AI Basic Society
Overview
AI Basic Society (AI 기본사회) is a concept that defines artificial intelligence not as the exclusive possession of a particular company or expert, but as foundational infrastructure (basic goods) that the whole of society should enjoy in common, like electricity, water, and the internet. In other words, it refers to a social paradigm that designs institutions, technology, and education so that all citizens can universally access and utilize AI capabilities and their outcomes. This includes a policy orientation aimed at mitigating social inequality by combining the fruits of AI-driven productivity gains with basic income, public services, and welfare, rather than concentrating them in the hands of a few.
Key Content
1. Concept and Background
The term "AI Basic Society" developed along two main lines. First is the view of AI as a public good, which argues that the state should build large-scale computing infrastructure (GPU clusters, data centers) and foundation models as public assets and open them to the public. Second is the social safety net in the AI era perspective, which discusses institutionalizing basic income, retraining, and lifelong learning in response to job displacement caused by automation. The two perspectives meet at the common question: "How should the wealth created by AI be distributed?"
2. Core Components
- Public AI infrastructure: State-level super-large AI models, shared data centers, open data platforms.
- Universal right to AI access: The right of all citizens to use AI services free of charge or at low cost.
- AI literacy education: Enhancing AI utilization capabilities of the entire population through schools, vocational training, and adult education.
- Linkage with the social safety net: Basic income, unemployment response, and job transition support programs.
- Governance and ethics: Regulatory frameworks for algorithmic transparency, bias control, and personal data protection.
3. Policy Implications
Governments adopt a dual strategy of viewing AI both as an object of industrial promotion and as public infrastructure. This is an approach that encourages private-sector innovation while securing foundation models and computing resources publicly and opening them to small and medium-sized enterprises, researchers, and citizens. In addition, to preemptively mitigate the unemployment and disparities arising from AI adoption, funding measures such as "AI dividends," "robot taxes," and "national AI funds" are being discussed.
4. Country Cases
- South Korea: Defines AI as both a national strategic industry and a public service, and is making large-scale investments in super-large AI, AI semiconductors, and data infrastructure.
- EU: Introduces risk-based regulation through the AI Act, seeking to establish trustworthy AI as a social foundation.
- Nordic countries such as Finland and Denmark: Experimenting with welfare models that combine AI education for citizens with public-sector AI adoption.
Latest Trends
Entering 2024–2025, discussions of the AI Basic Society spread rapidly along with the popularization of generative AI. First, as generative AI such as ChatGPT and Gemini became everyday tools, the "right to AI access" emerged as a new basic right. Second, the trend of governments directly building and opening public AI clouds and national representative models became pronounced. Third, as the labor market shock caused by AI became a reality, experiments with AI-responsive social safety nets such as basic income and retraining vouchers increased. Fourth, as AI safety and ethics norms (e.g., national AI framework acts, the International AI Safety Summit) were put in place, "trustworthy AI" is emphasized as a precondition for the basic society. Lastly, digital inclusion policies to bridge the AI divide are trending toward combining with education, welfare, and balanced regional development.
Related Topics
- [[Artificial Intelligence]]
- [[Basic Income]]
- [[Super-large AI]]
- [[AI Regulation]]
- [[Digital Inclusion]]
- [[Job Displacement]]
- [[Public Data]]