[ADRN Working Paper] Mapping East Asian Initiatives on AI Governance for Democracy (Part 7~11)

Media

AI is increasingly affecting the role of the media as a watchdog of power, particularly through its implications for copyright protection and the public’s right to know. However, adequate measures to ensure the sustainability of news organizations remain limited. Different challenges and responses have emerged across countries, including technological and fact-checking initiatives in Japan and regulatory gaps in the governance of new media in South Korea. Taiwan, meanwhile, has explored a different direction. After the failure of comprehensive platform regulation, legislative discussions have shifted toward a bargaining framework between news organizations and digital platforms. Yet the feasibility of this approach remains uncertain.

1. Japan

1.1. Concerns about AI

Japanese news organizations have expressed sustained concern about the impact of generative AI on copyright, business sustainability, and the public’s right to know. Statements issued by the Japan Newspaper Publishers & Editors Association since 2023 point to confusion in the information space, privacy concerns, deficiencies in existing legal frameworks, and a lack of transparency (Japan Newspaper Publishers & Editors Association 2023). The Association argues that the unauthorized use of news content in generative AI systerns threatens the economic foundations of journalism and may reduce the availability of high-quality reporting that supports democratic processes. It maintains that news content constitutes intellectual property created through significant labor and cost, and that generative AI developers and service providers should obtain authorization and provide compensation when using such content. Although recent policy discussions and interpretative guidance on copyright and AI have clarified some issues, the Association (Japan Newspaper Publishers & Editors Association 2024) considers existing protections insufficient and has called for legislative reform rather than reliance on interpretation alone.

Concerns have intensified (Japan Newspaper Publishers & Editors Association 2025) with the expansion of retrieval-augmented generation and “zero-click search,” in which users rely on AI-generated summaries without accessing original news sources. News organizations warn that such practices may reproduce articles without authorization, generate inaccurate outputs, and erode the credibility of original reporting. Litigation has followed these concerns: in August 2025, Yomiuri Shimbun (Yomiuri Shimbun 2025), followed by Nikkei and Asahi (Nikkei 2025a), filed lawsuits against Perplexity alleging copyright infringement. These cases highlight perceived gaps in copyright law and the uncertainty surrounding statutory exceptions, particularly provisions allowing certain uses without authorization.

1.2. Countermeasures and Their Limitations

Alongside legal advocacy, media organizations have pursued technical and institutional responses to protect information integrity. Many have participated in the development of OP (Originator Profile) technology[1], which embeds verified originator information into online content to strengthen traceability and authenticity. Fact-checking efforts have also expanded. In 2025, news organizations began coordinated fact-checking (Yomiuri Shimbun 2025) during elections with the cooperation of JFC, and more than 200 fact-check articles were published during the House of Councillors election in 2025 (NHK 2025).

However, empirical findings suggest limitations. Surveys indicate that a high proportion of individuals who encountered widely circulated false information during elections in 2025 (NHK 2025) and in 2026 (Jiji Press 2026) believed it to be true, and television remained a major exposure channel. This indicates that reporting on misinformation may inadvertently contribute to its wider recognition, while public trust in traditional media has been challenged in an attention-driven information environment.

The Japanese news industry frames generative AI as posing intertwined risks to copyright protection, economic sustainability, and democratic information functions. While advocating stronger legal safeguards, media organizations are also investing in authentication technologies and fact-checking initiatives. Structural challenges remain, including legal ambiguity, platform practices, and the difficulty of countering misinformation without amplifying it.

2. South Korea

2.1. Traditional Media and AI

Traditional media is actively integrating AI while striving to fulfill its public mandate of providing essential information for democracy. To uphold journalistic integrity, public and private sector entities, such as Korea Press Foundation and various press outlets, are collaboratively and individually establishing AI journalism guidelines (Kang 2024) and ethical standards. However, intensifying copyright disputes remains a critical burden. Despite the Ministry of Culture, Sports, and Tourism’s interpretation (Lim 2025) that unauthorized AI summarization constitutes infringement, the government's "use-first, compensate-later" approach has fueled significant friction (Yoo 2026). This conflict is exemplified by the collective lawsuit (Choi 2025) from the three major broadcasting companies against Naver, highlighting the struggle over the fair valuation of journalistic assets in the AI era.

2.2. The Regulatory Vacuum in New Media

Even with the AI Basic Act, a regulatory vacuum persists in the digital sphere. Current legislation (National AI Strategy Committee 2025) focuses on imposing mandates primarily on AI developers and service providers, failing to hold accountable the actual content producers, including news outlets and high-impact YouTubers, who create AI-driven narratives. This gap significantly hinders information transparency. Moreover, while global platforms bear the ability to trap citizens in a polarized environment with engagement-based algorithms exacerbating the echo chamber effect, they lack direct responsibility for the AI-generated content they distribute. Specifically, current safe harbor provisions (National Assembly 2025) allow these intermediaries to avoid proactive liability, while their limited cooperation with domestic investigations, hesitating to provide subscriber data for disinformation cases, further complicates legal efforts to identify and penalize malicious actors.

While Korea’s push for AI journalism ethics signals an institutional commitment, this integrity remains functionally hollow without the infrastructure of enforceable copyright protections, leaving traditional media to bear the disproportionate burden of maintaining high editorial standards without sufficient legal recourse. On the other hand, the regulatory gap is also prominent in new media, focusing primarily on AI developers while allowing safe harbor protections to shield platforms. Ultimately, Korea’s media governance finds itself caught between high-level ambition and structural permissiveness. Closing this divide will require a paradigm shift that extends legal and ethical accountability beyond the technology's developers to include both the platforms and the content producers themselves.

3. Taiwan

3.1. Challenges for Traditional News Media

Taiwan’s news industry has become heavily dependent on multinational digital platforms such as Google and Meta for both distribution channels and advertising revenue. In 2021, the Legislative Yuan raised concerns that large digital platforms benefit from news content without fairly sharing the resulting advertising value with news organizations, placing traditional media under growing economic pressure (Tsai et al. 2025). China Times reported that, of Taiwan’s digital advertising market, worth approximately NT$61 billion (US$1.87 billion), Google and Meta together account for NT$40–50 billion (US$1.23–1.54 billion), thereby placing significant pressure on media management (Zhuge 2025).

This pressure has been further intensified by the spread of generative AI. According to United Daily News (Yu 2026) and The Reporter (Hsieh and Chien 2026), since the introduction of Google’s AI Overview, more users have begun leaving search results pages after reading AI-generated summaries alone, and some news websites have experienced declining click-through rates. Moreover, since generative AI can learn from large volumes of news content and produce summaries, rewrites, and personalized articles, it may increasingly become a central intermediary in the circulation of news. As AI agents come to read across multiple articles and generate responses tailored to users’ requests, audiences may encounter not original reporting itself, but secondary information reconstituted by AI, thereby further destabilizing the business foundations of news organizations.

In addition, in the Excellent Journalism Electronic Newsletter (Chen 2026), Lin Yu-Pen argues that news media are increasingly compelled to adjust headlines and content formats to platform preferences in order to secure visibility. As a result, adaptation to algorithms tends to take precedence over public value and professional editorial judgment, constituting a structural constraint on media autonomy.

3.2. The Failure of Comprehensive Regulation

In response to these developments, the need for digital platform regulation has been recognized in Taiwan. In June 2022, the National Communications Commission (NCC) released a draft of the Digital Intermediary Services Act (National Communications Commission 2022), conceived as a Taiwanese counterpart to the EU’s Digital Services Act (Institute of Geoeconomics 2024), with the aim of comprehensively regulating platform accountability, transparency, and responses to illegal content. However, the draft encountered strong resistance from businesses and industry groups because of the breadth of its regulatory scope (Chohan 2022). It also triggered substantial public opposition: on JOIN[2], 38,795 users expressed opposition, compared to only 163 in support. In particular, provisions that would allow the removal of information or restriction of access generated serious concerns regarding freedom of expression. As a result, in early September 2022, the NCC suspended the legislative process and returned the draft to a working group for further review. In effect, Taiwan’s attempt to introduce a comprehensive platform regulation law came to a halt.

3.3. The Shift to Bargaining Act

Following the failure of comprehensive regulation, debate in Taiwan has increasingly shifted toward institutionalizing compensation for the use of news content. According to the Taipei Times (Shan 2025) and United Daily News (Li and Tang 2025), in 2025 the Legislative Yuan began deliberating a proposed News Media and Digital Platform Bargaining Draft Act that would require major digital platforms to negotiate with news organizations over the benefits generated by the use of news content (Lin et al. 2025). At the June 2025 public hearing on media bargaining legislation, it was confirmed that the KMT, DPP, andTPP had each submitted their own draft bills. MODA, however, adopted a cautious position, noting that such legislation could be interpreted by the United States as a trade barrier. At the same time, China Times reported that Zhuge Jun as arguing that the scope of the proposed bargaining framework should extend beyond Google and Meta to include generative AI companies as well (Zhuge 2025). Economic Daily News further reported that, as of March 2026, the government was still considering how to incorporate generative AI firms’ use of news content into a broader framework of licensing, compensation, and revenue-sharing arrangements (Yu 2026).■

[]Originator Profile Collaborative Innovation Partnership (OP-CIP), https://originator-profile.org/en-US/.

[2]Public consultation on the Draft Act on Digital Intermediary Services, National Communications Commission (NCC), Taiwan, June 29–August 29, 2022. https://join.gov.tw/policies/detail/43dbdcc4-af21-4fcb-9173-d3b5993ab88d.

Education

AI education has emerged as a key policy domain, but approaches differ across countries. Japan is promoting the use of AI in education while emphasizing literacy, critical evaluation, and responsible use, although institutional frameworks, particularly in formal education, remain under development. South Korea is advancing the digital transformation of education and places strong emphasis on inclusivity in AI education. Taiwan is institutionalizing AI education through active collaboration with civil society, integrating it into broader efforts to strengthen digital citizenship and the information environment.

1. Japan

1.1. AI in Education

AI literacy and education are positioned as key components of Japan’s response to AI-related societal risks. The National AI Basic Plan in 2025 (Cabinet Office 2025) emphasizes improving information utilization skills in primary and secondary education and supporting all citizens in developing AI literacy through demonstration projects and educational initiatives.

In primary and secondary education, policy orientation is generally supportive of AI use. The Ministry of Education, Culture, Sports, Science, and Technology issued provisional guidelines (Ministry of Education, Culture, Sports, Science and Technology 2024) on the use of generative AI in education in July 2023 and released a revised version in December 2024. The guidelines describe generative AI as a potentially useful tool and stress that outputs should be treated as reference material, with final judgment and responsibility remaining with human users after considering associated risks. Based on these guidelines, pilot projects[1] promoting the use of generative AI have been implemented since 2023, and reports were submitted by dozens of junior and senior high schools in 2024. Some schools introduced practices such as fact-checking AI-generated outputs.

Educational policy discussions also link AI literacy to democratic participation. In the review of the next national curriculum guidelines from 2030 (MEXT 2026), the discussion highlighted the need to foster individuals capable of participating in society in the digital age, taking into account the potential for social division caused by social media and generative AI. Current curricula are considered insufficient in addressing media literacy, particularly in terms of critically evaluating information, understanding its social and cultural context, and participating in digital society (MEXT 2026). Proposals have therefore been made to clarify and strengthen these elements as part of broader information technology education. Across educational stages, from primary to higher education, policy documents emphasize learning both about AI and through AI, including understanding human-centered design, recognizing errors and biases in outputs, and assessing how information influences users’ judgment and behavior.

1.2. Literacy for the General Population

Efforts also target broader age groups. Government roadmaps for improving ICT literacy highlight the need to organize knowledge on generative AI, identify priority competencies, and develop and disseminate educational content (MIC 2023). Public educational materials provide introductory guidance on the use of generative AI, including explanations of risks related to information accuracy, data leakage, intellectual property, and user responsibility[2]. Awareness-raising content also frames AI as both a source of social risk, such as the spread of disinformation, and a tool for problem-solving (Boston Consulting Group 2025). Public–private collaboration has expanded, including DIGITAL POSITIVE ACTION, launched in 2025 to improve digital literacy through cooperation among platform companies, telecommunications operators, IT firms, and related organizations[3].

However, implementations are ongoing. A government survey in 2025 found that while 87.8% of respondents considered ICT literacy important, 75.3% reported having undertaken little or no concrete action to improve it (Ministry of Internal Affairs and Communications 2025a). Comparative data also suggest weaker initial conditions in Japan. A 2023 survey comparing Japan, Korea, and the United States found that Japanese respondents were less likely to verify primary sources or check the timing of information, and awareness of key concepts related to the attention economy was significantly lower (Yomiuri Shimbun 2024).

At the same time, social conditions are rapidly changing. A 2025 survey showed that awareness and use of generative AI among elementary school students had increased substantially since 2023 (Benesse Corporation 2025). Many users reported relying on AI when they did not understand something and had experience encountering errors in AI outputs. These trends indicate growing exposure to AI at early ages and suggest the increasing importance of systernatic literacy development.

1.3. Cyber/AI Capacity-Building

In terms of education for developing cybersecurity talent, initiatives include the Cyber Defense Exercise with Recurrence (CYDER)[4] for Japanese government agencies, local governments, and critical infrastructure operators; the Security+Hackathon 365 Days (SecHack365)[5] and Security Camp[6] for fostering young security innovators; the opening of the cybersecurity exercise platform CYDERANGE to the private sector as an Open Platform (CYROP, NICT 2022); and cybersecurity capacity-building support for ASEAN countries (ASEAN-Japan Cybersecurity Capacity Building Centre: AJCCBC)[7]. Each of these initiatives has already produced hundreds of graduates, and the next challenge is finding ways to retain these talents in the AI and cybersecurity fields.

2. South Korea

2.1. Digital Transformation and AI

South Korea is promoting digital education transformation through the “High-Touch High-Tech" model (Ministry of Education 2023). AI handles personalized knowledge delivery, allowing teachers to serve as learning designers who prioritize critical thinking and emotional mentorship. This approach is reflected in the private sector. Platforms like Seoltab utilize AI (Jang 2024) to create personalized learning plans and designs centered on the student’s questioning process through non-face-to-face formats. However, this transition has faced social friction regarding the role of educators. A notable controversy involving Gyeonggi Province’s "Hi-Learning" platform, where promotional material depicted AI as superior to teachers and described their words as empty, sparked a significant backlash from teachers’ unions, eventually leading to a public apology (Jin 2025).

2.2. Universal AI Literacy and Inclusiveness

Through the "AI for All" initiative (Ministry of Education 2025), Korea ensures that all citizens, from youth to seniors, can acquire AI as a basic civic literacy. To centralize these efforts, the Ministry of Education established the "AI Talent Support Bureau" (Ministry of Education 2025) in late 2025 to oversee the whole lifetime AI competency across all educational stages. This national framework is localized through targeted welfare projects. Busan provides AI-based smart learning and emotional support for vulnerable children (Smart City Korea 2022). Similarly, initiatives such as "Digital Competency Centers"[8] are expanding to offer digital literacy programs, and recently especially encompassing AI literacy. In parallel, public-led initiatives such as "Seoul AI Edutech,"[9] operated by the Seoul AI Foundation, are intensifying their focus on bridging the digital divide for the elderly and marginalized groups. By tailoring technology to specific vulnerable demographics, Korea is working to bridge the digital divide across all generations.

With Korea's private tutoring market surging to nearly 30 trillion won (Ministry of Education and Statistics Korea 2025) and high-income households spending five times more than those at the bottom (Lee 2023), AI risks becoming a premium advantage that well-resourced families enjoy first, potentially widening the gap it aims to close. Yet, the same technology holds genuine promise as an equalizer. If deployed with serious infrastructure investment, personalized AI tools could be the most effective way to deliver quality education to students in rural and underserved areas. Ultimately, whether AI becomes a structural barrier or a ladder for social mobility will depend entirely on how boldly Korea addresses the underlying inequalities of its educational landscape.

3. Taiwan

3.1. National Strategy and the Positioning of AI Education

In Taiwan’s AI New Ten Major Infrastructure Projects Plan (National Development Council 2026), the section on “Digital Foundations” states that AI education should begin in elementary and junior high school, continue in senior high school, expand into interdisciplinary learning in universities and technical colleges, support the cultivation of industry-ready talent, and improve AI literacy and usage capacity among the wider public. Thus, in Taiwan, AI education is framed not simply as part of schooling, but as a broader talent ecosystern linked to industrial competitiveness and societal capacity-building.

3.2. School Education

The Ministry of Education has introduced age-specific materials for the generative AI era (Department of Information and Technology Education 2026). Learning with AI encourages upper elementary students to use generative AI as a learning aid through questioning, revision, and self-evaluation (Ministry of Education 2025), while Harnessing AI, Seeing the Future: A Required Course for Digital Citizens helps secondary students develop responsible digital citizenship through topics such as information verification, media literacy, intellectual property, privacy, and safety (Ministry of Education 2025). These efforts are reinforced by the Curriculum Guidelines of 12-Year Basic Education (National Academy for Educational Research 2018), which embed AI-era competencies in formal education: junior high students learn computational thinking and problem-solving through programming, data, and networks, together with digital ethics and security, while senior high students are introduced to big data, data mining, and machine learning.

In addition, Taiwan emphasizes digital competence as well as digital literacy. Audrey Tang emphasizes that learners should be not only receivers of information but also producers of knowledge, highlighting source verification and fact-checking as practical skills[10]. In this view, digital education is not merely technical training but a reciprocal form of learning in which students engage with society and contribute knowledge back to it. A related initiative is the T Ambassador Training Program, a practice-based scheme for university and junior college students and other eligible young people (Small and Medium Enterprise adrninistration 2020). It combines online coursework and hands-on training, while supporting the digital transformation of small and micro enterprises, and provides stipends and certificates to participants.

3.3. Civil Society Initiatives in Schools and Communities

In Taiwan, AI and information literacy education extends beyond formal schooling and is also pursued through collaboration with civil society. For example, TFC[11] has also advanced information literacy beyond formal schooling by linking media education with digital inclusion. Its initiatives include workshops in schools and local communities (Ho 2022) on fact-checking tools and verification practices, as well as training mobile-phone instructors who support older adults (Wu 2022). The IORG[12] has translated research-based approaches to information literacy into practice through cooperation with educators and civic actors. Its activities include teacher training, student lectures, teacher–student co-creation workshops, and collaboration with community workers, including those in outlying island regions. It has also published A Guide to Information Literacy, a practical resource designed for educational use (IORG 2022).

Taken together, these initiatives suggest that information literacy in Taiwan is being developed through a layered and socially embedded ecosystern that extends across schools, communities, and civil society organizations.

3.4. Limits of Current Literacy Approaches

At the same time, some argue that the current scope of literacy education remains insufficient. In an interview, Chihhao Yu[13] of IORG emphasized that, beyond technical skills, it is crucial to cultivate the capacity to discuss politics with peers in ways that are informed, respectful, and resilient to manipulation. Tim Niven[14] of DoubleThink Lab and Summer Chen[15] of FactLink similarly emphasized that education should focus not only on debunking individual stories or claims, but also on helping citizens understand the recurring narratives, tropes, and the broader strategic playbook of PRC information manipulation. From this perspective, greater awareness of these broader structures would enable citizens to identify and interpret new, highly granular disinformation narratives more independently.■

[1]"Leading DX School Generative AI Pilot School | Leading DX School" (In Japanese). https://leadingdxschool.mext.go.jp/ai_school/.

[2]Ministry of Internal Affairs and Communications (MIC), Japan. "First Steps with Generative AI: Introductory Usage and Precautions." Safe and Secure Internet Use Guide. https://www.soumu.go.jp/use_the_internet_wisely/special/generativeai/index.html.

[3]Ministry of Internal Affairs and Communications (MIC), Japan. "DIGITAL POSITIVE ACTION: Creating a Safe Digital Space for Everyone." https://www.soumu.go.jp/dpa/about/.

[4]National Institute of Information and Communications Technology (NICT), Japan. "CYDER: Practical Cyber Defense Exercise." National Cyber Training Center. https://cyder.nict.go.jp/.

[5]National Institute of Information and Communications Technology (NICT), Japan. "SecHack365: Long-Term Hackathon Program for Security Innovators." https://sechack365.nict.go.jp/.

[6]Information-technology Promotion Agency (IPA), Japan. "Security Camp: Advanced Security Education Program for Students." https://www.ipa.go.jp/jinzai/security-camp/index.html.

[7]ASEAN-Japan Cybersecurity Capacity Building Centre (AJCCBC). "About Us." Managed by the National Cyber Security Agency (NCSA) of Thailand and the Japan International Cooperation Agency (JICA). https://ajccbc.ncsa.or.th/.

[8]National Information Society Agency (NIA), Republic of Korea. "AI Digital Learning Center (in Korean)." https://www.디지털배움터.kr/entry.do.

[9]Seoul AI Foundation. "Seoul AI EduTech: Digital Education Platform for Seoul Citizens." https://sdfedu.seoul.kr/main/index.jsp.

[10]TBS CROSS DIG with Bloomberg. "Audrey Tang's Ally Microsoft Economist Glen Weyl: Beyond Majority Rule — Democracy in Japan and Taiwan, and How 'Conflict' Drives Innovation (In Japanese)." CROSSDIG 1on1. YouTube. https://www.youtube.com/watch?v=gTWqbdfTc2g.

[11]Taiwan FactCheck Center (TFC). https://en.tfc-taiwan.org.tw/.

[12]Taiwan Information Environment Research Center (IORG). "About IORG." https://iorg.tw/_ua/about.

[13]Chihhao Yu, co-director of the Taiwan Information Environment Research Center (IORG). Profile at Global Taiwan Institute. https://globaltaiwan.org/member/chihhao-yu/.

[14]Tim Niven, PhD, Deputy CEO, Doublethink Lab. Google Scholar profile. https://scholar.google.com/citations?user=B9vqlpwAAAAJ&hl=en.

[15]Summer Chen, founder of FactLink; former chief editor of Taiwan FactCheck Center (2019–2024). Profile at Global Taiwan Institute. https://globaltaiwan.org/member/summer-chen/.

Labor

Challenges derived from labor issues constitute a critical dimension of AI’s democratic implications. Economic inequality driven by AI-induced job displacement can erode existing disparities, posing broader risks to the health of democratic societies. Simultaneously, the non-transparent use of AI in hiring decisions directly threatens core democratic values such as fairness, non-discrimination, and due process, while raising fundamental questions of algorithmic accountability that democratic governance must address. Two labor-related concerns emerge across countries: job displacement caused by automation and potential discrimination in AI-assisted hiring. Policy responses to job replacement differ. In addressing employment protection, Taiwan relies more on statutory provisions that guarantee worker protections, while South Korea seeks to address labor transitions through negotiations and union pressure. Japan frames AI primarily as a productivity tool and focuses on reskilling and labor mobility. AI-assisted recruitment is widely introduced across cases. At the same time, concerns exist regarding potential algorithmic discrimination, addressed largely through soft law.

1. Japan

1.1. Labor Transition and Countermeasures through Reskilling

In Japan, population decline and the resulting constraints on labor supply are widely recognized as urgent policy challenges. Within this context, AI is discussed not only as a source of labor risk but also as a tool for maintaining productivity. The AI Business Guidelines identify unemployment as a potential risk and emphasize human dignity, autonomy, and education and reskilling as guiding principles (Ministry of Economy, Trade and Industry 2025). An October 2025 report by AISI also refers to possible impacts on labor markets and economic inequality (Japan AI Safety Institute 2025). At the same time, METI’s 2025 “2040 scenario” estimates that promoting AI and robotics, combined with reskilling, could help offset a projected shortfall of approximately 2 million workers (METI Industrial Structure Council 2025). The draft of the 12th Basic Plan for Vocational Ability Development in 2026 similarly notes that AI may reduce demand in certain occupations but stresses investment in “human capital” and skills development (Ministry of Health, Labour and Welfare 2025).

At the firm level, early signs of labor substitution have appeared. For example, in November 2025, NTT, one of the largest telecommunications companies in Japan, stated that more than half of its operations could be handled by AI within five years (Nikkei 2025b). A Nikkei survey of over 100 major firms found that several companies expect AI to supplement 30–40 percent of internal tasks.

Policy responses focus primarily on reskilling and labor mobility. Vocational training policies have been expanded. These measures include direct financial support for individuals, indirect support through firms, and training programs delivered through private training providers. At the same time, several challenges have been pointed out, including a policy bias toward firm-mediated programs, barriers to self-directed learning, and unequal access for non-regular workers and younger employees (Nitta and Tanaka 2025). These support measures are not limited to AI-related skills and are intended to address broader changes in the labor market. The Ministry of Health, Labor, and Welfare has launched model projects to create practical training environments for digital and AI skills[1]. In the private sector, the Japanese Electrical, Electronic, and Information Union has begun providing AI-related reskilling programs in cooperation with Microsoft across affiliated unions (Matsui 2026).

While large-scale unemployment has not yet materialized in Japan, concerns about inequality have been raised. In a March 2026 interview, Takahiro Anno, the leader of the opposition party, argued that AI may disproportionately affect higher-income white-collar workers and widen income gaps, calling for measures such as refundable tax credits and discussions of basic income or basic services (Bloomberg 2026). Some also note that policy discussions on AI strategy lack a perspective of workers (Nitta and Tanaka 2025). Although productivity enhancement is central to policy discourse, the broader social and democratic implications of occupational restructuring and income divergence remain only briefly addressed.

1.2. AI in Recruitment

AI is increasingly influencing recruitment practices. Although surveys report varying figures, many private companies have begun to use AI in hiring processes. While the use of AI in recruitment can improve efficiency, it also entails several risks. As highlighted in the AI Business Guidelines (MIC and METI 2025b), these include the possibility that biased training data may lead to discriminatory outputs, the risk of excessive reliance on AI in decision-making, and the potential for inappropriate use of personal data. The document calls for efforts to mitigate the bias and for intervention by human decisions (MIC and METI 2025a).

As the use of AI expands in the private sector, public employment support institutions have also begun to explore how AI might be utilized in their services (Employment Security Bureau 2025). Current policy directions emphasize that AI should not replace all human tasks but should instead be used as a tool to enhance the accessibility and efficiency of employment services. From 2026 onward, pilot projects and systern design initiatives are expected to advance toward implementation. Within these discussions, particular attention has been given to preventing the leakage of personal and confidential information and to mitigating the generation of inappropriate or biased outputs.

2. South Korea

2.1. Labor Transition Struggle

In February 2026, the Ministry of Employment and Labor and the two national trade union confederations—the Korean Confederation of Trade Unions and the Federation of Korean Trade Unions—inaugurated high-level consultative bodies to address AI-driven industrial restructuring and job security through monthly policy dialogues (Ministry of Employment and Labor 2026). However, these discussions face immediate friction on the production floor. At Hyundai Motor, the union has strongly opposed the introduction of the Atlas humanoid robot, asserting that not a single unit can be deployed without a formal labor-management agreement (Park 2026). Furthermore, industry voices strong concern (Kang 2026) that the Yellow Envelope Law (Trade Union and Labor Relations Adjustment Act 2025) could further empower such opposition by bringing managerial decisions, including the adoption of AI and robotics, into the scope of collective bargaining[2]. This regulatory shift, from an industrial perspective, risks turning technological transitions into a prolonged cause of industrial deadlock.

2.2. Algorithmic Justice in Labor Fields

Korea is pursuing algorithmic justice in the labor fields through Article 37 of the Personal Information Protection Act[3] and the AI Basic Act[4]. Furthermore, guidance from the Personal Information Protection Commission clarifies that AI-based hiring and dismissal decisions generally fall within the category of automated decisions that significantly affect rights (PIPC 2025). However, concerns persist regarding legal ambiguity and the significant capability gap between firms. Especially for small and medium-sized enterprises, which employ approximately 80% of the workforce, AI utilization stood at just 36% in 2025 (Park 2025), merely half the rate of large corporations, due to limited access to human resources and legal counsel. Simultaneously, conflicts between society and corporations regarding algorithmic transparency are becoming increasingly prominent. A representative conflict involves Baemin, Korea’s largest food delivery platform, which has faced repeated calls for algorithmic transparency but maintains that such information constitutes trade secrets (Gye 2023).

Korea's AI labor transition is being built on a fractured foundation, unfolding in a market where generational inequality is reaching a breaking point. While high-level dialogues signal institutional awareness, they face a harsh reality. Youth employment is stalling despite record education levels, and the elderly, those already suffering from the OECD's highest poverty rate and accounting for approximately 70% of workers in jobs under 15 hours per week, see their already unstable roles threatened by AI and automation (Yu 2025). With SMEs employing over 80% of workers (Ministry of SMEs and Startups N.d.) but lacking the capacity to adapt, dialogue risks outpacing structural readiness. Ultimately, unless policies prioritize the most vulnerable segments, the AI transition may deepen existing social fractures.

3. Taiwan

3.1. AI-Driven Job Displacement

Taiwan is increasingly confronting concerns over the implications of artificial intelligence for labor markets, workers’ rights, and social protection. Public debate has intensified around the prospect of technological unemployment, particularly as automation is expected to replace repetitive and routine tasks more rapidly than other forms of work. These anxieties are reflected in a Taipei Times report suggesting that Taiwanese firms anticipate AI could displace nearly one-third of existing jobs over the coming decade (Taipei Times 2024). In response, Taiwan’s emerging AI governance framework has begun to address labor-related risks.

Article 12 of the AI Basic Act stipulates that the government must protect workers’ occupational safety, while also providing reemployment assistance to those who become unemployed as a result of AI adoption (Chien 2025). Beyond this general principle, the Workforce Development Agency under the Ministry of Labor (MOL) has introduced concrete policy measures to facilitate workforce adaptation (Workforce Development Agency 2024b). These include subsidized AI-related training for employed workers, youth-targeted vocational programs such as the Industrial Talents Program, and retraining initiatives that enable workers to receive financial support while undertaking online learning. At the same time, the Executive Yuan frames AI investment not merely as a source of regulatory and social challenges, but also as a key pillar of economic growth and job creation, as demonstrated by its promotion of the Ten Major AI Infrastructure Projects (Reuters 2025).

3.2. AI in Hiring and Algorithmic Discrimination

A 2024 survey conducted by MOL found that 3.0 percent of firms were already using AI interview tools in recruitment, while 34.3 percent were considering adopting them (Workforce Development Agency 2024a). Although such tools may help reduce recruitment costs, concerns remain that they may generate discriminatory outcomes in employment, even unintentionally. Article 4(6) of the AI Basic Act stipulates that, throughout the research, development, and application of AI, algorithmic bias and discrimination should be avoided as far as possible, and that AI must not result in discriminatory outcomes against particular groups (Executive Yuan 2025).

March 2026 United Daily News (Ye 2026) and CNA (Zhang 2026) reports indicate that MOL is drafting Guidelines on the Introduction and Use of Artificial Intelligence by Business Entities, which could be issued as early as mid-2026. The reports suggest that the draft guidelines are centered on transparency, human oversight, labor-management consultation, and privacy protection, with particular attention to preventing unfair treatment or discrimination in recruitment, selection, performance evaluation, and dismissal. The United Daily News report further notes that, if AI is used in recruitment, employers would be expected to inform job applicants in advance and ensure that final decisions remain subject to human judgment; likewise, where AI is used in employee performance evaluation, employers would be expected to disclose the evaluation criteria in advance, retain human oversight in final decision-making, and be able to explain the evaluation results (Ye 2026). However, some experts contend that non-binding guidelines alone are insufficient, and that the government should undertake a comprehensive review of existing legal frameworks to assess whether statutory amendments are necessary (Zhang 2026).■

[1]Ministry of Health, Labour and Welfare (MHLW), Japan. "Model Project for Developing Practical Opportunities for Digital Human Resource Development (In Japanese)." Commissioned operator: Pasona Co., Ltd. Project period: FY2023–FY2025. https://dx-jinzai.mhlw.go.jp/ (site no longer available; see also https://www.mhlw.go.jp/stf/seisakunitsuite/bunya/koyou_roudou/jinzaikaihatsu/program_development_00019.html).

[2]Republic of Korea. Framework Act on Artificial Intelligence Development and Establishment of Trust (in Korean), Act No. 21311 (enforced January 22, 2026). https://www.law.go.kr/lsInfoP.do?lsId=014820&ancYnChk=0#0000.

[3]Republic of Korea. Personal Information Protection Act (in Korean), Act No. 19234 (partially amended March 14, 2023; enforced September 15, 2023), Article 37. https://www.law.go.kr/lsInfoP.do?lsId=014820&ancYnChk=0#0000.

[4]Republic of Korea. Framework Act on Artificial Intelligence Development and Establishment of Trust (in Korean), Act No. 21311 (enforced January 22, 2026). https://www.law.go.kr/lsInfoP.do?lsId=014820&ancYnChk=0#0000.

Assistance for Developing Countries

As the evolution of AI can produce and amplify global inequality, foreign assistance to developing countries has become crucial to mitigate this effect. In this regard, East Asian democracies exhibit different levels and approaches. Japan stands out as the most active provider, focusing especially on governance support and capacity-building, framed in terms of human-centered and trustworthy AI. South Korea adopts a more explicitly value-driven approach, emphasizing inclusivity and democratic governance in its international initiatives. Taiwan engages less through large-scale assistance, but civil society actors play an active role in international collaboration through research, network-building, and capacity-building activities.

1. Japan

1.1. Active AI Cooperation with a Human-Centered Emphasis

Japan is actively assisting and collaborating with the Global South in AI. Japan has promoted the “co-creation of a safe, secure, and trustworthy AI ecosystern” as a key concept in its engagement with the Global South. Based on this approach, it has advanced AI-related cooperation with partners including India (Ministry of Foreign Affairs 2026), ASEAN (MOFA, MIC, and METI 2025a), Central Asia (MOFA, MIC, and METI 2025b), and African countries (Ministry of Foreign Affairs 2025). These initiatives focus on four pillars: problem-solving through the use of AI, institutional assistance, human resource development and capacity-building, and infrastructure support, including data centers and AI models for local languages. As the table indicates, the scope of cooperation varies across partner regions. Several initiatives have seen further developments to strengthen collaboration.

Table 12-1: Japan’s international AI diplomacy with the Global South

The Japan International Cooperation Agency (JICA) has incorporated a human-centered AI approach into its development assistance[1]. JICA programs aim to improve public services through AI while acknowledging potential risks such as digital divides and algorithmic discrimination. Current initiatives include support for national AI strategy formulation, AI literacy programs, and pilot projects that implement AI applications in sectors such as education, health, and public adrninistration.

These cooperation efforts are also linked to Japan’s broader international AI governance agenda. The Ministry of Foreign Affairs positions the Hiroshima AI Process as a component of governance assistance in cooperation with partner countries. Japan has also promoted exchanges between the OECD and Southeast Asian countries by means of workshops on AI governance tools at the Japanese embassy in Bangkok (Ministry of Foreign Affairs 2025a).

At the same time, cooperation with the Global South often frames AI governance in terms of human-centeredness and safe, secure, and trustworthy AI, a formulation that places less explicit emphasis on democracy and human rights than multilateral discussions such as the Hiroshima AI Process, where democratic values are explicitly mentioned.

2. South Korea

2.1. The Global AI Basic Society

Korea is championing the "AI Basic Society" as a new global standard, ensuring that technological benefits are redistributed to bridge the digital divide (Office of the President 2025). At the 2025 Gyeongju APEC Summit, Korea led the "APEC AI Initiative," the first ministerial consensus signed by both the U.S. and China (Korea Policy Briefing 2025). This initiative serves as the global blueprint for an inclusive AI society, focusing on shared growth and equitable access across the Asia-Pacific. By positioning AI as a public good, Korea is attempting the transition from a competitive innovation race to a collaborative, value-driven global governance model.

2.2. K-Democracy ODA

Centered on the AI Democracy Subcommittee established in 2026, Korea is endeavoring to extend its “K-Democracy ODA" to share its unique expertise in institutionalizing digital democracy. By exporting platforms that integrate cutting-edge technology with democratic values, Korea tries to solidify its normative leadership within the global AI governance architecture. Complementing this value-based approach, Korean enterprises are also gaining experience in supporting other nations to build their own sovereign AI. A representative example is the export and co-development of LLM platforms and infrastructure in Thailand, demonstrating Korea's capacity to help states secure sovereignty through localized AI development.

Korea’s effort to treat AI as a public good through the "AI Basic Society" vision has successfully evolved from a domestic concept into a global agenda, marked by the significant diplomatic achievement of securing both U.S. and Chinese support at APEC. This normative ambition is further reinforced by "K-Democracy ODA," which distinguishes Korea on the global stage by sharing its practical experience in building civic platforms, supporting digital sovereignty, and promoting AI literacy rather than merely exporting technology. While this proactive international engagement represents one of the strongest chapters in Korea’s global AI strategy, its long-term credibility remains intrinsically linked to domestic performance. Ultimately, the real test for Korea will be whether it can resolve its own internal policy tensions effectively enough to ensure that its domestic practices live up to the value-driven model it seeks to champion abroad.

3. Taiwan

Given Taiwan’s distinct international position, international engagement in this area has often relied less on formal state-led outreach than on the transnational activities of civil society organizations.

In this context, Doublethink Lab[2] provides a particularly relevant example in the field of AI and digital governance. Founded in Taiwan in 2019, it is a civil society research organization that examines Chinese digital influence operations, disinformation, and the transnational diffusion of digital authoritarian practices. Its relevance to AI and digital governance is reflected in its work on AI-enabled disinformation and surveillance, as well as in the practical investigative methods it has developed to detect and analyze such threats. Its activities extend beyond Taiwan through research, election observation, and capacity-building initiatives in countries considered vulnerable to information manipulation. During India’s 2024 general election, for example, it coordinated an election observation effort (Yu 2024), while in the Philippines it has provided training for journalists since 2023 using OSINT-based investigative methods and analytical frameworks (Doublethink Lab 2024). It has also examined Thailand as a case in which Chinese CCTV systerns and AI-enabled facial recognition technologies may have been used in political repression (Lee 2025). As Tim Niven[3] noted in an interview, the organization is also exploring initiatives in countries including Zambia, Nigeria, and Malaysia, while deepening cooperation with partners in New Zealand and South Korea.

More broadly, the Taiwan Foundation for Democracy plays a complementary role in sustaining the transnational networks and normative dialogue that underpin more issue-specific cooperation (Taiwan Foundation for Democracy 2025). Established in 2003, it is a quasi-public democracy-assistance foundation with public support and a cross-party institutional basis. In recent years, it has also begun to engage with issues at the intersection of AI and democracy. One example is its international forum on local democracy (TECRO in Japan 2026), held in January 2026 under the theme “AI × Democracy.” Moderated by Audrey Tang, the event brought together 12 participants from six countries.■

[1]Japan International Cooperation Agency (JICA). "AI Cooperation: JICA's Six Pillars of DX (In Japanese)." https://www.jica.go.jp/about/dx/six_pillars/pillar_3/.

[2]Doublethink Lab. "Strengthen Democracy Through Enhancing Digital Defenses." https://doublethinklab.org/.

[3]Tim Niven, PhD, Deputy CEO, Doublethink Lab. Google Scholar profile. https://scholar.google.com/citations?user=B9vqlpwAAAAJ&hl=en.

Gaps Existing Initiatives and Way Forward

We have thus far outlined the initiatives being undertaken by each country. What this paper aims to clarify next is what has not been done and what must be done in the future.

Although the intensity varies by country and time period, Japan, South Korea, and Taiwan have all placed a high priority on reconciling AI governance with values such as the rule of law, human rights, diversity, equity, democracy, inclusivity, non-discrimination, transparency, and accountability. However, fundamentally, these three countries are in a position where they are striving to catch up with AI-leading countries like the United States and China, and they are implementing policies that also prioritize the promotion of innovation in the AI field.

In terms of international principle and norm formation, most notable is the Hiroshima AI Process, established in 2023, along with its International Guidelines and International Code of Conduct. These are positioned to apply not only to those who develop AI but also to those who use it. However, most of the content of the guidelines and code is formulated with developers in mind. Furthermore, while stating that values such as democracy must not be compromised during use, these documents do not provide guidance on how to safeguard democratic values in cases where the design of AI systems or the manner of their use could easily undermine democratic values within the societies of the user countries.

Furthermore, the values essential to upholding liberal democracy—such as the rule of law, human rights, due process, diversity, equity, and democracy—which were highlighted as norms in the Hiroshima AI Process, have not been consistently endorsed in subsequent international initiatives observed in East Asia. The fact that the 2024 Seoul AI Business Pledge barely touches upon these values is a case in point. This is due not only to differing priorities among countries and actors but also to the non-binding nature of the guidelines.

Efforts to strengthen democratic governance through the use of digital tools are not yet being implemented nationwide in Japan, South Korea, or Taiwan; rather, they remain at the experimental or localized stage. These initiatives are based on the principle of participatory democracy, which seeks to broadly incorporate domestic public opinion. However, given that public opinion itself is increasingly influenced by AI—which has been shaped by non-democratic actors through LLM grooming—or is taking on more undemocratic and discriminatory tones due to the rise of populism, it is difficult to say that measures to safeguard democratic values and institutions without being swayed by these trends have been incorporated at this stage. Furthermore, digital democracy initiatives do not extend beyond national borders. That said, Taiwan’s digital democracy initiatives appear to be more advanced than those of Japan and South Korea. In particular, the role of the civic tech community is integrated, and it is expected to play a role not only in collaborating with the government but also in monitoring it.

Awareness is growing in every country regarding the spread of AI-generated misinformation, malicious content, fake images, and fake videos, and efforts are underway to address the significant impact this has on the integrity of information. Differences in the situation can be observed across countries: Japan tends to prioritize freedom of expression and relies heavily on platform self-regulation; in South Korea, fact-checking organizations are caught up in societal polarization; and in Taiwan, the anti-China factor politicizes its counter-FIMI approaches.

However, in all cases, efforts to counter information manipulation through disinformation and malinformation—which have significantly increased in speed and volume due to AI, accelerated by the fragility of the international society—are unlikely to be sufficient to address the problem, especially as this trend is expected to accelerate further. The barriers to addressing this issue have become even higher, partly because major U.S. tech giants significantly reduced their funding for counter-disinformation efforts starting in 2025. Furthermore, the fundamental problem remains that we have not been able to regulate the attention economy model of platforms themselves, which inherently provides incentives to mass-distribute political videos and images. Unless this issue is resolved, it will be difficult to curb the politics of emotion.

Japan, South Korea, and Taiwan—countries facing serious cyber threats—are implementing multi-layered initiatives that address both “Security for AI” (defending against cyberattacks targeting AI) and “AI for Security” (preventing cyberattacks that exploit AI). They are also engaged in capacity-building efforts for developing countries across Asia. While cybersecurity is crucial for the stability of democratic societies—as evidenced by examples of election interference using “hack and leak” tactics in the United States and elsewhere—efforts in this area are inevitably dominated by security and financial considerations.

Ensuring the security of information regarding democratic societies and pro-democracy actors—such as data theft by authoritarian states and the collection of foreign data by Chinese companies, to which the Chinese government then gains access—is a critical issue. Japan, South Korea, and Taiwan are all actively working on data protection, but the focus is often on protecting data from their own governments and companies, and measures such as imposing fines are being implemented.

The “sovereign AI” initiative, which aims to build each country's own AI system, seeks to independently develop AI infrastructure capable of aggregating information, analyzing it, and formulating countermeasures without relying on AI from other countries. These measures were devised with the understanding that it is necessary to promote AI-driven innovation and establish governance frameworks while protecting data from foreign governments. However, none of these three countries currently host major AI companies, and they are still in the early stages of preparing to build sovereign AI systems. All of these initiatives began in 2025, and they have not yet reached the stage of providing support to other countries in this field.

When AI indiscriminately ingests large amounts of information and uses it for output, information whose accuracy is not necessarily guaranteed can spread rapidly. In contrast, actors essential to the foundation of a democratic society—such as media outlets that verify information to disseminate accurate content—may suffer a loss of commercial revenue and become unsustainable if their content is accessed for free. For this reason, copyright protection is crucial for democratic societies.

Amid the conflict between the content industry and the tech industry, countries are struggling to determine appropriate regulatory frameworks and have not yet reached the stage of providing support to other countries in this area. Since these three countries do not own major AI companies, their discussions focus not only on how to protect their domestic content industries from foreign AI companies but also on how to safeguard content creation while enabling the training of domestic AI companies. These discussions themselves could serve as a reference point for other countries.

In an era where AI is accelerating the spread of misinformation, AI literacy education is crucial for maintaining the resilience of democratic societies. All three countries examined incorporate AI and media literacy education into their primary and secondary school curricula. Additionally, they are implementing training programs to prevent social division and build capacity in the fields of AI and cybersecurity. Support for developing countries in this area is also active. However, support for developing countries is primarily directed at government agencies; there is no capacity-building support for citizens seeking to protect themselves from surveillance or oppression by their own government, major tech companies, or foreign governments. Constructive criticism from Taiwan’s civil society also highlights the lack and importance of digital civic education to safeguard civic space.

Issues such as the replacement of human labor by AI and wage disparities stemming from access to AI are problems that could widen economic inequality and destabilize democratic societies. Consequently, measures are being taken to mitigate these impacts, such as promoting recurrent education in the field of AI. However, forecasts regarding the extent to which the labor market will be affected by AI, as well as the scope of recurrent education, are limited to domestic contexts; analyses do not include the impact on labor markets in other countries. While providing the content of recurring education currently offered in Japan, South Korea, and Taiwan to developing countries is one option, it is also necessary to raise awareness within developed nations regarding how their AI technologies are affecting the labor markets of developing countries, and to advance analyses of the impact this has on democracy in those nations and the international community, along with corresponding countermeasures.

From the perspective of supporting developing countries, Japan's focus is overly skewed toward providing aid to governments, and the lack of necessary support for non-governmental actors to safeguard democracy is a significant issue. Given that many developing countries have recently adopted China's surveillance systems, aid from countries like Japan and South Korea must not serve to strengthen or complement these surveillance capabilities; instead, it must support the capacity to counter them. Furthermore, in recent years, an increasing number of countries, such as Thailand, have been digitizing adrninistrative data and using AI to flag potential corruption. However, the absence of third-party oversight bodies to monitor the AI algorithms used for anti-corruption efforts leaves room for such measures to be exploited for political purposes.

By contrast, Taiwan's civil society organizations have established cross-border partnerships and are enhancing the capabilities of civil society groups worldwide through joint research and capacity-building. That said, there are limits to relying solely on a handful of organizations like Double Think Lab to carry out these activities, and Double Think Lab’s capacity-building support is not funded entirely by its own resources. Support for civil society—including funding from Asian organizations—is essential.

Japan, South Korea, and Taiwan—all of which seek to safeguard democratic values and institutions while advancing the goals of enhancing AI capabilities and fostering innovation—are undertaking numerous initiatives. However, several common issues are evident. First, these efforts largely remain domestic, providing little support to strengthen the democratic values and institutions of other countries in relation to AI. Second, insufficient efforts are being made to establish international norms for protecting democracy from and with AI. Third, due to the absence of an international perspective, the potential for authoritarian governments to use AI for data theft, strengthening surveillance systems, and exploiting seemingly democratic actions, such as anti-corruption measures, for political gain is not fully recognized or included in the scope of countermeasures. Fourth, despite the weakening of democracy in other countries, support for civil society is inadequate, despite its essential role in such contexts.

This shows the necessity of launching initiatives with multiple elements. First, the focus should be on transborder aspects to support developing countries suffering from the unavoidable impact of AI from developed countries. Second, support must be provided to civil society actors, who are absent from existing initiatives in East Asian countries. Third, these initiatives should prioritize the protection of democratic norms and values over technological advancement. Fourth, these initiatives will likely require the involvement of civil society actors from developed countries who are well-versed in both democracy and AI.

Japan, South Korea, and Taiwan are perfectly suited to embark on such an endeavor. Japan is eager to set global norms, South Korea is adept at launching tech-based initiatives quickly, and Taiwan has rich human resources and experience in the civil society sector. A coalition of actors from these three countries is well suited to support democracy from and with AI.■

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