Yolanda Ma from the University of Hong Kong on making AI training mandatory in journalism education

In this episode of Splice Pink, we speak with Yolanda Ma, a lecturer at the Journalism and Media Studies Centre at the University of Hong Kong. ChatGPT describes her as “an influential figure in the fields of digital policy and global partnerships.” We agree.

Yolanda has a vast career in international development, data, and journalism, and recently won approval to make AI training a mandatory subject for the masters program in journalism. In this podcast, she talks about why she pushed for it, and what's needed in journalism education today.

Connect with Yolanda on LinkedIn

Find out more about the journalism program at the University of Hong Kong

The transcript

This audio recording was transcribed by Whisper. These tools can make mistakes, especially when adjusting for and paraphrasing spoken words. Check important information against the actual podcast.

Alan: Hello, this is Splice Pink. This is a podcast of quick conversations with people around the global media ecosystem. Now we’ve spoken with media startup founders, journalists and funders to all the tech data and design folks. I’m Alan.

Rishad: And I’m Rishad — and we also speak to university lecturers. Today we’re talking to Yolanda Ma who teaches a course on media technology and society at the University of Hong Kong. Hey, Yolanda.

Yolanda: Hello. Hi, Rishad. Hi, Alan. Thank you for having me here.

Rishad: Thank you for turning up. I have a burning question for you. You did an amazing thing recently. You convinced your university leadership to do two things and you can tell we’re very excited about this. The first one was you convinced them to start a new course on AI. And you also convinced them to make this mandatory. Tell us about your thinking behind this.

Yolanda: Actually, these two things are one thing, but thank you for making it sound like a big thing. But this is actually easier than I thought. You know, I thought making an AI course is already difficult, especially given that I’m not from an AI background. I can talk more about that later. But also making that mandatory for all the incoming master of journalism students. And this is not a computer science school, right? It’s a journalism school. Why are we making that compulsory? That actually turns out to be easier than I thought. There have been some concerns, which I can elaborate later. But things just got the discussion went literally like 20 minutes. And that’s it. And we just figured out, okay, we’ll make it. And then we went for the administrative kind of approvals, which, you know, universities, we need to do some of that. And then I think.

Alan: Were you surprised at how quickly this went?

Yolanda: Let me put it this way. I would expect like a few weeks for some proper discussions for, you know, consultations. And I was expecting some pushbacks, right? I was expecting or not even pushback, not necessarily pushbacks, but at least questions. But we had like an all-instructor meeting recently where I kind of announced that that’s already after the leadership kind of given endorsement, right? So I announced that. But I was expecting questions from the other instructors, especially those who are not necessarily very familiar with AI. I didn’t get any questions like zero. Everyone’s like nodding. So I was, oh, that’s actually surprising. But like great surprise, like good surprise.

Alan: What was the hardest question you were anticipating?

Yolanda: I think the hardest question I was anticipating was like, will AI stay? Like, is it just another buzzword? Like some other technologies come and go, right? Because that’s something like we like, you know, I started working on data journalism a decade ago. At that time, you know, we had similar kind of questions, you know, is data something that’s going to stay? Do we need to set up teams in the newsrooms? You know, even before data, there was social media. Like, remember those days when the media didn’t even have any social media accounts, right? I mean, things come in waves. So I think I was kind of expecting questions around, you know, is AI going to stay or not? And that’s a question. Like, you know, it’s not a question I have a 100% convincing answer to, right? Maybe in a few years, it will become something different. Like, I’m not going to say AI is going to disappear. It’s already embedded in so much of our lives, not just in journalism. But how big an impact it’s going to have on the journalism industry, that’s something I think everyone’s still trying to figure out. So I’m trying to make an argument. Well, I don’t have a 100% clear answer. So that’s something I was anticipating. There might be a challenging conversation. But it turns out that question just came as like quick administrative question when people were thinking about how we name the course. Because they don’t want to change it every six months.

Rishad: So I’m curious, you’ve told us, you know, you’ve told us what the question was, you’ve told us that you did this, you know, you, you, you suggested the course. I’m more curious about why you think it’s mandatory. What is your thinking around that? Why, why are you so convinced that this is something that journalists or journalism students don’t have an option about? That they have to know how to use AI. I’m very curious about that.

Yolanda: And my thinking also has been changing a lot in the past few months. Let me put it that way. And I think there are three kind of stages. Rishad, when you introduced me, you already mentioned that I’m already teaching a course on media technology and society. Where in that course, I already went through topics like AI, which was one class of the 12-week course, fake news, algorithm bias, future of journalists. I already covered those topics in the current course. And somewhere halfway into the semester, I started to realize that the students are eager to learn more about AI. So they are already on it, like before we even ready to teach, right? So for example, they need to do a mini case study of their own choice and my students already working on things like how newsrooms are leveraging AI. So they want to know, right? And secondly, there was already an AI course in the journalism school, actually, which is not mandatory, which is an elective course. They use generative AI for visual storytelling, for filmmaking, and the students are already using tools like ChatGPT, mid-journey to generate like text, image, video kind of things. And actually, they already went into a student film festival, so it’s like very good feedback. So I think that gave me and also other teachers like really confidence in terms of students wanted and students love it, right? And then thirdly, what kind of starts really make me think, and your question is about not just why AI, but why mandatory, right? Is I keep thinking in the past few weeks, also in discussion with the leadership, as we prepare for the next academic year, what does our students or, and this is a master of journalism program, right? So this is preparing practitioners and HKU journalism school is very practitioner driven. So we’re not like work on communication theories, like that’s not our cup of tea. So we are preparing our students for industry. So the question is, what, what does the future journalism practitioners need? And it’s not even a far future. This is like three to five years.

So if AI is already changing the industry, then you need to make sure [the students] are, if not five steps ahead of time, at least like one step ahead of the time, right? So that is really driving my thinking and some of other colleagues here.

Alan: You know, as you said, you’ve been spending well, quite a bit of time thinking about this, right? Since you, you were doing, you know, data journalism back in the day. Right. This is just an extension of some of that, I guess. Now you’ve been at the University of Hong Kong for about five months, six months, right?

Yolanda: And before that you were at UNDP for about six years?

Yolanda: Actually, nine years.

Alan: Nine years, okay.

Yolanda: Almost too long.

Alan: Your LinkedIn profile is lying then. How much of this was, was an idea that you were thinking about even back then, you know, at UNDP? Surely, you know, yeah, you were probably thinking, how do we use this? Where’s all this going? You know, what, what was that like for you?

Yolanda: Yeah. Thanks for that question. That’s interesting. I didn’t do a personal reflection on that yet. So this is a great opportunity. The, I think for, so for, for, for those who are listening, I spent nine years in UNDP, which is United Nations Development Program, where I spent a couple of years on social innovation, a couple of years on impact investment, but for the past four years, I’ve been working on digital transformation at the national level. So I actually worked on cases like countries’ AI policy. How do they prepare for their country? Like at the central level for emerging technologies, right? So that is a very high level digital thinking and policy design. And that is a great learning and practice for me. It’s really valuable because I get to really look at things from a very holistic and top-down perspective. You know, what does a country really need? So like, for example, we also worked on key issues like information integrity, which is very relevant to all of us, right? So because UNDP worked on 70 countries every year on their elections. So like election misinformation is a huge issue. So things like that really give me a chance to really look into these real country issues and how emerging technologies such as AI can really help.

So, and how does ecosystem come together? Splice work on media ecosystem. So, you know, you know, probably too much about ecosystem. But in many cases, many of us are just thinking in our small industry or our specific discipline. Oh, we don’t think about things from that ecosystem perspective. So even coming back here, that experience really helped me to think through things through that very holistic lens. For example, when I teach students about algorithm bias, I wouldn’t say it’s all big tech’s fault, right? It has, you need to think about the regulations. You need to think about users, media or online literacy. You need to think about, you know, those who are offline. You need to think about so many different things and how you put things together. Now coming back to this AI course, I think now it gives me opportunity to kind of drill down into a focus to see how a smaller ecosystem works, right? And how a specific technology works for this ecosystem. So I’m really excited about this opportunity. And I’m actually looking forward to co-shaping the learning with my students because they sometimes know better than I do, you know, through my experience in the limited five months that I worked with them.

Rishad: Would you ever take this beyond journalism? How do you, would you, would you make AI or learning AI or working with AI? Would you take, would you teach it to students who are not in your journalism school?

Yolanda: Yeah, that’s a great question. I’m already thinking about it. Haven’t talked to my boss yet. But, but University of Hong Kong is actually having some discussions internally and the decision has already been made about making AI compulsory for all the undergrad students starting from 2025. So since it’s like one little bit more than one year from now. So now it’s more early discussions because now we made that compulsory, but we don’t have enough courses. So I actually went to it like across university, like university-wide discussion. So it’s voluntary. So anyone who’s interested can join as I went together with a couple of other colleagues from the J school. So I get a chance to really talk to other people interested parties from other faculties and departments. And it was a really interesting conversation. And the and just to clarify what will be compulsory for all the undergrad is what we call a common core course, which is like called general education. I think it’s the U.S. So it’s basically for year one or year two students, you need to do some general courses and AI will be one additional kind of stream in addition to four existing streams. Right. So and everyone is to compulsory to take one course from all the AI related courses that will be provided. And for us, any faculties or any departments, we can propose courses to be a common core course. So I’m already thinking like what kind of courses I might be able to propose or offer. And the content needs to be adjusted because then it’s like it shouldn’t be too deep into journalism. It needs to be kind of at the right level for all kind of like people from all majors basically. And, you know, for undergrad, it’s also slightly different kind of level of knowledge as well.

Alan: So when when you’re as you’re preparing all of these courses and as you’re looking outside of the university and seeing all the other programs and courses that are out there, what do you think is currently missing in this instruction, you know, space when it comes to AI? What are we missing in terms of thinking and knowledge?

Yolanda: I think what is missing? I honestly, it’s missing. I do see a little bit of a mismatch in terms of people’s understandings of AI. Some of them, but I think you probably see that in the meeting industry as well. Some of them are way optimistic and some of them are way pessimistic, right? And then the level of understanding in terms of the technical understanding is also very different, right? Some people when they come and start talking about machine learning and the technical details, you know, our lovely colleagues from Faculty of Engineering or Computer Science, well, we probably will not be able to talk at that level.

So when you talk to each other, even if you’re both talking about AI, are you talking about the same thing?

Like, you know, that is already like the first question and the first mismatch, right? So how do you do that leveling? How do you kind of make sure you’re kind of communicating in the way that each other actually understand each other and build on each other? So that’s what I think is one of the biggest issues, but things are just starting. I think everyone is trying to figure it out. And I do see there are some industry efforts starting happening like CUNY’s AI Journalism Lab. And yesterday, I joined the Pulitzer Centre’s AI Reporting series, which I think hundreds of journalists joined. So I think those efforts are super useful in terms of making sure like everyone talking about AI, we’re talking about the same thing. Or different things, which is also cool because you bring this, you know, multifactorial, multidisciplinary kind of excitement into AI, which is exactly what makes it exciting.

Alan: Right.

Yolanda: Yeah. The other thing I might add is I feel like in this part of the world, and this is more a personal observation, I feel like people don’t talk about the downsides of AI or technologies enough. When I was in New York, like I feel like algorithm bias, ethical technology, there is more discussion around that. But, you know, in the US, there’s also more specific focus like the racism, like, you know, you know, so here, I feel like that’s not talk about enough. That’s not recognized enough. So that’s something that I try to build in at least in my courses for now.

Rishad: Would you ever use AI to build a curriculum or a, you know, or help you in your courses? I, you know, I think it’s great as long as you, you know, say that that you’ve used it.

Yolanda: Yeah, I do, actually. And I even think I’m not using that enough. And, you know, I sometimes use that for the size more exercises for students. I use that like, even when I was drafting the syllabus for the existing for the upcoming course, I kind of asked ChatGPT, you know, what are the existing kind of areas I need to think about? Just help me think, right? I will not rely on it. But I think it’s good kind of thinking starter for me to kind of make sure, you know, I might kind of generate some things that I haven’t thought about. Then I might look into like, then I will do my proper research and build on that.

Rishad: Yeah. Listen, I think we’re going to wrap. Thank you so much for this, Yolanda. Super.

Yolanda: Yeah. Thank you for offering the time.

Rishad: Of course, for spending some of your afternoon with us. We’re very excited about where this is going. And of course, I’m going to volunteer us if you ever need our help.

Yolanda: Oh, yes. I need all the help and suggestions and guest speakers to call out to all your listeners. Let me know if you have any.

Alan: Yeah. Well, Splice is made up of completely non AI human beings. But if that’ll do, let us know.

Yolanda: Well, non AI human beings are the best. Thank you.

Rishad: Anyway, that’s it for this episode of Splice Pink. If you like our conversations with people across the information ecosystem and want more, please subscribe or even better, share this with someone and get in touch. We’re on splicemedia.com. Thank you, Professor Ma.

Alan: Thank you.

Yolanda: Thank you, Rishad. Thank you, Alan.

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