
What what is basic literacy,right?
You can read, you can, you cando numbers, you can you can have
(38:32):
critical thinking skills, youcan identify you know, you can
tell truth from fiction, allthat stuff, right?
Um and uh you can you can youcan you can you can communicate
well, um all of that it's it'sbasic literacy.
So if you translate that intoAI, by the way, I think it's a
continuum of digital literacy.
I think AI it's so new, so wedifferentiate that from
(38:56):
traditional computer sciencetech technologies, but I think
eventually it's gonna fall intojust tech.
Um AI um is a tech, it's this abit of a joke about that to say,
oh, it's it's AI until it's notnew and shiny, and then it's
just regular tech, right?
And so I think it's a continuumof what we've been building for
(39:19):
like the past 20 years of whatwe call digital literacy.
Um so translating that frombasic literacy is you know, you
you need to understand thetechnology.
What what what is AI?
It's not one thing, it's a it'sa collection of different
techniques.
Um the definition changes overtime, and AI um, you know,
(39:43):
there's different domains withinthat.
Uh just different ways of doingAI, just your gen AI, there's
predictive AI, just robotics,and a whack of different fields
together.
So people need to have a generalunderstanding, right?
You need to have a generalunderstanding of how data works
with what AI.
How does how does that impact AImodels and output?
(40:06):
You need to understand criticalthinking skills, you need to
understand how creativity, youknow, uh the relationship
between creativity and AI.
You need to understand uh whatare some use cases in AI, you
need to understand the ethicalconcerns, which is another topic
that we can talk for anotherhour, Keith.
(40:26):
Um But fluency really it's it'suh to me at least is another
step of because you think aboutspeaking a language.
I can speak uh French.
Am I fluent in it?
SPEAKER_01 (40:42):
No.
SPEAKER_02 (40:43):
So there's a there's a a difference in mastery, I
think.
Right.
Um so fluency is yeah, you canuh perhaps teach these concepts
to other people.
Uh you could uh drive policies,uh, you could impact change in
in light of uh AI developmentand advancement.
So fluency it's it's that uhthat mastery level that you can
(41:07):
actually um uh help uh shape thefield.
It doesn't necessarily need tobe technical, you could be
someone that understanding umlimitations of AI and the risks,
and so you can shape policy thatway from a more sociological
perspective.
Um so by me advocating AIliteracy and fluency, it doesn't
(41:31):
mean everybody need to be a datascientist.
It doesn't mean everybody needsto start building AI models, but
I think everybody needs to getinvolved and first have a
baseline understanding and tohave that voice out there to
shape actively on how thistechnology is gonna develop and
(41:53):
impact us.
SPEAKER_00 (41:54):
So whose responsibility do you think it
is to make sure that we havethat level of well, we'll start
at the baseline literacy umacross a population?
SPEAKER_02 (42:06):
So who's responsibility before for basic
literacy?
Government, right?
Because we have education, wehave compulsory education, and
and so I think government needto take the lead to start with
that.
Um as you know, we as humanbeings are are not very
self-motivated or disciplined inin any shape and form.
(42:29):
Speaking for myself here, butbut I think um there needs to be
um uh some structure in place,if you will, to to help guide us
and also to help us understandwhy we need it so much, right?
SPEAKER_00 (42:47):
Yeah.
Well, and even if I think backto bring it to a kind of a maybe
a more digestible analogy, theone of the biggest things that
kind of separated people back inthe you know, the before time, I
don't know, 1800s, 1700s, etc.
etcetera, um was the ability toread, the ability to write.
(43:09):
Right, yeah.
Um and and not to be able tocode, but the ability to just
read a book.
And and the the knowledge gapand the knowledge boost that
came from being able to do that,all of a sudden you gave way
more power to people, you wereyou gave way more power to um
you know different thought, etc.
etc.
And the ability for nations,areas, regions, geographies to
(43:33):
compete really came from theability to educate their um
their population.
Don't don't you think and seethis as an imperative to just be
competitive at a at a baseeconomic level?
SPEAKER_02 (43:45):
Absolutely.
Oh, a hundred percent.
I mean, government is just thefirst step, right?
Um from a capitalisticdemographic society perspective,
we also need that as a um acompetitive advantage and also
as um it's something that youyou need to do so you're not
(44:06):
being excluded or or leftbehind.
So think about if you don't readhow much of information is being
left out for you.
So if you don't understand AI,it's increasingly embedded in
everything we do in in our inour houses, right?
It's all the AI embedded devicesas well.
(44:26):
So you don't want to be left outof the society.
So I think there's also personalinterest involved.
It's also I think the communityalso needs to take on some
responsibilities as as um ascommunities.
I think that needs to be uh um acommunity level education, uh
(44:47):
support in in understanding anddeveloping that literacy.
I I think of course school, butalso society, um nonprofit
organizations, like so.
I guess my response is everyoneat different levels needs to be
uh take up that responsibilityof of developing the literacy
(45:07):
for AI.
SPEAKER_00 (45:09):
I love that, and that makes complete sense.
Libraries.
Yeah.
SPEAKER_02 (45:12):
I mean, like they they play a major role in
information literacy, right?
So it's a natural extension tobe advocating and supporting AI
literacy at at the librarylevel.
SPEAKER_00 (45:24):
I think so.
And the the infrastructure isthere already.
Yeah, exactly.
SPEAKER_02 (45:27):
Everyone has a gathering place.
SPEAKER_00 (45:30):
So I I love it.
So so if we think about umturning the corner to you know
very practically if I'm abusiness leader, if I run a um
$20 million um mid-cap uh oiland gas company.
SPEAKER_02 (45:47):
I thought I was gonna say, I thought you are a
business leader.
SPEAKER_00 (45:50):
I guess I guess I don't have to pretend that much.
Exactly.
And maybe I'll I'll kind oftransport it.
I I feel like I know enough tobe dangerous in this space.
I feel like I still haveinfinity questions, but um
there's a lot of people that Italk to that are just so
overwhelmed about where to getstarted.
And so they I know.
Yeah they know that it'simportant.
SPEAKER_01 (46:12):
Yep.
SPEAKER_00 (46:12):
They know that it's something that that has to be
part of their business strategy,yeah, but have zero clue of
where to get started when itcomes to taking the first step
on this journey.
So from your perspective, whatdo they do?
SPEAKER_02 (46:29):
I completely understand that.
Um even as someone who actuallyhas a com-site background, I
feel overwhelmed all the time.
Like literally every day youwake up, there's this 10 stories
about AI, right?
It's it's it's overwhelming.
(46:50):
But I think um the impetus isyou have to get started
somewhere, and it's never toolate.
I I I really dislike thenarrative out there sometimes.
You hear it's like if youhaven't used AI, it's too late.
I'm like, no, like that is not agood place to start in terms of
(47:12):
encouraging people to try.
Um so I think it's never toolate.
It's you know, start at anytime.
But it doesn't have to be a bigthing.
I I it doesn't have the mediahyped up so much about AI, so
it's this mystical, almost likegodlike being, which isn't.
It's it's a tool, right?
It's a tech it's a technique,it's a platform.
(47:34):
Yeah, it's it's it's somethingthat's it's it's pretty it's a
pretty big deal, but it doesn'thave to be.
And it doesn't have to beingested in one goal.
It you can start by taking alittle bite here, a little bite
there, and um and start withjust one thing.
(47:55):
And I would start with what isit that like from a business
perspective?
I I work with businesses uh onthat, and I always say, well,
start with your your businessneeds.
Like, you know, what what whatare what are something that you
you're um dealing with that arethat are a bit of a a pin point
for you?
Like what is something that it'sa bottleneck or or or where are
(48:18):
the opportunities you're tryingto like seek out?
Where where do you want to growyour company?
What do you think um theseopportunities are or where are
something that's holding youback?
Like what are some problemsyou're dealing with from a
business perspective, right?
So start there.
I don't start with AI.
I I start with like what'swhat's your own use cases and
and and start thinking about,okay, you've it's um for
(48:43):
example, uh customer complaints,you get lots of them from uh
your your call centers.
Uh it's it's it's becoming aproblem.
So start there and look at whatAI tools, platforms, technology
can help with that and starttesting that.
Start investigating into maybe Itry this one tool and see if
(49:08):
that helps and use it in a in avery um in a in a creative
experimental pilot kind of way.
Say let's implement this for sixmonths, let's try it out, let's
have put a small team together,um, you know, test it and and
and make sure you measure you'veif it works, right?
(49:30):
And and that's all there is toit.
You don't have to start withthis big implementation of AI in
every department.
You don't have to start witheverybody need to be up and
running with, you know, aninternal AI that's it's built,
it's massive, that thateverything needs to be checked.
Um it's it's just with that thatalready gets you started.
(49:53):
And there's no two ways aboutit.
You need to start playing, youneed to start like testing, you
need to start uh shopping andlooking at tools or or you
whether you build it internallyor you work with an external
vendor, you start kind oftesting things and and get
demos, get people to to try itout and get some feedback.
SPEAKER_00 (50:12):
So as people get started, do they need different
people around them?
Do they need like if if you wereto think of the a demographic of
someone that helps organizationsget through this?
Did does the um soft skills ofthis person change?
Um or the the things that theybring to these leaders?
(50:33):
Like w what are some of thoseskills that are needed to help
organizations through this?
SPEAKER_02 (50:38):
Yeah, I think you definitely need different
business departments to worktogether.
I think it's one um I think it'sa unique thing about AI.
It's sometimes when youimplement a piece of tech in a
past, you can you can just havetwo or three departments and
that's it.
And I I AI cuts across so manydepartments.
You f you need to workcommunications department,
(50:59):
right?
Because you need to communicatethis, you know, how does this
being done, how is it affectingpeople, what are some risk
associated with that.
So you might have to work withlegal, you might have to work
with um L and D for training andand and and and upskilling
people, you probably need towork with procurement, you you
(51:21):
know, so so I think um I thinkif anything else, the soft
skills is even more importantnow because you have to work
with so many different groupsand you have to to manage and
negotiate relationships and makesure that everybody has a say
and everybody can bring a youknow a pr a piece of the AI lens
to this project.
(51:41):
So um so if anything else, Ithink it's even more important
about teamwork, aboutcommunications, about empathy,
right?
Because we we work with uh andcultural awareness.
I think that's becoming andculture doesn't just mean
countries, but also likedifferent subcultures within the
organization.
(52:01):
Uh like, you know, the IT teamshave their own culture, HR has
their own culture, even tounderstand how to make sure you
communicate so they understood,you know, the language, the
share language, if you will.
Um so so those are all the softskills that um perhaps we need
to about game a little bit more.
SPEAKER_00 (52:21):
I that makes complete sense to me.
So um you and I could keeptalking for probably three or
four more hours.
SPEAKER_02 (52:27):
Are we getting a signal now to stop talking?
SPEAKER_00 (52:30):
I don't I don't know.
I like I said, I I think that uhI I have one thing that I want
to end with, which is you know,if you have kind of some final
thoughts around maybe theopportunity um that's in in
front of us as as businessleaders, as a society, um, from
AI and from some of thesetechnologies that are going to
be game-changing, um, you know,what thought would you want to
(52:53):
leave people with?
SPEAKER_02 (52:57):
Wow.
So many.
SPEAKER_00 (53:00):
You gotta pick one.
SPEAKER_02 (53:01):
Okay.
Um I think don't be scared byAI, but also don't get bought
into the hype.
I think looking like go into itwith a a balanced lens.
There's gonna be opportunities,but there's also limitations and
(53:24):
and challenges and and thingsthat are risky.
So um so think about that andand make sure you do it in in a
way that's responsible, in a waythat's transparent, in a way
that you know, don't get caughtup in the efficiency game.
Think about impact, think aboutopportunities.
SPEAKER_00 (53:47):
I love it.
And so I'm sure people comingfrom this conversation will have
just as many questions as I did,and probably even more for you.
SPEAKER_02 (53:55):
I have more questions than answers,
honestly.
SPEAKER_00 (53:58):
I if people wanted to get in touch with you, is
there a way, um the best way todo that if they want to learn
more about you around the workyou're doing in Paradox?
Um, what's the best way?
SPEAKER_02 (54:07):
Um so my website is paradoxlearning.com, and you can
email me at Stella atParadoxLearning.com.
I am fairly active on LinkedInas well.
My LinkedIn handle is a StellaL, or just search my name.
I think um you should be able toget to me.
Uh I'm always happy to have aconversation.
(54:29):
I'd love to like I say I havemore questions to have answers
for.
So uh I love hearing otherpeople's perspectives as well.
So yeah.
SPEAKER_00 (54:39):
Fantastic.
This has been an absolutepleasure.
Thank you so much for taking thetime to come with us.
Thank you.
SPEAKER_02 (54:43):
It's a great conversation.
Thanks for having me.
SPEAKER_00 (54:46):
And I I feel like there's a part two in our
future, but this is this hasbeen fantastic.
So thank you so much today.
SPEAKER_02 (54:51):
Thanks, Keith.
SPEAKER_00 (54:53):
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