Artificial intelligence (AI) standardization is a critical component in the development and application of AI technologies. According to recent reports, the AI standard architecture consists of six key components: basic standards, platform/support standards, key technical standards, product and service standards, application standards, and safety/ethics standards. These standards aim to provide a comprehensive framework that supports the growth and integration of AI across industries.
With the rapid development of the AI industry, the need for standardized guidelines has become more urgent than ever. On January 18, the National Standardization Management Committee officially established the National Artificial Intelligence Standardization Group and the Expert Advisory Group. The overall group is led by Zhao Bo, Dean of the China Electronics Standardization Institute, while the deputy head candidates include experts from Alibaba Cloud, Hong Kong University of Science and Technology, the Chinese Academy of Sciences, Peking University, Beihang University, and the Institute of Instrumental Technology and Economy Tubes. Pan Yunhe, an academician of the Chinese Academy of Engineering, leads the expert advisory group.
The National AI Standardization Group plays a central role in coordinating, planning, and implementing AI-related standards both domestically and internationally. It is responsible for developing China’s AI standardization strategies, policies, and systems, as well as setting baseline performance and industry-specific standards. Meanwhile, the expert advisory group provides guidance on strategic planning, policy development, and other critical aspects of AI standardization.
Zhao Bo emphasized that standardization plays a fundamental, supportive, and leading role in AI development. “Although China has a strong foundation in AI, there is still a pressing need to improve infrastructure, policies, regulations, and standards that align with AI development,†he said. This initiative follows the release of the “Three-Year Action Plan for the Development of a New Generation of Artificial Intelligence Industry (2018–2020),†which outlines specific goals, including the establishment of an AI support system, standardization framework, testing, and security systems.
Globally, countries like the U.S., EU, and Japan have also prioritized AI standardization. Initiatives such as the U.S. National AI Research and Development Strategy, the EU’s Human Brain Project, and Japan’s AI/Big Data/IoT Safety Integrated Projects all emphasize the importance of core technologies, talent development, and regulatory frameworks to gain a competitive edge in the global tech landscape.
As AI products and applications become more widespread, it's essential to use standardization to solidify technological achievements and drive innovation. For instance, issues like uneven quality in face recognition systems, smart speakers, and service robots highlight the need for unified standards to enhance product reliability and user experience.
Ethical concerns, such as the "trolley problem" in autonomous driving or data privacy breaches like the iPhone fingerprint leak, also require robust safety and ethical standards to ensure AI systems align with human values. Moreover, as major companies build proprietary ecosystems, data silos are forming, making interoperability and collaboration among vendors more challenging. Standardization can help bridge these gaps.
Wu Wenjun, deputy head of the National AI Standardization Group and a professor at Beihang University, noted that basic, technical, and ethical standards will be key considerations moving forward. “Research and discussions in these areas will go hand in hand,†he said.
From an industry perspective, Jun Jun, Vice President of HKUST, highlighted the urgent need for standardization, particularly in system frameworks, capability definitions, AI interfaces, data standards, and evaluation methods. “These areas are crucial for the future of AI development,†he added.
The AI standard architecture, as outlined by the China Electronics Standardization Institute, includes six layers: basic standards (covering terminology, reference architecture, data, and testing), platform/support standards (integrating hardware, software, networks, and data), key technical standards (focusing on NLP, human-computer interaction, computer vision, biometrics, and VR/AR), product and service standards, application standards, and safety/ethics standards that span the entire system.
Huawei’s Song Zhe emphasized that AI is an enabling technology that can boost internal efficiency. He advocated for incorporating open source into the standardization process, stating that open-source platforms have become de facto standards in the industry. “Including open source in the standard-setting process ensures that real-world standards are practical and effective,†he said.
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