Data Standardization Must Come First for Successful AI Adoption

Korean engineering experts warned at a National Assembly seminar that AI adoption is pointless without data standardization, discussing AI era response strategies. The seminar, themed 'Ways to Utilize AI in Engineering Specialties,' featured professional engineers from diverse fields including fire safety, architectural structures, electrical engineering, and information and communication technology, who explored strategies for the AI transformation (AX) era.

During the discussion, Professor Yoon Jong-moon of Cheongju University highlighted that AI-based security threats target national infrastructure. He stressed the necessity of ensuring data integrity and building cyber response systems in parallel as AI is increasingly integrated into foundational infrastructure. Kim Han-soo, CEO of LabQ, asserted the importance of understanding the probabilistic nature of generative AI, advocating for its acceptance as a tool to enhance productivity rather than replace experts.

Shin Ju-il, CEO of Real Leadership, proposed three policy tasks: establishing high-purity data by consolidating sector-specific laws, technical standards, and on-site expertise with government budgets and support; forming a convergent engineering AI forum; and setting verification standards for AI simulation results. Seo Hae-yeol, a fire safety engineer, pointed out the scarcity of domestic fire data, noting that the country often pays to use U.S. data and that discussions on data standardization are unfamiliar at the field level. Kim Seok-joong, Vice Chairman of the Korea Institute of Information and Communication Technology Professionals, urged that it's time to discuss execution, emphasizing that meaningful AI utilization is only possible if the government opens public databases for the engineering sector.