Urban Engineering Dept., Chungbuk National University

Distinguish some of the facts on the AI and their future impacts and limitations

• Safe, secure and trustworthy AI
• Social, economic, ethical, cultural, linguistic and technical implications of AI
• Open-source software, open data and open AI models
• Protection and promotion of human rights

Are we on the right track for AI development? We have to develop more meticulously not only AI systems but also AI governance. We are currently facing chain reactions from the use of AI in our social systems. We need to build more concrete and well-designed AI governance in our society. The most vulnerable groups have been hit hard by the waves of AI adoption without enough preparation or countermeasures. Is this truly leading to the evolution of humanity, or only benefiting a small portion of wealthy people?

The cascading effects of artificial intelligence on our social systems are not being adequately addressed by responsible institutions around the world. The negative side effects are spreading widely, while the benefits are concentrated among a small portion of the population, resulting in an unbalanced distribution of AI's impacts. Without sufficient countermeasures and governance frameworks, the well-being of humanity may not be achievable.

The transfer and development of AI technologies should be sustained, particularly in high-technology sectors where innovation is essential. However, in some areas, the speed of technological development needs to be carefully controlled. AI should not be applied indiscriminately across all sectors without considering social, ethical, and economic impacts.

AI Dialogue can play an important role in advancing international cooperation on AI governance by providing a platform where governments, industries, researchers, and civil society can share perspectives and discuss common challenges. Through AI Dialogue, we can draw attention to the current status of AI use and its future directions by collecting opinions from various stakeholders across different regions and sectors. One of the biggest challenges in AI governance is that AI development is happening at different speeds and under different regulatory systems around the world. Without international communication and cooperation, this could lead to regulatory gaps, technological inequality, and conflicts over standards and data governance. AI Dialogue can help countries better understand each other's policies, concerns, and priorities, which can reduce misunderstandings and promote more coordinated governance frameworks. In addition, AI Dialogue can help identify the cascading effects and side effects of AI on society, the economy, and labor markets, especially for vulnerable groups. By sharing experiences and policy responses, countries can learn from each other and develop more balanced and responsible AI governance systems. Ultimately, AI Dialogue should not only focus on technological development but also on fairness, safety, sustainability, and the well-being of humanity. International cooperation through continuous dialogue will be essential to ensure that AI benefits are shared more broadly and that risks are managed collectively.

We have focused too much on the benefits of AI and not enough on its side effects and cascading impacts on society. Technological development always brings unintended consequences, and AI is no exception. At this stage, what we need is not only faster innovation, but better preparation, stronger governance, and deeper understanding of the risks and limitations of AI. The future of AI should be guided not only by technological capability, but also by social responsibility and human well-being.

Different stakeholders can contribute to the AI Dialogue by sharing their perspectives, data, experiences, and policy approaches related to AI development and governance. Governments can provide regulatory frameworks and public policy perspectives, while private companies can share technological developments, industry standards, and practical challenges. Academic researchers can contribute scientific knowledge, risk assessments, and ethical frameworks. Civil society organizations can represent public interests, human rights concerns, and the impacts of AI on vulnerable communities. One important issue that should be discussed in the AI Dialogue is the drawbacks and side effects of AI use. These include job displacement, data privacy issues, algorithmic bias, misinformation, concentration of technological power, and the cascading social and economic effects caused by rapid AI adoption. These problems cannot be solved by one sector alone. Therefore, interdisciplinary approaches are necessary. For example, engineers and computer scientists can work on technical solutions such as fairness algorithms and privacy-preserving technologies. Economists and social scientists can analyze labor market impacts and inequality. Legal scholars and policymakers can develop regulatory frameworks and governance structures. Educators can develop reskilling and lifelong learning systems to respond to labor market changes. Regarding the format and structure of the AI Dialogue, it should include multi-stakeholder panels, regional workshops, expert working groups, and public consultations. The dialogue should be continuous rather than a one-time event, and it should include both technical discussions and social impact discussions. A structured platform that connects technology, policy, society, and ethics would make the AI Dialogue more effective and meaningful.

Currently, global discussions on AI governance are largely dominated by major technology companies, powerful countries, and political institutions. As a result, many voices are underrepresented, including developing countries, small and medium-sized enterprises, workers affected by automation, women, minority groups, and socially or economically vulnerable populations. These groups are often the most affected by AI-driven changes such as job displacement, digital inequality, and data exploitation, yet they have limited opportunities to participate in decision-making processes. This imbalance may lead to AI governance systems that primarily reflect the interests of technologically advanced countries and large corporations rather than the global population. To address this issue, international organizations should create more inclusive participation mechanisms. For example, they could provide training programs, capacity-building workshops, and funding opportunities for participants from developing countries and underrepresented communities. International bodies could also support education and reskilling programs to help vulnerable groups adapt to AI-driven labor market changes. In addition, AI governance discussions should include labor unions, educators, local communities, and non-governmental organizations, not only governments and large technology companies. Public consultation platforms and open forums could allow more people to share their experiences and concerns regarding AI use. Including diverse voices will not only improve fairness but also lead to more realistic and sustainable AI governance, because AI affects different regions and communities in different ways.

To foster meaningful and dynamic engagement during the AI Dialogue, more diverse and innovative participation formats are needed beyond traditional government-led conferences and formal meetings. While government participation is important, discussions should also include independent experts, civil society organizations, industry practitioners, and ordinary citizens, because government representatives may sometimes present politically filtered information. One effective format could be multi-stakeholder roundtables where participants from different sectors discuss specific topics such as AI ethics, labor markets, education, and data governance. Scenario-based workshops could also be useful, where participants discuss hypothetical future situations involving AI risks and opportunities and propose policy responses. Another innovative approach could be citizen panels or public deliberation forums, where ordinary people can express their concerns and expectations regarding AI. This would help policymakers understand public perceptions and social impacts more accurately. Hackathons and policy labs could also be organized to bring together engineers, policymakers, social scientists, and designers to collaboratively develop governance ideas, regulatory frameworks, or technical solutions. Online global platforms could allow broader participation from people who cannot attend international meetings in person. Overall, the AI Dialogue should not be limited to formal speeches and presentations. Instead, it should encourage interactive discussions, collaborative problem-solving, and participation from diverse groups. This would make the dialogue more transparent, inclusive, and effective in addressing the complex global challenges posed by AI.

Several policies, practices, and governance approaches around the world provide useful examples for effective AI governance and for addressing the social, economic, and ethical challenges of AI. One notable example is the EU AI Act, which adopts a risk-based approach to AI regulation. The Act classifies AI systems into risk categories such as unacceptable risk, high risk, limited risk, and minimal risk, and applies different regulatory requirements accordingly. This approach allows innovation to continue while ensuring safety, transparency, and accountability for high-risk applications such as healthcare, critical infrastructure, and law enforcement. Another important initiative is the OECD AI Principles, which emphasize human-centered AI, transparency, robustness, accountability, and inclusive growth. These principles provide international guidelines that many countries use when developing their national AI strategies and regulations. In addition, the Global Partnership on AI promotes international cooperation on responsible AI development by bringing together governments, researchers, and industry experts to work on issues such as data governance, AI ethics, and the future of work. From a policy perspective, good AI governance practices should include risk-based regulation, transparency requirements, data protection laws, algorithm auditing systems, and public participation in AI policy discussions. Governments should also invest in education, reskilling programs, and social safety nets to address job displacement and inequality caused by AI adoption. Overall, effective AI governance requires not only regulation but also international cooperation, interdisciplinary research, public engagement, and continuous policy adaptation. AI governance should aim not only to promote technological innovation but also to ensure fairness, safety, sustainability, and the well-being of society.