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The future belongs to those who understand tech. Are we ready?
Watch Beyond the Headlines LIVE with Cherry Lyn Sta. Romana, Dean of the College of Computer Studies at Cebu Institute of Technology – University, as we break down the trends shaping the next generation of IT professionals.
From coding to career opportunities—what should students and professionals know today?
📲 Join the discussion LIVE!
Watch Beyond the Headlines LIVE with Cherry Lyn Sta. Romana, Dean of the College of Computer Studies at Cebu Institute of Technology – University, as we break down the trends shaping the next generation of IT professionals.
From coding to career opportunities—what should students and professionals know today?
📲 Join the discussion LIVE!
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NewsTranscript
00:37Good afternoon. Welcome to Beyond the Headlines. I'm DJ Moises.
00:42March is the National Women's Month and around the world, tech leaders are warning that artificial intelligence may dramatically disrupt
00:50IT and BPO services within just a few years.
00:54Today, we are joined by a woman who sits at the heart of that transformation.
01:00The Dean of the College of Computer Studies of Cebu Institute of Technology University, Dr. Cherry Lynn Santarumana.
01:07This afternoon, we go beyond the headlines. We ask the real question.
01:12Will Cebu hesitate or will it evolve?
01:16Dean Cherry, welcome back to the program.
01:18Yes, hello DJ. Thank you for inviting me again.
01:21Always grateful to have a conversation with you on or off cam.
01:26So when you took computer science back then, so this is your younger years, did you already envision or imagine
01:37that artificial intelligence will be this powerful today?
01:42You know, that was super a long time ago.
01:44I studied computer science in 1986.
01:47And would you believe that I actually took an elective on artificial intelligence in 1989?
01:53So artificial intelligence has been existing for a long time.
01:57However, ChatGPT sort of disrupted that.
02:00So we have what we call traditional AI and then now we have, you know, all of these different models
02:06being used right now.
02:08But I felt then that there's a future for AI, you know, even then, except that we did not get
02:14that much support or use from the industry.
02:19That's why it did not take off.
02:21But AI has been there for a long time.
02:23But right now, it's because of the industry use of AI.
02:26That's why it's becoming really powerful.
02:29Sige, let's start with at least your engagement with the current students taking up computer studies.
02:36In the overall, what's your impression?
02:39Are they anxious about the future or are they confident about the future in general?
02:46In general.
02:46So I think for CIT, you know, because we are offering computer science and as far back as 20 years
02:52ago, we have embedded AI as elected and we made it required in 2018.
02:57So our students, I think they are ready.
02:59They are excited because for the longest time when students graduate, they get hired as software developers, even though they
03:05did their research on AI.
03:06So they were not able to apply AI back then.
03:09But right now, we see that when they go and apply for jobs, they are actually getting these roles as
03:15AI solutions developers.
03:16So I think it's more of excitement.
03:18Even if it's not their major, no?
03:20Yes, because the foundation of AI is computer science.
03:23So if you have a solid foundation in computer science and then you get to learn AI in additional required
03:29courses, you are ready, you know, to, how do you say this, to incorporate AI in the software that you
03:35create.
03:35And I think that's what the industry needs right now.
03:38I think that's promising, no?
03:40Yeah, yeah.
03:41That's very promising, no?
03:42At least the mindset is already there, no?
03:45Yes.
03:45So now let's move to the ITBPM industry, no?
03:49So IBIPA President and Chief Executive Officer Cijac Madrid said that the industry has breached the $40 billion mark, no?
03:59So that means that the growth is there, no?
04:02And have added 80,000 new jobs last year, no?
04:06But based on Binod Koshla's statement, he is a prominent Silicon Valley venture capitalist.
04:15He said and he believed that ITBPM services can really disappear in five years.
04:22Now, what are your thoughts about this one?
04:24I think it's a very strong statement, no?
04:28If it will disappear, no?
04:30I think it will be transformed more than disappear.
04:33So maybe the jobs that are repetitive will be replaced.
04:36But then we have to provide higher-level service, I think, higher-level jobs.
04:42So we have to upgrade, I would think.
04:44We have to upgrade, yeah.
04:45Yeah, yeah.
04:45If we do not want it to disappear, we have to level up also so that we can provide the
04:50higher-level jobs.
04:51And then, before I will ask you about what you think are the specific jobs that would disappear, the numbers
04:59in the Philippines in the ITBPM, especially, unfortunately, even in this age of data analytics, they vary, no?
05:08Some people would say 70% are boys.
05:11Some people would say 80% are boys.
05:13But regardless, it would tell us that the majority of what we do in the Philippines, not just in Cebu,
05:19are primarily call center work.
05:22That's why not many people are able to migrate from calling the industry BPO to ITBPM because what they see
05:31more are those taking calls.
05:35So now, as the world is progressing towards artificial intelligence, what do you think are the jobs that are more
05:43vulnerable compared to the others?
05:46Yeah, I do not really know what exactly are being done.
05:50But the back office operations, those that can be automated, I would think, because we also do a lot of
05:56those, right, in the BPO sector.
05:58And right now, they're doing a lot of, like, you know, they can change your voice to be Americanized or
06:05anything like that.
06:06Or neutralized.
06:07Or neutralized.
06:08Those are problems before, but right now, those can be solved by AI.
06:13So maybe those, even the voice, no, will be affected.
06:16Those jobs will be affected.
06:19And yes, you mentioned about back office work, you know, and at least from what I know also from the
06:25industry,
06:26and this is for the education of our viewers because you made a good point when you said anything that
06:31can be automated.
06:32And our translation of that statement is any task that is repetitive.
06:39Yes, repetitive.
06:41So these are vulnerable works.
06:44So for those of us who are watching, you can already check the kind of work that you do.
06:48If there's a procedure or a process that will tell you do this and don't do this,
06:54then most likely that is a vulnerable work.
06:57You know, I want to give an example.
06:59And this was a long time ago, no?
07:01You know, I would rather change flight in AirAsia talking to a chatbot.
07:06It's very efficient, you know?
07:07You just give your, how do you say this?
07:10You just give your, what do you call that, the booking reference.
07:13And then it will just, you know, it's very easy to change.
07:16And you know that you're talking with AI, but it's very easy.
07:19So those kinds of jobs, I think, because, and this was even before ChatGPT,
07:24and they were already doing those things.
07:25And by the way, now that you're saying that, although I've heard about this many times,
07:29but this conversation also became like a moment for me.
07:33No, things like that happen.
07:34We see them every day, but it takes a conversation to trigger the brain.
07:37Because I knew that in the past, people would prefer conversations to a human being.
07:46So that's why there are scripts like, how's the weather out there?
07:51How are you today?
07:52But I think because the world has also evolved into a very fast-paced world,
07:59so there are also evolving clients or customers who would prefer just straightforward,
08:05just do the job, and then I'll hang up the call.
08:08I don't need this conversation about the weather because I'm in a hurry.
08:12And you don't even have to dictate, you know?
08:14You just type it in.
08:17I think the more that people become more technical,
08:19the more that they would appreciate doing things very straightforward using tech.
08:25Yes.
08:26So now, on the reverse, what are the roles you think are the safest?
08:32Because I'm an advocate for computer science education
08:35or anything related to engineering and technology,
08:37I would think those are safe.
08:39Of course, I would still push for computer science.
08:43I think two days ago, I posted that the demand for computer science graduates is increasing.
08:50I posted it in my Facebook.
08:52I shared it.
08:52Because people are saying that programming is being replaced by AI, but I don't think so.
08:57Personally, even if AI can produce code, and I always say this,
09:02we have the calculator for a long time, but we still teach students how to add, right?
09:08It's the same thing because programming, and I call it computational thinking,
09:13it trains students on problem-solving skills.
09:15And it's going to become useful regardless of the industry that you get into.
09:22It does not really matter.
09:23So it's very important because it teaches problem-solving.
09:26The ability to identify a problem, formulate solutions in a step-by-step manner
09:30that can be executed by either a machine or a human.
09:33So regardless of what you end up with doing, a computer science degree is very useful.
09:37But engineering degrees are also very useful.
09:40For example, right now, electrical engineering, for example, solar power, and so on.
09:47So I think there will be a great demand for that.
09:50So yeah, engineering and computing disciplines would be good.
09:54By the way, this is also another aha moment, and I've seen this many times and ever,
09:59but when you answer the question, it's also like an aha moment for me
10:02because engineering, in the past, when people would ask me,
10:08because I'm an engineer, but I did not practice the profession,
10:10but they would say that, so what value did it give you?
10:13And my answer is not computing.
10:14My answer is algebra.
10:15Because engineering taught me the discipline every day
10:19to, given what's required, find the solution.
10:25Yeah, so it's problem-solving, basically.
10:27Yeah, so now my answer will no longer be algebra.
10:30My answer will be computing.
10:32Yeah, yeah.
10:32Computational, computational thinking.
10:35Computational thinking.
10:36Yeah, yeah, yeah, computational thinking.
10:37So, and also right now, domain expertise is also very important.
10:42So, for example, even with data science, you might be very good in,
10:46for example, in all of these different techniques and so on,
10:50but if you do not understand the data that you are processing,
10:53so it's going to become complicated.
10:54So we still need domain experts.
10:57Ideally, they should also have data science skills, for example,
11:01which is now part of artificial intelligence.
11:04So now this is more of like Cebu,
11:07or you can also comment whether, because of your CHED engagement,
11:11engagement, you can also comment on Philippines, you know.
11:15But are we at a point now when we can say that AI is replacing humans,
11:21or are we at a point when we can say that humans are upgrading to know AI?
11:27Which phase are we?
11:29I think that the second one, humans are upgrading to use AI.
11:34So I think, I hope that we're like that.
11:37So there are many initiatives right now.
11:39I just attended the CHED race event in Iloilo.
11:42So there's a big push.
11:44It's not only CHED, you know.
11:45Almost all government agencies, I think, right now.
11:49I don't know if I can say this.
11:51I sort of have this feeling that there's a panic moment going on about AI.
11:59So how are we going to approach it, you know.
12:01But so many initiatives going on, which I think is good,
12:05for as long as they know exactly what is it that they want to attack
12:09in terms of AI literacy, AI fluency, AI engineering roles, etc.
12:15And I'm glad once again that you mentioned about the panic
12:20because on my personal observation,
12:24I really thought in the past that we have become comfortable
12:31with the idea that AI will not replace humans,
12:35implying that it is okay not to do anything.
12:39So I'm glad there is panic now.
12:41So that means that we will do something, no?
12:45To upgrade the skills of Filipinos to move forward with AI.
12:51So Cebu grew also, and even the Philippines,
12:55because of the IT BPM industry.
12:58It has given so many opportunities, even for undergrads,
13:04to have better quality of life, and even the support industries.
13:09In fact, what I always want to say,
13:13especially when I'm advocating for the industry is,
13:15it's not even making a difference just for the people within the industry,
13:19but it has a multiplier effect, no?
13:21Times 2.9.
13:22So imagine almost three people per one person employed in the industry.
13:26But now that there is a threat, what do you think?
13:30Assuming that we're not going to do anything,
13:32what will happen to our fresh graduates?
13:35Or I will even have to say college-level people.
13:43Undergrad.
13:44Sige.
13:45I think for computer science and IT,
13:48assuming that they are trained well by the universities,
13:51and I hope that they are trained well on the foundational skills
13:53that will allow them to adapt and survive with changes in the discipline,
13:57I think that they will still survive.
14:00However, I don't know if I can say this.
14:02For the other degree programs, I don't know.
14:04I think they have to level up
14:06because there are certain degree programs
14:08that would probably be doing stuff that can be automated.
14:14Especially memorization kind of work.
14:18Yeah, something like that.
14:19So I think that we need to be able to upgrade the graduates
14:23and the students, for example,
14:25to also adapt to technology at the same time
14:28because I think some disciplines are still very traditional.
14:34No, I think the reason why,
14:36if you notice, maybe my eyes went somewhere to continue.
14:39Yes, but I have a comment on that.
14:41Yeah, so I think that some degree programs
14:42are still very traditional.
14:43So I hope that they will be more technology-oriented.
14:48And I think that they should be able to adapt
14:51because then otherwise,
14:52I was just talking to one board member from SibDAT
14:55the last time that we met.
14:57And she was saying that
14:59this particular area will be affected, etc., etc.
15:02because the jobs are repetitive.
15:06And so on, and can be automated.
15:09So we need to be able to upgrade.
15:11And actually, the reason,
15:13another aha moment now,
15:15and I've heard about this many times,
15:16but the conversation triggered it
15:17because we gave a heads up to our viewers
15:22that if what they're doing is repetitive,
15:24then it's vulnerable.
15:25I think on the part of the students also,
15:28if their disciplines would require them
15:31to memorize and parrot a certain principle,
15:37then that's also vulnerable.
15:39Because at the end of the day,
15:40artificial intelligence will be able to do that
15:43times 100 better and faster.
15:47So if all they are doing right now in school
15:49are just memorizing,
15:51you're in danger.
15:53Yeah, they should be more on problem-solving,
15:56I would think.
15:57Correct, yes.
15:57They should be bombarded, you know,
16:00and trained on critical thinking,
16:02analysis, etc.
16:04And usually that's why,
16:05usually you get them from a STEM education.
16:08That's why we're pushing for STEM.
16:12And, yes, but before that,
16:14because I also am passionate about it,
16:17but let's go on how the curriculum
16:20or the universities and colleges
16:22are also adapting.
16:24How fast are we in terms of adapting
16:29and updating the curriculum?
16:33Yeah, so I've been a member
16:35of the CHAT technical panel,
16:36I think since 2010.
16:38Okay, now I know that it's not really fast.
16:40The EDCOM report, for example,
16:42says that in CHED,
16:44it takes 11 years, you know,
16:45for a new,
16:46we call it policy standards
16:48and guidelines to come out.
16:50Now for computer science, for example,
16:52and IT education in general,
16:54the last CMO was actually in 2015,
16:56and it's 2026 now, right?
16:58So it's 11 years.
16:59So I was telling the technical panel,
17:01that's us, right?
17:02It's 11 years.
17:03But the thing is,
17:04the universities,
17:05they tend to blame
17:07the policy standards and guidelines,
17:09but I beg to disagree.
17:10Because the 2015 version,
17:12for example,
17:13it was very flexible.
17:15So in there,
17:16we stated that there are 18 units
17:18that the university is given freedom
17:19to change
17:20and implement whatever they want.
17:23For a particular program?
17:24For computer science,
17:25IT, and information systems.
17:26Oh, yeah,
17:27because, I'm sorry,
17:27that's your domain.
17:30For the IT education,
17:32for example,
17:33there are 18 units there.
17:34The university has the freedom
17:36to adapt whatever specialization
17:37they want to put there.
17:39On top of that,
17:40they have 12 units
17:41of elective course,
17:42especially for IT.
17:43So I think it's very open.
17:44That's why every time I talk
17:46to different events,
17:48I always tell them,
17:49you know,
17:50do not wait
17:51for a new policy standards
17:52and guidelines.
17:53Do not wait
17:53for the new PSG.
17:54You can change
17:55the curriculum
17:56and implement it.
17:57You have the freedom.
17:58Just follow the minimum requirements
18:00and 18 units,
18:01if you want to do it,
18:03channel that to AI,
18:04channel that to whatever
18:05it is that you want
18:06based on the needs
18:07of your region
18:08or whatever,
18:09then you are free to do so.
18:10Because they have a tendency
18:11to really blame it.
18:13I hear that a lot also.
18:14So for example,
18:15CIT,
18:16we have a 2018 version,
18:17a 2022 version,
18:18and a 2023 version.
18:21Because sometimes
18:22it's just a matter
18:23of rearranging
18:24the prerequisite,
18:25et cetera.
18:25So I think it's,
18:27that's just for IT.
18:29But unfortunately,
18:29for other disciplines,
18:31it's very,
18:33how do you say this?
18:34It's very prescriptive.
18:35Like you have to follow
18:37this exactly.
18:37There's no room for,
18:39They don't have the 18 units.
18:41Yeah, they don't have that.
18:42Yeah, sometimes
18:43very little elective.
18:44So I think there has to be
18:46a lot of elective programs
18:47because that's where
18:48you can put
18:48the new technologies,
18:50whatever is needed
18:51in the industry,
18:52you can put it
18:52in the elective program.
18:55For example,
18:56and I do not want to blame,
18:57you know,
18:58I might get in trouble
18:59if I say this.
19:00Because the engineering program
19:02changed from five years
19:03to four years.
19:04So because of that,
19:05they had to put in
19:06so many of the,
19:07so during your time,
19:09it was five years.
19:09Now it's four years.
19:10So how,
19:11and because they expect
19:12that everything will be covered
19:13in the senior high school,
19:15but in reality,
19:15it's not.
19:16So the curriculum
19:17is very full.
19:18So if you want
19:19to do innovation there,
19:20I think you have
19:20to insert it
19:21in the required courses.
19:23So the CMO
19:24already requires
19:25certain courses.
19:26I do not know
19:27maybe you can strengthen it
19:28in terms of
19:28what's already existing.
19:30And then,
19:31because there's
19:31very little room
19:32for electives.
19:34But at least
19:35I'm glad that
19:36at least in
19:37computer studies,
19:38they have room
19:39to move,
19:40no?
19:41Yeah.
19:41at least,
19:42no?
19:42Sigur,
19:42now you've covered
19:44a little bit of this
19:45about the other programs,
19:47but do you also think
19:48that artificial intelligence,
19:51no?
19:51In whatever level,
19:53should also be mandatory
19:54across all programs,
19:57no?
19:57Not just computer studies.
19:59Yeah,
19:59I think everyone
20:00should have
20:01what you call
20:01AI fluency,
20:02no?
20:04I just want to promote this.
20:05And even at the
20:06high school level,
20:07right?
20:07So CIT has been
20:08designated as
20:10an ASEAN AI.
20:12There's this program,
20:13ASEAN AI Ready
20:16program.
20:16So we have been
20:19authorized
20:19to basically
20:20offer it.
20:21So we can actually
20:22offer it to
20:24basic education,
20:25for example.
20:26So that senior
20:26high school students,
20:27for example,
20:27all of them
20:28will have AI fluency
20:29and understanding
20:30of AI in general,
20:33including ethics,
20:34data privacy
20:35considerations,
20:36generative AI.
20:37et cetera.
20:38Those things are covered.
20:39So now let's move
20:40to the darling
20:42of the ASEAN.
20:44So I'm talking
20:44about Vietnam.
20:45So Vietnam is
20:47considered a
20:47primary threat
20:48in the Philippines
20:49IT BPM market share,
20:51no?
20:52With a growing
20:53reputation for
20:54high quality,
20:55cost effective,
20:57which is supposed
20:58to be our edge,
20:59technical services.
21:00The industry is
21:01dominant in
21:02IT outsourcing,
21:03software development,
21:05and increasingly
21:06high value services
21:07like AI,
21:09robotics,
21:10process automation,
21:11and data management.
21:12Given their
21:15ascend,
21:17are we losing
21:18ground,
21:18at least from
21:19your observation?
21:21You know,
21:23I've been hearing
21:25about Vietnam.
21:26I remember in
21:262017,
21:27we were sent
21:28to Japan,
21:29a group of
21:29women in tech.
21:31we were sent
21:32to Japan,
21:32and we visited
21:33companies.
21:34Even then,
21:35all the companies
21:36that we visited,
21:36it's unimaginable
21:37that they were
21:38saying that
21:38they're moving
21:39their business
21:40from this country
21:41to Vietnam.
21:42From this country
21:43to Vietnam.
21:44All of them
21:44Vietnam.
21:44And so I was
21:45asked,
21:45how come not
21:46the Philippines?
21:47Because CIT in
21:47particular,
21:48we're trying to
21:49target the
21:49Japanese companies
21:51here in Cebu.
21:52We are asking
21:53our students
21:53to take the
21:54Philnitz,
21:54and so on
21:54and so forth.
21:55So I was
21:56wondering,
21:56how come it's
21:57not the Philippines
21:57who is in the
21:58radar?
21:58And this
21:59was a long
21:59time ago,
22:00right?
22:00So it hurts
22:01me as a
22:02Filipino,
22:02because I
22:03want the
22:05Filipinos to
22:05have opportunities,
22:06right?
22:06That they have
22:07to choose the
22:08Philippines as
22:08their location.
22:10And then I
22:11have attended,
22:11I know that
22:12what we're doing
22:13in CIT,
22:14for example,
22:14we're letting
22:15the students
22:15take the
22:16Philippine
22:16National IT
22:17Standards,
22:17which is
22:17recognized in
22:18Japan.
22:19Vietnam is
22:20doing that.
22:21We're taking
22:21the top seat
22:22examination,
22:23the Korean
22:23examination.
22:25And when we
22:25attended the,
22:26how do you
22:27say this,
22:27the awarding of
22:28the top
22:28not sure
22:29because our
22:29student got
22:30the top,
22:31Vietnam is
22:31there.
22:32So everything
22:33they're doing
22:34there at a
22:35high level
22:35because I
22:36heard that
22:36it's being
22:37mandated by
22:37the government.
22:38I think
22:38that's the
22:39difference.
22:40I even
22:41heard that
22:41the government
22:42is pushing
22:43their students
22:43to learn
22:44Japanese.
22:44That's why
22:45they are the
22:45priority of
22:46the Japanese
22:47government.
22:47So it's
22:48very purposive,
22:50I think.
22:51And I
22:52really feel
22:54frustrated sometimes
22:55that it's that
22:56purposive in
22:57Vietnam.
22:57that's why
22:58you know
22:58exactly what's
22:59happening because
22:59you know.
23:00Yeah,
23:01I haven't
23:02captured the
23:02word for
23:04this segment.
23:06Not the
23:06day,
23:06but purposive.
23:08Because my
23:09aha moment
23:09also in this
23:10particular situation
23:12was in my
23:13company when we
23:14were hiring
23:14systems integrator
23:16for a client.
23:17and then we
23:19had difficulty
23:20pricing it
23:21because there's
23:23not much
23:24available talent
23:25in the
23:26Philippines,
23:26at least during
23:27that time.
23:28So that means
23:29the applicants
23:29are also pricing
23:30it high because
23:31the supply is
23:33lower compared
23:34to the demand.
23:35So when I
23:36gave the
23:36feedback to
23:37the client on
23:39how we are
23:40pricing it,
23:41that's when he
23:41told me that,
23:43are you,
23:43did not know,
23:44did not tell me
23:45the price difference,
23:45but after they
23:46awarded the
23:47contract,
23:47he actually
23:48openly gave
23:49me a feedback
23:50that actually
23:51Vietnam gave
23:53the lower
23:54price.
23:54Your only
23:55edge,
23:56it's because
23:56your candidate
23:57can speak
23:58English.
23:59Otherwise,
24:00you won't
24:01get the
24:02contract.
24:03And that's
24:03when it's
24:04like,
24:04and knowing
24:05that there
24:05are a lot
24:06of Filipinos
24:06in Vietnam
24:07right now
24:08teaching English,
24:09so,
24:10and now
24:11you're saying
24:11that Japanese
24:12also then,
24:13it's really
24:14purposive.
24:16I really
24:17appreciate
24:18the Vietnamese
24:18people,
24:19you know.
24:20A long
24:20time ago,
24:21I attended
24:21the opening,
24:23the launching
24:24of FPT.
24:25So,
24:26FPT is a
24:26Japanese
24:26company.
24:28Vietnamese.
24:29Yeah,
24:29sorry,
24:29it's a
24:29Vietnamese
24:30company.
24:30So,
24:31I really
24:31felt,
24:32you know,
24:32wow,
24:33they're
24:33very
24:34nationalistic.
24:35It's like
24:35they're saying
24:36that they
24:36want FPT
24:37to grow
24:37and compete
24:38with other,
24:39you know,
24:40other similar
24:41companies,
24:42consulting
24:43companies in
24:44the Philippines
24:44and they're
24:45projecting,
24:46this is an
24:46Asian company
24:47that can
24:48compete
24:48with the
24:48best in
24:49the world.
24:49So,
24:50I felt,
24:50wow,
24:51I felt that
24:51the Filipino
24:52is part of
24:53the thing
24:53that they
24:54want to
24:54grow.
24:54So,
24:55it's a
24:56totally
24:56different
24:57mentality.
24:59The way
25:00that they're,
25:00you know,
25:01pushing,
25:01pushing really,
25:02you know,
25:02the growth
25:03in the IT
25:03sector.
25:04It's really,
25:04you know,
25:05it's amazing.
25:05I envy,
25:08you know,
25:08the way
25:08that they
25:09push it.
25:10And speaking
25:11of
25:11purposive
25:12and pushing
25:13it,
25:14so,
25:14the data
25:15that I have
25:16here,
25:16and I think
25:17you mentioned
25:17it already
25:18earlier,
25:19is Vietnam
25:20is aggressively
25:21growing its
25:21IT outsourcing
25:24sector,
25:24and it is
25:25driven by a
25:26strong STEM
25:27focused
25:28education
25:29system.
25:31So,
25:32can you
25:32elaborate more
25:33also about
25:34that
25:34observation?
25:40I don't
25:41see that
25:41happening in
25:42the Philippines.
25:43And of
25:43course,
25:43we have
25:43DOST
25:44and we
25:45have,
25:45you know,
25:45all of
25:46this DOST,
25:49how do you
25:49say this,
25:50the Philippine
25:50Science High
25:51School,
25:51for example,
25:51under the
25:52DOST
25:52system.
25:53But I
25:54think it's
25:54not enough
25:55the way
25:55that we
25:56are promoting
25:57STEM in
25:58the Philippines.
25:58We have
25:59priority
25:59courses,
26:01but it's
26:01almost all
26:02courses
26:02listed,
26:03especially in
26:03the CHED
26:04priority
26:04courses,
26:04they will
26:05be
26:05mad at
26:05me
26:05for
26:05saying
26:06this.
26:06CHED
26:07priority
26:07courses
26:07and
26:07almost
26:08all
26:08courses,
26:08it's
26:09like we
26:09do
26:09not
26:09want
26:09to
26:09offend
26:10other
26:11disciplines.
26:11That's
26:12how I
26:12feel.
26:12But of
26:13course,
26:13if it's
26:13DOST,
26:14it's only
26:14the
26:15Science
26:15and
26:15Technology
26:15courses,
26:16but
26:16outside
26:16of
26:17DOST,
26:18it's
26:18really
26:19open to
26:20everyone.
26:20Basically,
26:21we cannot
26:21really see
26:22the focus.
26:23And I
26:24remember
26:25also because
26:25in one
26:26of the
26:27outreach
26:27that I
26:30was part
26:30of in
26:31Rotary,
26:32in one
26:33of the
26:33remote
26:34areas,
26:35in
26:35Cebu,
26:36there
26:36seems to
26:38be a
26:39lack,
26:40and lack
26:41is even
26:41generous,
26:42in terms of
26:43understanding
26:44the
26:45opportunities
26:46that are
26:46out there.
26:47So they
26:48ended up
26:48having
26:49courses
26:49for the
26:50sake of
26:51just having
26:51courses
26:52instead of
26:52being,
26:53I think I
26:54like the
26:54word,
26:54purposive.
26:55Maybe
26:56because we
26:57also lack
26:57teachers.
26:58I remember
27:01when they
27:01created the
27:03senior high
27:03school program,
27:05and so
27:05they have
27:05a STEM
27:06strand.
27:07I stood
27:08up and
27:08asked,
27:08how come
27:09there's
27:09no
27:09computing
27:10strand?
27:11Because
27:11computing
27:12is where
27:12you're
27:13directing
27:13the
27:14students
27:14towards
27:14computer
27:14science,
27:15IT,
27:15and
27:15IS.
27:16They
27:16only
27:16have
27:17a
27:17technical
27:17vocational
27:18IT strand.
27:19Computer
27:20science is
27:20a very
27:21challenging
27:21discipline.
27:22You
27:23really need
27:23to have
27:23an
27:24academic
27:24strand
27:24for
27:25computing.
27:26They
27:26were
27:27not
27:27able
27:27to
27:27answer
27:27me.
27:28and
27:28finally
27:28when
27:28they
27:28did,
27:29and
27:29this
27:29was
27:2910
27:29years
27:29ago,
27:30if
27:30we
27:30make
27:31it
27:31a
27:31required
27:31strand,
27:32who
27:33will
27:33teach
27:33it?
27:34Who
27:34will
27:34teach
27:34the
27:35computing
27:36strand?
27:36We
27:37have
27:37a
27:37problem
27:37with
27:38teachers
27:39handling.
27:39I
27:39think
27:40it's
27:40the same
27:40is true
27:40for
27:40STEM.
27:42And
27:42my
27:44recent
27:45meeting,
27:45which is
27:46aligned to
27:46this,
27:46so this
27:47is on
27:47the
27:47academia
27:48side,
27:49I also
27:50had a
27:50meeting,
27:50which we
27:51talk about
27:51this
27:52offline,
27:52but I
27:52will not
27:53name
27:53the
27:53agency.
27:55I
27:55had a
27:55meeting
27:56also
27:56with
27:56this
27:56government
27:56agency
27:57about
27:57days
27:58ago,
27:58and
27:59then
27:59when
27:59I
27:59asked
27:59about
28:00the
28:00future
28:00state
28:00of
28:01artificial
28:01intelligence
28:02and
28:03is
28:03there
28:04a
28:04way
28:04that
28:04we
28:04are
28:05also
28:05educating
28:05the
28:06small
28:07micro
28:07medium
28:08enterprise
28:08in terms
28:09of the
28:09possibilities
28:10and
28:11then
28:11the
28:12feedback
28:12actually
28:12was
28:12there
28:13was
28:13little
28:13to
28:13none
28:14and
28:14the
28:14reason
28:14for
28:14that
28:15is
28:15because
28:15the
28:16people
28:16in
28:17the
28:17agency
28:17are
28:17even
28:17struggling
28:18in terms
28:19of
28:19adapting
28:20to
28:20technologies
28:21how much
28:21more
28:21artificial
28:22intelligence
28:24there's
28:24just
28:24tremendous
28:25manual
28:25work
28:27right
28:27where
28:27they
28:28are
28:28so
28:28how
28:28are
28:29they
28:29in
28:29the
28:29position
28:29to
28:30tell
28:30people
28:30about
28:30the
28:30possibilities
28:31but
28:31that
28:31said
28:33we're
28:33dangerous
28:34the
28:35side
28:35so
28:36do
28:37you
28:37think
28:37STEM
28:38should
28:38be
28:38considered
28:39as part
28:40of the
28:40national
28:41priority
28:41especially
28:42that
28:42the
28:42world
28:43is
28:43really
28:43moving
28:44towards
28:44AI
28:44including
28:45Vietnam
28:46yes
28:47yes
28:47but
28:47that
28:47means
28:48that
28:48we
28:48have
28:49to
28:49support
28:49you
28:49know
28:50more
28:50on
28:51I
28:51think
28:51they're
28:52doing
28:52that
28:52right
28:52now
28:53though
28:53we
28:53have
28:53to
28:53support
28:54more
28:55teachers
28:56you
28:56know
28:57the
28:57basic
28:57ed
28:57teachers
28:58first
28:58of
28:58all
28:58a lot
28:59of
28:59them
28:59should
28:59be
28:59taking
29:00STEM
29:00related
29:02majors
29:03because
29:04that
29:04is
29:05the
29:05problem
29:05even
29:06in
29:06the
29:06ed
29:06com
29:06right
29:07that
29:07you
29:07know
29:08non
29:08STEM
29:09majors
29:09are
29:09being
29:09asked
29:10to
29:10teach
29:10STEM
29:11so
29:11it's
29:11very
29:11difficult
29:12right
29:12if
29:13you
29:13cannot
29:13give
29:14what
29:14you
29:14do
29:14not
29:14have
29:15so
29:15we
29:16have
29:16to
29:16start
29:16in
29:16the
29:16basic
29:17ed
29:17you've
29:18covered
29:18it
29:18you've
29:19answered
29:19this
29:19already
29:20but
29:20I
29:20still
29:20like
29:20to
29:21ask
29:21it
29:21because
29:21maybe
29:21you
29:22can
29:22elaborate
29:22some
29:23more
29:23so
29:23in
29:23the
29:23Philippines
29:24where
29:24exactly
29:35reading
29:35comprehension
29:36in
29:36particular
29:38I'm
29:38really
29:39pushing
29:39that
29:39before
29:40we
29:40teach
29:40any
29:40other
29:41thing
29:41we
29:41have
29:41to
29:41make
29:42sure
29:42that
29:42the
29:42students
29:42are
29:43you
29:43know
29:44they
29:44have
29:44solid
29:45reading
29:45comprehension
29:46skills
29:47because
29:48you
29:48cannot
29:48really
29:48understand
29:49science
29:49right
29:50and
29:50the
29:50science
29:51books
29:51are
29:52in
29:52English
29:52for
29:52example
29:53and
29:53you
29:53see
29:53the
29:53textbooks
29:54of
29:54the
29:54elementary
29:55very
29:55very
29:56heavy
29:56sometimes
29:57I
29:57feel
29:57do
29:57they
29:58have
29:58to
29:58learn
29:58these
29:58things
29:59as
29:59early
29:59as
29:59now
30:00sometimes
30:00as
30:00a
30:00parent
30:01do
30:01they
30:02have
30:02to
30:02learn
30:02these
30:02things
30:02as
30:03early
30:03as
30:03now
30:03because
30:04they
30:04can
30:04learn
30:05it
30:05if
30:05they
30:05have
30:05a
30:05solid
30:06reading
30:06comprehension
30:06so
30:07I
30:07do
30:07not
30:07know
30:07maybe
30:08if
30:08I
30:08become
30:09part
30:09of
30:11how
30:11do
30:11we
30:11change
30:12the
30:12educational
30:12system
30:14because
30:15I
30:15like
30:16the
30:16Japanese
30:17educational
30:18system
30:18right
30:18they
30:19teach
30:19life
30:19skills
30:20in
30:20the
30:20first
30:20three
30:21years
30:21I
30:21think
30:21it's
30:21very
30:21good
30:22maybe
30:22they
30:23are
30:23also
30:23teaching
30:23reading
30:23comprehension
30:24in the
30:24first
30:24three
30:25years
30:25because
30:25it's
30:26not
30:26very
30:26full
30:26right
30:27but
30:27our
30:28educational
30:28system
30:28we're
30:29putting
30:29so
30:30many
30:30things
30:30in the
30:31first
30:31three
30:32years
30:32and
30:32we
30:32have
30:33not
30:33yet
30:33developed
30:33the
30:35comprehension
30:35skills
30:36and
30:36that's
30:37why
30:37it also
30:37worries me
30:38to see
30:38numbers
30:39of
30:39functional
30:40literacy
30:40declining
30:41that's
30:42also
30:43worrying
30:43me
30:43because
30:44technology
30:44is
30:45improving
30:46and
30:46then
30:46our
30:47functional
30:47literacy
30:47is
30:48decreasing
30:49okay
30:51it's so sad
30:51because
30:52you know
30:52how much
30:53percent
30:53is that
30:54only how
30:54many percent
30:55is
30:55functional
30:56literate
30:5670
30:57at least
30:58so what
30:58will happen
30:59all of
30:59these people
31:00will go
31:00into the
31:01universities
31:01right
31:01because
31:02that's
31:02how it
31:02is
31:02in the
31:03Philippines
31:03now
31:03everyone
31:04can
31:04go to
31:05university
31:05and so
31:07yeah
31:08how will
31:08they survive
31:09and honest
31:10to goodness
31:10you know
31:10university
31:11education
31:12if they
31:12are not
31:13functional
31:13literate
31:14yes
31:17I'm one
31:18with you
31:18with that
31:19question
31:20so
31:20the other
31:21thing
31:21also
31:22is
31:22at least
31:22from your
31:23observation
31:23are we
31:24producing
31:25graduates
31:27without
31:29strong
31:30quantitative
31:31foundations
31:36so
31:37I'm going
31:38to go
31:39back to
31:39the first
31:39statement
31:41because
31:41it's
31:42hard
31:42because
31:43if
31:43these
31:44are the
31:45kinds
31:46of
31:46students
31:47going
31:47into
31:47the
31:48university
31:48right
31:48so
31:49basically
31:50it's
31:50very
31:51difficult
31:51to
31:51basically
31:52do
31:52bridging
31:53bridging
31:53bridging
31:53bridging
31:54so
31:54instead
31:55of
31:55discussing
31:55for
31:55example
31:56what's
31:56supposed
31:56to be
31:57covered
31:57instead
31:58of
31:58ensuring
31:59that
31:59these
31:59outcomes
31:59are
32:00met
32:00you
32:00have
32:00to
32:00go
32:00back
32:01and
32:01ensure
32:01that
32:01the
32:01outcomes
32:02that
32:02should
32:02have
32:02been
32:03met
32:03in
32:03the
32:04high
32:04school
32:04level
32:04are
32:05attained
32:07and so
32:08it's
32:08sorts of
32:09degrades
32:09as you
32:10go along
32:10just
32:10like
32:11you
32:11know
32:11from
32:13elementary
32:13going
32:14into
32:14junior
32:14high
32:14school
32:14if
32:15they
32:15have
32:15not
32:15attained
32:16the
32:16outcomes
32:16that
32:16you
32:16expect
32:17from
32:17grade
32:17six
32:18and so
32:18you
32:18tend
32:18to
32:19go
32:19back
32:19right
32:19and so
32:20on
32:20and so
32:20far
32:20so
32:21maybe
32:21it's
32:21because
32:21of
32:22that
32:22so
32:22instead
32:22of
32:23being
32:23able
32:24to
32:26ensure
32:26that
32:27outcomes
32:27are
32:27met
32:28at
32:28the
32:28university
32:28level
32:29it's
32:30just
32:30an
32:30outcomes
32:31of
32:31the
32:31high
32:32school
32:32level
32:32that
32:33we're
32:33trying
32:34to
32:34attain
32:35I
32:35don't
32:35know
32:35it's
32:36hard
32:36now
32:37in
32:37terms
32:37of
32:38okay
32:38this
32:39is
32:39also
32:39for
32:39the
32:40parents
32:40or
32:41those
32:41who
32:42are
32:42guardians
32:43of
32:44our
32:45younger
32:45population
32:46how
32:47much
32:47of
32:48STEM
32:48also
32:49although
32:50you've
32:50mentioned
32:50it in
32:51passing
32:51is
32:51curriculum
32:52and how
32:53much
32:53of it
32:53also
32:54is
32:54culture
32:55meaning
32:55do we
32:56have
32:56a
32:56culture
32:57that
32:57actually
32:59supports
33:00STEM
33:01and
33:02the
33:03reason
33:03why
33:03I'm
33:04raising
33:04this
33:04and
33:04I
33:04don't
33:05have
33:05the
33:05numbers
33:05so
33:06if
33:06we
33:06have
33:06viewers
33:06who
33:07would
33:07like
33:07to
33:07correct
33:07me
33:08but
33:08I
33:08do
33:08have
33:09an
33:09impression
33:09that
33:10in
33:10India
33:11also
33:11they
33:12seem
33:12to
33:12have
33:13a
33:13preference
33:14for
33:14math
33:15and
33:15sciences
33:15that's
33:16just
33:16my
33:16impression
33:17I
33:18don't
33:18have
33:18the
33:18numbers
33:19so
33:19that's
33:19why
33:19I
33:20think
33:20there's
33:20also
33:21culture
33:21that gets
33:22into
33:23that
33:23if
33:23more
33:24and more
33:24people
33:24would
33:24recognize
33:25or
33:26see
33:26success
33:27in
33:27those
33:28disciplines
33:28then
33:29maybe
33:29it
33:29also
33:29promotes
33:30STEM
33:31I'm
33:32not
33:32so
33:32sure
33:32also
33:33but
33:33I
33:33think
33:33the
33:34biggest
33:35population
33:35is in
33:36business
33:36and
33:37education
33:37business
33:39side
33:39and
33:40education
33:40I
33:40think
33:40that's
33:41the
33:41bulk
33:41of
33:41where
33:41the
33:42students
33:43are
33:44I
33:44can
33:46try
33:46to
33:46verify
33:46that
33:47because
33:47those
33:48are
33:48the
33:48very
33:48easy
33:49degree
33:49programs
33:49to
33:50teach
33:50regardless
33:50of
33:51where
33:51you
33:51are
33:51it's
33:52hard
33:52to
33:52teach
33:52an
33:52engineering
33:53degree
33:53program
33:53because
33:54of
33:54the
33:54laboratory
33:54requirements
33:55the
33:55faculty
33:56requirements
33:56etc
33:56so
33:57I
33:58think
33:58the
33:58easiest
33:58one
33:58to
33:59comply
33:59will
33:59be
34:00education
34:00and
34:01business
34:01that's
34:01why
34:01almost
34:02all
34:03schools
34:03are
34:03offering
34:04education
34:04and
34:05business
34:05so
34:06the
34:06next
34:06question
34:07is
34:07an
34:07attempt
34:07I know
34:08that
34:08this
34:08is
34:08can I
34:09just
34:10insert
34:10something
34:10I
34:11just
34:11realized
34:11going back
34:13to
34:13Vietnam
34:14Vietnam
34:14is
34:14actually
34:15teaching
34:15coding
34:15at the
34:16basic
34:16education
34:17level
34:17but we
34:18cannot
34:18do
34:18that
34:19we
34:19cannot
34:19even
34:19put
34:20it
34:20in
34:20senior
34:24in
34:24Vietnam
34:24when
34:25they
34:25graduate
34:26from
34:27senior
34:27high
34:27school
34:28they
34:28already
34:28know
34:28coding
34:29and
34:30computational
34:30thinking
34:32I
34:32have
34:33read
34:33about
34:33that
34:34and
34:34in
34:34Singapore
34:35also
34:35so
34:36many
34:36other
34:37countries
34:38they
34:38have
34:38already
34:39pushed
34:39computational
34:40thinking
34:40in
34:41general
34:41at
34:41the
34:41basic
34:42education
34:42level
34:42in
34:43the
34:43Philippines
34:43some
34:44schools
34:44will
34:45do
34:45that
34:45but
34:45we
34:45cannot
34:45make
34:46it
34:46a
34:46requirement
34:46because
34:47nobody
34:47will
34:47teach
34:47it
34:48and
34:48by
34:48the
34:48way
34:49now
34:49that
34:49you've
34:49mentioned
34:50that
34:50and
34:50this
34:50is
34:51also
34:51for
34:51the
34:51awareness
34:51of
34:52the
34:52viewers
34:53it
34:53was
34:53only
34:54with
34:54my
34:54engagement
34:55also
34:55with
34:56outreach
34:56to
34:57remote
34:57schools
34:58when I
34:58realized
34:58that
34:59we
34:59still
34:59have
34:59public
35:00schools
35:00that
35:02would
35:03draw
35:03the
35:04computer
35:04using
35:04the
35:05cartulina
35:05this
35:06is
35:06the
35:06monitor
35:07this
35:08is
35:08the
35:09keyboard
35:09this
35:10is
35:10the
35:10button
35:11that
35:11you're
35:11going
35:11to
35:11switch
35:12it
35:12on
35:12and
35:12I
35:12was
35:13just
35:13surprised
35:14we
35:15still
35:15have
35:15that
35:15at
35:16this
35:16age
35:17and
35:17time
35:17that
35:18we're
35:18teaching
35:20tech
35:21in that
35:21manner
35:22or
35:22some
35:23schools
35:23it's
35:24already
35:24progressive
35:25if they
35:26have
35:26a
35:26unit
35:26that's
35:27not
35:27working
35:27but
35:28at
35:28least
35:28it's
35:29a
35:29physical
35:30unit
35:30it's
35:30not
35:31drawn
35:31on
35:32a
35:32cartulina
35:33so
35:34sad
35:34anyway
35:37it's
35:38impossible
35:38to teach
35:39coding
35:39if that
35:40is
35:40the
35:40situation
35:41right
35:41so
35:42now
35:42I
35:43know
35:43that
35:43this
35:43is
35:44a
35:44much
35:44more
35:44complex
35:47answer
35:47but
35:48if
35:48we
35:48then
35:49are
35:49to
35:50rank
35:50future
35:51proof
35:52skills
35:53moving
35:54forward
35:55so
35:55I
35:56have
35:56here
35:56AI
35:57development
35:57cyber
35:59security
35:59there's
36:00data
36:01analytics
36:01and
36:02there's
36:03cloud
36:03engineering
36:04which
36:04among
36:05this
36:06is
36:07the
36:07most
36:07urgent
36:08as of
36:09today
36:09we
36:10can
36:11have
36:11many
36:11answers
36:11but
36:12rank
36:12I
36:12think
36:13all
36:14are
36:15important
36:15yeah
36:15all
36:16I
36:16think
36:18cyber
36:18security
36:18is
36:18a
36:19very
36:19safe
36:21job
36:22to
36:23be
36:23a
36:23cyber
36:23security
36:23specialist
36:24because
36:24you
36:25know
36:25with
36:25all
36:25of
36:25this
36:26new
36:26developments
36:26in
36:27software
36:27you
36:27have
36:27to
36:27make
36:28sure
36:28that
36:28they
36:28are
36:28secured
36:29and
36:30then
36:30if
36:30you
36:30want
36:31to
36:31basically
36:33at least
36:34compete
36:34in terms
36:35of
36:35talent
36:35because
36:35they
36:36are
36:36saying
36:36that
36:36talent
36:37will
36:37be
36:37needed
36:37software
36:37developers
36:38basically
36:38with
36:39AI
36:39skills
36:39and
36:40so
36:40it's
36:40also
36:40very
36:41important
36:41not
36:42necessarily
36:43developing
36:44new
36:44models
36:45AI
36:46models
36:48do
36:48that
36:48too
36:49that
36:50we
36:50can
36:50compete
36:51but
36:51right
36:52now
36:52I
36:52think
36:52we
36:52can
36:53compete
36:53in
36:53terms
36:54of
36:54developing
36:55I
36:55think
36:55for
36:55the
36:56Philippines
36:56there
36:56are
36:57so
36:57many
36:58problems
36:58agricultural
36:59problems
36:59that
37:00maybe
37:00we
37:00can
37:00use
37:00AI
37:01to
37:01solve
37:01health
37:02problems
37:02some
37:03of
37:04the
37:04problems
37:04right
37:04now
37:05being
37:05done
37:05by
37:06our
37:06students
37:06they
37:07have
37:08coordinated
37:08with
37:09the
37:09Philippine
37:10Rice
37:10Research
37:10Institute
37:11for
37:11example
37:11trying
37:12to
37:12determine
37:12the
37:12quality
37:13of
37:13rice
37:13grains
37:14for
37:14example
37:14those
37:14things
37:15okay
37:15some
37:16of
37:16our
37:16students
37:17did
37:17you
37:18know
37:19in
37:20health
37:20because
37:20for
37:21example
37:21in
37:21the
37:21far
37:22flung
37:22areas
37:22of
37:23the
37:23Philippines
37:23where
37:24for
37:24example
37:25equipment
37:25are not
37:26possible
37:26or
37:27few
37:27doctors
37:27for
37:28example
37:28to be
37:28able
37:28to
37:29read
37:29for
37:29example
37:30as
37:31scanned
37:31images
37:32or anything
37:32like
37:32that
37:33I
37:33think
37:33we
37:33can
37:33use
37:34AI
37:34right
37:34identify
37:35symptoms
37:36something
37:36like
37:36that
37:37so
37:37AI
37:37can
37:37be
37:38used
37:38for
37:38that
37:38and
37:38of
37:39course
37:39it's
37:39still
37:39the
37:39doctor
37:40who
37:40will
37:40eventually
37:40decide
37:41but
37:41at
37:41least
37:41we
37:42can
37:42make
37:42the
37:42job
37:42of
37:42the
37:43doctor
37:43easier
37:43because
37:44there's
37:44already
37:44support
37:45AI
37:46systems
37:47now
37:47we
37:48move
37:48to
37:49the
37:49pageant
37:49questions
37:51are
37:52those
37:52not
37:52pageant
37:53questions
37:53I
37:53think
37:54I
37:54will
37:54get
37:54in
37:54trouble
37:57because
37:57of
37:58all
37:58my
37:58answers
37:58I
37:58just
37:59want
37:59to
37:59say
37:59those
38:00are
38:00personal
38:01answers
38:01of
38:01Sherilyn
38:02Santa
38:02Romana
38:02it's
38:03not
38:03the
38:04it's
38:05not
38:05the
38:05how
38:05do
38:05you
38:05say
38:05it
38:06it's
38:06not
38:06anyway
38:06related
38:07to
38:07where
38:07I
38:07work
38:08etc
38:08or
38:08what
38:09I
38:09represent
38:09because
38:10the
38:11next
38:11one
38:11is
38:11if
38:12you
38:12are
38:12to
38:12lead
38:13Depend
38:14and
38:14CHED
38:14I
38:14believe
38:15that
38:16if
38:16you
38:16were
38:16to
38:17lead
38:17Depend
38:18and
38:18CHED
38:18today
38:18what
38:19would
38:19be
38:20the
38:20top
38:20three
38:21urgent
38:22reforms
38:23I
38:24think
38:24I
38:24will
38:24look
38:25at
38:25the
38:25grades
38:30comprehension
38:32because
38:32I
38:32think
38:32the
38:33other
38:33things
38:33can
38:33be
38:33learned
38:34they
38:34don't
38:35need
38:35to
38:35learn
38:35all
38:35of
38:35those
38:36things
38:36very
38:36early
38:36on
38:37because
38:38if
38:38they
38:38know
38:38how
38:38to
38:39read
38:39they
38:39can
38:39learn
38:39those
38:39things
38:40and
38:41then
38:41this
38:41one
38:41is
38:41on
38:42the
38:42flip
38:42side
38:43now
38:43because
38:43we're
38:43towards
38:44the
38:44end
38:44of
38:44the
38:44year
38:44by
38:45the
38:45way
38:45our
38:46floor
38:46director
38:46should
38:47warn
38:47us
38:47also
38:47because
38:48we
38:48might
38:48go
38:49overtime
38:50like
38:50we
38:50always
38:51do
38:51in
38:51our
38:51conversation
38:53but
38:54on
38:55the
38:55other
38:55side
38:55what
38:56are
38:56the
38:56human
38:56skills
38:57that
38:58can
38:59what
39:01are
39:01the
39:02human
39:02skills
39:02that
39:02AI
39:03cannot
39:03replicate
39:04so
39:05at least
39:05there's
39:06the
39:06other
39:06side
39:07of
39:07it
39:08would
39:09have
39:09to
39:09be
39:09empathy
39:09the
39:10connection
39:11the
39:11human
39:12connection
39:13that
39:13AI
39:13basically
39:14cannot
39:14do
39:14so
39:14I
39:15think
39:15the
39:16Filipinos
39:16can
39:16still
39:16be
39:17competitive
39:17because
39:18we're
39:18naturally
39:19empathetic
39:20we're
39:20naturally
39:21friendly
39:22and so
39:22on
39:22so
39:23I
39:23think
39:23that
39:23will
39:23be
39:23an
39:23edge
39:24for
39:24us
39:25because
39:25we're
39:26in
39:26the
39:26service
39:26industry
39:27right
39:27that's
39:27why
39:27we're
39:28very
39:28successful
39:28in
39:28the
39:28service
39:29industry
39:29because
39:29of
39:30how
39:30we
39:31are
39:31right
39:31as
39:32a
39:32Filipino
39:32people
39:33that
39:33we're
39:33very
39:34friendly
39:35you know
39:37empathetic
39:38this
39:39this
39:39one
39:40is
39:40I
39:40think
39:40we
39:40covered
39:40this
39:41before
39:41the
39:42camera
39:43started
39:43to
39:43roll
39:44should
39:44government
39:44fund
39:48more
39:49AI
39:50labs
39:53that's
39:54our
39:54biggest
39:54problem
39:54our
39:55biggest
39:55problem
39:56is
39:56that
39:56we
39:57do
39:57not
39:57have
39:58what
39:58you
39:58call
39:58compute
39:59power
40:00okay
40:00so
40:01if
40:01you're
40:02gonna
40:02do
40:02honest
40:03to
40:03goodness
40:03AI
40:03you
40:04have
40:04to
40:04train
40:04data
40:05and
40:05right
40:05now
40:06the
40:06biggest
40:06problem
40:06is
40:07how
40:08do
40:08you
40:08train
40:08this
40:08data
40:08big
40:09you
40:10know
40:10the
40:10really
40:10big
40:11data
40:11with
40:12billions
40:12of
40:12parameters
40:12as
40:13they
40:13were
40:13saying
40:13I
40:14happen
40:14to
40:15have
40:15this
40:15former
40:16student
40:16who
40:17is
40:17now
40:17studying
40:18MS
40:18computer
40:18science
40:19in
40:19Peking
40:19University
40:20and
40:20he
40:20visited
40:21me
40:21last
40:21February
40:22and
40:23he
40:23was
40:23saying
40:23like
40:23he
40:25studied
40:25in
40:25Peking
40:25University
40:26and
40:26he
40:26was
40:26saying
40:26I
40:27have
40:27this
40:27research
40:27mom
40:28and
40:28they
40:29are
40:29giving
40:29me
40:29eight
40:30high
40:30performance
40:31computing
40:31units
40:32to do
40:32my
40:32training
40:33we
40:33don't
40:33even
40:34have
40:34that
40:35here
40:35in
40:35the
40:35Philippines
40:35even
40:36in
40:36UPD
40:36Lima
40:37they
40:37are
40:38offering
40:38Master of
40:39Engineering
40:39AI
40:39they
40:40have
40:40very
40:41limited
40:41facilities
40:42so
40:42if
40:43you
40:43want
40:43to
40:43do
40:43honest
40:43to
40:44goodness
40:44AI
40:44similar
40:45to
40:45what
40:45China
40:46is
40:46doing
40:46for
40:46example
40:47we
40:47need
40:48computing
40:49power
40:49basically
40:50all of
40:51this
40:51hardware
40:51because
40:52if
40:53you
40:53want
40:53to
40:53do
40:53those
40:54model
40:54training
40:55and
40:55so
40:55on
40:55so
40:56there
40:56is
40:57a
40:57need
40:57to
40:57support
40:57that
40:57because
40:58the
40:58universities
40:59do
40:59not
40:59have
41:00the
41:00very
41:01expensive
41:01equipment
41:03to find
41:04that
41:04now
41:06in
41:07five
41:07years
41:07from
41:08now
41:08so
41:08fast
41:08forward
41:09if
41:09we
41:10continue
41:10to
41:10do
41:11what
41:11we
41:11are
41:12doing
41:12today
41:12do
41:14you
41:14think
41:14Cebu
41:15or
41:16ITBPM
41:16in
41:17general
41:17will
41:17be
41:18disrupted
41:20or
41:20are
41:21you
41:21confident
41:22that
41:23we
41:23are
41:24able
41:25to
41:25reinvent
41:27the
41:28industry
41:28five
41:29years
41:30from
41:30now
41:30if
41:31we
41:31continue
41:31to
41:31do
41:32what
41:32we
41:32are
41:32doing
41:34I
41:34think
41:34we
41:34have
41:34to
41:35hurry
41:35up
41:36sorry
41:37I'm
41:37not
41:37so
41:37sure
41:37but
41:37I
41:38think
41:38that
41:38we
41:39have
41:39to
41:39panic
41:40also
41:40at
41:40the
41:40same
41:41time
41:41although
41:41you
41:41know
41:41you
41:42can
41:42feel
41:42the
41:42panic
41:42but
41:43I
41:43think
41:43right
41:44now
41:44the
41:45companies
41:45in
41:45Cebu
41:46they're
41:46trying
41:46to
41:46level
41:47up
41:47they're
41:47trying
41:47to
41:48do
41:48more
41:48training
41:48for
41:49their
41:49employees
41:51you have
41:52to
41:52analyze
41:53where
41:53can
41:54you
41:54go
41:54outside
41:54of
41:55the
41:55things
41:55that
41:55you
41:55are
41:55doing
41:56I
41:56think
41:56and
41:57then
41:57for
41:57the
41:57universities
41:58of course
41:58they also
41:58have to
41:59level up
41:59because
42:00if they
42:01think
42:01that
42:01they
42:01should
42:01not
42:02review
42:02the
42:02curriculum
42:02or
42:03they
42:03should
42:03not
42:03inject
42:04anything
42:04new
42:05into
42:05the
42:05curriculum
42:06or
42:06how
42:06they
42:06train
42:06their
42:07students
42:07I
42:08think
42:08we
42:08will
42:08be
42:08left
42:08behind
42:10unfortunately
42:11and
42:12the
42:12final
42:12question
42:13actually
42:13is
42:13for
42:14the
42:14viewers
42:15or
42:15the
42:15guardians
42:15who
42:16are
42:16watching
42:16and
42:17then
42:17they
42:17are
42:18in
42:18the
42:18position
42:19not
42:19necessarily
42:19to
42:20force
42:20but
42:21at
42:21least
42:22influence
42:22their
42:24children
42:25on
42:26how
42:27they
42:27can
42:27be
42:27more
42:28successful
42:28in
42:29the
42:29future
42:29what
42:30would
42:30be
42:31your
42:32suggestion
42:32to
42:33them
42:34when
42:34they
42:34are
42:35helping
42:35a
42:36child
42:36discern
42:37the
42:38path
42:38that
42:38he
42:39or
42:39she
42:39should
42:40be
42:40taking
42:41so
42:41I
42:42will
42:42still
42:42push
42:42for
42:42STEM
42:43but
42:44more
42:44than
42:44that
42:44I
42:44want
42:45to
42:45tell
42:45the
42:45students
42:48develop
42:49your
42:49problem
42:50solving
42:50skills
42:51develop
42:51your
42:52foundational
42:52skills
42:53if
42:54you're
42:54in
42:54university
42:56right
42:56now
42:56make
42:57sure
42:57that
42:58in
42:58the
42:58first
42:58two
42:58years
42:59you're
42:59very
42:59strong
42:59in
43:00the
43:00fundamentals
43:00and
43:01the
43:01foundational
43:02competencies
43:02because
43:03technologies
43:04will
43:05change
43:05very
43:06fast
43:06and
43:06if
43:07you
43:07do
43:07not
43:07have
43:07the
43:07solid
43:08foundation
43:08you will
43:09not
43:09be
43:09able
43:09to
43:09adapt
43:09so
43:10what
43:10I'm
43:10scared
43:11about
43:11and
43:11I
43:11want
43:12to
43:12say
43:12this
43:12is
43:13that
43:13right
43:14now
43:14students
43:14are
43:15using
43:15AI
43:16so
43:16much
43:16and
43:16I
43:17want
43:17students
43:18to
43:19use
43:19AI
43:19but
43:19if
43:20they
43:20have
43:20not
43:20developed
43:21their
43:21problem
43:22solving
43:22skills
43:23right
43:23and
43:24they're
43:24passing
43:24on
43:25the
43:25thinking
43:25to
43:25AI
43:26and
43:26it's
43:26called
43:26cognitive
43:27offloading
43:27so
43:28if
43:28they're
43:28always
43:29doing
43:29cognitive
43:29offloading
43:30right
43:30instead
43:31of
43:31thinking
43:32on how
43:32to solve
43:32a problem
43:33you're
43:33passing
43:33it
43:34to
43:34AI
43:34and
43:35you're
43:35saying
43:35that
43:35I can
43:36save
43:36time
43:36by
43:36passing
43:37it
43:37to
43:37AI
43:37and
43:38so
43:38AI
43:38learns
43:39but
43:40the
43:40student
43:40does
43:40not
43:41and
43:42so
43:42eventually
43:43I
43:43think
43:44the
43:44problem
43:45solving
43:45skills
43:45will
43:45not
43:46be
43:46developed
43:46the
43:47analytical
43:47the
43:48critical
43:48and
43:48so
43:48on
43:48because
43:49they
43:49always
43:49get
43:49passed
43:50on
43:50to
43:50AI
43:50so
43:51I
43:51would
43:51like
43:51to
43:51caution
43:52the
43:52parents
43:52and
43:53the
43:53students
43:53that
43:55they
43:56have
43:56to
43:56use
43:56AI
43:57properly
43:57it's
43:58very
43:58hard
44:00we have
44:00to go
44:01back
44:01to
44:01basics
44:02we have
44:02to
44:02train
44:02our
44:03brains
44:03to
44:03think
44:04that's
44:04the
44:04only
44:05way
44:05that
44:06can
44:06help
44:06you
44:06survive
44:07changes
44:08in
44:09this
44:09time
44:09develop
44:11the
44:11thinking
44:12because
44:13if
44:13the
44:13thinking
44:13is
44:13not
44:13developed
44:14because
44:14of
44:14constant
44:15use
44:15of
44:15AI
44:15I'm
44:16very
44:16scared
44:16about
44:17what
44:17will
44:17happen
44:17to
44:18the
44:19future
44:19I
44:20think
44:20and
44:21correct
44:21me
44:21if
44:21I'm
44:21wrong
44:22because
44:22that's
44:23also
44:23my
44:24own
44:24personal
44:25journey
44:25with
44:26AI
44:26if
44:27my
44:27thinking
44:28when I
44:28use
44:28AI
44:29is
44:29what
44:30should
44:30I
44:31do
44:31then
44:31it's
44:32dangerous
44:33because
44:33that means
44:33I don't
44:34have an
44:34idea
44:35and I'm
44:35asking
44:36AI
44:36what
44:36should
44:37I
44:37do
44:37but
44:38if
44:38the
44:38approach
44:38actually
44:39is
44:39here
44:40is
44:40what
44:40you
44:40should
44:41do
44:41do
44:42this
44:42for
44:42me
44:43then
44:43we're
44:43safe
44:44because
44:45you have
44:45to think
44:45about
44:46the problem
44:46first
44:47and then
44:47we ask
44:47AI
44:49it's
44:49really
44:50scary
44:50I'm
44:51scared
44:51about
44:52how
44:53it is
44:53even
44:53for
44:54the
44:54teachers
44:54they have
44:55to change
44:55the way
44:55that
44:56they
44:56assess
44:56the
44:56students
44:57in
44:58order
44:58to
44:58make
44:58sure
44:58that
44:59the
44:59students
44:59develop
44:59their
45:00problem
45:01solving
45:01skills
45:02for
45:02example
45:02and
45:03if
45:03their
45:03approach
45:03I
45:04think
45:04we
45:04covered
45:05this
45:08uprising
45:08then
45:10it's
45:11not
45:11really
45:11going
45:14to do
45:14them
45:15really
45:15good
45:16moving
45:16forward
45:17but
45:17anyway
45:17I
45:18think
45:18this
45:18is
45:18part
45:19two
45:19but
45:19there
45:19will
45:20be
45:20parts
45:20three
45:20four
45:21five
45:21six
45:21seven
45:21eight
45:22nine
45:22ten
45:23with
45:24you
45:24because
45:24it's
45:25always
45:25also
45:25a
45:26learning
45:26experience
45:27for me
45:27having
45:27a
45:27conversation
45:28with
45:28you
45:28so
45:28thank
45:29you
45:29for
45:29this
45:29conversation
45:30beyond
45:30the
45:31headlines
45:32the
45:33question
45:33is
45:33no
45:33longer
45:34whether
45:34artificial
45:34intelligence
45:35will
45:35change
45:36the
45:36ITBPM
45:37landscape
45:38it
45:38will
45:39the
45:39real
45:40question
45:40is
45:41will
45:41Cebu
45:41or
45:42the
45:42Philippines
45:43simply
45:43react
45:44or
45:45will
45:45we
45:46redesign
45:47how
45:47we
45:48educate
45:48train
45:49and
45:50compete
45:51as
45:52we
45:52celebrate
45:53National
45:53Women's
45:54Month
45:54the
45:54future
45:55of
45:55AI
45:55will
45:56not
45:56be
45:56shaped
45:57by
45:57just
45:57one
45:58gender
45:58one
45:59country
45:59or
45:59one
46:00mindset
46:00it
46:01will
46:01be
46:01shaped
46:01by
46:02those
46:02who
46:03prepare
46:03to
46:04rise
46:04to
46:05the
46:05moment
46:06I'm
46:06DJ
46:06Moises
46:07this
46:07has
46:07been
46:07beyond
46:08the
46:08headlines
46:08see
46:09you
46:09on
46:10Monday
46:11have
46:11a
46:11good
46:11weekend
46:12time
46:40to
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