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AI, News, and the State: Reinstitutionalising Journalism in Global China’s Algorithmic Age: A conversation with Dr. Joanne Kuai
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- [00:01]
A
Welcome to the New Books Network. This is the Nordic Asia Podcast.
- [00:14]
B
Welcome to the Nordic Asia Podcast, a collaboration sharing expertise on Asia across the Nordic region. My name is Ao Ning and I'm a PhD student at the center for east and Southeast Asian Studies at Lund University in Sweden. Today it's my pleasure to welcome Dr. Joanne Kwai from the Royal Melbourne Institute of Technology. She is a Research Fellow in the School of Media and Communication at Armit University and holds a PhD from Costa University in Sweden. Her research focuses on digital journalism, the social implications of automation and algorithms, and the governance of data and AI. Her work has been published in leading journals including telecommunications Policy, digital journalism and new Media and society. Before entering academia, she worked as a reporter, editor and news anchor in China. She's also a longtime contributor to the New Books Network and an old friend of our channel. Thank you very much, Joanne, for joining me today to talk about your recent studies on journalism in in the age of AI in China and across the world.
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A
Thank you very much for having me.
- [01:25]
B
Okay, so let's start at the very beginning. Could you share the story behind your project titled AI News and the Reinstitutionalizing Journalism in Global China's Algorithmic Age? What sparked the idea and what drew you to explore how AI journalism and state influence intersect in today's media landscape?
- [01:47]
A
So. So this PhD dissertation project of mine examines how AI technologies are reshaping journalism as an institution, focusing on China, but also drawing comparative insights from Europe and us. The project itself actually began from a very personal existential crisis dated back to 2017, when there were a lot of discussions around how to be human in the age of artificial intelligence. And there were a lot of newsrooms at that time when I was doing my master's degree in the uk, visiting all these newsrooms, talking about how they want to leverage the power of data and AI. So as someone who has previously worked as a journalist, journalism became my way of exploring the topic of AI, the disruption of AI, and how to be human in the age of AI. So at first I thought I was just studying how AI was changing journalism, changing the journalistic routines, practices and the role of journalists. But the deeper I went, especially in the Chinese context, it becomes very clear that the state also plays a decisive role. It's no surprising when it comes to journalism, but also how the artificial intelligence itself, the technology, has been developed, adopted and used in China. So my research also evolved into an inquiry about the co construction on how journalism, technology and the state are intertwined in shaping each other. So AI, I also come to realize, isn't just a set of neutral tools or set of algorithms. It's also this socio technical phenomenon that reflects and reinforces particular power dynamics, especially in the context where the state and tech companies are deeply embedded in each other's institutional log.
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B
So let's dive a little bit into your project. For this study you did textual analysis of journalists news coverage on AI and also interviewed a number of journalists about their opinions of AI. Can you tell us a little bit more about your findings there?
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A
Yes. So in the study of the textual analysis, me and my collaborators examined how Chinese journalists report on AI and algorithmic systems, particularly in stories where we would consider as critical journalism or investigative reporting. So the findings have shown that contrary to the stereotype that Chinese journalists merely act as this party mouthpiece, we find that they are also striving to fulfill their watchdog role and the civic role within the political constraints. So a great example here is the People's Magazine's investigative reporting on food delivery platforms and how this algorithmic system has exploited economy workers. So the reporting itself has actually led to national policy discussion and eventually some improvement in the workers welfare algorithmic design. So the same time the journalist actually has been less critical when it comes to the AI systems developed by the state. You can see that within this restricted meeting environment, the many platform they're they the journalists, they have to play this very dual and delicate role. So they are the loyal facilitator of the state goal while attempting to expose risks and injustice in the private sector, in the technological sector. So in doing so they often had to position the state as a responsible custodian of the technological progress.
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B
And I'm also like particularly curious about whether there are significant differences among news practitioner working with different formats because you interview them and they all work in different sectors, like TV sectors, radio, newspaper, and also whether AI technologies have similar effects on both journalists working in larger organizations and freelancers.
- [06:06]
A
So these insights came from my field work that took place last year 2024. I would say that the differences aren't much about the format, say TV versus the print, but more about the institutional capacity and the resources that they have where the journalist has been working. Large news organizations often have the infrastructure to adopt AI. They can invest in developing the AI technologies, they have dedicated R and T teams and they even have training programs and sometimes even internal guidelines on how to use AI for the news workers. So their staff tend to be more confident and even positive towards AI. And partly because they also have to align with the national Discourse about China wanting to be this AI superpower globally. And this has been set in the China's national strategy since 2017. So the smaller newsrooms by contrast, they tend to be more cautious and skeptical because they see the potential of AI, but they don't have the capacity to implement it in a meaningful way. And they are very much aware of this discrepancy and this inequality. And the freelancers, I would say are the most wary group. And this is also makes sense because their main concern, it comes to the copyright and authorship. So whether it's automated production like AI generated news or AI assisted content distribution, they really blurs the idea of like authorship ownership and content distribution. So the freelancers here, they really risk losing both the recognition and their income. So they are the group that's mostly fearful of this or worried about this technological development. And I will also say that because I was asked before, like whether the journalist individuals show some differences when it comes to gender, which I didn't really observe. But interestingly, in contrary to the Western counterparts, that sometimes you would think the younger generations of journalists are more open towards technology in the Chinese context, actually the senior journalists are more enthusiastic about AI than their younger peers. I think it's partly because they're in the, a lot of times the more senior positions or in the leadership roles in the news organizations, so they must engage with this top down AI national strategies. So younger journalists in the meanwhile often express more skepticisms and concerns about this, like ethical implications of AI, the technological limitations and the labor implications.
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B
Yes, very surprising because before reading your research, I also thought the freelancers might have some different, quite critical opinions about the like the state policy and also AI at that time. I think that perhaps because they are independent reporters and news practitioners, they might be able to be more open to this kind of technology. But as you mentioned, they are actually not. They feel quite sort of insecure in this new age of AI. Very fascinating.
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A
In the Chinese context, I would say freelance journalist doesn't mean or doesn't equal independent journalists. Freelance is more like a status of their employment, which means their freelance can be more, the employment status can be more precarious. And they are also writing for these bigger news organizations. Like those magazines can be state owned, so doesn't necessarily mean they have higher autonomy when it comes to the topic they choose. And they're at very much a more precarious and disadvantaged position. Some of them choose to be like that, but sometimes it's not up to them. Right.
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B
You mentioned that you also interviewed some researchers in AI research institutes and technologists in journalism innovation. But this part was not actually included in your project. I was wondering if you can share that, if they share any particular insights that are markedly different from news practitioners.
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A
So the technologists and the researchers I spoke to were generally less concerned about these editorial or ethical issues that worry the journalists. For instance, when discussing AI written articles or automated journalism, the engineers who developed the technology actually said, I don't care if we put a byline to indicate this piece of news is written by a robot or a human, because readers come here to our website for the contents, not for the byline. So they didn't address any kind of editorial ethical concerns. And their focus is more on the technical efficiency and innovation. So they don't question when it comes to authorship, transparency or even editorial independence. They operate within a system where technology development is more considered inherently positive and also politically supported. So the concerns about e.g. algorithmic bias, AI accountability or surveillance that we often hear in the Western debates, I would say are less pronounced in the Chinese context.
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B
Very interesting because I thought they might have some self reflection on this whole system. But they are actually sort of, this particular group of people benefit from this development. So they are more like immersed in this environment.
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A
So that links to the article I just mentioned, right? The people's magazine's article, the title of the article is actually called Trapped in the System. So a lot of times these engineers, technologists, they are also trapped in the system which was described in the article itself. So sometimes they are either trapped in this day to day workflow that they didn't have the time or capacity to think about these issues, or they are also very much caught up in this discourse of innovation. So they are also chasing this what we call like bright and shiny syndrome. But I have to say my data set around these interviews around technologists are. I didn't systematically process them or it's not enough to draw any generalizable conclusions. So this is just anecdotally what I could share.
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B
Hmm, yes. So let's redirect our attention from individual practitioners to the larger picture. I have to say that my main source of news are social media and news articles posted on social media. But from a researcher's perspective, what is the current landscape of news distribution like in China and who are actually the main actors in this ecosystem of China's news distribution?
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A
So this directly relates to the third article in my article based compilation thesis where we studied the algorithmic news distribution market in China and that study actually dated back to 2021, even though it took a long time to be published. But the most notable change at that time wasn't so much about how news was produced, but how it was distributed and consumed. And so it's very much related to even the audience side. So we say in China or even globally, audience no longer seek out information, but instead the information had to seek out people. So news consumption has very much shifted from the traditional outlets like newspapers or TV to this multi platform ecosystem. Before the journalists, they would talk about what we say like, like two way, one app. So that means like WeChat and Weibo and their own app. So news organizations will concentrate on distributing news on these kind of platforms. And now they also have to evolve into what they call nowadays like Quan Juan, which means like all media metrics. And this include a lot of this multi platform ecosystem, including like Toutiao, the news aggregator, Douyin, the news video sharing app, or Xiaohongshu, this type of social media and a lot of other platforms. So news organizations have to adapt to this new reality and tailoring their presence to different platforms and a lot of times their targeted audience. So the key actors here are not just media organizations or the audience, but also the tech platforms because they act as the distributors and creators and they are shaping how information gets their visibility, so effectively becoming this meta gatekeeper in the hybrid media ecosystem.
- [15:32]
B
Another question is that what roles does AI actually play for different actors in this ecosystem that you just described? And what roles do tech companies play in reinstitutionalizing journalism and AI?
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A
Yes, so I talk about reinstitutionalizing journalism. It's also counter the narrative, what we hear a lot in the world west about the deinstitutionalization of journalism. So when I talk about reinstitutionalization, I mean the process through which journalism adapts its norms, rules and legitimacy under this new technological and political arrangements. So AI is very much central to this reconfiguration. And in China especially, instead of this breakdown of journalistic authority, we see this recalibration. So journalists, media organizations and the state, they're integrating AI in the way that align with what the state defined boundaries of legitimacy. In the meantime, the tech companies, they are actually deeply embedded, politically embedded actors. So they are both engines of innovation in the journalistic context and even like a tool of. So I talked about automating governance when you're using AI to implement that. So to give you one example, in the journalist context we also have this automated content moderation, what they call like content risk management in The Chinese context, the journalists, they really welcome this kind of AI systems or these like tools, they're powered by machine learning algorithm or computer vision that they help to flag in the textual contents, the banned keywords, the censored keywords, and when it comes to, you know, broadcast images, the computers can easily tell you who's who. So the censored celebrities, those disgraced celebrities, or even corrupted officials, they're banned to appear on like, you know, news programs or even all these like political sensitive topics. Right. So this task, actually it's very hard to track manually because this list of banned people or words, they just keep updating. So the journalists and the editors I talk to, they say, oh, this tool really saved us our lives. Because sometimes when you have one frame or maybe a shot of three seconds of 100 people, you wouldn't be able to tell any one of these political officials. They could be already sacked or banned. And the machines were able to tell. So this means that these tools are reinforcing the institutional logic of the state. So over what counts as this like safe journalism or like this, like politically aligned journalism, they have journalism that way. So AI in this case is not just replacing, they are not replacing the journalistic institution, but you reconfigure them to align with the technological development advancement, with the political authority. So the result is a form of journalism in the Chinese context that is politically compatible and technologically enhanced, but also institutionally controlled.
- [19:02]
B
Yes, very fascinating. And I think as a Chinese web user, we all have that experience of being somehow censored. So moving on to our next question, since tech companies initiate and still largely dominate AI development, we hear lots of talks about the necessity of AI regulation. And also recently, the co founder of OpenAI also talked a lot about safe superintelligence. But there is also this kind of looming fear of losing in this competition that is manifesting both tech companies and also nation states. So I was wondering, what is the current situation regarding AI regulation, legal frameworks adopted and developed by both state and corporate actors? Because in your research, you actually did a comparative project regarding AI regulation and framework.
- [19:57]
A
So comparatively speaking, I would say China actually has been quite proactive in formalizing AI governance and regulations. So it introduced regulation on algorithmic recommendation as early as 2021. And they also launched a regulation on deep synthesized content or deepfakes in 2022 and on generative AI services in 2023. So they are also deliberating on a more comprehensive regulation on regulating AI in general. So in comparison, the European Union's artificial Intelligence act, which takes a very comprehensive and risk based approach was finalized only in 2024. So the Chinese approach can be considered as more experimental and piecemeal. So you regulate specific technologies as they emerge. But that's what I would consider smart of the Chinese authorities because you don't know what you don't know. So what's fascinating about this regulation as they are really doubling the data gathering effort, right? So the companies are required to disclose the technical details about their systems, the data they have to collect, the algorithmic architecture that they have to use in these systems, which helps the state to understand the AI development and in order to shape it. I would say in contrast the US approach so far has remained still largely market driven and rely on the sector to basically to do self regulation and often justified in terms of global competition, especially when it comes to the so called US China rivalry. So you know in the book that we previously discussed, Karen ho's empire of AI that has a focus on OpenAI, they also made an argument of like AI can just be whatever this like tech, Silicon Valley tech bros want them to be like one is want to justify the investment is this US China AI rivalry. But when it's like trying to court the Congress, they will say oh it's about citizen welfare, it's about regulation. So this competitive framing of the fear of the losing AI race can sometimes really sideline the broader questions about equities and safeties and AI accountability.
- [22:27]
B
I realized that you also focus particularly on Chinese copyright law and its impact on AI innovation. Can you tell us more about what you found there?
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A
Yes. So I got interested in the case of Chinese copyright law because when I started a project around 2020, there was a case where a Chinese court ruled in favor of like copyright protection of AI generated news. It was a course based in Nanshan district in Shenzhen, ruling favor of Tencent, one of Tang, China's tech giants news writing blog, Dream Writer. And it was considered one of the first cases in the world where AI generated content has been granted copyright protection. And that was the time where China was also revising its amending its copyright law. So we find out like first a case study on just the Chinese copyright law, how China's copyright framework has taken relatively progressive stance by recognizing that AI generated content can be protected but not granting authorship or acknowledging authorship to the machine itself. So this benefits the tech firms and the state backed innovation agenda. But this also comes in the detriment of journalists and especially the smaller media organizations who don't have the leverage and power to negotiate deals or who doesn't have leverage over their own creative work. So later on I was also interested in what's going on globally and I conducted this like comparative study which I've come to find out that in the eu, copyright reform has been slower and more fragmented and well, it is being framed as more human centered. It still tends to protect those larger corporate interests over smaller players. In the US so far we witnessed more of policy silence. So across this context we see that the laws about AI and copyright, they're not neutral, they really embody the political and economic priorities in each of these contexts. So in a way, the copyright law doesn't just regulate this creative work, it really shapes who gets to speak and be recognized as an author in the AI age. So the question I ask in this part of the research is also whose interests are written into these laws and whose are being left out? Because in this research it really shows that copyright policymaking not only affects the dynamics within the newsroom, but it also has implications for the distribution of power in the whole media ecosystem. So it is not only affecting who is decided as the author, but also where the normative ideals of AI are being reimagined and it can inform and create or constrain the conditions of technological development. So it really has to question what is copyright, even the rhetoric of copyright. And it shouldn't be regarded as this incontestable God given right. So what copyright law says and how copyright operates, it's a lot of times as we see now, are defined by this large corporate state and whoever has the upper hand in this ecosystem. So I was also making an argument with the whole dissertation about institutionalization of algorithms and AI and this institutionalist view really also require us to consider the legal, social, political, economic and cultural foundations of the values and norms so that direct conditions for constructing these algorithms as these institutions. And I believe this is very important because I think all powers should be held accountable, whether it is political, economic, governmental or algorithmic. And I want to also make the argument about the centrality of human. And it is important to consider human not only because it allows us human to really unleash the potential, the creativity, and it also really facilitates the establishment, the chain of accountability, because there shouldn't be any rights without responsibilities. And putting human there really helps to establish this chain of accountability.
- [27:04]
B
So after listening to what you've just said, I think that AI, as this technological innovation and this great power now playing in the world, it's actually like you argued, not only shaping just the journalist Sphere, but also sort of reinstitutionalizing anything that is related to this technology and also sort of spread its influence more extensively, even pocus to think about not only actually copyright law, but the whole legal framework surrounding any kind of new technology. So that's really fascinating.
- [27:42]
A
Yeah. And there is also this discourse going on about artificial general intelligence. So when AI actually surpass human intelligence. I personally don't think it is coming anytime soon. But with this dissertation project, it teased my personal exercise into thinking how to be human in the age of AI. But also invitation for everybody to join me into thinking about this question. And to be honest, I've been digging into this topic for years. And in most recently in the past few years, especially since the launch of ChatGPT and also after Deep Seek, the discourse has shifted a lot. And I see some positive signs because before, maybe not that many people or only people have like more tech savvy mind they will care about the topic of AI, but now we see more and more people like they have encountered this technology and then really prompt them into thinking, what is my relationship with the technology? What is my relationship with other human being mediated by this technology? And what does it mean to my role as a human, as like a worker? And even some of the other bigger questions. So I see this growing discussion and debates around AI a very positive side. Now there are also people thinking about what is a critical thinking. If I use generative AI tools, when I gave guest lectures to students, they would ask me these kind of questions. And I think by asking this question, they are already applying critical thinking when it comes to AI, generative AI or any other technological development. So I wanted to leave it at quite a positive note when it comes to that.
- [29:29]
B
Yeah, yeah, yeah, definitely. And I also noticed you collaborate quite a lot when you're doing this research. What was it like working with so many scholars with diverse background and knowledge?
- [29:42]
A
So I feel incredibly fortunate to have the opportunity to collaborate with many brilliant scholars from many different countries and disciplines. And it's been a very intellectually stimulating but also humbling experience. So each collaboration, you know, they bring fresh perspectives and different ways of thinking. Sometimes it can be challenging, but it's always a very enriching experience. So it also taught me to be more flexible and actually more forgiving, both towards other people, but also to myself, because sometimes I'm at the point of failure too. As we all know, research can be very demanding work and our line of work just doesn't have a natural stopping point. And this collaboration can really reminds us that the kindness and care are essential to as part of this academic life. So we have to lift each other up through this shared curiosity and to make it sustainable. So this is a collective learning process and I feel very fortunate to have the opportunity and also very proud to be part of this community of knowledge production.
- [31:00]
B
And I'd like to end our conversation with some recommendations from you because in this project you covered like both on individual level, on organizational actors and also tech companies level and also like legal more copyright related research. And what should we read more if we want to educate ourselves more about AI and its social and technological implications.
- [31:26]
A
I will first just shamelessly plug my own research. This PhD project, the dissertation itself is publicly online, it's open access because there are some questions I wasn't able to elaborate much and it's an article based dissertation but I also wrote like over a hundred pages of what we call Kappa in the Swedish context. So like a comprehensive introduction thing to side thing. My contribution which I am now on also thinking about turning them into a book project. So yeah, keep look out for that. But if I were to recommend one book that really tackles the blind spots of how law and policy shape the information economy, I will be recommending Julie Cohen's Between Truth and Power, the Legal Constructions of Informational Capitalism. I took a lot of inspiration from that work. And for those who want to keep up with this very fast changing intersections of technology, business and geopolitics, especially between like us, China, I would recommend Kevin Xu's bilingual newsletter, the Interconnected. So I subscribe to it and it's a really good newsletter that really tackles this intersection with like a lot of great insights. And beyond that I will recommend a few culture works that I really enjoy. So first of all, Ghost in the shell, not the 2017 Hollywood movie, but the original 1995 anime. Okay. Like the Japanese anime Ghost in the Shell that really explores the identity and the consciousness in this like cybernetic world. And also the video game Detroit Become Human. I don't know if there's any like gamers among our listeners. So in this game Detroit Human, you get to play the playable characters as androids. So both these works really raise a lot of questions for me and make me keep thinking about human machine relationships and also how to be human in the age of AI.
- [33:34]
B
Thank you for your recommendations and thank you so much for joining us today. Joanne.
- [33:38]
A
Thank you so much. Ning, it's really good to see you and thank you so much for having.
- [33:42]
B
Me to our listeners. Be sure to follow Joanne and explore her work through Armet University, research gate and LinkedIn. We will include all the links in the show notes below. If you enjoy this episode, don't forget to subscribe and stay tuned for more conversations like this. Thank you for listening to the Nordic Asia Podcast showcasing Nordic collaboration in studying Asia.
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A
You have been listening to the Nordic Asia Podcast. Sam.