Korea's AI ethics principles lack binding force, specificity

The government's new artificial intelligence (AI) ethics principles provide a broad framework for responsible AI use but lack legal force and specific implementation standards, experts noted, raising questions about their practical impact.

The government announced national principles for the ethical development and use of AI on Monday, setting out three core values and seven guidelines for AI use across industries and everyday life. The principles provide a common but nonbinding reference for developers, providers, users, government agencies and civil society, the Ministry of Science and ICT said.

Choi Kyoung-jin, director of the Center for AI, Data and Policy at Gachon University, said the principles should be viewed as a broad declaration of values rather than a set of enforceable rules, with their effectiveness ultimately depending on how they are translated into sector-specific practices.

“The principles should be understood as declaring the fundamental principles that we need to think about in this era,” Choi said.

“Ethical principles are something that would be good to follow, but there are no sanctions for not following them.”

He said ethical issues can vary substantially depending on the AI systems, services and industries involved.

“This is not an obligation,” he said. “It seems to have been created with the goal of guiding society by saying that the government considers these things important in the current era.”

The framework is built around three overarching values: human dignity, meaning people should be respected as ends in themselves rather than as means to an end; the common good, under which AI should contribute to social trust and collective interests beyond individual benefits; and the sustainability of humanity, aimed at ensuring that AI benefits both present and future generations.

Seven guiding principles are set under these values: human-centeredness, privacy protection, fairness and inclusiveness, accountability, safety, reliability and transparency.

The initiative comes as AI use expands rapidly across industries and everyday life, bringing productivity gains as well as new challenges, including excessive reliance on AI, changes in employment, copyright disputes and the spread of false or manipulated information.

“The true measure of success in the AI race lies not only in developing advanced technologies, but in delivering AI that is put to use across industries and in people’s everyday lives,” Science and ICT Minister Bae Kyung-hoon said.

“As the adoption of AI grows, ethical principles to ensure safety and trust are becoming increasingly important. We will foster a healthy AI ecosystem where technological innovation and responsibility go hand in hand.”

Under the human-centeredness principle, AI should support human judgment and decision-making rather than replace it. Developers are encouraged to clearly define the role of AI, allow human intervention when necessary and guard against excessive reliance on automated systems.

The privacy principle calls for personal information to be processed only for specified purposes and within the necessary scope, while the fairness and inclusiveness principle sets standards aimed at ensuring fair treatment and participation in the development and use of AI.

The accountability principle calls for responsibilities to be clearly assigned among AI-related actors. The safety and reliability principles call for risk management and performance standards appropriate to each system's purpose.

The transparency principle requires information about AI use, its limitations and decision-making criteria to be provided, particularly when AI affects people's rights, obligations or opportunities.

Choi said more concrete rules should ultimately be developed by individual industries and companies based on how AI is actually used.

“Principles are principles, but there should be more efforts in the private sector to give greater weight to concrete codes of conduct for individual services or to ethical issues that may arise depending on how AI is used in each field,” he said.

An industry official also said many of the principles already represent basic requirements for companies developing AI, limiting their immediate practical impact.

“From the perspective of companies developing AI, these are things that we obviously need to do anyway,” the official said.

“So, in terms of effectiveness, I think the general perception is that it is simply a framework and does not have much practical impact beyond that.”

The government plans to develop case-based guidance and sector-specific self-guided checklists to help translate the broad principles into practice.