AI Uncovered — From Newsroom to Classroom and Beyond | The Howie Severino Podcast

15 hours ago

AI expert Jaemark Tordecilla returns to GMA Network for a wide-ranging conversation with Howie Severino on the technology reshaping journalism, education, and everyday life.

They are joined by several dozen high school and college students in the podcast’s first-ever recording with a live audience.

Jaemark is the former head of digital operations for GMA News, who led the creation of The Howie Severino Podcast at the start of the pandemic.

He later took a year-long study break at Harvard, where he examined AI applications in journalism as well as the technology’s potential risks and unintended consequences.

One student in the audience raises the idea of an AI-driven “creative renaissance,” sparking a lively exchange on the enduring value of human intelligence in an increasingly automated world.

Tune in for that and much more.

Transcript

00:00:03Good morning, Podmates!

00:00:05Welcome to the live recording of our podcast.

00:00:12Thank you to all the young people who made it all the way here.

00:00:15I know, the others who come from the province,

00:00:17Batangas, Bulacan, Cavite.

00:00:21Wow! We have more than 50 of you here today.

00:00:26Today, we're going to be talking about artificial intelligence.

00:00:30And how it will affect our lives.

00:00:32It's already impacting us in ways that we're not even aware of.

00:00:36So, I want to introduce our expert guest for today.

00:00:41A long-time colleague and friend, Mr. J. Mark Tordesilla.

00:00:45Journalist, technologist, and media advisor on AI.

00:00:48Harvard Nieman Fellow and former editor-in-chief of GMA News Online.

00:00:53J. Mark!

00:00:59J. Mark, I'd like to share that you're a colleague for a long time.

00:01:03During the pandemic, when we all have locked down,

00:01:07isa ka sa nag-isip na kailangan na tayong mag-podcast?

00:01:10Actually, we helped develop itong Howie Severino Podcast during the pandemic.

00:01:15Because we can't see each other, but there still was a need for us to communicate.

00:01:22And we've come such a long way.

00:01:24Now, we have a live audience.

00:01:26Before, hindi tayo pwede magkita-kita in person, and now we're doing it live.

00:01:30Alright, J. Mark, you don't call yourself an expert.

00:01:33I called you an expert kanina when I introduced you.

00:01:36You're being a bit modest.

00:01:38Kasi, sa totoo lang, maraming journalist,

00:01:42pero iilan lang, I don't know, you might be one of the very few who's also a computer programmer.

00:01:48Hindi ka man lang nag-major, nag-UP Diliman ka, but you went to Philippine Science High School,

00:01:54which is, of course, for science-oriented students.

00:01:57And then, anong inaaral mo sa UP Diliman?

00:01:59So, actually, my background is in tech.

00:02:02I majored in computer science at UP Las Baños,

00:02:06did my master's degree in technology management in UP Diliman.

00:02:10So, I was working in tech, started even at GMA New Media.

00:02:14And then, a few years into that career, I made either what was the best or the worst decision of

00:02:21my life,

00:02:22which was to become a journalist.

00:02:24And I worked with Howie Severino at the Philippine Center for Investigative Journalism,

00:02:29and then eventually back at GMA News Online.

00:02:33And so, I have my feet in both fields.

00:02:36My background is in tech, but most of my career has been spent in journalism.

00:02:42So, don't think about it.

00:02:44If you want to become a journalist, you just need to learn journalism studies or communication studies

00:02:49because you took a roundabout way to get to where you are.

00:02:53You're now a news leader in addition to being a technologist.

00:02:57I myself majored in history.

00:02:59That's why I do a lot of history documentaries.

00:03:00But I've also been in news for a long time.

00:03:03But, fast forward, we're here now.

00:03:06And one reason why you appear here, and you've been appearing in various other forums,

00:03:12especially on AI, is you took a year off from journalism, even from the Philippines,

00:03:19from the Philippines scene.

00:03:21You did Harvard, you did Neiman Fellow, J. Mark.

00:03:23And what did you study there?

00:03:25So, in 2023, I left GMA and went on my fellowship at Harvard.

00:03:33And it was the most exciting time to be on campus because everyone on campus was talking about ChatGPT.

00:03:41It had only been a few months after the release of ChatGPT.

00:03:44Number one, in the context of journalism, hindi nila inisip yung journalism at all.

00:03:52And number two, they weren't thinking about AI in the context of the Philippines and the larger global south.

00:03:58And so, that sort of became my lane because of my background in both tech and journalism.

00:04:04Ako yung nag-iisip ng mga issue, paano ba maapektuhan ang journalism at paano ba maapektuhan yung mga bansa tulad

00:04:13ng Pilipinas.

00:04:14Well, I'm kind of surprised na sabi mo, Harvard na yun, you would think cutting edge sila in all things

00:04:20journalism and technology.

00:04:23Pero sabi mo, hindi nila masyadong iniisip yung impact ng AI sa journalism.

00:04:28So, basically, you helped trigger that conversation there?

00:04:32Yeah, well, kasi sa Harvard, walang journalism majors.

00:04:37Merong parang student publication, merong Neiman Foundation for journalists,

00:04:43but it's a foundation for journalists who want to get away from journalism for a year.

00:04:50So, iba-iba yung interest na pinupursue ng mga tao.

00:04:53So, in the general population of the university, hindi talaga naiisip yung impact ng AI in journalism.

00:05:00So, yun yung iniisip ko.

00:05:02And so, I've been thinking about how AI will impact our industry and also our country in general going forward.

00:05:10So, AI, of course, in addition to being the trendy technology now, it's what everyone is talking about.

00:05:19But it's also parang superpower ngayon, no?

00:05:25I mean, it has a huge capacity for both good and harm.

00:05:32How can we make sure that this technology supports the truth, defends the truth, and democratic life, no?

00:05:40Kailangan natin tanungin yan because we've learned from previous technologies that technology is a double-edged sword, di ba?

00:05:48May benefit yan at may potential for harm, no?

00:05:53So, napag-isipon mo yan sa Harvard, no?

00:05:56It's not just all about creating things and generating content, no?

00:06:00It's also about making sure that there are guardrails para hindi ito maging parang Frankenstein and, you know, destroys the

00:06:07world.

00:06:08Siguro, to start, no?

00:06:10Isipin natin, the Philippines is actually one of the top countries in terms of using AI and in particular ChatGPT.

00:06:19And when I started thinking about it, there was a very funny graph that I showed you before

00:06:27where the search interest for ChatGPT would spike when classes would start and it would dip when it was vacation

00:06:39time.

00:06:39Kitang-kita mo, pag-Christmas, pag-undas, pag-summer, bababa.

00:06:44So, alam mo na kung sino yung gumagamit ng ChatGPT.

00:06:49Ewan ko lang, for what, but it's a very good data point to present.

00:06:53Now, medyo ngayon, nag-level off. Now, everyone seems to be using AI.

00:06:58But it started with the people that we're with today.

00:07:02It was students who pioneered the use of AI here in the Philippines.

00:07:07Can I just pause you there? I just wanna ask the audience now, no?

00:07:09Narinig nyo si J. Mark, nag-spike pag nag-uumpisa yan.

00:07:13So, let's do an honest survey.

00:07:15Sino sa inyo ang gumagamit ng ChatGPT in your daily life?

00:07:19Or kahit anong AI models?

00:07:21O, magtaas na ng kamay.

00:07:22Honest survey, sino sa inyo?

00:07:24Okay, so this is familiar, not just as a concept, but as a tool, no?

00:07:28As a tool, no?

00:07:29So, I just wanna ask, paano nyo ginagamit?

00:07:32I mean, any volunteers, how do you use ChatGPT?

00:07:36I'm Guneth Ariso from De La Salle University, Das Marinas.

00:07:40I mostly use Gemini po gamit ko.

00:07:43And I use Gemini kasi Google is such a big database of information.

00:07:47So, pag nagmamadali ako, at kailangan ko mag-research ng napakalaking topic, and I don't have the time to go

00:07:55through so many information at a very short, limited time, I use the deep research tool of Gemini po talaga.

00:08:05So, you use it for research?

00:08:06Yes, for researching.

00:08:07Can we get a couple of other answers?

00:08:09Okay, I don't know.

00:08:10Does anyone have a different answer?

00:08:12Okay, over here.

00:08:14So, ma'am, you're a teacher, right?

00:08:17Yes.

00:08:17Okay, so how do you use it?

00:08:18I'm Heidi Gonzalez from Batanga State University, the National Engineering University.

00:08:23So, for classroom instruction, like for example, I have to prepare slides for presentation.

00:08:31So, I do the content, but to make it faster and on my end to be, so that I can

00:08:39be more productive, I use AI to help me or assist me in preparing the slides.

00:08:46Okay, so it's being used by a college student, by a college teacher.

00:08:50Anyone from high school use?

00:08:52Okay, yan.

00:08:54Sa likod, yung high school student naman.

00:08:56High school student.

00:08:58Good morning, sir, Howie.

00:08:59Ako po si Marcus Nubla from Marcelo H. Del Pilar National High School.

00:09:04At ako po personally isang campus journalist.

00:09:06Lumalaban po ako sa mga press conference.

00:09:08And ginagamit ko po yung AI para ma-improve yung gawa ko.

00:09:12Bale, magsusulat po ako ng raw, sariling gawa po.

00:09:15Then gagamitin ko yung AI to learn how to improve it more para mas ma-improve ko pa yung mga

00:09:21next drafts ko ng article.

00:09:23So, anong tool, anong AI tool ginagamit mo?

00:09:25Gemini rin po.

00:09:26Gemini rin.

00:09:27Okay, Gemini.

00:09:27So, J-Mark.

00:09:28Alam mo Howie kung bakit Gemini?

00:09:31Kasi galante sa free tier ang Gemini eh.

00:09:35So, you can ask a lot of questions to Gemini even if you're on the free tier.

00:09:40Kung nabanggit mo kanila kasi chat GPT.

00:09:42So, what's the difference?

00:09:43No, basically, they're all similar.

00:09:47Some chat bots are better at some tasks than others but the differences are negligible.

00:09:58At this level, parang pare-pareho na yung level ng mga chat bots like yung chat GPT, yung Claude at

00:10:06saka itong Gemini.

00:10:37I've been doing workshops.

00:10:38As journalists.

00:10:39As journalists.

00:10:40As journalists, our industry.

00:10:41I've been doing workshops around the country to talk about how we could use AI for our work.

00:10:47And the first thing I say is that our audience is already very familiar with AI tools.

00:10:55They're ahead of it than us.

00:10:57And obviously, they search a lot of it on Google to find the latest models.

00:11:04And yet, in the newsrooms, even here at GMA, there's some hesitation about using AI.

00:11:13And it's a problem because our audience is ahead of us.

00:11:18We don't understand the technology well enough.

00:11:21And how can we report on it and explain it to our audiences if we don't understand it well enough

00:11:28ourselves?

00:11:29And this is a movie we saw with social media before where the audience was also ahead of us.

00:11:35The trolls were ahead of us, di ba, before maka-catch up yung news industry.

00:11:40So, importante for our news industry to understand how to use it, how to use it ethically, and where the

00:11:49red lines are.

00:11:50Baka nagtataka lang yung mga estudyante, journalists, nahuhuli.

00:11:53Bakit tayo nahuhuli?

00:11:55Why are we hesitant to use such an important and powerful tool?

00:11:59A lot of it is hesitation about how it's...

00:12:05Obviously, there were reports at the start where journalists tried to use it.

00:12:11And they didn't use it without human oversight or editorial oversight.

00:12:15They didn't fact check.

00:12:16And it was full of hallucinations.

00:12:19Right?

00:12:20And so, that's a problem...

00:12:21Define hallucinations first.

00:12:22Hallucinations is when AI very confidently says one thing, pero hindi siya accurate.

00:12:29Right?

00:12:31Yung AI, parang yung kaklase mo na ang tapang sa recitation, tapos nakala mo tama, di ba?

00:12:36Tapos pag sinek mo yung work, hindi pala tama yung sinabi sa'yo.

00:12:42And so, it's in the earlier iterations of these chatbots, it was only drawing from what it was trained on.

00:12:55Right?

00:12:55And so, it was problematic if you were doing it for research because it was trained on Western data.

00:13:02It's going to be dumber about Philippine history or Philippine context than it would be about American history, for example.

00:13:12Ngayon, meron ng capabilities. Sabi nga, in deep research, it's now able to search the web and it would give

00:13:20you the links.

00:13:21But you're still going to have to fact check and check every link to make sure na tama yung pagkakasummarize

00:13:29ng AI doon sa link na binigay niya sa'yo.

00:13:33In other words, huwag masyadong magtiwala sa mga lumalabas sa mga...

00:13:37Huwag magtiwala at all.

00:13:38Huwag magtiwala at all.

00:13:39Oo. So, you can't trust its output. You have to still check its output for accuracy, lalo sa ating mga

00:13:48journalists.

00:13:49Kasi, pag nagkamali tayo sa article o sa video na nilabas natin, hindi naman ChatGPT ang sisisihin. Ang sisisihin tayo.

00:13:59Diba?

00:13:59Okay. But these days, ginagamit ang ChatGPT for search.

00:14:05Actually, Google is a form of AI. Diba? Pero ChatGPT ngayon yung parang naging trendy search engine.

00:14:11Napansin ko, pag nag-search ka sa ChatGPT, may mga lumalabas na links.

00:14:15So, you're really able to... Minsan, GMA News or other news organizations ang lumalabas na source ng sinasabi ng ChatGPT.

00:14:21So, it's really possible to verify.

00:14:23So, you would suggest clicking on those links to see kung paano na-process ng ChatGPT.

00:14:28Still verify. Oo. Kasi minsan, magkakamali. Lalo ngayon, if you use Google, they are pushing AI overviews. Diba?

00:14:36The first few results are AI generated. And ewan ko kung napapansin nyo, ang dami niyang mali. Diba?

00:14:45If you only read the AI summary, usually, magkakamali siya once every ten times. And so, that's not acceptable for

00:14:56journalism. We have a lot of journalism majors here.

00:14:59And it's not acceptable in a lot of other facets of life to be that inaccurate. So, kailangan mo pa

00:15:06rin i-check.

00:15:07Okay. I have a practical question. Kasi this is something on the minds of many college students. Lalo na the

00:15:14ones nearing graduation.

00:15:17And I'm sure high school students are also thinking about this. Kasi iniisip nila kung ano yung imi-major nila.

00:15:23Ano ba yung mga jobs that will be gone because of AI? At ano naman yung mga job opportunities?

00:15:34I'm sure that this is a medyo broad question yan. But maybe just off the top of your head, ano

00:15:40yung mga trabaho na maaring mawala in the next couple of years?

00:15:44O baka nawala na, nawawala na, no? And ano naman yung pwede nilang paghandaan na mga bagong trabaho dahil nga

00:15:52dito sa mga bagong technologies?

00:15:55Masalimuot na usapan yan, Hawi. Pero isipin na lang natin that technology brings about disruption.

00:16:02So maybe when you started your journalism career, wala pang laptops. Ewan ko kung may desktops na. Siguro yung layout

00:16:13artist may desktop, right?

00:16:14When I first started, manual typewriters.

00:16:17Exactly. And if you were an executive back then, you would have had a secretary assigned to you just to

00:16:29type your memos, right?

00:16:31And that job has gone away because everyone is now using laptops to type their own memos, right?

00:16:39Ano nangyari dun sa mga tao na yun? They found other jobs in the office. They found other roles in

00:16:47the office.

00:16:47And so, hindi naman nagbago yung job level natin, eh, di ba?

00:16:55So, ganun din sa tingin ko ang mangyayari sa AI. Magbabago yung nature nung trabaho.

00:17:02So, for the journalism industry, for example, we put a lot of focus on writing, right?

00:17:10When we teach J School, a lot of it is trying to get students to write. And it's a very

00:17:18important skill, right?

00:17:20But AI can write faster, right?

00:17:23And so, where does your value lie as a journalist, di ba?

00:17:27Ano yung kaya mong gawin na hindi kaya ang gawin ng AI, right?

00:17:32Ikaw yung kaya mong pumunta sa komunidad, sa rural community, makihalubilo ron at alamin yung kwento nila.

00:17:40At maikwento yung isang kwento na ikaw lang ang makakapagkwento, right?

00:17:46And so, that would, sa trabaho natin, yung balance ng reporting at saka writing, parang 50-50.

00:17:54Would it make that balance different? Would it make the allocation of our resources different?

00:18:01So, ang hirap sagutin ng question na yan, but I'm sure magkakaroon ng pagbabago.

00:18:06Okay, nabanggit mo yung writing skills and the importance of that, not just in journalism, but in almost everything.

00:18:13Traditionally, emphasis yung pagtuturo ng writing sa mga humanities courses, social sciences, even in sciences.

00:18:21As a scientist, a doctor, lawyers, you have to have a proficiency in writing to have a successful career, no?

00:18:28So, may disadvantage yung mga hindi proficient.

00:18:31Kahit matalino, hindi naman lahat ng matalino, magaling magsulat, di ba?

00:18:34Ngayon, with ChatGPT, would you say that the value of writing proficiency has gone down?

00:18:44Because you can easily prompt ChatGPT to produce a nice memo, nicely written letter, speech, even article.

00:18:54Well, ang sinasabi mo is because writing is basically even the playing field for many.

00:19:03Kasi maraming ang magagaling na journalists.

00:19:05In other words, magaling maghanap ng facts, magaling mag-interview, magaling sa observation.

00:19:11Pero hindi sila mahusay, mag-synthesize, and then baka hindi nakabisado yung English grammar.

00:19:16So, minsan, oo. Mali-mali yung grammar, no?

00:19:18So, AI actually can be democratizing in that way.

00:19:23Think about a journalist from, say, Mindanao, a far-flung area in Mindanao,

00:19:28who can go into those communities and find those stories that we're talking about.

00:19:35Ngayon, pwede na siyang mapublish ng isang American publication dahil maayos na yung English niya.

00:19:43Before, kaya niya lang magsulat in his or her local language, di ba?

00:19:50So, that is AI democratizing that field.

00:19:55Ngayon, does that mean na hindi na tayo dapat mag-invest ng oras natin sa writing?

00:20:00No, I think importanteng skill pa rin siya.

00:20:04And I think kailangan pa rin natin matuto without using AI how to write well.

00:20:10The way I think about it is if you're training for a marathon, right?

00:20:16So, you practice running, right?

00:20:19But that's not the most efficient way to get from one place to another, di ba?

00:20:25Pwedeng mag-grab ka na lang o mag-jeep ka na lang.

00:20:28Pero pag nag-jeep ka, hindi ka lalakas.

00:20:31Hindi lalakas yung resistensya mo, di ba?

00:20:34If you want to get better at writing, then practice writing, right?

00:20:40And then, I think there's still going to be value in good writing.

00:20:45In fact, some of the AI labs are hiring good writers to try to teach AI how to write better.

00:20:52Ah, okay.

00:20:53But that's for a high level of writing na.

00:20:57Pero yung basic technical writing, pwede mo na ipagawa sa AI yan?

00:21:02I'm interested in the ethics of this.

00:21:04Sabi mo nga kanina, may mga journalists na mahusay maghanap ng info.

00:21:10Mahusay mag-report, basically.

00:21:12Pero medyo mahina sa writing.

00:21:15So, it's kind of democratized writing.

00:21:17Lahat pwede na maging good writer, no?

00:21:19So, you can feed the information to an AI tool,

00:21:22and it's going to come out with a smoothly written, grammatical, maybe even stylish article

00:21:28that can be published.

00:21:30Sabi mo nga, pwede na mag-compete internationally.

00:21:32But are there ethical issues about that?

00:21:36Do you have to declare na ginawa ito ng AI?

00:21:39It was your lived experience.

00:21:42This is your information.

00:21:44Pero you fed your notes into the AI tool.

00:21:47Ang lumabas, napakagandang article.

00:21:51I can't help thinking na parang may ethical issue yan, J. Mark.

00:21:55Yes, I think, syempre, ang background natin, journalism,

00:22:01nasa isa sa mga tenets natin, yung transparency, di ba?

00:22:05Na i-declare.

00:22:06Paano ba natin ginawa itong storya na ito?

00:22:10And so, ideally, people would declare when they use AI tools for writing.

00:22:15But the reality right now is that you see all these Facebook pages pretending to be use organizations,

00:22:24and their output has all the hallmarks of AI writing.

00:22:31They're not even, you know, they're so lazy that they don't even take the time to get out all those

00:22:39hallmarks.

00:22:39Yung mga M-dash, yung mga it's not this, it's that, di ba?

00:22:45At saka yung sobrang dramatic, it's not just a lost cat, it's a heartache.

00:22:51Di ba?

00:22:51Yung sobrang purple prose.

00:22:54Nakikita natin sa Facebook,

00:22:56meron akong mga finafollow na so-called thought leaders na parang biglang gumaling sa English.

00:23:02Merong biglang boomer na to, pero ba't ang daming emoji ng post niya, di ba?

00:23:08How did he do that if he were typing on a desktop computer, right?

00:23:14Howie, do you know how to insert emoji into your writing, right?

00:23:19And so that's a telltale sign that they probably used AI and they probably didn't declare it.

00:23:25Now, ideally they would, but you see these pages getting tens of thousands of followers,

00:23:33sometimes even hundreds of thousands of followers.

00:23:35So, unfortunately, it seems like the audience doesn't care.

00:23:42And that's the third person in this conversation.

00:23:45Yung audience ba natin, do they care?

00:23:48Yung audience tang journalists and writers for publication.

00:23:52Let's talk about AI in schools.

00:23:55Kasi alam ko, nag-a-appear ka rin sa mga campus para pag-usapan ito.

00:24:00Ano yung mga lumalabas na issues dyan?

00:24:02Kasi yung ibang teachers na nakakausap ko,

00:24:06they seem fixated on preventing cheating via AI.

00:24:11But what would constitute cheating in this day and age

00:24:15when these tools are so available, it's on your phone,

00:24:18I mean, should teachers even be devoting time to finding out kung gumamit ng AI tool yung isang estudyante sa

00:24:28kanyang submission?

00:24:29Or should teaching itself change and incorporate AI literacy or AI tools in education?

00:24:39The problem, how we know, is that there are tools, websites, that claim to be AI detectors

00:24:45that some faculty members are using, but have been proven to be ineffective.

00:24:53So, merong hindi na didetect kung AI nga yung ginamit.

00:24:57And then worse, merong false positives.

00:25:04Like sinasabi, kahit ako yung gumawa nito, dahil maganda yung pagkakasulat ko,

00:25:11the tool thinks that it's AI.

00:25:14For the longest time, we've used writing and English language writing

00:25:18as a way to measure the critical thinking skills of students.

00:25:24I think there needs to be a larger conversation about whether that's still effective.

00:25:31So, merong mga techniques like other teachers would require long-hand writing

00:25:38na hindi ka gagamit ng laptop, gagawin mo sa classroom

00:25:42para may baseline sila ng writing level ng mga estudyante nila.

00:25:46And then pagbiglang gumanda yung writing, then that's a tail-tail sign na nag-AI yung estudyante.

00:25:53When I was at Harvard, I took a history class.

00:25:57And I took it because it was about countries that the U.S. occupied,

00:26:02which obviously the first country they occupied was the Philippines.

00:26:06So, I just wanted to see how the American professor would teach our history.

00:26:11And there was a very interesting policy in that class

00:26:16where the professor said,

00:26:18I allow students to generate papers using ChatGPT with one catch.

00:26:26When you submit your paper, disclose it,

00:26:30and also tell us the prompt that you used to generate the paper.

00:26:36And so, that prompting sequence or that prompt actually would give you a better idea

00:26:43of whether the student understood the assignment,

00:26:46whether they knew which sources to go to,

00:26:50and what critical thinking they applied to the assignment.

00:26:56Kasi delikado rin yung paggamit ng AI.

00:27:00We've seen reports, di ba, na it made up lists of sources that did not exist.

00:27:08So, hindi naman bago yung tamad na estudyante.

00:27:13Hindi naman inubento yun ng AI, di ba?

00:27:15Pero yung AI makes it apparent na,

00:27:18oh, itong source na to doesn't exist,

00:27:21pero nasa paper ng estudyante na to,

00:27:25dahil kahit AI na nga,

00:27:27trabahong tamad pa rin yung ginawa niya.

00:27:29Okay, sabi mo nga,

00:27:30we need to enlarge the conversation about

00:27:33AI in school.

00:27:34So, I wanna just ask the audience,

00:27:36I mean, sino sa inyo yung nagkaroon na ng klase

00:27:40or classroom experience

00:27:42where AI was actually taught

00:27:45or was made part of the methodology ng teacher

00:27:48na pag-usapan?

00:27:51Is it become part of the classroom conversation?

00:27:54Yes.

00:27:54Good morning, I'm Farina Manzano from Adamson University.

00:27:58So, yes, it was introduced to us.

00:28:00We were asked to write about the recent issues

00:28:04for our contemporary world

00:28:06about the certain issues that we want to focus on.

00:28:11And then our prof stated na,

00:28:13we can use AI to assist us.

00:28:16We just have to disclose it

00:28:18and sabihin na,

00:28:20we used AI assistance to write.

00:28:25Yan po, thank you.

00:28:26So, my disclosure,

00:28:27but you can use it for research.

00:28:29I mean, what do you think of that, J. Mark?

00:28:31Baka wala nang gumamit ng mga iba't-ibang website, no?

00:28:36Yung Britannica Encyclopedia, dati.

00:28:38I mean, my brother and I used to have a set

00:28:40na mga libro mismo sa,

00:28:43obviously, obsolete na yun.

00:28:44But then you have that online now.

00:28:46But now with ChatGPT,

00:28:47you can actually get rid of, you know,

00:28:49online libraries and just rely on that.

00:28:53Yeah, it's a problem, no?

00:28:54Kasi yung sustainability,

00:28:57nung ground,

00:28:57yung tinatawag natin na

00:28:59grounding information, di ba?

00:29:01There's training data

00:29:03and there's grounding data.

00:29:04Yung training data,

00:29:06yun yung ginamit

00:29:07nung LLM,

00:29:09nung Gemini,

00:29:10ng ChatGPT,

00:29:12to learn how to read and write.

00:29:15Right?

00:29:15That's the training data.

00:29:17That's not reliable,

00:29:18that's prone to hallucinations.

00:29:20Now, to correct that,

00:29:21there's grounding data

00:29:23where they read your question

00:29:26and then they search the web

00:29:28for data

00:29:29that would help answer your question accurately.

00:29:34Ang problema sa industriya ngayon,

00:29:36na

00:29:37I think a lot of newsrooms around the world

00:29:40are panicking about it,

00:29:42is the idea of

00:29:43Google Zero,

00:29:44where

00:29:45people just look at the AI summary

00:29:49and then

00:29:50they don't click through

00:29:51to the website.

00:29:53And so,

00:29:53websites like ours,

00:29:55GMA News Online,

00:29:56won't get the advertising revenue

00:29:59anymore

00:29:59of

00:30:01that click.

00:30:02And yet,

00:30:03they spent all this money

00:30:05to do the reporting

00:30:06for that information.

00:30:08So,

00:30:09yun,

00:30:10kailangan din pag-usapan

00:30:11paano ba makokompensate

00:30:13ang mga publishers,

00:30:15both yung

00:30:16Encyclopedia Britannica

00:30:19and

00:30:19news websites

00:30:20dahil yung

00:30:22data nila yung updated,

00:30:24yung tama

00:30:24na ginagamit

00:30:25na grounding data

00:30:27ng mga chatbots

00:30:28and how will they pay

00:30:30for their work.

00:30:31So,

00:30:32iniisip din natin

00:30:33sa industriya

00:30:34kung

00:30:34ano ba yung

00:30:35tamang sistema

00:30:37para makompensate tayo.

00:30:38And of course,

00:30:39before the

00:30:40AI tools,

00:30:41there was a similar issue

00:30:43with Google

00:30:43na ang laki nang kinikita

00:30:45from advertising

00:30:46without really producing

00:30:48original content.

00:30:49It was just make,

00:30:50you know,

00:30:50just lining up links

00:30:52to,

00:30:53for your queries

00:30:54and a lot of the

00:30:56advertising went to them

00:30:57rather than

00:30:58the websites

00:30:59that were the links

00:31:01that Google was sharing

00:31:02with the general public.

00:31:04Right.

00:31:04And so,

00:31:05masusupercharge yun

00:31:06with AI.

00:31:07Kasi yung AI,

00:31:07sinabi na sa'yo.

00:31:09And kahit sabihin ko sa inyo,

00:31:11mag-click pa rin kayo

00:31:12sa link,

00:31:13i-check nyo pa rin,

00:31:14chances are

00:31:15the people

00:31:15who are not

00:31:16in this room,

00:31:17they probably

00:31:18won't click

00:31:19on the link.

00:31:19They'll just

00:31:20read whatever

00:31:21it gave them.

00:31:23Kasi,

00:31:23tanya nyo naman,

00:31:24merong mga

00:31:24studyante

00:31:25na pati yung

00:31:26end ng prompt

00:31:28ng chat GPT,

00:31:29nakokopia nila

00:31:30dun sa papers nila,

00:31:31di ba?

00:31:31And so,

00:31:32if we can't

00:31:33even get them

00:31:34to delete

00:31:34that part,

00:31:35how can we

00:31:36get them

00:31:36to click

00:31:37on the link?

00:31:38Now,

00:31:39there are

00:31:40news organizations

00:31:41including GMA

00:31:42who are trying

00:31:43to figure out

00:31:44how to use AI

00:31:45to derive

00:31:45more value

00:31:46for them.

00:31:48I think

00:31:48an organization

00:31:50like GMA,

00:31:51for example,

00:31:52is well-positioned

00:31:53because

00:31:55merong data

00:31:56galing sa

00:31:56Reuters Institute

00:31:57na

00:31:57Filipinos

00:31:59would rather

00:31:59watch the news

00:32:00than read the news.

00:32:02And so,

00:32:03if you're a TV

00:32:03broadcaster

00:32:04or a video

00:32:05publisher,

00:32:06then you're

00:32:06in a good

00:32:07position

00:32:07because now

00:32:08you can take

00:32:09your reports,

00:32:10turn them

00:32:10into short-form

00:32:11video.

00:32:12The Howie Severino

00:32:13podcast is one

00:32:14of our first

00:32:15projects

00:32:16dito sa

00:32:16Digilab

00:32:17which was

00:32:18created

00:32:18specifically

00:32:19to create

00:32:20short-form

00:32:21video.

00:32:22And

00:32:23iba-iba

00:32:24yung magiging

00:32:25strategy

00:32:26ng mga

00:32:27media

00:32:28companies.

00:32:29Meron ding

00:32:29media companies

00:32:30who are

00:32:32keeping

00:32:32data to

00:32:33themselves

00:32:34and then

00:32:34selling

00:32:35subscriptions

00:32:36to that

00:32:36and they

00:32:37would put

00:32:37AI

00:32:38on top

00:32:38of that

00:32:39so you

00:32:40can talk

00:32:40to their

00:32:41archives

00:32:41if you're

00:32:42doing research

00:32:43but you need

00:32:43to pay

00:32:44for it.

00:32:45So,

00:32:45iba-iba

00:32:45yung

00:32:46naging

00:32:46model

00:32:46at

00:32:47mga

00:32:47strategies.

00:32:49Okay,

00:32:50I just

00:32:50want to

00:32:51again ask

00:32:51the

00:32:52students,

00:32:53are AI

00:32:55tools

00:32:55actually

00:32:56being

00:32:56taught

00:32:57to any

00:32:57of you?

00:32:58Yung

00:32:58AI

00:32:58literacy.

00:33:00Sinabi

00:33:01ng

00:33:01estudyante

00:33:01kanina

00:33:02na

00:33:02pwedeng

00:33:03gamitin

00:33:04pero

00:33:04kailangan

00:33:05i-disclose

00:33:06but

00:33:06itong

00:33:07methodologies,

00:33:07itong

00:33:08mga

00:33:08sinasabi

00:33:09ni

00:33:09J-Mark

00:33:10na

00:33:10actually

00:33:12pwedeng

00:33:12ituro.

00:33:13Are

00:33:14these

00:33:14being

00:33:14taught

00:33:14to

00:33:15any

00:33:15of

00:33:15you?

00:33:15May

00:33:16classroom

00:33:17instruction?

00:33:18Hi

00:33:18po,

00:33:19sirs.

00:33:19I'm

00:33:19Nisha

00:33:20po

00:33:20from

00:33:20USD

00:33:21and

00:33:21actually

00:33:22it's

00:33:22not

00:33:22a

00:33:23class

00:33:23po

00:33:23but

00:33:23actually

00:33:24one

00:33:24of

00:33:24the

00:33:24programs

00:33:25po

00:33:26nung

00:33:26organization

00:33:27day

00:33:27po

00:33:27namin.

00:33:27So

00:33:28meron

00:33:28kaming

00:33:29naging

00:33:29org

00:33:29day

00:33:29na

00:33:30pangalan

00:33:30po

00:33:30is

00:33:31AI

00:33:31and

00:33:31Inc.

00:33:32And

00:33:32one

00:33:32of

00:33:32our

00:33:32speakers

00:33:33po

00:33:33na

00:33:33mention

00:33:34niya

00:33:34po

00:33:34na

00:33:34AI

00:33:35po

00:33:35ang

00:33:35ginagamit

00:33:36niya

00:33:36po

00:33:37knowledge

00:33:38is

00:33:38yung

00:33:38binibigay

00:33:38po

00:33:39ng

00:33:39users.

00:33:40So

00:33:40bala

00:33:40nagsa-circulate

00:33:41po

00:33:41yung

00:33:41knowledge

00:33:41niya

00:33:42yung

00:33:42pinoposit

00:33:42po

00:33:42ng

00:33:43users

00:33:43is

00:33:43yung

00:33:43bumabalik

00:33:44po

00:33:44sa

00:33:45new

00:33:45users

00:33:45na

00:33:45nagtatanong.

00:33:46So

00:33:47with

00:33:47that

00:33:47po

00:33:47tinuruan

00:33:48po

00:33:48nila

00:33:48kami

00:33:48on

00:33:49proper

00:33:49prompting

00:33:50and

00:33:50paano

00:33:50po

00:33:50na

00:33:51dapat

00:33:52po

00:33:52namin

00:33:52ibigay

00:33:53sa

00:33:53AI

00:33:53is

00:33:54tamang

00:33:54information

00:33:55po

00:33:55para

00:33:56ang

00:33:56ibibigay

00:33:57po

00:33:57ng

00:33:57AI

00:33:57sa

00:33:57ibang

00:33:58tao

00:33:58once

00:33:58nagtanong

00:33:59sila

00:33:59is

00:33:59also

00:34:00tamang

00:34:00information.

00:34:01What do you think

00:34:02of that

00:34:02Jamer?

00:34:03I think

00:34:04that's

00:34:04a good

00:34:05approach.

00:34:06What I

00:34:07tell

00:34:07media

00:34:08organizations

00:34:08when I

00:34:09do

00:34:09workshops

00:34:10AI

00:34:10is

00:34:11not

00:34:11a good

00:34:12source

00:34:12of

00:34:12information

00:34:13but

00:34:14it's

00:34:14a good

00:34:15tool

00:34:16for

00:34:16processing

00:34:17information.

00:34:19Kanina

00:34:19merong

00:34:20use case

00:34:20na

00:34:21meron

00:34:21siyang

00:34:21sariling

00:34:22gawa

00:34:22and

00:34:23then

00:34:23he

00:34:23feeds

00:34:24it

00:34:24to

00:34:24AI

00:34:25and

00:34:25it

00:34:26comes

00:34:26up

00:34:27with

00:34:27a

00:34:28better

00:34:29version

00:34:29or

00:34:29a

00:34:30more

00:34:30grammatical

00:34:31version

00:34:31of

00:34:32his

00:34:32story

00:34:33then

00:34:34that's

00:34:34a good

00:34:34use

00:34:35of

00:34:35AI.

00:34:36Nakita

00:34:37rin

00:34:38natin

00:34:38on

00:34:38the

00:34:38other

00:34:38hand

00:34:39merong

00:34:40media

00:34:40organizations

00:34:41they

00:34:41used

00:34:41AI

00:34:42to

00:34:42generate

00:34:42articles

00:34:43and

00:34:43they

00:34:44published

00:34:44it

00:34:45without

00:34:45any

00:34:46editorial

00:34:46oversight

00:34:47and

00:34:48it

00:34:48had

00:34:48so

00:34:49many

00:34:49hallucinations

00:34:50and

00:34:50so

00:34:50it

00:34:51was

00:34:51embarrassing

00:34:52for

00:34:52them

00:34:52and

00:34:53so

00:34:53I

00:34:54think

00:34:54that's

00:34:55a good

00:34:55framework

00:34:56to

00:34:56think

00:34:56about

00:34:57AI

00:34:57it's

00:34:58not

00:34:58a good

00:34:59source

00:34:59of

00:34:59information

00:35:00but

00:35:00it's

00:35:01a good

00:35:01way

00:35:01to

00:35:01process

00:35:02information

00:35:02so

00:35:03now

00:35:03it

00:35:04can

00:35:04even

00:35:04process

00:35:05code

00:35:06programming

00:35:07code

00:35:07it

00:35:08can

00:35:08process

00:35:09data

00:35:10well

00:35:10nabanggit

00:35:11mo

00:35:11that

00:35:12AI

00:35:12can

00:35:12now

00:35:12write

00:35:13code

00:35:13that

00:35:14used

00:35:14to

00:35:14be

00:35:14a

00:35:14major

00:35:15occupation

00:35:15for

00:35:15a lot

00:35:16of

00:35:16I know

00:35:16you

00:35:16write

00:35:17code

00:35:17JMR

00:35:18so

00:35:18is

00:35:18that

00:35:18an

00:35:18endangered

00:35:19occupation

00:35:20now

00:35:20no

00:35:21in

00:35:22fact

00:35:22it

00:35:23has

00:35:23made

00:35:24programmers

00:35:25more

00:35:25productive

00:35:26I've

00:35:27been

00:35:27working

00:35:29on

00:35:29several

00:35:30projects

00:35:31that

00:35:31I

00:35:31wouldn't

00:35:32have

00:35:32been

00:35:32able

00:35:33to

00:35:33do

00:35:33if

00:35:34I

00:35:34hadn't

00:35:35used

00:35:35coding

00:35:35agents

00:35:36so

00:35:37like

00:35:37I

00:35:38mentioned

00:35:38kanina

00:35:38tech

00:35:39yung

00:35:40background

00:35:40ko

00:35:40so

00:35:40I

00:35:41have

00:35:41a

00:35:41computer

00:35:41science

00:35:42background

00:35:42but

00:35:42I

00:35:42haven't

00:35:43been

00:35:43doing

00:35:43programming

00:35:44in

00:35:44years

00:35:45so

00:35:45huling

00:35:46huli

00:35:46na

00:35:46yung

00:35:46knowledge

00:35:47ko

00:35:47but

00:35:48I

00:35:48still

00:35:49know

00:35:49how

00:35:49to

00:35:50do

00:35:50architecture

00:35:51of

00:35:51programs

00:35:52right

00:35:52of

00:35:53websites

00:35:53and

00:35:54so

00:35:54I've

00:35:55been

00:35:55able

00:35:55to

00:35:55use

00:35:56that

00:35:56to be

00:35:56more

00:35:56productive

00:35:57so

00:35:58so

00:35:59coding

00:36:00kasi

00:36:00kakaiba

00:36:00yung

00:36:02coding

00:36:02is not

00:36:03the fun

00:36:03part

00:36:04the fun

00:36:04part

00:36:05is

00:36:05imagining

00:36:06the

00:36:06site

00:36:07or

00:36:07the

00:36:07app

00:36:08imagining

00:36:09how

00:36:09it

00:36:09works

00:36:10and

00:36:11then

00:36:11the

00:36:11coding

00:36:12is

00:36:12the

00:36:12hard

00:36:13manual

00:36:13labor

00:36:14part

00:36:15so

00:36:16importante

00:36:17pa rin

00:36:17yung

00:36:18programmers

00:36:18na

00:36:19naiintindihan

00:36:19ano

00:36:20ba

00:36:20yung

00:36:20gine

00:36:21generate

00:36:21ng

00:36:22AI

00:36:22tama

00:36:23ba

00:36:23to

00:36:23it

00:36:23check

00:36:24mo

00:36:24kung

00:36:25may

00:36:25errors

00:36:25may

00:36:26bugs

00:36:26so

00:36:27magbabago

00:36:27rin

00:36:28yung

00:36:28again

00:36:28magbabago

00:36:29yung

00:36:29nature

00:36:30ng

00:36:30trabaho

00:36:30hindi

00:36:31ka

00:36:31na

00:36:31nagsusulat

00:36:32so

00:36:32much

00:36:33ng

00:36:33code

00:36:33pero

00:36:34ikaw

00:36:34yung

00:36:34nag

00:36:35check

00:36:35tama

00:36:35ba

00:36:36yung

00:36:36ginawa

00:36:36nito

00:36:37tama

00:36:37ba

00:36:37yung

00:36:38architecture

00:36:38nito

00:36:39is

00:36:39it

00:36:39connecting

00:36:40to

00:36:40the

00:36:40right

00:36:40data

00:36:41sources

00:36:42mag

00:36:43iiba

00:36:43yung

00:36:44nature

00:36:44ng

00:36:44trabaho

00:36:45okay

00:36:45I want

00:36:46to

00:36:46open

00:36:46up

00:36:46the

00:36:47floor

00:36:47now

00:36:47for

00:36:47some

00:36:47of

00:36:47the

00:36:47questions

00:36:48students

00:36:49have

00:36:49submitted

00:36:50let

00:36:51me

00:36:56hi

00:36:57good

00:36:57morning

00:36:59yes

00:36:59I'm

00:37:00Jewel

00:37:00from

00:37:01Marcelo

00:37:02H.

00:37:02Del

00:37:02Pilar

00:37:02National

00:37:02High

00:37:03School

00:37:04my

00:37:04question

00:37:05first

00:37:05let me

00:37:06give

00:37:06a

00:37:06primer

00:37:07on

00:37:07a

00:37:08certain

00:37:08piece

00:37:09of

00:37:09vocabulary

00:37:09and the

00:37:10question

00:37:10which

00:37:10you

00:37:10some

00:37:11might

00:37:11not

00:37:11be

00:37:11familiar

00:37:12with

00:37:12in

00:37:12the

00:37:13status quo

00:37:13artificial

00:37:14intelligence

00:37:14engineers

00:37:15programmers

00:37:16and

00:37:16technologists

00:37:16have

00:37:17been

00:37:17creating

00:37:18the

00:37:18efforts

00:37:18to

00:37:18grant

00:37:19AI

00:37:19the

00:37:19ability

00:37:20to

00:37:20have

00:37:20qualia

00:37:21or

00:37:21in

00:37:22other

00:37:22words

00:37:22humanizing

00:37:23AI

00:37:24and

00:37:24granting

00:37:24them

00:37:24the

00:37:25capacity

00:37:25to

00:37:25process

00:37:26the

00:37:26complexities

00:37:27of

00:37:27subjective

00:37:28and

00:37:28qualitative

00:37:28experiences

00:37:29like

00:37:30we

00:37:30humans

00:37:31do

00:37:31as

00:37:32a

00:37:32journalist

00:37:33do

00:37:33you

00:37:34think

00:37:34integrating

00:37:35qualia

00:37:35into

00:37:36AI

00:37:36would

00:37:37be

00:37:37beneficial

00:37:37for

00:37:38the

00:37:38journalism

00:37:38community

00:37:39and

00:37:39our

00:37:40overall

00:37:40society

00:37:41or

00:37:41would

00:37:42it

00:37:42be

00:37:42a

00:37:42detriment

00:37:42and

00:37:43why

00:37:43thank

00:37:44you

00:37:44is

00:37:45it

00:37:45helpful

00:37:45for

00:37:46journalists

00:37:47I

00:37:47think

00:37:48it

00:37:48could

00:37:48be

00:37:48because

00:37:50a

00:37:51lot

00:37:51of

00:37:51journalists

00:37:52we

00:37:52know

00:37:52how

00:37:52we

00:37:52they

00:37:53say

00:37:54and

00:37:54siguro

00:37:55yung

00:37:55mga

00:37:56and

00:37:56majoring

00:37:57in

00:37:57comms

00:37:58or

00:37:58journalism

00:37:58they

00:37:59would

00:37:59say

00:37:59nag

00:38:00comms

00:38:00ako

00:38:00o

00:38:01nag

00:38:01journalism

00:38:01ako

00:38:02kasi

00:38:02ayoko

00:38:02ng

00:38:03math

00:38:03I

00:38:04don't

00:38:05want to

00:38:06deal

00:38:06with

00:38:06math

00:38:06now

00:38:07if

00:38:08if

00:38:08have

00:38:08an

00:38:08AI

00:38:08where

00:38:09you

00:38:09can

00:38:09ask

00:38:10who

00:38:11are

00:38:11the

00:38:11top

00:38:12flood

00:38:12control

00:38:13contractors

00:38:14in

00:38:14this

00:38:14area

00:38:15instead

00:38:15of

00:38:16doing

00:38:16code

00:38:16or

00:38:17doing

00:38:17math

00:38:18right

00:38:18and

00:38:19it

00:38:19actually

00:38:19answers

00:38:20you

00:38:20accurately

00:38:21then

00:38:22that

00:38:22is

00:38:23a

00:38:23benefit

00:38:23already

00:38:24to

00:38:24journalism

00:38:25because

00:38:25what

00:38:26it

00:38:26does

00:38:27it

00:38:27takes

00:38:28your

00:38:28natural

00:38:28language

00:38:29question

00:38:30it

00:38:30turns

00:38:31it

00:38:31into

00:38:31code

00:38:32and

00:38:32it

00:38:32queries

00:38:33the

00:38:33database

00:38:33for

00:38:34that

00:38:34code

00:38:34and

00:38:35it

00:38:35again

00:38:36answers

00:38:37you

00:38:37in

00:38:37natural

00:38:37language

00:38:38so

00:38:39kahit

00:38:40takot

00:38:40ka

00:38:40sa

00:38:40numbers

00:38:41nakita

00:38:42mo

00:38:42pa

00:38:42rin

00:38:42nakuha

00:38:43mo

00:38:43pa

00:38:43rin

00:38:44yung

00:38:44story

00:38:44na

00:38:44kailangan

00:38:45mong

00:38:45hanapin

00:38:46okay

00:38:46we

00:38:46have

00:38:46a

00:38:47question

00:38:47from

00:38:47Alteryx

00:38:48Tangilan

00:38:49my

00:38:50name

00:38:50is

00:38:50Alteryx

00:38:50J.D.

00:38:51Tangilan

00:38:51from

00:38:51Serizal

00:38:52University

00:38:53thank you

00:38:54so

00:38:54much

00:38:54so

00:38:55my

00:38:55question

00:38:55is

00:38:56what

00:38:56is

00:38:56the

00:38:56possibility

00:38:57that

00:38:57AI

00:38:58can

00:38:58be

00:38:58an

00:38:59effective

00:38:59and

00:39:00reliable

00:39:00tool

00:39:01for

00:39:01medical

00:39:01students

00:39:02in

00:39:02verifying

00:39:03one

00:39:03sickness

00:39:05yeah

00:39:05and I

00:39:05think

00:39:05related

00:39:06to

00:39:06that

00:39:06it's

00:39:07not

00:39:07just

00:39:07for

00:39:07medical

00:39:07students

00:39:08but

00:39:08for

00:39:08patients

00:39:09no

00:39:10malaking

00:39:10problema

00:39:11sa

00:39:11Pilipinas

00:39:11in a lot

00:39:12of

00:39:12poor

00:39:12countries

00:39:13kulang

00:39:14sa

00:39:14access

00:39:14sa

00:39:14healthcare

00:39:15to

00:39:15medical

00:39:15personnel

00:39:16that's

00:39:16why

00:39:16napaka

00:39:17popular

00:39:18din

00:39:18yung

00:39:18mga

00:39:19adbolaryo

00:39:20yung

00:39:20mga

00:39:20faith

00:39:21healer

00:39:21ets

00:39:21that

00:39:21hindi

00:39:21nakaka

00:39:22afford

00:39:22ng

00:39:22scientific

00:39:23diagnosis

00:39:24pati

00:39:24yung

00:39:24mga

00:39:24fake

00:39:25doctors

00:39:25on

00:39:25Facebook

00:39:26meron

00:39:27din

00:39:27I guess

00:39:29that's

00:39:29also

00:39:29related

00:39:29to

00:39:29this

00:39:30question

00:39:30does

00:39:32AI

00:39:32open

00:39:32up

00:39:33this

00:39:33new

00:39:33vista

00:39:34of

00:39:34service

00:39:35where

00:39:36that's

00:39:37affordable

00:39:37that's

00:39:38accessible

00:39:38basta

00:39:39may

00:39:39chat

00:39:39GPT

00:39:40ka

00:39:40na

00:39:40meron

00:39:40kang

00:39:41symptoms

00:39:41pwede

00:39:42ka

00:39:42magpa

00:39:42diagnose

00:39:43sa

00:39:43AI

00:39:44tool

00:39:44I'm

00:39:45not

00:39:45an

00:39:45expert

00:39:46no

00:39:46Howie

00:39:46on

00:39:47medicine

00:39:48but

00:39:49the

00:39:49latest

00:39:50research

00:39:50and the

00:39:51latest

00:39:51reports

00:39:52indicate

00:39:52na

00:39:52they're

00:39:54not

00:39:54reliable

00:39:54tools

00:39:55for

00:39:58diagnosing

00:39:59you

00:39:59kasi

00:39:59wala sila

00:40:00nung

00:40:00clinical

00:40:01experience

00:40:01now

00:40:02there

00:40:03have

00:40:04also

00:40:04been

00:40:04studies

00:40:05and

00:40:05hindi

00:40:06pa

00:40:06ito

00:40:06super

00:40:07na

00:40:07review

00:40:08na

00:40:08final

00:40:09na

00:40:09but

00:40:10there

00:40:10are

00:40:10early

00:40:11indications

00:40:11that

00:40:12it's

00:40:12helpful

00:40:12for

00:40:13doctors

00:40:13who

00:40:14have

00:40:15the

00:40:15clinical

00:40:15experience

00:40:16na

00:40:17nao-augment

00:40:18ng

00:40:18AI

00:40:19yung

00:40:20trabaho

00:40:20nila

00:40:21famously

00:40:22a few

00:40:23years

00:40:23ago

00:40:23one of

00:40:24the

00:40:24so-called

00:40:24godfathers

00:40:25of

00:40:25AI

00:40:26si

00:40:26Geoffrey

00:40:26Hinton

00:40:28sinabi

00:40:28niya

00:40:29in a

00:40:29few

00:40:29years

00:40:30there

00:40:30will

00:40:31be

00:40:31no

00:40:31more

00:40:32radiologists

00:40:33because

00:40:34papalitan

00:40:35na ng

00:40:35AI

00:40:35ang

00:40:36radiologists

00:40:36sila

00:40:37nag

00:40:37analyze

00:40:38ng

00:40:38x-ray

00:40:39ng

00:40:39x-ray

00:40:40o

00:40:40because

00:40:40AI

00:40:41can

00:40:41now

00:40:41read

00:40:41images

00:40:42what

00:40:43has

00:40:43happened

00:40:43how we

00:40:44is

00:40:44the

00:40:44opposite

00:40:45mas

00:40:46dumami

00:40:46pa

00:40:46yung

00:40:46radiologists

00:40:47and yet

00:40:48a lot

00:40:49of

00:40:49them

00:40:49now

00:40:49are

00:40:50looking

00:40:50into

00:40:51AI

00:40:51tools

00:40:52to

00:40:52help

00:40:53them

00:40:53process

00:40:54more

00:40:54information

00:40:55and so

00:40:56what has

00:40:56happened

00:40:57is that

00:40:57hindi

00:40:58na wala

00:40:58yung

00:40:59trabaho

00:40:59nagbago

00:41:00yung

00:41:02nature

00:41:04and AI

00:41:06becomes

00:41:06a part

00:41:07of the

00:41:08arsenal

00:41:08of the

00:41:09radiologists

00:41:09to

00:41:11service

00:41:12more

00:41:13patients

00:41:13that

00:41:14they

00:41:14otherwise

00:41:15wouldn't

00:41:15be able

00:41:16to

00:41:16service

00:41:17and so

00:41:18a lot

00:41:19of the

00:41:19systems

00:41:20that I

00:41:20work

00:41:20on

00:41:20as a

00:41:21journalist

00:41:21is

00:41:22actually

00:41:22are

00:41:23actually

00:41:24systems

00:41:24that

00:41:25involve

00:41:25both

00:41:26human

00:41:26and

00:41:27AI

00:41:27and so

00:41:28right

00:41:28now

00:41:29today

00:41:30most

00:41:31of

00:41:32the

00:41:32best

00:41:33AI

00:41:33systems

00:41:34amplify

00:41:34human

00:41:35expertise

00:41:37and so

00:41:38kailangan

00:41:39pa rin

00:41:39ng human

00:41:40at saka

00:41:40AI

00:41:41interaction

00:41:41now

00:41:42down the

00:41:42line

00:41:43five years

00:41:43down the

00:41:44line

00:41:44ten years

00:41:44down the

00:41:45line

00:41:45I don't

00:41:46know

00:41:46how much

00:41:46better

00:41:47the

00:41:47technology

00:41:47is going

00:41:48to get

00:41:48but

00:41:50as of

00:41:50now

00:41:50parang

00:41:51kailangan

00:41:52pa rin

00:41:52nung

00:41:54parang

00:41:55cyborg

00:41:56na

00:41:56operation

00:41:58combination

00:41:59ng human

00:42:00at saka

00:42:00ng AI

00:42:01that's

00:42:02quite

00:42:02clear

00:42:02okay

00:42:03we

00:42:03have

00:42:03a

00:42:03question

00:42:03from

00:42:04Punzalan

00:42:05Leia

00:42:06Angeline

00:42:06or

00:42:07Leia

00:42:08Angeline

00:42:08Punzalan

00:42:08of

00:42:09De La

00:42:09Sal

00:42:09Dasma

00:42:11hello

00:42:11po

00:42:12I

00:42:12am

00:42:12Leia

00:42:12Punzalan

00:42:13from

00:42:14De La

00:42:15Sal

00:42:15Dasmarinas

00:42:16my

00:42:17question

00:42:17is

00:42:18being

00:42:18in

00:42:19the

00:42:19industry

00:42:19where

00:42:19the

00:42:20truth

00:42:20is

00:42:20essential

00:42:21how

00:42:22does

00:42:23AI

00:42:23help

00:42:23in

00:42:24terms

00:42:24of

00:42:24sifting

00:42:25true

00:42:25misinformation

00:42:27can

00:42:28it

00:42:28be

00:42:28utilized

00:42:28in

00:42:29such

00:42:29ways

00:42:29or

00:42:30how

00:42:32we

00:42:33know

00:42:34our

00:42:34friends

00:42:35at

00:42:35Verifiles

00:42:36last

00:42:37year

00:42:38they

00:42:38worked

00:42:38on

00:42:38a

00:42:39project

00:42:39where

00:42:40they

00:42:41took

00:42:41their

00:42:41fact

00:42:42checking

00:42:42database

00:42:43and

00:42:44they

00:42:44created

00:42:45an

00:42:45AI

00:42:45engine

00:42:46so

00:42:46that

00:42:47you

00:42:47will

00:42:47be

00:42:47able

00:42:48to

00:42:48search

00:42:48that

00:42:49database

00:42:50of

00:42:50their

00:42:51fact

00:42:51checks

00:42:52right

00:42:52so

00:42:53that's

00:42:53very

00:42:53valuable

00:42:54already

00:42:54to us

00:42:55as

00:42:55journalists

00:42:55and

00:42:56people

00:42:56who

00:42:56do

00:42:56research

00:42:57like

00:42:57you

00:42:58can

00:42:58see

00:42:58what is

00:43:00the latest

00:43:00misinformation

00:43:01about

00:43:02the flu

00:43:03for example

00:43:04vaccines

00:43:05what are

00:43:07the latest

00:43:07scams

00:43:08but that's

00:43:10only the

00:43:10tip of

00:43:11the

00:43:11iceberg

00:43:11of the

00:43:12potential

00:43:12of that

00:43:13kind

00:43:13of

00:43:13application

00:43:15think

00:43:16about

00:43:16scams

00:43:17that

00:43:17transcend

00:43:18borders

00:43:19for example

00:43:20Howie

00:43:20I don't

00:43:20know

00:43:21if

00:43:21you've

00:43:21been

00:43:21a

00:43:21victim

00:43:22to

00:43:22this

00:43:22but

00:43:22I

00:43:22know

00:43:23our

00:43:24colleague

00:43:25Jessica

00:43:25has

00:43:26been

00:43:26a

00:43:26victim

00:43:27where

00:43:27her

00:43:28likeness

00:43:29was

00:43:29used

00:43:30in a

00:43:30deep

00:43:30fake

00:43:31to

00:43:32sell

00:43:32pills

00:43:33or

00:43:33other

00:43:34medication

00:43:35Howie

00:43:35I was

00:43:36selling

00:43:38health

00:43:39supplements

00:43:40what's

00:43:41funny

00:43:41is that

00:43:42when I

00:43:43was at

00:43:43Harvard

00:43:43I

00:43:44talked

00:43:44to

00:43:44the

00:43:45leading

00:43:46newscaster

00:43:46in

00:43:47Canada

00:43:48Vicky

00:43:49Morales

00:43:50of

00:43:50Canada

00:43:51and

00:43:51when

00:43:52she

00:43:52found out

00:43:53I was

00:43:53working

00:43:54on

00:43:54AI

00:43:54the

00:43:55first

00:43:55thing

00:43:55she

00:43:55told

00:43:55me

00:43:56was

00:43:56actually

00:43:57victim

00:43:57ako

00:43:58ng

00:43:58deep

00:43:58fake

00:43:59na

00:43:59nagbebenta

00:44:00ng

00:44:00gano'ng

00:44:01health

00:44:02supplements

00:44:03so

00:44:04it's

00:44:04transnational

00:44:05already

00:44:05so

00:44:06alam mo

00:44:06na

00:44:07pare-pareho

00:44:08now

00:44:09going back

00:44:10to that

00:44:10misinformation

00:44:11database

00:44:12yung mga

00:44:12na fact

00:44:12check

00:44:13ng isang

00:44:13fact

00:44:14checking

00:44:14organization

00:44:15imagine

00:44:16if we

00:44:16can share

00:44:17that

00:44:17across the

00:44:17world

00:44:18and

00:44:18we

00:44:19can

00:44:19use

00:44:19AI

00:44:19to

00:44:20spot

00:44:20trends

00:44:21na

00:44:21oh

00:44:21ang

00:44:22daming

00:44:22scam

00:44:22na

00:44:23ganito

00:44:23sa

00:44:24ganitong

00:44:24kabansa

00:44:25baka

00:44:26pwedeng

00:44:26other

00:44:26countries

00:44:27can

00:44:27take

00:44:28preemptive

00:44:28action

00:44:29here

00:44:30at

00:44:30GMA

00:44:31sa

00:44:31Digilab

00:44:32we've

00:44:32tried

00:44:33to

00:44:33create

00:44:35projects

00:44:36to

00:44:37pre-bank

00:44:37misinformation

00:44:38which is

00:44:39trying

00:44:40to

00:44:41inoculate

00:44:41parang

00:44:42bakuna

00:44:42you

00:44:42inoculate

00:44:43the

00:44:43people

00:44:44to

00:44:45misinformation

00:44:45uunahan

00:44:46mo na

00:44:46yung

00:44:47misinformation

00:44:47so if

00:44:49you have

00:44:49databases

00:44:50of that

00:44:50around

00:44:51the

00:44:51world

00:44:51and you

00:44:51connect

00:44:52them

00:44:52baka

00:44:53we can

00:44:54learn

00:44:54from each

00:44:54other

00:44:55we can

00:44:55surface

00:44:56trends

00:44:56and we

00:44:57can

00:44:57fight

00:44:58misinformation

00:44:58more

00:44:59effectively

00:45:00na

00:45:00now

00:45:01we can

00:45:03information

00:45:04if

00:45:04a

00:45:04fact

00:45:05check

00:45:05but

00:45:05too

00:45:06late

00:45:06and

00:45:06we can

00:45:07the

00:45:07scam

00:45:08may

00:45:08people

00:45:09may

00:45:10be

00:45:12preemptive

00:45:13ito

00:45:14yung

00:45:14scam

00:45:15sa

00:45:15ibang

00:45:16bansa

00:45:16baka

00:45:17dapat

00:45:17alamin

00:45:18na

00:45:18how

00:45:18to

00:45:19create

00:45:20content

00:45:20that

00:45:21would

00:45:21protect

00:45:22our

00:45:23audiences

00:45:23and

00:45:24our

00:45:24citizens

00:45:24from

00:45:25that

00:45:25type

00:45:25of

00:45:25scam

00:45:26What do

00:45:26you think

00:45:27of

00:45:27regulating

00:45:28AI

00:45:29tools

00:45:29so that

00:45:30at

00:45:30that

00:45:30level

00:45:31they

00:45:31filter

00:45:32out

00:45:33known

00:45:34sources

00:45:35of

00:45:36disinformation

00:45:37of

00:45:37falsehood

00:45:38para

00:45:39hindi na

00:45:40kailangan

00:45:41i-fact

00:45:41check

00:45:41dahil

00:45:41yun nga

00:45:42yung

00:45:42reliability

00:45:43ng

00:45:43mga

00:45:44queries

00:45:45sa

00:45:46chat

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00:45:46for

00:45:46example

00:45:47ay

00:45:48tumaas

00:45:48so

00:45:49you're

00:45:49less

00:45:49suspicious

00:45:50na

00:45:50may

00:45:51makakalusot

00:45:52na

00:45:52fake

00:45:52I'm

00:45:53always

00:45:54suspicious

00:45:54of

00:45:55efforts

00:45:56from

00:45:57government

00:45:57to

00:45:58regulate

00:45:58any

00:45:59platforms

00:46:00we've

00:46:00seen

00:46:00that

00:46:01in

00:46:01the

00:46:02anti-terror

00:46:02bill

00:46:03and

00:46:03the

00:46:03cyber

00:46:04crime

00:46:04bill

00:46:05where

00:46:05inevitably

00:46:06they're

00:46:07being

00:46:07used

00:46:07to

00:46:08threaten

00:46:09independent

00:46:10actors

00:46:11including

00:46:11journalists

00:46:12right now

00:46:13wala akong

00:46:14makita

00:46:14na harm

00:46:15ng

00:46:16AI

00:46:16na hindi

00:46:17pa

00:46:17pwedeng

00:46:18kasuhan

00:46:18like

00:46:18for

00:46:19example

00:46:19pag

00:46:20ginamit

00:46:20ng

00:46:20AI

00:46:21para

00:46:21iscam

00:46:22ka

00:46:22pwede

00:46:23mong

00:46:23ihabla

00:46:24yun

00:46:24dahil

00:46:25nasa

00:46:25cyber

00:46:26crime

00:46:26bill

00:46:26na

00:46:26bawal

00:46:28mang

00:46:28scam

00:46:28online

00:46:29now

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00:46:30problema

00:46:30natin

00:46:31yung

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00:46:32di ba

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00:46:34crime

00:46:35it's

00:46:35distributed

00:46:36but

00:46:37the

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00:46:38crime

00:46:38division

00:46:38of

00:46:39our

00:46:39law

00:46:39enforcement

00:46:40is

00:46:41centralized

00:46:41right

00:46:42hindi

00:46:43ka

00:46:43pwede

00:46:43pumunta

00:46:43sa

00:46:44presinto

00:46:44at

00:46:44magreklamo

00:46:45na

00:46:46na

00:46:46scam

00:46:47ka

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00:46:47Facebook

00:46:48sasabihin

00:46:48sa'yo

00:46:49pumunta

00:46:49ka

00:46:49sa

00:46:50Maynila

00:46:50or

00:46:50sa

00:46:51whatever

00:46:51center

00:46:52to file

00:46:53a cyber

00:46:53crime

00:46:54complaint

00:46:54so

00:46:55yung

00:46:55law

00:46:55enforcement

00:46:56yung

00:46:56hindi

00:46:56nakakahabol

00:46:57there are

00:46:58efforts

00:46:59now

00:46:59by the

00:47:00platform

00:47:00some

00:47:00efforts

00:47:01like

00:47:01for

00:47:01example

00:47:02google

00:47:02has

00:47:04watermarking

00:47:05technology

00:47:06on their

00:47:07synthetic

00:47:07images

00:47:08and videos

00:47:09so

00:47:10if

00:47:10you

00:47:11suspect

00:47:11a

00:47:12video

00:47:12that's

00:47:13spreading

00:47:13misinformation

00:47:14or

00:47:14curious

00:47:15lang

00:47:15kayo

00:47:15kung

00:47:16AI

00:47:16ba

00:47:16it

00:47:16the

00:47:18first

00:47:18thing

00:47:18you

00:47:18should

00:47:19do

00:47:19is

00:47:19screenshot

00:47:20that

00:47:20image

00:47:22or

00:47:22that

00:47:23video

00:47:23and

00:47:24ask

00:47:24Gemini

00:47:25if

00:47:26it

00:47:26generated

00:47:27that

00:47:28video

00:47:28and

00:47:29it's

00:47:30a

00:47:30technology

00:47:30called

00:47:31SynthID

00:47:31it's

00:47:32a

00:47:32watermarking

00:47:33technology

00:47:33and

00:47:34if

00:47:34it

00:47:35was

00:47:35generated

00:47:36by

00:47:36Google

00:47:36it

00:47:37will

00:47:38say

00:47:38that

00:47:38it

00:47:39was

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00:47:39now

00:47:40the

00:47:40problem

00:47:40how

00:47:40we

00:47:40there

00:47:41is

00:47:41that

00:47:42other

00:47:43companies

00:47:43don't

00:47:44want

00:47:44to

00:47:44adopt

00:47:44it

00:47:45maybe

00:47:46because

00:47:46of

00:47:46competition

00:47:47and

00:47:47also

00:47:48the

00:47:48platforms

00:47:48don't

00:47:49want

00:47:49to

00:47:49label

00:47:49AI

00:47:50so

00:47:50ang

00:47:51daming

00:47:51kong

00:47:52kilala

00:47:52from

00:47:53gen

00:47:53alphas

00:47:54to

00:47:55boomers

00:47:55na

00:47:55naloloko

00:47:57or

00:47:57natutuwa

00:47:57sa

00:47:58AI

00:47:58generated

00:47:59content

00:47:59sa

00:48:00Instagram

00:48:00di ba

00:48:01so

00:48:03actually

00:48:03inisip

00:48:04ko

00:48:04feeling

00:48:05ko

00:48:05ang una

00:48:06madidisrupt

00:48:06nitong

00:48:07AI

00:48:07generated

00:48:08content

00:48:09creators

00:48:10na

00:48:10puro

00:48:11paandar

00:48:11lang

00:48:11o puro

00:48:12patawa

00:48:12lang

00:48:12sa

00:48:13Instagram

00:48:13di ba

00:48:14sila

00:48:14yung

00:48:15matithreaten

00:48:15ng

00:48:16AI

00:48:16okay

00:48:16we

00:48:16have

00:48:16a

00:48:16question

00:48:17for

00:48:17Marcos

00:48:17Nubla

00:48:18my

00:48:19question

00:48:19is

00:48:19actually

00:48:19similar

00:48:20to

00:48:20what

00:48:20Sir

00:48:20J.

00:48:21Mark

00:48:21shared

00:48:21earlier

00:48:22about

00:48:22radiology

00:48:23so

00:48:24many

00:48:25think

00:48:25that

00:48:25AI

00:48:25will

00:48:26cause

00:48:26widespread

00:48:26unemployment

00:48:27and

00:48:28replace

00:48:28human

00:48:28creativity

00:48:29but

00:48:30but

00:48:30do

00:48:30you

00:48:30think

00:48:30about

00:48:31the

00:48:31idea

00:48:31that

00:48:31AI

00:48:32will

00:48:32spark

00:48:32instead

00:48:33a

00:48:34modern

00:48:34creative

00:48:34renaissance

00:48:35some

00:48:36argues

00:48:37that

00:48:37the

00:48:37widespread

00:48:38presence

00:48:38of

00:48:38AI

00:48:39will

00:48:39first

00:48:39free up

00:48:40people

00:48:41from

00:48:41mindless

00:48:41jobs

00:48:42giving

00:48:42them

00:48:42the

00:48:42opportunity

00:48:43to

00:48:43pursue

00:48:44truly

00:48:44creative

00:48:45jobs

00:48:45and

00:48:46second

00:48:46raise

00:48:47the

00:48:47value

00:48:47and

00:48:48demand

00:48:48of

00:48:48pure

00:48:48human

00:48:49creativity

00:48:49in

00:48:49a

00:48:50world

00:48:50full

00:48:50with

00:48:50AI

00:48:51slop

00:48:51what

00:48:51is

00:48:51your

00:48:52perspective

00:48:52about

00:48:52that

00:48:53okay

00:48:53so

00:48:54we've

00:48:54been

00:48:55talking

00:48:55about

00:48:55the

00:48:55dangers

00:48:55the

00:48:57potential

00:48:59blessings

00:49:00benefits

00:49:01of

00:49:02AI

00:49:02I think

00:49:03it's already

00:49:03happening

00:49:04especially

00:49:05sa

00:49:05development

00:49:07sa

00:49:07programming

00:49:09a lot

00:49:10of

00:49:10programmers

00:49:11are reporting

00:49:12being more

00:49:13productive

00:49:13using

00:49:14coding

00:49:14agents

00:49:16madali

00:49:17kasi

00:49:17domain

00:49:18yung

00:49:18programming

00:49:19because

00:49:20if

00:49:20there's

00:49:20an error

00:49:21in your

00:49:21code

00:49:21it

00:49:22just

00:49:22wouldn't

00:49:23work

00:49:23and

00:49:23then

00:49:23AI

00:49:24will

00:49:24be

00:49:24forced

00:49:25to

00:49:25debug

00:49:25it

00:49:25to

00:49:27your

00:49:27point

00:49:28about

00:49:29in

00:49:30a

00:49:31world

00:49:31full

00:49:31of

00:49:32AI

00:49:32slop

00:49:32I

00:49:32think

00:49:33that's

00:49:34a

00:49:34correct

00:49:34point

00:49:35I

00:49:35think

00:49:35there's

00:49:36a

00:49:36lot

00:49:36of

00:49:36value

00:49:37that's

00:49:38going

00:49:38to

00:49:38be

00:49:39given

00:49:39to

00:49:40writing

00:49:41that

00:49:41is

00:49:42human

00:49:42that

00:49:42is

00:49:43original

00:49:43that

00:49:43is

00:49:43creative

00:49:44how

00:49:45we

00:49:45were

00:49:45talking

00:49:45in

00:49:46the

00:49:46back

00:49:46earlier

00:49:46I

00:49:47liken

00:49:47it

00:49:47to

00:49:48chocolate

00:49:48most

00:49:49of

00:49:50the

00:49:50chocolate

00:49:50you

00:49:50eat

00:49:51whatever

00:49:51brand

00:49:52it

00:49:52is

00:49:53mass

00:49:53produced

00:49:53it's

00:49:54probably

00:49:55bad

00:49:55for

00:49:55you

00:49:56but

00:49:57you

00:49:57just

00:49:57consume

00:49:58it

00:49:58to

00:49:58get

00:49:58that

00:49:58fixed

00:49:59right

00:49:59most

00:50:00of the

00:50:01writing

00:50:01we

00:50:01consume

00:50:02mass

00:50:03produced

00:50:05commoditized

00:50:06update

00:50:06on the

00:50:07weather

00:50:07update

00:50:08on the

00:50:08road

00:50:08closure

00:50:09when

00:50:10when I

00:50:10was

00:50:10with

00:50:11GMA

00:50:11news

00:50:11online

00:50:12our

00:50:12top

00:50:12content

00:50:13every

00:50:14year

00:50:14is

00:50:15walang

00:50:15pasok

00:50:16content

00:50:16kasi

00:50:17you

00:50:19keep

00:50:19refreshing

00:50:20the

00:50:21news

00:50:21page

00:50:21for

00:50:22in

00:50:22announce

00:50:23na ba

00:50:23na

00:50:23walang

00:50:23pasok

00:50:24kaya

00:50:25madalas

00:50:25pinifake

00:50:26din yun

00:50:26kaya

00:50:27nabibiktima

00:50:28rin

00:50:28kayo

00:50:28kaya

00:50:29dapat

00:50:29sa

00:50:29GMA

00:50:30news

00:50:30online

00:50:30lang

00:50:31kayo

00:50:31mag

00:50:31monitor

00:50:31ng

00:50:32walang

00:50:32pasok

00:50:32no

00:50:33okay

00:50:34but

00:50:34back

00:50:34to

00:50:35the

00:50:35chocolate

00:50:35analogy

00:50:36most

00:50:36chocolate

00:50:37is

00:50:37mass

00:50:37produced

00:50:37but

00:50:39chocolate

00:50:39that

00:50:40people

00:50:41pay

00:50:41a lot

00:50:41of

00:50:42money

00:50:42for

00:50:42that's

00:50:43not

00:50:43produced

00:50:44by

00:50:44machines

00:50:44that are

00:50:45handmade

00:50:45right

00:50:46and I

00:50:47think

00:50:47that

00:50:48is

00:50:48how

00:50:48it's

00:50:49going

00:50:49to

00:50:49change

00:50:50the

00:50:50writing

00:50:53landscape

00:50:54where

00:50:55there's

00:50:55writing

00:50:56that's

00:50:57handmade

00:50:57that

00:50:58people

00:50:58are

00:50:59going

00:50:59to be

00:50:59willing

00:51:00to

00:51:00pay

00:51:00for

00:51:01and I

00:51:02hope

00:51:02it

00:51:02also

00:51:03applies

00:51:03to

00:51:04all

00:51:04other

00:51:05creative

00:51:05industries

00:51:06in a

00:51:07world

00:51:07full of

00:51:07slop

00:51:08back

00:51:08mayroon

00:51:09space

00:51:09for

00:51:10our

00:51:10artisanal

00:51:11products

00:51:12okay

00:51:13before we

00:51:13leave the

00:51:13question of

00:51:14a creative

00:51:15renaissance

00:51:15because of

00:51:16AI

00:51:16I just

00:51:16want to

00:51:17ask

00:51:17people in

00:51:18the audience

00:51:18may experience

00:51:19na ba

00:51:20yung

00:51:20iba

00:51:20sa inyo

00:51:21creating

00:51:22things

00:51:23using

00:51:24AI

00:51:24aside from

00:51:25writing

00:51:25kadalasan

00:51:26ang alam

00:51:27natin

00:51:27chat

00:51:27GPT

00:51:28Gemini

00:51:29which

00:51:29creates

00:51:30writing

00:51:31content

00:51:32hi

00:51:32I'm

00:51:33Janine

00:51:33Miranda

00:51:34of

00:51:34Rosario

00:51:34University

00:51:35recently

00:51:36I

00:51:37used

00:51:37AI

00:51:38to

00:51:38make

00:51:39an

00:51:39ad

00:51:40for

00:51:40our

00:51:41subject

00:51:42in

00:51:43credit

00:51:43and

00:51:43collection

00:51:44it's

00:51:45about

00:51:45we made

00:51:47our own

00:51:47lending

00:51:47company

00:51:48and we

00:51:48have

00:51:49to

00:51:49make

00:51:49a

00:51:49promotional

00:51:50video

00:51:51about

00:51:51it

00:51:52what

00:51:52I

00:51:52did

00:51:52was

00:51:53I

00:51:53feed

00:51:54prompt

00:51:56information

00:51:56to

00:51:57cop

00:51:57images

00:51:59and then

00:52:00it

00:52:00generated

00:52:01images

00:52:01and then

00:52:02I

00:52:02used

00:52:02Grok

00:52:03for

00:52:05animation

00:52:06so

00:52:07he

00:52:08created

00:52:08images

00:52:09that

00:52:10firstly

00:52:11created

00:52:12an AI

00:52:14and then

00:52:14I made

00:52:15it a

00:52:15video

00:52:16and then

00:52:16I

00:52:19did

00:52:20the

00:52:20voiceover

00:52:20and then

00:52:21I

00:52:21produced

00:52:22this

00:52:22whole

00:52:22ad

00:52:23using

00:52:24just

00:52:24AI

00:52:25but

00:52:26what

00:52:27frustrated

00:52:28me

00:52:28is

00:52:28that

00:52:29a

00:52:30lot

00:52:30of

00:52:30my

00:52:31classmates

00:52:31or

00:52:32people

00:52:32thought

00:52:33it

00:52:33was

00:52:33easy

00:52:34because

00:52:35AI

00:52:35so

00:52:36yeah

00:52:37I

00:52:37used

00:52:37AI

00:52:38all

00:52:39AI

00:52:39to

00:52:40create

00:52:41even

00:52:41the

00:52:41flow

00:52:42of

00:52:42the

00:52:42video

00:52:42I

00:52:43used

00:52:43chat

00:52:43GPT

00:52:44to

00:52:44create

00:52:45a

00:52:46flow

00:52:46I

00:52:46just

00:52:46feed

00:52:47what

00:52:47I

00:52:47wanted

00:52:48to

00:52:48I

00:52:49wanted

00:52:49the

00:52:50video

00:52:50to

00:52:50look

00:52:50like

00:52:51can

00:52:52I

00:52:52ask

00:52:52did

00:52:53your

00:52:53teacher

00:52:53know

00:52:54did

00:52:54you

00:52:54know

00:52:54did

00:52:56she

00:52:57encourage

00:52:57you

00:52:58to

00:52:58use

00:52:58it

00:52:58not

00:52:59encourage

00:53:00but

00:53:00it

00:53:00was

00:53:01permitted

00:53:01we

00:53:02can

00:53:02do

00:53:03anything

00:53:03any

00:53:03way

00:53:04to

00:53:05make

00:53:06the

00:53:06promotional

00:53:07video

00:53:07a lot

00:53:08of

00:53:08my

00:53:08classmates

00:53:08just

00:53:09use

00:53:09videos

00:53:11from

00:53:11online

00:53:12and then

00:53:12they

00:53:12just

00:53:13change

00:53:13the

00:53:14voice

00:53:14over

00:53:14but

00:53:14I

00:53:15thought

00:53:15I

00:53:16want

00:53:16to

00:53:16make

00:53:17it

00:53:17our

00:53:18own

00:53:18but

00:53:19I

00:53:19didn't

00:53:19make

00:53:20it

00:53:20edit

00:53:21or

00:53:21to

00:53:22really

00:53:22animate

00:53:23videos

00:53:23so

00:53:24I

00:53:25searched

00:53:25or

00:53:26asked

00:53:27my

00:53:27other

00:53:28friends

00:53:28if

00:53:29they

00:53:29know

00:53:29an

00:53:29app

00:53:30or

00:53:30a

00:53:31website

00:53:31that

00:53:32I

00:53:32can

00:53:32use

00:53:32that

00:53:33was

00:53:33very

00:53:33interesting

00:53:34because

00:53:35of

00:53:35course

00:53:36she

00:53:36used

00:53:37AI

00:53:37tools

00:53:38to

00:53:38develop

00:53:39and

00:53:40to

00:53:40create

00:53:40that

00:53:41video

00:53:41but

00:53:42she

00:53:42also

00:53:42the skills

00:53:43to

00:53:45come up

00:53:46with a

00:53:47good

00:53:47enough

00:53:47video

00:53:48but

00:53:48at

00:53:48the

00:53:48same

00:53:48time

00:53:49she

00:53:49admitted

00:53:49she

00:53:49used

00:53:50AI

00:53:51to

00:53:51compensate

00:53:51for

00:53:52the

00:53:52skills

00:53:52she

00:53:53did

00:53:53not

00:53:53have

00:53:53so

00:53:53she

00:53:54didn't

00:53:54run

00:53:55or

00:53:55video

00:53:56edit

00:53:56so

00:53:58she

00:53:58had

00:53:58advantage

00:53:59over

00:54:00those

00:54:00that

00:54:00mag

00:54:00edit

00:54:01pero

00:54:02nakikita

00:54:02natin

00:54:03yun

00:54:03sa

00:54:03AI

00:54:04videos

00:54:04the

00:54:05best

00:54:05AI

00:54:06videos

00:54:06actually

00:54:07have

00:54:08good

00:54:08script

00:54:09they

00:54:10have

00:54:10good

00:54:10storytelling

00:54:12and

00:54:13so

00:54:13if

00:54:13you

00:54:13can't

00:54:14tell

00:54:14stories

00:54:14well

00:54:15you

00:54:15can't

00:54:16tell

00:54:16stories

00:54:16well

00:54:17with

00:54:17AI

00:54:17so

00:54:18it's

00:54:18going

00:54:18to

00:54:18be

00:54:19like

00:54:19I

00:54:19said

00:54:20before

00:54:21magbabago

00:54:21yung

00:54:22nature

00:54:22ng

00:54:22trabaho

00:54:23ngayon

00:54:24baka

00:54:25hindi

00:54:25kailangan

00:54:26magaling

00:54:27ka

00:54:27mag

00:54:27edit

00:54:27pero

00:54:28kailangan

00:54:28magaling

00:54:29alam

00:54:30mo

00:54:30pa

00:54:30rin

00:54:30yung

00:54:30kwento

00:54:31na

00:54:32gusto

00:54:32mong

00:54:32ikwento

00:54:33now

00:54:34that

00:54:36might

00:54:36not

00:54:37play

00:54:38well

00:54:38with

00:54:38our

00:54:38industry

00:54:39where

00:54:41others

00:54:42jobs

00:54:43may be

00:54:43lost

00:54:44or

00:54:44the

00:54:44nature

00:54:45of

00:54:45jobs

00:54:45may

00:54:46change

00:54:46reminds

00:54:47reminds

00:54:47how

00:54:48we

00:54:48have

00:54:48our

00:54:48projects

00:54:48at

00:54:49PCIJ

00:54:49last

00:54:50year

00:54:50where

00:54:50I

00:54:51turned

00:54:51an article

00:54:55by

00:54:55Sheila

00:54:55Coronel

00:54:56into

00:54:57a

00:54:5730

00:54:58minute

00:54:58video

00:54:59that's

00:54:59animated

00:55:00and

00:55:00voiced

00:55:01using

00:55:01AI

00:55:02so

00:55:03it

00:55:03was

00:55:03well

00:55:04received

00:55:04it

00:55:04went

00:55:05viral

00:55:05around

00:55:05the

00:55:06world

00:55:06as

00:55:06an

00:55:07example

00:55:07of

00:55:08what

00:55:08they

00:55:08call

00:55:09liquid

00:55:09content

00:55:10so

00:55:10liquid

00:55:10content

00:55:11the idea

00:55:12is

00:55:12you use

00:55:12AI

00:55:13susulat

00:55:14ka

00:55:14ng article

00:55:14AI

00:55:15can turn

00:55:16it

00:55:16into

00:55:16a

00:55:17video

00:55:17AI

00:55:18can

00:55:18turn

00:55:18it

00:55:18into

00:55:19a

00:55:19podcast

00:55:19with

00:55:20little

00:55:20human

00:55:22effort

00:55:22so

00:55:23I

00:55:24created

00:55:24that

00:55:25video

00:55:25in

00:55:25two

00:55:26days

00:55:26if

00:55:27I

00:55:27had

00:55:27to

00:55:28work

00:55:28with

00:55:28humans

00:55:28it

00:55:29would

00:55:29have

00:55:29taken

00:55:29me

00:55:29weeks

00:55:31and

00:55:32so

00:55:32it

00:55:32was

00:55:32well

00:55:32received

00:55:33around

00:55:33the

00:55:33world

00:55:33but

00:55:34the

00:55:34big

00:55:34pushback

00:55:35we

00:55:35got

00:55:35here

00:55:36in

00:55:36the

00:55:36Philippines

00:55:37were

00:55:37from

00:55:38communities

00:55:38of

00:55:39artists

00:55:39not

00:55:40because

00:55:41they

00:55:42feel

00:55:43that

00:55:44they

00:55:45work

00:55:45that

00:55:46wasn't

00:55:46even

00:55:46their

00:55:47fear

00:55:47their

00:55:48problem

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00:55:49it

00:55:49was

00:55:50it

00:55:51was

00:55:51the

00:55:51PCIJ

00:55:52and

00:55:52we

00:55:53were

00:55:53using

00:55:54image

00:55:55generators

00:55:55which

00:55:56they

00:55:56say

00:55:57and

00:55:57accurately

00:55:58to

00:55:58stole

00:55:59the

00:56:00work

00:56:00or

00:56:00train

00:56:00on

00:56:02artists

00:56:02work

00:56:03without

00:56:03permission

00:56:04and

00:56:04without

00:56:06compensation

00:56:07and so

00:56:08there's

00:56:08the ethical

00:56:09part

00:56:10of that

00:56:10too

00:56:11yes

00:56:12we were

00:56:12able to

00:56:13produce

00:56:13but

00:56:14there's

00:56:14a certain

00:56:15part

00:56:15of the

00:56:16audience

00:56:16who

00:56:16won't

00:56:17like

00:56:17that

00:56:17because

00:56:18of

00:56:18the

00:56:18ethics

00:56:19of

00:56:19it

00:56:19but

00:56:20knowing

00:56:21that

00:56:21there's

00:56:21that

00:56:21push

00:56:22back

00:56:22how

00:56:22would

00:56:22you

00:56:23do

00:56:24it

00:56:24in

00:56:24the

00:56:24future

00:56:25it

00:56:26depends

00:56:26on

00:56:29the

00:56:30media

00:56:30organization

00:56:31right

00:56:32if it

00:56:32were

00:56:33GMA

00:56:33doing

00:56:33it

00:56:34right

00:56:34there

00:56:35might

00:56:35be

00:56:35more

00:56:36push

00:56:36back

00:56:36because

00:56:37they

00:56:37would

00:56:37say

00:56:38why

00:56:39would

00:56:39GMA

00:56:39use

00:56:40AI

00:56:40when

00:56:40it

00:56:41could

00:56:41use

00:56:41artists

00:56:42to

00:56:42do

00:56:43it

00:56:43they

00:56:43can

00:56:44pay

00:56:44artists

00:56:44but

00:56:45if

00:56:45you're

00:56:45a

00:56:45small

00:56:46publication

00:56:47in

00:56:47say

00:56:48Palawan

00:56:48you only

00:56:49have

00:56:49five

00:56:50people

00:56:50maybe

00:56:52it's

00:56:52more

00:56:52acceptable

00:56:53to

00:56:53audiences

00:56:55if

00:56:56you

00:56:56use

00:56:56synthetic

00:56:57images

00:56:58or

00:56:58synthetic

00:56:59video

00:56:59no

00:57:00audiences

00:57:01don't

00:57:02seem to

00:57:02mind

00:57:02lahat

00:57:03ng

00:57:03Facebook

00:57:03pages

00:57:04chat

00:57:06gpt

00:57:06generated

00:57:07you

00:57:08may

00:57:09make a

00:57:13caricature

00:57:14of

00:57:14myself

00:57:14and

00:57:15chat

00:57:16gpt

00:57:16and

00:57:17if

00:57:17you

00:57:17were

00:57:17on

00:57:17Facebook

00:57:18or

00:57:18Instagram

00:57:18people

00:57:19were

00:57:19using

00:57:20chat

00:57:20gpt

00:57:21to

00:57:21generate

00:57:21pictures

00:57:22of

00:57:22themselves

00:57:22so

00:57:23it's

00:57:24evolving

00:57:25yung

00:57:25attitudes

00:57:26ng

00:57:26audiences

00:57:27but

00:57:28that's

00:57:29something

00:57:30that

00:57:30news

00:57:30organizations

00:57:31would

00:57:31have

00:57:32to

00:57:32reckon

00:57:32with

00:57:32attitude

00:57:34at

00:57:35comfort

00:57:35level

00:57:36ng

00:57:36audience

00:57:36dito

00:57:37sa

00:57:37ganitong

00:57:37type

00:57:38ng

00:57:39media

00:57:40good advice

00:57:41but

00:57:42so

00:57:42one last

00:57:42piece

00:57:43of

00:57:43advice

00:57:43so

00:57:43what

00:57:44can

00:57:44you

00:57:44advise

00:57:46students

00:57:46on

00:57:48how

00:57:48to

00:57:48prepare

00:57:49for

00:57:49a

00:57:49future

00:57:50where

00:57:51AI

00:57:51becomes

00:57:52an

00:57:52even

00:57:52more

00:57:53dominant

00:57:53tool

00:57:54in

00:57:54many

00:57:55facets

00:57:55of

00:57:56life

00:57:56I

00:57:57think

00:57:57they're

00:57:57already

00:57:58doing

00:57:58it

00:57:58I

00:57:59think

00:57:59they're

00:57:59already

00:58:00experimenting

00:58:01there are

00:58:02a lot

00:58:02of

00:58:03resources

00:58:03online

00:58:04we'll

00:58:04talk

00:58:05about

00:58:05them

00:58:05later

00:58:06in

00:58:06our

00:58:06workshop

00:58:06too

00:58:07about

00:58:08how

00:58:08to

00:58:08use

00:58:09it

00:58:09for

00:58:09your

00:58:09work

00:58:10but

00:58:10then

00:58:11again

00:58:11I

00:58:11go

00:58:11back

00:58:12to

00:58:12the

00:58:12marathon

00:58:12analogy

00:58:13you

00:58:14need

00:58:15to

00:58:15learn

00:58:15to

00:58:16go

00:58:16and

00:58:17grab

00:58:18because

00:58:20you're

00:58:20going

00:58:20to

00:58:22it

00:58:22and

00:58:26know

00:58:26when

00:58:26you

00:58:27have

00:58:27to

00:58:28put

00:58:28that

00:58:28constraint

00:58:29on

00:58:29yourself

00:58:30not

00:58:30to

00:58:31use

00:58:31it

00:58:31so

00:58:31that

00:58:32you

00:58:32get

00:58:32better

00:58:33at

00:58:33the

00:58:33skill

00:58:34that

00:58:34you're

00:58:35trying

00:58:35to

00:58:35do

00:58:35so

00:58:36for

00:58:36example

00:58:37if

00:58:37you

00:58:37want

00:58:37to

00:58:38learn

00:58:38video

00:58:38editing

00:58:39don't

00:58:40take

00:58:40that

00:58:40shortcut

00:58:41of

00:58:41using

00:58:42AI

00:58:42because

00:58:43you don't

00:58:43learn

00:58:44the

00:58:44fundamentals

00:58:45of

00:58:45video

00:58:45editing

00:58:46right

00:58:47and

00:58:47same

00:58:47for

00:58:48writing

00:58:48same

00:58:48for

00:58:49programming

00:58:49and

00:58:50so

00:58:50figure

00:58:50out

00:58:51when

00:58:52you

00:58:53should

00:58:53be

00:58:53using

00:58:54AI

00:58:54because

00:58:55you

00:58:55want

00:58:56to

00:58:56better

00:58:56yourself

00:58:57and

00:58:58then

00:58:58also

00:58:58figure

00:58:58out

00:58:59when

00:58:59you

00:58:59should

00:58:59use

00:59:00AI

00:59:00to

00:59:00experiment

00:59:01and

00:59:01try

00:59:02to

00:59:02find

00:59:02things

00:59:03that

00:59:03you don't

00:59:04know

00:59:04that

00:59:05you'll

00:59:06discover

00:59:06somebody

00:59:07else

00:59:08had

00:59:08their

00:59:08hand

00:59:08up

00:59:08in

00:59:09terms

00:59:09of

00:59:10creation

00:59:11experience

00:59:12with

00:59:12creation

00:59:13yung

00:59:13mga

00:59:14hindi

00:59:14pa

00:59:14nakakapagsalita

00:59:15yung

00:59:15nasa

00:59:15gitna

00:59:16I'm

00:59:16Christine

00:59:17J.

00:59:17Reyes

00:59:18from

00:59:18JRU

00:59:19a

00:59:19nursing

00:59:19student

00:59:20so

00:59:21in

00:59:21our

00:59:22part

00:59:22we

00:59:23have

00:59:23this

00:59:24nursing

00:59:24informatics

00:59:25subject

00:59:25wherein

00:59:26our

00:59:26professor

00:59:27encouraged

00:59:28us

00:59:28to

00:59:28use

00:59:29different

00:59:30tools

00:59:31AI

00:59:32tools

00:59:33para

00:59:33mag

00:59:33generate

00:59:34mag

00:59:34prototype

00:59:36something

00:59:37na

00:59:38wala

00:59:38pa

00:59:38po

00:59:39inside

00:59:40the

00:59:40hospital

00:59:41or

00:59:41outside

00:59:42in

00:59:42the

00:59:42community

00:59:43na

00:59:44magagamit

00:59:44para

00:59:45mas

00:59:45mapabilis

00:59:45yung

00:59:46monitoring

00:59:46sa

00:59:47mga

00:59:47patients

00:59:47and

00:59:48in

00:59:48our

00:59:48case

00:59:49po

00:59:49is

00:59:50for

00:59:52the

00:59:55elders

00:59:56na

00:59:56makakatulong

00:59:57po

00:59:57sa

00:59:57mga

00:59:58elders

00:59:58inside

00:59:58the

00:59:59hospital

00:59:59since

00:59:59hindi

01:00:00po

01:00:00lahat

01:00:01ng

01:00:01patients

01:00:01is

01:00:01merong

01:00:02bantay

01:00:0224-7

01:00:03and

01:00:04some

01:00:04of

01:00:04hospitals

01:00:05po

01:00:05is

01:00:05hindi

01:00:05nila

01:00:05ina-allow

01:00:06so

01:00:07we

01:00:08use

01:00:08the

01:00:08AI

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01:00:09which

01:00:09is

01:00:09the

01:00:09chat

01:00:10GPT

01:00:10to

01:00:11make

01:00:12po

01:00:12yung

01:00:12image

01:00:13which

01:00:14is

01:00:14requested

01:00:15by

01:00:15our

01:00:16professor

01:00:16kung

01:00:16pwede

01:00:17daw

01:00:17po

01:00:17kaming

01:00:17gumawa

01:00:17ng

01:00:18video

01:00:18or

01:00:19ng

01:00:19image

01:00:20na

01:00:20talaga

01:00:20makikita

01:00:21kung

01:00:21para

01:00:22saan

01:00:22yung

01:00:22purpose

01:00:22niya

01:00:22talaga

01:00:23at

01:00:23mas

01:00:23mavi

01:00:23visualize

01:00:24po

01:00:24namin

01:00:24yung

01:00:25magiging

01:00:25purpose

01:00:26po

01:00:26ng

01:00:26product

01:00:26namin

01:00:28interesting

01:00:28nursing

01:00:34use

01:00:35case

01:00:35that's

01:00:36a

01:00:36use

01:00:36case

01:00:37of

01:00:37ideation

01:00:38you

01:00:39were

01:00:40using

01:00:40the

01:00:40image

01:00:41as a

01:00:42media

01:00:43storyboard

01:00:44or

01:00:46brainstorm

01:00:47about

01:00:49how

01:00:49you

01:00:50can

01:00:50effectively

01:00:51change

01:00:52the

01:00:52system

01:00:53and

01:00:54AI

01:00:55allow

01:00:55you

01:00:55to

01:00:55visualize

01:00:56that

01:00:56actually

01:00:57ideation

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01:00:59one

01:00:59of

01:00:59the

01:00:59best

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01:01:01of

01:01:01AI

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01:01:04what

01:01:04do

01:01:05we

01:01:05say

01:01:05there

01:01:06are

01:01:06no

01:01:07bad

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01:01:08take

01:01:09as

01:01:09much

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01:01:10many

01:01:11ideas

01:01:11from

01:01:11AI

01:01:12as

01:01:12you

01:01:12could

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01:01:14them

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01:01:15ideas

01:01:16right

01:01:17if

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01:01:18ask

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01:01:1910

01:01:19ideas

01:01:19how

01:01:19it

01:01:20will

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01:01:20give

01:01:21you

01:01:21nine

01:01:21bad

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01:01:22but

01:01:22if

01:01:22only

01:01:23one

01:01:23idea

01:01:23is

01:01:24good

01:01:24then

01:01:25that's

01:01:25already

01:01:25a

01:01:26worthwhile

01:01:26use

01:01:27of

01:01:27AI

01:01:27another

01:01:29thing

01:01:29that

01:01:29you

01:01:29can

01:01:30do

01:01:30is

01:01:30you

01:01:30can

01:01:30use

01:01:33arguments

01:01:33I'm

01:01:34sorry

01:01:34what's

01:01:35that

01:01:35steel

01:01:35man

01:01:36arguments

01:01:36so

01:01:37yun

01:01:37yung

01:01:37steel

01:01:37man

01:01:38steel

01:01:38man

01:01:38kabaliktaran

01:01:40ng

01:01:40straw

01:01:40man

01:01:41diba

01:01:41pag

01:01:41yung

01:01:42straw

01:01:42man

01:01:42fallacy

01:01:43we

01:01:44build

01:01:44a

01:01:44weak

01:01:45opponent

01:01:46so

01:01:46that

01:01:46we

01:01:47can

01:01:47knock

01:01:47them

01:01:47down

01:01:48diba

01:01:48so

01:01:49that's

01:01:49a

01:01:49fallacy

01:01:50but

01:01:51build

01:01:51a

01:01:51steel

01:01:51man

01:01:52parang

01:01:52if

01:01:52you

01:01:53write

01:01:53an

01:01:53article

01:01:53build

01:01:54a

01:01:54steel

01:01:54man

01:01:56kalaban

01:01:57mo

01:01:57you

01:01:58debate

01:01:58with

01:01:59it

01:01:59right

01:01:59so

01:02:00if

01:02:00you

01:02:01write

01:02:01an

01:02:03mga

01:02:04troll

01:02:04na

01:02:05ganito

01:02:05yung

01:02:05point

01:02:06of

01:02:06view

01:02:06about

01:02:07this

01:02:07article

01:02:07what

01:02:08are

01:02:08the

01:02:08weaknesses

01:02:09in

01:02:09my

01:02:09argument

01:02:10right

01:02:10so

01:02:11again

01:02:11it's

01:02:12not a

01:02:12good

01:02:13source

01:02:13of

01:02:14information

01:02:14but

01:02:15it's

01:02:15a

01:02:15good

01:02:15way

01:02:15for

01:02:16processing

01:02:16information

01:02:17that

01:02:17you

01:02:18already

01:02:18feed

01:02:19it

01:02:19okay

01:02:20I

01:02:21saw

01:02:21a

01:02:21couple

01:02:21of

01:02:22other

01:02:22hands

01:02:22here

01:02:22anyone

01:02:23else

01:02:23want

01:02:23to

01:02:23contribute

01:02:24yeah

01:02:24over

01:02:24here

01:02:26from

01:02:26good

01:02:27morning

01:02:28my name

01:02:28is

01:02:28James

01:02:28Andrew

01:02:29Valencia

01:02:29from

01:02:30the

01:02:30National

01:02:30University

01:02:30The

01:02:31Watchdog

01:02:33and

01:02:33doing

01:02:34filmmaking

01:02:34and

01:02:35also

01:02:35creative

01:02:35works

01:02:36for

01:02:36organizations

01:02:37and

01:02:38businesses

01:02:38I

01:02:39use

01:02:39AI

01:02:40it

01:02:40made

01:02:41my

01:02:41life

01:02:41easier

01:02:41specifically

01:02:42when it

01:02:42comes to

01:02:43generating

01:02:43let's

01:02:43say

01:02:44for a

01:02:44storyboard

01:02:44before

01:02:45we

01:02:45used

01:02:46to

01:02:46draw

01:02:46it

01:02:46but

01:02:46now

01:02:47we

01:02:47could

01:02:47use

01:02:47the

01:02:48nano

01:02:48banana

01:02:48pro

01:02:49of

01:02:49Google

01:02:49to

01:02:49just

01:02:50generate

01:02:50the

01:02:50images

01:02:51itself

01:02:51and

01:02:52also

01:02:52we

01:02:52use

01:02:52Higgs

01:02:53field

01:02:53AI

01:02:53in

01:02:54terms

01:02:54of

01:02:54let's

01:02:56say

01:02:56transitions

01:02:56and

01:02:57also

01:02:57making

01:02:58it

01:02:59also

01:02:59makes

01:02:59our

01:03:01visions

01:03:01using

01:03:03backplating

01:03:03or

01:03:04green

01:03:04screens

01:03:04and

01:03:05just

01:03:05using

01:03:06it

01:03:06in

01:03:06ways

01:03:07we

01:03:08could

01:03:08not

01:03:08use

01:03:08before

01:03:09we

01:03:09have

01:03:10to

01:03:10do

01:03:11it

01:03:11ourselves

01:03:11but

01:03:14now

01:03:15it

01:03:15just

01:03:15made

01:03:16it

01:03:16a lot

01:03:17easier

01:03:17for

01:03:17us

01:03:18in

01:03:18our

01:03:18creative

01:03:18and

01:03:19also

01:03:19to

01:03:19sound

01:03:20design

01:03:20we

01:03:20can

01:03:21also

01:03:21generate

01:03:22our

01:03:22own

01:03:23AI

01:03:24voices

01:03:24and

01:03:25also

01:03:25music

01:03:26and

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01:03:26the

01:03:27prompt

01:03:27so

01:03:27as

01:03:28a

01:03:28creative

01:03:28myself

01:03:28it

01:03:29made

01:03:29our

01:03:30lives

01:03:31easier

01:03:31but

01:03:31what

01:03:32do

01:03:32you

01:03:32think

01:03:32yeah

01:03:33I

01:03:34think

01:03:34that's

01:03:34a

01:03:35very

01:03:35advanced

01:03:36use

01:03:36of

01:03:36AI

01:03:37a lot

01:03:38of

01:03:38newsrooms

01:03:38around

01:03:39the

01:03:39country

01:03:40don't

01:03:40even

01:03:40know

01:03:41how

01:03:41to

01:03:41use

01:03:41AI

01:03:42that

01:03:42way

01:03:42I

01:03:43go

01:03:43back

01:03:44to

01:03:44our

01:03:44experiment

01:03:44on

01:03:47PCIJ

01:03:48I

01:03:48used

01:03:48AI

01:03:49voices

01:03:50for

01:03:51that

01:03:51and

01:03:52what's

01:03:52interesting

01:03:52was

01:03:53when

01:03:53I

01:03:53made

01:03:54my

01:03:55friends

01:03:56from

01:03:56the

01:03:56US

01:03:56listen

01:03:57to

01:03:57it

01:03:57they

01:03:59hated

01:03:59it

01:03:59they

01:04:00said

01:04:00it

01:04:00sounded

01:04:00so

01:04:01AI

01:04:01right

01:04:02so

01:04:02nega

01:04:03sa

01:04:03kanila

01:04:03yun

01:04:04pero

01:04:05when

01:04:06Filipino

01:04:06journalists

01:04:07listen

01:04:07to

01:04:07it

01:04:07even

01:04:08Sheila

01:04:08Coronel

01:04:09I

01:04:09already

01:04:09told her

01:04:10this

01:04:10is

01:04:10AI

01:04:11her

01:04:11first

01:04:11question

01:04:12to

01:04:12me

01:04:12was

01:04:12is

01:04:13this

01:04:13really

01:04:13AI

01:04:14because

01:04:15because

01:04:15because I

01:04:15a

01:04:15voice

01:04:16model

01:04:16that

01:04:17spoke

01:04:18with

01:04:19a

01:04:19very

01:04:19slight

01:04:20hint

01:04:20of

01:04:21a

01:04:21Filipino

01:04:21accent

01:04:22right

01:04:22so

01:04:23the

01:04:23narrative

01:04:23was

01:04:24in

01:04:24English

01:04:24pero

01:04:25may

01:04:25hint

01:04:26ng

01:04:26Filipino

01:04:26accent

01:04:27dun

01:04:27and so

01:04:28actually

01:04:29that

01:04:29project

01:04:30did

01:04:30better

01:04:31on

01:04:31the

01:04:32podcast

01:04:32than

01:04:33it

01:04:33did

01:04:33on

01:04:34video

01:04:34because

01:04:34the

01:04:35Filipino

01:04:36ear

01:04:36can hear

01:04:37the

01:04:37Filipino

01:04:37accent

01:04:38in the

01:04:38AI

01:04:39and

01:04:39that

01:04:40I

01:04:40think

01:04:41for me

01:04:41that

01:04:41underscores

01:04:42the importance

01:04:43of

01:04:43inclusivity

01:04:44that

01:04:45there was

01:04:46Filipino

01:04:46voice

01:04:47model

01:04:47that

01:04:47before

01:04:48TikTok

01:04:48was

01:04:49like

01:04:51the

01:04:51English

01:04:52accent

01:04:52was

01:04:53the pronunciation

01:04:53of Filipino

01:04:54names

01:04:55and it

01:04:56became

01:04:56a thing

01:04:57on

01:04:57TikTok

01:04:57but

01:04:57now

01:04:58AI

01:04:59models

01:04:59are

01:05:00good

01:05:00enough

01:05:00to

01:05:00put

01:05:01Filipino

01:05:02accents

01:05:02now

01:05:03there's

01:05:04a divide

01:05:04pa

01:05:04rin

01:05:05AI

01:05:06is

01:05:06good

01:05:07at

01:05:07English

01:05:08with

01:05:08Filipino

01:05:08accent

01:05:09it's

01:05:09okay

01:05:10in

01:05:11Filipino

01:05:12and

01:05:12in

01:05:12Cebuano

01:05:13it

01:05:13can

01:05:13do

01:05:14Cebuano

01:05:14but

01:05:15what

01:05:15about

01:05:15Waray

01:05:16or

01:05:17Bicolano

01:05:18or

01:05:18Ilongo

01:05:18and

01:05:19the

01:05:20BARM

01:05:20right

01:05:21and

01:05:21you

01:05:21can't

01:05:22use

01:05:22AI

01:05:22to

01:05:23transcribe

01:05:23interviews

01:05:24in

01:05:24the

01:05:24BARM

01:05:25where

01:05:25there's

01:05:26so

01:05:26much

01:05:27data

01:05:27that

01:05:28needs

01:05:28to

01:05:28be

01:05:28collected

01:05:29in

01:05:29Muslim

01:05:30Mindanao

01:05:30Muslim

01:05:31Mindanao

01:05:32they're

01:05:33behind

01:05:34in

01:05:34all

01:05:34metrics

01:05:35of

01:05:35human

01:05:35development

01:05:36so

01:05:37we

01:05:37need

01:05:37to

01:05:38spend

01:05:38more

01:05:38time

01:05:39there

01:05:39but

01:05:40we

01:05:40can't

01:05:40use

01:05:40AI

01:05:41tools

01:05:41suddenly

01:05:42they're

01:05:42not

01:05:42as

01:05:43effective

01:05:43we

01:05:44can't

01:05:44use

01:05:44it

01:05:45for

01:05:45transcription

01:05:45so

01:05:46we

01:05:47use

01:05:47we

01:05:48need

01:05:48more

01:05:49time

01:05:49to

01:05:49do

01:05:50the

01:05:50work

01:05:50there

01:05:51and

01:05:51so

01:05:51that's

01:05:52where

01:05:52we

01:05:52call

01:05:53digital

01:05:54divide

01:05:55AI

01:05:56can

01:05:57also

01:05:57widen

01:05:58that

01:05:58kind

01:05:59of

01:05:59divide

01:05:59you

01:06:00know

01:06:00we

01:06:00have

01:06:01to

01:06:01wind

01:06:01down

01:06:01now

01:06:01you

01:06:02you've

01:06:02been

01:06:02such a

01:06:02sharp

01:06:03and

01:06:03articulate

01:06:04audience

01:06:04thank you

01:06:07so much

01:06:11thank you

01:06:12so much

01:06:12for

01:06:12the

01:06:13terrific

01:06:13insights

01:06:14and

01:06:14the

01:06:14service

01:06:15that

01:06:15you're

01:06:15doing

01:06:16to

01:06:16prepare

01:06:16society

01:06:17for

01:06:17the

01:06:17age

01:06:18of

01:06:18AI

01:06:18thank

01:06:19you

01:06:19J.

01:06:20Mark

01:06:20thank

01:06:20you

01:06:20Howie

01:06:21and

01:06:21thank

01:06:21you

01:06:21everyone

01:06:22for

01:06:22having

01:06:22me

01:06:22here

01:06:24okay

01:06:25let's

01:06:25to

01:06:26the

01:06:28long

01:06:28attention

01:06:29span

01:06:29life

01:06:30and

01:06:30remember

01:06:31forever

01:06:49you

01:06:50you

01:06:51you

AI Uncovered — From Newsroom to Classroom and Beyond | The Howie Severino Podcast

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