Standardization Trends on Safety and Trustworthiness Technology for Advanced AI

Artificial intelligence (AI) technology has been evolving more rapidly over the past decade. With new ML models, data sources, and increased computational power, AI researchers have developed AI technologies that can understand language, recognize and create images and videos, program, and make scientific inferences. Recent advances in advanced AI technologies have evolved beyond traditional narrow domain AI to approximate or exceed artificial general intelligence (AGI) based on large language models (LLMs) or foundation models (FMs). These advanced AI systems are performing at or above human levels in complex problem solving, sophisticated natural language processing, and multi-domain tasks, and have the potential to revolutionize a wide range of fields, including science, industry, healthcare, and education. They are already surpassing human capabilities in certain task domains, such as Go, strategy games, and protein folding prediction [1] [2]. For these reasons, concerns about the safety and trustworthiness of advanced AI are growing rapidly alongside its development. The increasing complexity and autonomy of advanced AI systems is raising concerns that they could lead to new forms of safety and security risks, such as (1) uncontrollability, (2) conflicts with human values in ethical decision-making, (3) long-term socioeconomic impacts, and (4) safety assurance. In response, international standardization efforts are underway to ensure the safety and trustworthiness of advanced AI. By developing internationally agreed technical standards, efforts are being made to apply consistent safety and trustworthiness criteria to the development and use of advanced AI systems and minimize potential risks.