Host Jeff Yan continues his discussion with Clea Ramos, a Computer Engineering and Studio Arts student at Bucknell University, about the impact of AI tools like ChatGPT on education and the tech industry.
They examine effective strategies for leveraging AI while upholding learning integrity, reflecting on the future job market and potential entrepreneurial opportunities.
Clea shares her experiences leading a senior design project and offers insights on interdisciplinary learning. She highlights how AI transforms the connection between students and professionals in their work and education.
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
(00:00):
Welcome to DigicationScholars Conversations.
I'm your host, Jeff Yan.
In this episode, you will hear part twoof my conversation with Clea Ramos, a
student studying Computer Engineeringand Studio Arts at Bucknell University.
More links and information about today'sconversation can be found on Digication's
Twitter, Facebook, and Instagram.
(00:21):
Full episodes of Digication ScholarsConversations can be found on
YouTube or your favorite podcast app.
So, yeah, let me ask you then, like,what are your current view as a
soon-to-graduate student, especiallyGen A... Gen, um, A.I., you know, became
(00:41):
available to us two and a bit years ago,but really became like pretty dominant
probably in the last, let's call it ayear and a half, something like that.
What, how has that beenlike for you as a student?
I remember when ChadGPT came out, Ibelieve the winter of my sophomore year,
(01:03):
and students were using it for everythingat the time, and it was still pretty new,
so I would just hear about it here andthere, and because it's Liberal Arts,
I have friends in Engineering, I havefriends in Humanities, And I know the
Humanities have been pretty strict onit because their assignments comprise
of mostly writings and readings, andthey don't want you to ask ChatGPT to
(01:25):
summarize it or to write you a paragraphthat you're supposed to write yourself
because you're not learning at that point.
So I've taken a few classes inhumanities and some professors are
very strict about it in that sense.
But in, in the tech world and CompSci,it's a really great tool for debugging.
So you can put your code in itand say, I have an error here.
(01:45):
Can you please help me fix it?
And it won't do it 100 percentof the time completely correct.
So sometimes you have to edityour query and be more specific.
Uh, but I remember I was very hesitantto use it because it felt like cheating,
and it was kind of a morality issue.
And I've seen students who justuse ChadGPT to finish their whole
(02:07):
coding assignment for them, whichis against the point of doing
the coding assignment yourself.
So, Uh, our professor, a lot of professorsin, uh, STEM and in coding, specifically
CompSci, um, are for the use of it,sometimes as long as you cite it or
as long as you know the implicationsof it and use it as a tool rather
than using it to do your work for you.
(02:29):
So in that sense, I think it is a veryefficient tool because it can save you
hours of debugging or if you know how todo something really quick, you can ask.
chat, GBT, or any AIto generate it for you.
And I think some people are afraidthat it will take over our jobs,
but it doesn't have, it doesn't havethat human aspect to it, like we were
saying earlier, it doesn't, it doesn'trecognize the value that you're creating.
(02:52):
So knowing that is, isreally important to consider.
So I would say I am for usingChatGPT, as long as you're using
it responsibly and as a tool, andit's very, it's a very powerful tool
to accomplish things efficiently.
But just to be sure you can't rely on it.
I, I, by the way, I'm, I'm also verymuch for using it e... responsibly.
(03:16):
And I also think a lot about, you know,for the convenience that it affords
you and like, how else does it changethe way we think about this world?
So like.
I think about like in your case,for example, I can already hear
(03:39):
from certain engineers thatsays, no, but Clea, you're wrong.
It's the suffering of likespending hours looking for that
really, really little tiny bugthat makes you force you to learn.
I used to be like that.
You did?
Yeah.
And what changed or what areyou, do you still think that way?
(04:01):
Well, because I was, I felt like, again,like it was cheating, like I didn't learn
from it, but now if you don't use it,sometimes you're behind because other
people will use it and generate it somuch more quickly than you can learn.
Learn it.
And because sometimes with a searchengine, you type in your question
(04:21):
and you have to click on links.
And sometimes it's not exactly whatyou're looking for, whereas using
AI, you type in your question andit will provide more resources and
exactly what you want, depending onhow clear you are in your comment.
So it's that aspect of beingefficient, um, allows you to kind of
get ahead and do things much faster.
And I, let me, let me justkeep asking that, right?
(04:44):
So if you got done something faster.
What does that do?
Does it give you more time to, what is,what do you do with the time, like the
hours of agony that it saved you, right?
Yeah, but what is that like?
So what now?
Like you've just saved four hoursof looking for this really tiny bug
that it just Turns out to be youmissed the semi colon somewhere.
(05:07):
Happens, right?
Yes.
The semi colon.
And, uh, so, so, so nowit saved you that time.
What do you do with thattime because of that?
Yes, so, I think, um, that it does savetime, but I, I make sure that I go back
and read it to make sure I understand how.
The, the code is being produced and whatit actually means, not just copy paste.
(05:31):
Cause then at that point, I'm not learninganything because sometimes with coding
assignments, it just takes a long time.
And a lot of the time is debuggingwhere you can just push it in and
then it'll output what you need.
So, um, I think it's more prevalent,especially in my senior design
project where we're on a timeline.
So we have a year long projectwith a client and we're supposed
(05:53):
to deliver a product at the end.
And we, since I'm project manager, I'msetting the deadlines for each team
member, you should be done with your.
Block by this date, we need tobe done integrating by this date.
So by saving time that way, it allowsus to make sure we're on track and
on progress for our next steps inthe timeline, because in the real
(06:13):
world, especially with softwareengineering, you have things to deliver.
You have a product to getout to a client on time.
So that time efficiency is important.
And I find by the way, that real worldlearning is so nice and so important.
I wanted to talk a littlebit about this time aspect.
A little bit more, if that's all rightwith you, I sort of have this thesis that
(06:36):
first of all, in your project, you're theproject manager, you probably are both
a project manager and you probably dosome of the project as well, I assume,
but you also take on that role of makingsure that the things run, run, run on
time, uh, from everyone and they allsort of get to, you know, can come, can
coexist together harmoniously, right?
(06:58):
Mm hmm.
Number one is that I, I have found,at least for myself, sort of pre-AI
assistant, and this is like, I mean, Ithink people think about sometimes like,
(07:19):
Oh, you're in an education environment.
It's different from if you'rein the real world environment,
it is supposed to be painful.
It's supposed to be this,supposed to be that.
Um, I don't know, I don'treally fully agree with it.
You know, at my company, we have,you know, like engineers and
they work together and do things.
They value learning very much themselves.
(07:41):
They will use the toolsthough, in whatever ways that
they think is best for them.
And best sometimes means moreefficient, but sometimes it's less
efficient, but in order to understandit further, um, just, you know, it's
something that you have to understand.
And especially sort of in, in thecurrent climate of AI getting more and
(08:04):
more capable in coding and all that.
Yeah.
I mean, being able to debug faster meansthat they have less, they, they spending
less energy and time to the debugging,which some people might say that that's
where the art of, you know, codingis, this is, you're supposed to suffer
through that, um, so that you get better.
(08:25):
But I will also argue that I observe inour, in our, with our engineers, we may
not have been able to ship something atall if we didn't get that efficiency.
So.
And forget the fact that you have, inyour case, a client to deliver it to, if
you didn't get to finish the entire cycleand you slow down the rest of the team
(08:50):
and all of the rest of it, you also getless learning done because you were able
to get through less of the whole process.
Yeah.
Yeah.
So in some sense, that speedingup of certain aspect of it, it
also gave you more opportunity.
To do, to experience things thatyou never would get to be able
(09:13):
to, to be, to be able to do.
It's almost like if you were trainingfor a marathon, but somehow you can
never run past the 20 mile mark.
You would never know whatthe last six miles look like.
Mm-hmm . Yes, for sure.
Yeah.
So you kind of, you know, like theefficiency gained also means you
now get to run the last six miles.
(09:35):
Mm-hmm . And having the entireexperience of finishing 26.2 miles.
Is maybe better than having thestruggle at Model 15 to 18 so much.
Yes.
It's a balance.
Yeah, it's a balance.
Some people will just use chat and thennot, not have that struggle, and then
(09:57):
it's frustrating to figure it on your own.
Just basically flat outlike cheated, right?
Yes.
Yeah.
Yeah.
So it's a balance, like at some point.
You, you need to balance the efficiencybecause sometimes we get stuck on a
problem and then we use chat and then atsome point you try everything and it's
not worth spending time over debugging.
You might as well just go tothe professor, go to office
(10:19):
hours, get it solved in class.
So it's a balance of like usingefficiency, but to some point it just
doesn't work and you, and you justhave to figure it out and you do end
up putting the hard work in, it's just,you're skipping over the things that are
more easily solvable by using ChatGPT.
I think you're absolutely right.
And this is the part that I sometimes,you know, try to try to try to look at
(10:41):
is you, you are, if you are someone who.
Actually just have it do everythingfor you and you just flat out
just not spending any time.
You're just, you know,basically doing a poor job.
What happens is that you get awayfor a very short time anyway,
because, you know, you, like yousaid, it's a year long project.
The project gets more and more complex asit goes and things are interrelated and
(11:04):
you really have to understand it for itto actually, for you to even contribute.
Because it builds.
Yeah, if you are that team memberwho's just like, I'm just going to
paste in whatever, you know, aftera couple of months, maybe the first
couple of months you are like, reallylike just slacking and not doing
anything, but after a couple of months,I don't think you can even contribute
(11:25):
at that team because you'd be lost.
It'll be like outsourcing someonewatching a. You know, eight
season-long, you know, series, you,you've got to watch to know the plot.
You can't follow it, you know,if you're not part of it.
Um, and I find that to be sort of like,so, I mean, you, you'd learn that lesson
(11:48):
relatively quickly, I think, you know, if,if your projects are real world enough.
I think it's problematic when theprojects are not real world enough,
where you are just asking problem setsand individual essays, because then,
yeah, it's really easy for someoneto just go, yeah, I just did that.
I passed it.
(12:08):
It has nothing to do withthe next project anyway.
Yeah.
So then, you know, like that.
That efficiency suddenly becomes very,so that you can cheat and it doesn't,
it doesn't, there's no concerns,you know, you weren't really being
asked to build on, on top of it.
I can't imagine in your projectthat your team members could survive
(12:31):
if they just kind of, you know,not actually know what's going on.
Um, I find it to be in my team, youknow, like if I have an engineers who
basically just kind of, they don'treally know what's going on, like.
They can't even last one discussionbecause we'll be talking about something,
be like, well, what do you think of this?
And they wouldn't be able to,they wouldn't know because they
(12:53):
didn't understand, you know, whythe decision was made before.
So it would be like, like I said,just asking you what happened with
last week's episode on severance.
And you're like, well, I didn'twatch it then, but you don't know.
You just simply don't know.
Right.
You can't cheat your way out of that.
Um, and so.
And it's not even so much about, I thinklike people want to do it at that point.
(13:17):
Um, they actually justwant to do the project.
And I also want, um, have oneobservation that I have found too,
which is because it's efficient.
We have started to be able to.
At least in our own engineeringand design projects that we've
been able to do sometimes
(13:39):
sort of additional iterationsthat previously we wouldn't
be able to afford to do.
Cause we only had time to do so much.
And you'd kind of have to kind of go,well, this is what we have time for.
This is what we're going with.
Sometimes even knowing that it may not bethe best solution, but we don't have time
(13:59):
to experiment with three other solutions.
Yes.
But now I feel like that we are startingto find ourselves that if we make it so
that we're just going to almost like letit generate something it's rough and we're
not going to actually use it, but we'regoing to do three different approaches
so that we can experiment a little bitand then we can like make some decisions.
(14:22):
Yeah.
That prototyping phases.
So yeah, it's like, it's tremendous, youknow, It's tremendous, like the ability
to prototype and then prototyping ismaybe is one of those processes that is
very well known in that design thinkingin the engineering, uh, design sort of
process, but maybe it's less so in, um,I don't know, um, writing an essay on
(14:45):
history, um, But historians have theirown, like, unique ways of thinking
that I think is really useful too.
So like, I think these are the kind ofthings that multiple, multidisciplinary
sort of thinking is really goingto enhance the way that we, we
function, especially with this sort ofexplosion of, you know, AI and so on.
(15:07):
So what do you think as someone who's,so you talked about it as a student,
what do you think, you know, as someonewho is about to graduate, do you feel
Prepared to go into the workforce.
Do you know, like thishopefully doesn't scare you.
I don't think you should be scared,but, um, I did see that, um, I think
(15:29):
Meta had said that they had the, in2025, they will not hire any junior
level developers, um, because they are.
Finding that, you know, they'regoing to either, you know, have AI
agents or something to replace that.
It definitely creates other problems,which is like, if you can't be junior, how
(15:51):
do you become the senior level developer?
There's a, there's a bit of a, you know,they're creating a bit of a chicken and
the egg, you know, breaking the cyclesomewhere in their, um, Salesforce.
Also said that they will in2025, they're freezing...
I think all hiring because they arerefocusing and trying to figure out
(16:14):
what their engineering needs are.
It doesn't mean that they will forevernot hire, but they're saying in 2025,
we're not hiring at all, we're puttinga freeze on hiring our engineers, which
is unheard of for that company before,because every year they would just hire
thousands of people at the same time.
There is a lot of needs for engineerseverywhere else, but I'm just sort
of like painting a picture for peopleto know, like, as in, you know, like
(16:37):
beginning of 2025, this is what the,the climate looks like right now as
someone who's about to graduate and inthe job market networking and so on.
What, uh, how do you feel about this?
Thank you for telling me about it.
Cause I, I didn't knowabout that until now.
So that is a little concerning,especially knowing that the job market
(16:59):
is also really competitive in terms ofthe computer science software space.
Um, I've been hearing of peoplehaving a hard time getting software
positions, internships, and jobs.
And.
I think that that's reallydiscouraging, especially if they're
using AI to replace those careers.
Cause when it's, like you said, takingaway from new graduates and it's also
(17:22):
taking away that, that human aspectthat I was talking about earlier,
although it is efficient and maybe maysave the company some money, you're,
you're taking away those opportunitiesof learning and building your sense
of, um, community within that company.
So that's, that is interesting.
(17:44):
But I, I really, by the way, I,I didn't mean to, um, scare you
during this conversation here, Clea.
Um, but I also think that there is nowa groundswell of people like yourself,
who has the skills, who has the thinkingprocess, who understand projects, who
(18:06):
understand how to work, you know, to ask,how to understand, how to ask questions.
That's actually one of the skills thatis necessary for people to, for example,
go with a much more entrepreneurial,you know, uh, path where there are
software engineers or engineers whodecide that, Hey, you know what?
I'm making something up here.
(18:27):
There wasn't a, a way for, forthe Filipino community to, beyond
Bucknell, but like in maybe in yourarea, wherever you end up being, you
know, and, um, and that now you can.
Because of the speed of development,because of the new tools, because of,
(18:48):
you know, the access to some of this,these AI tools, um, that I, I heard an, a
very interesting interview that said, wewonder at what point we're going to see
the first solo entrepreneur billionaire,which is a really interesting, um, sort
(19:12):
of, and I mean, billionaire is more likea symbol that I don't think, you know,
I don't even think any of like meremodels like me, um, can even understand
how much money that actually is.
But, but my point, I think the pointof it is more like you can potentially
be extremely successful at this job andthat you might even be, um, able to do
(19:38):
it with far fewer resources than, thanwhat used to be, you know, you don't have
to become the Google, you know, that hasemployees, many hundreds of thousands
of employees in order to do this reallydifficult job, it almost feels like
there's a lot more, um, opportunitiesfor people to be able to say, you know
(20:00):
what, if I think that bringing water to...
you know, places in need is the thingthat needs to exist in the world.
And there is not a businessthat is doing that right now.
I can do it because using theefficiency that's created by AI, um,
what used to have taken, you know,an insurmountable amount of resource.
(20:21):
Just to do the communication and thedesign and the PR and all that I might
in 2026 create agents that can takecare of a lot of that for me so that I
can do things that are more meaningful.
I think that's a reallydifferent kind of future.
I think it's scary on one hand, but it'salso like exhilarating on the other hand.
(20:44):
Yes, for sure.
That's so interesting because I,I've spoken to people who, when
networking, they didn't like majorin computer science or anything,
but they learned it on their own.
And I guess when learning onyour own, Chat, GPT, or AI
helpers are such a important andhelpful tool to learn as well.
(21:06):
So having that aspect to help you dothings on your own rather than always
relying on having to be taught orhaving to buy all of these resources
in order to get things done is soempowering because you can really
do anything on your own these daysbecause of all of the resources,
open source platforms available.
But it's also not necessary.
(21:27):
It doesn't have to be really solo.
But imagine if you can run a tremendouslyimpactful business or organization,
right, that do meaningful things,but it's just 10 of you, um, right.
It could also be this.
You know, but, but it wouldhave in the past would have
required a hundred people, right.
(21:50):
And it, like that to me is a reallyinteresting part of the world that I
don't think a lot of people are exploringbecause, you know, there's a lot
about replacing current jobs and, and.
And it might, I think that it willcreate, replace some jobs, maybe even
many jobs, um, especially what would beconsidered entry level jobs, or maybe
(22:10):
even to a certain degree, mid level jobs.
Um, but I think that.
You know, there, it, it feels liketo me, kind of like what I was
saying before, okay, you save timeover here, but you actually end
up spending the time elsewhere.
So now you're able to push it further.
Yes.
And so I feel like that, you know,taking something away from one
(22:32):
side will, will inevitably getbalanced out on the other side too.
Um, but it, it is difficult, youknow, especially for folks who
You know, this was forced on them.
This was a natural progression.
You know, if I've had this job forthe last 25 years, um, suddenly I
(22:54):
being forced to re-skill, up-skill,change skills, change jobs too.
To, to deal with this, youknow, new world, it, it feels
difficult and feels uncomfortable.
Um, but I, I kind of, you know, I wasreally interested in hearing sort of from
someone who's about to graduate, right?
I also think about, you know,for people who are, you know,
(23:19):
freshmen now at Bucknell, right?
Like when they graduate.
Yes.
What does the world look like then?
Because you are alreadyseeing a little bit of this.
In 2025, right?
Mm-hmm . I like 2028.
Like, that's gonna bereally different, right?
Mm-hmm . And I think the youngergenerations now have, they have so
(23:41):
much ambition and now they have alot of resources and more tools.
So I see them having more and moreprogress and more and more, um,
really cool projects coming out thatthey're really passionate about.
And I know they're gonnaachieve so much more.
So.
Well, you are part of theyounger generation, Clea.
Just wanted to say you, youhave those tools as well, and
(24:02):
you, you'll get to use them too.
Um, I, I hope that, by the way,that it wasn't, uh, you didn't
get scared from that, but, um.
I still have hope, youknow, cause, because I've.
I feel like what you were saying, it'snot enough to be just an engineer.
You need to have all of those skills andthat interdisciplinary, which I think
(24:22):
AI could never replace all of those likehuman aspects that makes a person a person
because what, how you provide value inyour work or like you said, your past
experience and your identity, how allof those aspects of your identity and
what you've been through affect how youdo your current work, which A.I. Could
never have that like history built in.
(24:44):
Yeah, and and that's right.
Actually, A.I. cannot do that for us.
Um, you have to be the one whoyou can have a lot of experience.
Someone can read aloud theexperiences to you, but you still
have to go through the heart.
The hard work is how do you process that?
And how do you.
Make sense of all those experiences.
I want to say that all that'sexactly what your reflections did.
(25:07):
You know, like doing the project itselfis one thing, but the reflection is
the part where you had the experience.
Now you get to process it andyou were able to make pretty big
jumps every time, you know, youbuild one from one to the other.
And those are the thingsthat stays forever, right?
Like the C sharp code that youwrote in for whatever that's going
(25:30):
to get obsolete, unfortunately.
Right.
But, but the ability to sortof take the thinking and like
combine those experiences.
And then figuring out what kind ofthinker you are, you know, as you would
solve problems, means that by the timeyou write the next piece of code that
is not even in C sharp, will, you willstill be able to apply those, right.
(25:53):
And, but it's really about even liketaking coding to design and all of
that is even make it even stronger.
I really believe that.
I think that's, that's,that's what it's going to be.
And you were talking about augmentedreality and virtual reality before.
I mean, that's another really like.
To me, surprisingly unspoken areatoo, you know, I was thinking about,
(26:15):
you know, like if you are trainingto become a nurse in 2025 right
now, and you're going to graduate in2028, we talked about that, right?
It may very well be that you are nolonger, or it may very well be that
(26:35):
the... you know, currently, I thinka lot of nursing majors have to learn
a humongous amount of content, likethe material is staggering, right?
Like every procedure that they'resupposed to know, every condition,
there's all the protocols, right?
(26:56):
I kind of kept imagining withengineers like you, who's
going to create a safe, secure.
Accurate, non hallucinogenicversion of some kind of AR glasses
that a nurse would be able to wearcomfortably, you know, all day.
(27:18):
And being able to say, like, generallyspeaking, if I, you know, have a
patient who is having a certainkind of symptoms or is having
certain kind of pain or knowingthat they are having a heart attack.
That your
AR will helpfully just go, this iswithout going through like public servers
(27:44):
and stuff, you know, like within thehospital, like it's always safe and it's
not sharing that material with anyone.
Being able to just go here,here are the next seven steps.
Here are some other additionalthings that you need to know.
This is the timing inwhich you need to do them.
Etc, etc. Not that the nurseshould just purely count on that.
(28:06):
Having that assistant wouldbe so incredibly useful.
Yes.
And being able to sort ofsay, like, did I do them?
Or did I, like, or you, maybe, maybea heart attack is common enough
that you just know that, right?
But maybe you come across somethingthat you've never done, or you
haven't done in three years.
Mm. Right?
Like, typically, by the way, likemany doctors and nurses in some
(28:32):
of those situations, they actuallyhave to look things up, right?
They have to, and this is also wheresometimes you, or sometimes some things
you missed and then you, you know,this is where like practice lawsuits
come in and so on and so forth.
But I could imagine that, youknow, a well developed tool like
that could be, you know, lifechanging for, for all of us, right?
(28:56):
In medical care.
Yeah.
And it would allow for, yeah, it wouldallow for someone to not count on what
if the nurse got tired because they didalready, it's their 12th hour working that
day and it's been a crazy day, you know,of all kinds of, you know, high adrenaline
events that happen over and over again.
Right.
It happens.
(29:17):
Right.
And, and what if you can create thattool and, and what, what does that
change for that nursing students?
You know, like, what if theyend up spending a little less
energy on acquiring all of thecontent, which is an investment.
For me, when I see it, I feel like it'san insurmountable amount of content
(29:42):
that in fact, it just keeps growingbecause, you know, people are researching
more, discovering more how to even.
Keep that in the, in our brain, you know?
Yes, it's impressive the workthey do and that there's so
much risk in Incorporating.
They put their lives at stake every singleminute because you never know like you
(30:03):
can Contract whatever it is that's causingsomeone to be sick, for example, right?
And so you're doing all of that Like,I almost imagine, like, wow, you would
be the person, you'll be the kind ofpeople who would have the skills to
create the AR technology that can helpsomeone like that, and in turn, it will
(30:25):
help save countless lives, and it willalso change their perspectives a lot too.
So, I remember.
You know, as a kid, I don't know whetheryou felt that way too, but as a kid,
I mean, if I'm an Asian family, likethere is some default professions that
(30:45):
are cool to do, doctor being one, right?
Yes, for sure.
And, um, I remember.
Learning the little, littlestbit about being a doctor.
And it was like, well,it's a lot of studying.
It was like a huge amount of memorizing,like lots and lots and lots of facts and
big words and, and, and, and systems.
(31:07):
And I remember thinking.
That's just not for me.
Now I speak with a lot of doctors,people who had gone through medical
training that says, well, yeah, thatis actually like legitimately really,
really hard, but that's not all I do.
In fact, that's not what I do.
(31:28):
So they think about the world verydifferently already, but I have this
like, you know, impression that thisis an unattainable thing because.
It's so, it's so much about memorizinga huge amount of content and that
I'm just like, that's not for me.
Like I may be able to do it, but like, youknow, like I can't, I don't find that to
(31:49):
be a good use of my, my, my, my, my time.
But if that got taken out of theequation, maybe not completely,
but like the pressure of like beingtested on those things as being your,
the majority of what you do, right.
It may mean that providing care forsomeone, becoming the, the, the,
(32:10):
the, uh, providing, making someoneelse's healthy, um, becomes, you
know, part of the equation, likethe bigger part of the equation.
It may change a lot of people's minds.
Yes.
Yeah.
I have a similar story of how peopleare saying, I was asking, um, A
friend who graduated and I was askingher, Oh, we have to learn so much
(32:30):
technical things in our ECEG classes.
Like how much of it do you actuallyuse similar to how the doctors have
to learn all of these procedures andmemorize a lot of things, but they don't
maybe directly use it in their work.
So I was asking her, howmuch do you actually.
Use this because she'san electrical engineer.
And she was saying not too much,all of the things that we learned,
(32:50):
because I think the processes atschool are just teaching you how to
learn, teaching you the fundamentalsand what you really do in a real time
job and work is like you learn, likethe processes that your company uses
and you need to learn how to learn.
And that's what school prepares you for.
And being able to find those things thatyou need to learn and learn by yourself.
(33:11):
I think that's what AI is really great.
For being able to learn fast on thejob when you need to know these things,
maybe not off the top of your head,but you have like that background.
That's beautifully said.
Clea, thank you so much forspending all this time with me.
I really, really enjoyed our conversation.
You are brilliant.
(33:32):
I, I, um, I am so impressed with,you know, this, you know, what
you have to say and how you thinkabout the world is fascinating.
Um, I think that, um, those of us,I'd be listening to this again, but,
and those of us, I think are alsolistening right now who are, you know,
(33:53):
from my generation or the, you know,the, even the older generations should
look at, you know, should listenclosely to what you are telling us.
And what you, how you think abouta world, what makes sense and, and,
and, and how you are, you know,what your real experience is like.
So that, you know, for those of us whoare in any positions of like making those
(34:18):
kinds of decisions, uh, thinking aboutlike the future of education, maybe.
So I know that there are people whoare Deans and, you know, Department
Chairs who have the ability to,to influence where this goes.
I think we have a lot of work to do.
I think we have a lot to do to makesure that our, you know, like, not
only for you graduating in 2025, butwhat about those who are graduating in
(34:40):
26, 27, 28, like we gotta, we gotta dothese things quickly to, to make sure
that you are not going to be, you know,getting out to the world and, and, and
feel like that you are sort of, youknow, you're not able to contribute,
um, because the real world looks toodifferent from what was presented to
(35:04):
you in, in, in an education environment.
Um, and I'm so glad thatyou're at Bucknell who.
Which, like you said, does not do that.
Um, it allows you to ask questions,like to work on real world project.
So you hear from here, Bucknelluniversity, please go check it out.
Um, I think many people already know this.
I'm in school is very well known,but I, for people who, who are really
(35:26):
not, um, you know, who are thinkingabout like, you know, engineering,
for example, like Clea, uh, was.
Should think about what it means to goto a program that has equal emphasis on
liberal arts, um, on sort of these abilityfor you to ask, ask questions yourselves
and to lead teams, um, and do all theseother things that, uh, is, is going to
(35:50):
go beyond just, you know, 25 really,really hard problem sets, um, right.
Um, and, um.
And for those, uh, last reminder forthose who are looking for the next
generations of the best talents, I thinkclear here is certainly one of them.
If you are creating those glassesfor AR, you know, for an AR company,
(36:12):
um, you know, contact her quicklyor she would be off the market.
All right.
Thank you all so much.
And, uh, Clea, I reallyappreciate this conversation.
I hope that we can get to,um, keep in touch and, uh, let
me, let me know how things go.
Okay.
Yes.
Thank you again so muchfor this opportunity.
I really enjoyed reflecting on my,my ePortfolios and all the projects
(36:33):
I've done and how much I've learnedsince then and how much Digication
has helped me to, to reflect on theseexperiences and to showcase them as well.
So thank you.
Well, I, I, I appreciate the kind words.
Take care and, uh, goodluck with everything.
And congratulations, uh, uh, in advanceon your, your completion of your degrees.
(36:54):
Thank you so much, Jeff.
Okay, take care.
Bye.
Thank you.
Bye bye.
This concludes our conversation.
To hear our next episode, be sureto subscribe to Digication Scholars
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The Digication Scholars ConversationSeries is brought to you by Digication,
(37:15):
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Thanks for tuning in.
Welcome to DigicationScholars Conversations.
I'm your host, Jeff Yan.
In this episode, you will hear part twoof my conversation with Clea Ramos, a
student studying Computer Engineeringand Studio Arts at Bucknell University.
More links and information about today'sconversation can be found on Digication's
Twitter, Facebook, and Instagram.
(00:21):
Full episodes of Digication ScholarsConversations can be found on
YouTube or your favorite podcast app.
So, yeah, let me ask you then, like,what are your current view as a
soon-to-graduate student, especiallyGen A... Gen, um, A.I., you know, became
(00:41):
available to us two and a bit years ago,but really became like pretty dominant
probably in the last, let's call it ayear and a half, something like that.
What, how has that beenlike for you as a student?
I remember when ChadGPT came out, Ibelieve the winter of my sophomore year,
(01:03):
and students were using it for everythingat the time, and it was still pretty new,
so I would just hear about it here andthere, and because it's Liberal Arts,
I have friends in Engineering, I havefriends in Humanities, And I know the
Humanities have been pretty strict onit because their assignments comprise
of mostly writings and readings, andthey don't want you to ask ChatGPT to
(01:25):
summarize it or to write you a paragraphthat you're supposed to write yourself
because you're not learning at that point.
So I've taken a few classes inhumanities and some professors are
very strict about it in that sense.
But in, in the tech world and CompSci,it's a really great tool for debugging.
So you can put your code in itand say, I have an error here.
(01:45):
Can you please help me fix it?
And it won't do it 100 percentof the time completely correct.
So sometimes you have to edityour query and be more specific.
Uh, but I remember I was very hesitantto use it because it felt like cheating,
and it was kind of a morality issue.
And I've seen students who justuse ChadGPT to finish their whole
(02:07):
coding assignment for them, whichis against the point of doing
the coding assignment yourself.
So, Uh, our professor, a lot of professorsin, uh, STEM and in coding, specifically
CompSci, um, are for the use of it,sometimes as long as you cite it or
as long as you know the implicationsof it and use it as a tool rather
than using it to do your work for you.
(02:29):
So in that sense, I think it is a veryefficient tool because it can save you
hours of debugging or if you know how todo something really quick, you can ask.
chat, GBT, or any AIto generate it for you.
And I think some people are afraidthat it will take over our jobs,
but it doesn't have, it doesn't havethat human aspect to it, like we were
saying earlier, it doesn't, it doesn'trecognize the value that you're creating.
(02:52):
So knowing that is, isreally important to consider.
So I would say I am for usingChatGPT, as long as you're using
it responsibly and as a tool, andit's very, it's a very powerful tool
to accomplish things efficiently.
But just to be sure you can't rely on it.
I, I, by the way, I'm, I'm also verymuch for using it e... responsibly.
(03:16):
And I also think a lot about, you know,for the convenience that it affords
you and like, how else does it changethe way we think about this world?
So like.
I think about like in your case,for example, I can already hear
(03:39):
from certain engineers thatsays, no, but Clea, you're wrong.
It's the suffering of likespending hours looking for that
really, really little tiny bugthat makes you force you to learn.
I used to be like that.
You did?
Yeah.
And what changed or what areyou, do you still think that way?
(04:01):
Well, because I was, I felt like, again,like it was cheating, like I didn't learn
from it, but now if you don't use it,sometimes you're behind because other
people will use it and generate it somuch more quickly than you can learn.
Learn it.
And because sometimes with a searchengine, you type in your question
(04:21):
and you have to click on links.
And sometimes it's not exactly whatyou're looking for, whereas using
AI, you type in your question andit will provide more resources and
exactly what you want, depending onhow clear you are in your comment.
So it's that aspect of beingefficient, um, allows you to kind of
get ahead and do things much faster.
And I, let me, let me justkeep asking that, right?
(04:44):
So if you got done something faster.
What does that do?
Does it give you more time to, what is,what do you do with the time, like the
hours of agony that it saved you, right?
Yeah, but what is that like?
So what now?
Like you've just saved four hoursof looking for this really tiny bug
that it just Turns out to be youmissed the semi colon somewhere.
(05:07):
Happens, right?
Yes.
The semi colon.
And, uh, so, so, so nowit saved you that time.
What do you do with thattime because of that?
Yes, so, I think, um, that it does savetime, but I, I make sure that I go back
and read it to make sure I understand how.
The, the code is being produced and whatit actually means, not just copy paste.
(05:31):
Cause then at that point, I'm not learninganything because sometimes with coding
assignments, it just takes a long time.
And a lot of the time is debuggingwhere you can just push it in and
then it'll output what you need.
So, um, I think it's more prevalent,especially in my senior design
project where we're on a timeline.
So we have a year long projectwith a client and we're supposed
(05:53):
to deliver a product at the end.
And we, since I'm project manager, I'msetting the deadlines for each team
member, you should be done with your.
Block by this date, we need tobe done integrating by this date.
So by saving time that way, it allowsus to make sure we're on track and
on progress for our next steps inthe timeline, because in the real
(06:13):
world, especially with softwareengineering, you have things to deliver.
You have a product to getout to a client on time.
So that time efficiency is important.
And I find by the way, that real worldlearning is so nice and so important.
I wanted to talk a littlebit about this time aspect.
A little bit more, if that's all rightwith you, I sort of have this thesis that
(06:36):
first of all, in your project, you're theproject manager, you probably are both
a project manager and you probably dosome of the project as well, I assume,
but you also take on that role of makingsure that the things run, run, run on
time, uh, from everyone and they allsort of get to, you know, can come, can
coexist together harmoniously, right?
(06:58):
Mm hmm.
Number one is that I, I have found,at least for myself, sort of pre-AI
assistant, and this is like, I mean, Ithink people think about sometimes like,
(07:19):
Oh, you're in an education environment.
It's different from if you'rein the real world environment,
it is supposed to be painful.
It's supposed to be this,supposed to be that.
Um, I don't know, I don'treally fully agree with it.
You know, at my company, we have,you know, like engineers and
they work together and do things.
They value learning very much themselves.
(07:41):
They will use the toolsthough, in whatever ways that
they think is best for them.
And best sometimes means moreefficient, but sometimes it's less
efficient, but in order to understandit further, um, just, you know, it's
something that you have to understand.
And especially sort of in, in thecurrent climate of AI getting more and
(08:04):
more capable in coding and all that.
Yeah.
I mean, being able to debug faster meansthat they have less, they, they spending
less energy and time to the debugging,which some people might say that that's
where the art of, you know, codingis, this is, you're supposed to suffer
through that, um, so that you get better.
(08:25):
But I will also argue that I observe inour, in our, with our engineers, we may
not have been able to ship something atall if we didn't get that efficiency.
So.
And forget the fact that you have, inyour case, a client to deliver it to, if
you didn't get to finish the entire cycleand you slow down the rest of the team
(08:50):
and all of the rest of it, you also getless learning done because you were able
to get through less of the whole process.
Yeah.
Yeah.
So in some sense, that speedingup of certain aspect of it, it
also gave you more opportunity.
To do, to experience things thatyou never would get to be able
(09:13):
to, to be, to be able to do.
It's almost like if you were trainingfor a marathon, but somehow you can
never run past the 20 mile mark.
You would never know whatthe last six miles look like.
Mm-hmm . Yes, for sure.
Yeah.
So you kind of, you know, like theefficiency gained also means you
now get to run the last six miles.
(09:35):
Mm-hmm . And having the entireexperience of finishing 26.2 miles.
Is maybe better than having thestruggle at Model 15 to 18 so much.
Yes.
It's a balance.
Yeah, it's a balance.
Some people will just use chat and thennot, not have that struggle, and then
(09:57):
it's frustrating to figure it on your own.
Just basically flat outlike cheated, right?
Yes.
Yeah.
Yeah.
So it's a balance, like at some point.
You, you need to balance the efficiencybecause sometimes we get stuck on a
problem and then we use chat and then atsome point you try everything and it's
not worth spending time over debugging.
You might as well just go tothe professor, go to office
(10:19):
hours, get it solved in class.
So it's a balance of like usingefficiency, but to some point it just
doesn't work and you, and you justhave to figure it out and you do end
up putting the hard work in, it's just,you're skipping over the things that are
more easily solvable by using ChatGPT.
I think you're absolutely right.
And this is the part that I sometimes,you know, try to try to try to look at
(10:41):
is you, you are, if you are someone who.
Actually just have it do everythingfor you and you just flat out
just not spending any time.
You're just, you know,basically doing a poor job.
What happens is that you get awayfor a very short time anyway,
because, you know, you, like yousaid, it's a year long project.
The project gets more and more complex asit goes and things are interrelated and
(11:04):
you really have to understand it for itto actually, for you to even contribute.
Because it builds.
Yeah, if you are that team memberwho's just like, I'm just going to
paste in whatever, you know, aftera couple of months, maybe the first
couple of months you are like, reallylike just slacking and not doing
anything, but after a couple of months,I don't think you can even contribute
(11:25):
at that team because you'd be lost.
It'll be like outsourcing someonewatching a. You know, eight
season-long, you know, series, you,you've got to watch to know the plot.
You can't follow it, you know,if you're not part of it.
Um, and I find that to be sort of like,so, I mean, you, you'd learn that lesson
(11:48):
relatively quickly, I think, you know, if,if your projects are real world enough.
I think it's problematic when theprojects are not real world enough,
where you are just asking problem setsand individual essays, because then,
yeah, it's really easy for someoneto just go, yeah, I just did that.
I passed it.
(12:08):
It has nothing to do withthe next project anyway.
Yeah.
So then, you know, like that.
That efficiency suddenly becomes very,so that you can cheat and it doesn't,
it doesn't, there's no concerns,you know, you weren't really being
asked to build on, on top of it.
I can't imagine in your projectthat your team members could survive
(12:31):
if they just kind of, you know,not actually know what's going on.
Um, I find it to be in my team, youknow, like if I have an engineers who
basically just kind of, they don'treally know what's going on, like.
They can't even last one discussionbecause we'll be talking about something,
be like, well, what do you think of this?
And they wouldn't be able to,they wouldn't know because they
(12:53):
didn't understand, you know, whythe decision was made before.
So it would be like, like I said,just asking you what happened with
last week's episode on severance.
And you're like, well, I didn'twatch it then, but you don't know.
You just simply don't know.
Right.
You can't cheat your way out of that.
Um, and so.
And it's not even so much about, I thinklike people want to do it at that point.
(13:17):
Um, they actually justwant to do the project.
And I also want, um, have oneobservation that I have found too,
which is because it's efficient.
We have started to be able to.
At least in our own engineeringand design projects that we've
been able to do sometimes
(13:39):
sort of additional iterationsthat previously we wouldn't
be able to afford to do.
Cause we only had time to do so much.
And you'd kind of have to kind of go,well, this is what we have time for.
This is what we're going with.
Sometimes even knowing that it may not bethe best solution, but we don't have time
(13:59):
to experiment with three other solutions.
Yes.
But now I feel like that we are startingto find ourselves that if we make it so
that we're just going to almost like letit generate something it's rough and we're
not going to actually use it, but we'regoing to do three different approaches
so that we can experiment a little bitand then we can like make some decisions.
(14:22):
Yeah.
That prototyping phases.
So yeah, it's like, it's tremendous, youknow, It's tremendous, like the ability
to prototype and then prototyping ismaybe is one of those processes that is
very well known in that design thinkingin the engineering, uh, design sort of
process, but maybe it's less so in, um,I don't know, um, writing an essay on
(14:45):
history, um, But historians have theirown, like, unique ways of thinking
that I think is really useful too.
So like, I think these are the kind ofthings that multiple, multidisciplinary
sort of thinking is really goingto enhance the way that we, we
function, especially with this sort ofexplosion of, you know, AI and so on.
(15:07):
So what do you think as someone who's,so you talked about it as a student,
what do you think, you know, as someonewho is about to graduate, do you feel
Prepared to go into the workforce.
Do you know, like thishopefully doesn't scare you.
I don't think you should be scared,but, um, I did see that, um, I think
(15:29):
Meta had said that they had the, in2025, they will not hire any junior
level developers, um, because they are.
Finding that, you know, they'regoing to either, you know, have AI
agents or something to replace that.
It definitely creates other problems,which is like, if you can't be junior, how
(15:51):
do you become the senior level developer?
There's a, there's a bit of a, you know,they're creating a bit of a chicken and
the egg, you know, breaking the cyclesomewhere in their, um, Salesforce.
Also said that they will in2025, they're freezing...
I think all hiring because they arerefocusing and trying to figure out
(16:14):
what their engineering needs are.
It doesn't mean that they will forevernot hire, but they're saying in 2025,
we're not hiring at all, we're puttinga freeze on hiring our engineers, which
is unheard of for that company before,because every year they would just hire
thousands of people at the same time.
There is a lot of needs for engineerseverywhere else, but I'm just sort
of like painting a picture for peopleto know, like, as in, you know, like
(16:37):
beginning of 2025, this is what the,the climate looks like right now as
someone who's about to graduate and inthe job market networking and so on.
What, uh, how do you feel about this?
Thank you for telling me about it.
Cause I, I didn't knowabout that until now.
So that is a little concerning,especially knowing that the job market
(16:59):
is also really competitive in terms ofthe computer science software space.
Um, I've been hearing of peoplehaving a hard time getting software
positions, internships, and jobs.
And.
I think that that's reallydiscouraging, especially if they're
using AI to replace those careers.
Cause when it's, like you said, takingaway from new graduates and it's also
(17:22):
taking away that, that human aspectthat I was talking about earlier,
although it is efficient and maybe maysave the company some money, you're,
you're taking away those opportunitiesof learning and building your sense
of, um, community within that company.
So that's, that is interesting.
(17:44):
But I, I really, by the way, I,I didn't mean to, um, scare you
during this conversation here, Clea.
Um, but I also think that there is nowa groundswell of people like yourself,
who has the skills, who has the thinkingprocess, who understand projects, who
(18:06):
understand how to work, you know, to ask,how to understand, how to ask questions.
That's actually one of the skills thatis necessary for people to, for example,
go with a much more entrepreneurial,you know, uh, path where there are
software engineers or engineers whodecide that, Hey, you know what?
I'm making something up here.
(18:27):
There wasn't a, a way for, forthe Filipino community to, beyond
Bucknell, but like in maybe in yourarea, wherever you end up being, you
know, and, um, and that now you can.
Because of the speed of development,because of the new tools, because of,
(18:48):
you know, the access to some of this,these AI tools, um, that I, I heard an, a
very interesting interview that said, wewonder at what point we're going to see
the first solo entrepreneur billionaire,which is a really interesting, um, sort
(19:12):
of, and I mean, billionaire is more likea symbol that I don't think, you know,
I don't even think any of like meremodels like me, um, can even understand
how much money that actually is.
But, but my point, I think the pointof it is more like you can potentially
be extremely successful at this job andthat you might even be, um, able to do
(19:38):
it with far fewer resources than, thanwhat used to be, you know, you don't have
to become the Google, you know, that hasemployees, many hundreds of thousands
of employees in order to do this reallydifficult job, it almost feels like
there's a lot more, um, opportunitiesfor people to be able to say, you know
(20:00):
what, if I think that bringing water to...
you know, places in need is the thingthat needs to exist in the world.
And there is not a businessthat is doing that right now.
I can do it because using theefficiency that's created by AI, um,
what used to have taken, you know,an insurmountable amount of resource.
(20:21):
Just to do the communication and thedesign and the PR and all that I might
in 2026 create agents that can takecare of a lot of that for me so that I
can do things that are more meaningful.
I think that's a reallydifferent kind of future.
I think it's scary on one hand, but it'salso like exhilarating on the other hand.
(20:44):
Yes, for sure.
That's so interesting because I,I've spoken to people who, when
networking, they didn't like majorin computer science or anything,
but they learned it on their own.
And I guess when learning onyour own, Chat, GPT, or AI
helpers are such a important andhelpful tool to learn as well.
(21:06):
So having that aspect to help you dothings on your own rather than always
relying on having to be taught orhaving to buy all of these resources
in order to get things done is soempowering because you can really
do anything on your own these daysbecause of all of the resources,
open source platforms available.
But it's also not necessary.
(21:27):
It doesn't have to be really solo.
But imagine if you can run a tremendouslyimpactful business or organization,
right, that do meaningful things,but it's just 10 of you, um, right.
It could also be this.
You know, but, but it wouldhave in the past would have
required a hundred people, right.
(21:50):
And it, like that to me is a reallyinteresting part of the world that I
don't think a lot of people are exploringbecause, you know, there's a lot
about replacing current jobs and, and.
And it might, I think that it willcreate, replace some jobs, maybe even
many jobs, um, especially what would beconsidered entry level jobs, or maybe
(22:10):
even to a certain degree, mid level jobs.
Um, but I think that.
You know, there, it, it feels liketo me, kind of like what I was
saying before, okay, you save timeover here, but you actually end
up spending the time elsewhere.
So now you're able to push it further.
Yes.
And so I feel like that, you know,taking something away from one
(22:32):
side will, will inevitably getbalanced out on the other side too.
Um, but it, it is difficult, youknow, especially for folks who
You know, this was forced on them.
This was a natural progression.
You know, if I've had this job forthe last 25 years, um, suddenly I
(22:54):
being forced to re-skill, up-skill,change skills, change jobs too.
To, to deal with this, youknow, new world, it, it feels
difficult and feels uncomfortable.
Um, but I, I kind of, you know, I wasreally interested in hearing sort of from
someone who's about to graduate, right?
I also think about, you know,for people who are, you know,
(23:19):
freshmen now at Bucknell, right?
Like when they graduate.
Yes.
What does the world look like then?
Because you are alreadyseeing a little bit of this.
In 2025, right?
Mm-hmm . I like 2028.
Like, that's gonna bereally different, right?
Mm-hmm . And I think the youngergenerations now have, they have so
(23:41):
much ambition and now they have alot of resources and more tools.
So I see them having more and moreprogress and more and more, um,
really cool projects coming out thatthey're really passionate about.
And I know they're gonnaachieve so much more.
So.
Well, you are part of theyounger generation, Clea.
Just wanted to say you, youhave those tools as well, and
(24:02):
you, you'll get to use them too.
Um, I, I hope that, by the way,that it wasn't, uh, you didn't
get scared from that, but, um.
I still have hope, youknow, cause, because I've.
I feel like what you were saying, it'snot enough to be just an engineer.
You need to have all of those skills andthat interdisciplinary, which I think
(24:22):
AI could never replace all of those likehuman aspects that makes a person a person
because what, how you provide value inyour work or like you said, your past
experience and your identity, how allof those aspects of your identity and
what you've been through affect how youdo your current work, which A.I. Could
never have that like history built in.
(24:44):
Yeah, and and that's right.
Actually, A.I. cannot do that for us.
Um, you have to be the one whoyou can have a lot of experience.
Someone can read aloud theexperiences to you, but you still
have to go through the heart.
The hard work is how do you process that?
And how do you.
Make sense of all those experiences.
I want to say that all that'sexactly what your reflections did.
(25:07):
You know, like doing the project itselfis one thing, but the reflection is
the part where you had the experience.
Now you get to process it andyou were able to make pretty big
jumps every time, you know, youbuild one from one to the other.
And those are the thingsthat stays forever, right?
Like the C sharp code that youwrote in for whatever that's going
(25:30):
to get obsolete, unfortunately.
Right.
But, but the ability to sortof take the thinking and like
combine those experiences.
And then figuring out what kind ofthinker you are, you know, as you would
solve problems, means that by the timeyou write the next piece of code that
is not even in C sharp, will, you willstill be able to apply those, right.
(25:53):
And, but it's really about even liketaking coding to design and all of
that is even make it even stronger.
I really believe that.
I think that's, that's,that's what it's going to be.
And you were talking about augmentedreality and virtual reality before.
I mean, that's another really like.
To me, surprisingly unspoken areatoo, you know, I was thinking about,
(26:15):
you know, like if you are trainingto become a nurse in 2025 right
now, and you're going to graduate in2028, we talked about that, right?
It may very well be that you are nolonger, or it may very well be that
(26:35):
the... you know, currently, I thinka lot of nursing majors have to learn
a humongous amount of content, likethe material is staggering, right?
Like every procedure that they'resupposed to know, every condition,
there's all the protocols, right?
(26:56):
I kind of kept imagining withengineers like you, who's
going to create a safe, secure.
Accurate, non hallucinogenicversion of some kind of AR glasses
that a nurse would be able to wearcomfortably, you know, all day.
(27:18):
And being able to say, like, generallyspeaking, if I, you know, have a
patient who is having a certainkind of symptoms or is having
certain kind of pain or knowingthat they are having a heart attack.
That your
AR will helpfully just go, this iswithout going through like public servers
(27:44):
and stuff, you know, like within thehospital, like it's always safe and it's
not sharing that material with anyone.
Being able to just go here,here are the next seven steps.
Here are some other additionalthings that you need to know.
This is the timing inwhich you need to do them.
Etc, etc. Not that the nurseshould just purely count on that.
(28:06):
Having that assistant wouldbe so incredibly useful.
Yes.
And being able to sort ofsay, like, did I do them?
Or did I, like, or you, maybe, maybea heart attack is common enough
that you just know that, right?
But maybe you come across somethingthat you've never done, or you
haven't done in three years.
Mm. Right?
Like, typically, by the way, likemany doctors and nurses in some
(28:32):
of those situations, they actuallyhave to look things up, right?
They have to, and this is also wheresometimes you, or sometimes some things
you missed and then you, you know,this is where like practice lawsuits
come in and so on and so forth.
But I could imagine that, youknow, a well developed tool like
that could be, you know, lifechanging for, for all of us, right?
(28:56):
In medical care.
Yeah.
And it would allow for, yeah, it wouldallow for someone to not count on what
if the nurse got tired because they didalready, it's their 12th hour working that
day and it's been a crazy day, you know,of all kinds of, you know, high adrenaline
events that happen over and over again.
Right.
It happens.
(29:17):
Right.
And, and what if you can create thattool and, and what, what does that
change for that nursing students?
You know, like, what if theyend up spending a little less
energy on acquiring all of thecontent, which is an investment.
For me, when I see it, I feel like it'san insurmountable amount of content
(29:42):
that in fact, it just keeps growingbecause, you know, people are researching
more, discovering more how to even.
Keep that in the, in our brain, you know?
Yes, it's impressive the workthey do and that there's so
much risk in Incorporating.
They put their lives at stake every singleminute because you never know like you
(30:03):
can Contract whatever it is that's causingsomeone to be sick, for example, right?
And so you're doing all of that Like,I almost imagine, like, wow, you would
be the person, you'll be the kind ofpeople who would have the skills to
create the AR technology that can helpsomeone like that, and in turn, it will
(30:25):
help save countless lives, and it willalso change their perspectives a lot too.
So, I remember.
You know, as a kid, I don't know whetheryou felt that way too, but as a kid,
I mean, if I'm an Asian family, likethere is some default professions that
(30:45):
are cool to do, doctor being one, right?
Yes, for sure.
And, um, I remember.
Learning the little, littlestbit about being a doctor.
And it was like, well,it's a lot of studying.
It was like a huge amount of memorizing,like lots and lots and lots of facts and
big words and, and, and, and systems.
(31:07):
And I remember thinking.
That's just not for me.
Now I speak with a lot of doctors,people who had gone through medical
training that says, well, yeah, thatis actually like legitimately really,
really hard, but that's not all I do.
In fact, that's not what I do.
(31:28):
So they think about the world verydifferently already, but I have this
like, you know, impression that thisis an unattainable thing because.
It's so, it's so much about memorizinga huge amount of content and that
I'm just like, that's not for me.
Like I may be able to do it, but like, youknow, like I can't, I don't find that to
(31:49):
be a good use of my, my, my, my, my time.
But if that got taken out of theequation, maybe not completely,
but like the pressure of like beingtested on those things as being your,
the majority of what you do, right.
It may mean that providing care forsomeone, becoming the, the, the,
(32:10):
the, uh, providing, making someoneelse's healthy, um, becomes, you
know, part of the equation, likethe bigger part of the equation.
It may change a lot of people's minds.
Yes.
Yeah.
I have a similar story of how peopleare saying, I was asking, um, A
friend who graduated and I was askingher, Oh, we have to learn so much
(32:30):
technical things in our ECEG classes.
Like how much of it do you actuallyuse similar to how the doctors have
to learn all of these procedures andmemorize a lot of things, but they don't
maybe directly use it in their work.
So I was asking her, howmuch do you actually.
Use this because she'san electrical engineer.
And she was saying not too much,all of the things that we learned,
(32:50):
because I think the processes atschool are just teaching you how to
learn, teaching you the fundamentalsand what you really do in a real time
job and work is like you learn, likethe processes that your company uses
and you need to learn how to learn.
And that's what school prepares you for.
And being able to find those things thatyou need to learn and learn by yourself.
(33:11):
I think that's what AI is really great.
For being able to learn fast on thejob when you need to know these things,
maybe not off the top of your head,but you have like that background.
That's beautifully said.
Clea, thank you so much forspending all this time with me.
I really, really enjoyed our conversation.
You are brilliant.
(33:32):
I, I, um, I am so impressed with,you know, this, you know, what
you have to say and how you thinkabout the world is fascinating.
Um, I think that, um, those of us,I'd be listening to this again, but,
and those of us, I think are alsolistening right now who are, you know,
(33:53):
from my generation or the, you know,the, even the older generations should
look at, you know, should listenclosely to what you are telling us.
And what you, how you think abouta world, what makes sense and, and,
and, and how you are, you know,what your real experience is like.
So that, you know, for those of us whoare in any positions of like making those
(34:18):
kinds of decisions, uh, thinking aboutlike the future of education, maybe.
So I know that there are people whoare Deans and, you know, Department
Chairs who have the ability to,to influence where this goes.
I think we have a lot of work to do.
I think we have a lot to do to makesure that our, you know, like, not
only for you graduating in 2025, butwhat about those who are graduating in
(34:40):
26, 27, 28, like we gotta, we gotta dothese things quickly to, to make sure
that you are not going to be, you know,getting out to the world and, and, and
feel like that you are sort of, youknow, you're not able to contribute,
um, because the real world looks toodifferent from what was presented to
(35:04):
you in, in, in an education environment.
Um, and I'm so glad thatyou're at Bucknell who.
Which, like you said, does not do that.
Um, it allows you to ask questions,like to work on real world project.
So you hear from here, Bucknelluniversity, please go check it out.
Um, I think many people already know this.
I'm in school is very well known,but I, for people who, who are really
(35:26):
not, um, you know, who are thinkingabout like, you know, engineering,
for example, like Clea, uh, was.
Should think about what it means to goto a program that has equal emphasis on
liberal arts, um, on sort of these abilityfor you to ask, ask questions yourselves
and to lead teams, um, and do all theseother things that, uh, is, is going to
(35:50):
go beyond just, you know, 25 really,really hard problem sets, um, right.
Um, and, um.
And for those, uh, last reminder forthose who are looking for the next
generations of the best talents, I thinkclear here is certainly one of them.
If you are creating those glassesfor AR, you know, for an AR company,
(36:12):
um, you know, contact her quicklyor she would be off the market.
All right.
Thank you all so much.
And, uh, Clea, I reallyappreciate this conversation.
I hope that we can get to,um, keep in touch and, uh, let
me, let me know how things go.
Okay.
Yes.
Thank you again so muchfor this opportunity.
I really enjoyed reflecting on my,my ePortfolios and all the projects
(36:33):
I've done and how much I've learnedsince then and how much Digication
has helped me to, to reflect on theseexperiences and to showcase them as well.
So thank you.
Well, I, I, I appreciate the kind words.
Take care and, uh, goodluck with everything.
And congratulations, uh, uh, in advanceon your, your completion of your degrees.
(36:54):
Thank you so much, Jeff.
Okay, take care.
Bye.
Thank you.
Bye bye.
This concludes our conversation.
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The Digication Scholars ConversationSeries is brought to you by Digication,
(37:15):
a technology platform poweringthe most innovative e-portfolio
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