Recently, Professor Jiang Xiaojuan from the University of Chinese Academy of Social Sciences gave a keynote speech titled "Artificial Intelligence Development and Governance: What Perspectives and Standards should Economics Have?" at the Annual Conference on the Development and Governance of China's Digital Economy. From an economic perspective, he deeply analyzed the key issues in the development and governance of artificial intelligence, emphasizing the need to construct a theoretical framework for technological development and rule design based on disciplinary logic, and providing new ideas for solving the dilemma of "emphasizing principles over theory, emphasizing concepts over practice" in artificial intelligence governance.

        From Moral Principles to Practical Rationality: The Legitimacy Standards for Reconstructing the Development Direction of AI. For a long time, discussions on the development rules and ethics of artificial intelligence have mostly focused on moral concepts and value advocacy. The 12 principles of safety, transparency, and accountability proposed in the Asilomar Principles for Artificial Intelligence launched in 2017, as well as the 6 priority issues of inclusiveness and sustainability emphasized in the statement signed by 58 countries at the Paris AI Summit in 2025, have gathered social consensus, but there are significant problems of insufficient theoretical support and practical translation.

        Jiang Xiaojuan stated that these principled statements lack an analyzable academic framework and measurable evaluation indicators, making it difficult to scientifically evaluate the advantages and disadvantages of technology or products, and unable to systematically weigh the implementation costs and social benefits of governance rules, resulting in slow implementation of relevant concepts. She emphasized that the legitimacy evaluation of the development direction of artificial intelligence should shift from abstract moral principles to practical rationality in economics, establish an analytical framework based on resource allocation efficiency and social equity, and form a verifiable logical loop between the "natural" goals and "actual" effects of technological development.

        Construct an economic evaluation system for the social value of AI, taking into account both efficiency and fairness. Jiang Xiaojuan believes that from an economic perspective, the core social value of artificial intelligence lies in whether it can promote the improvement of "social resource allocation efficiency" and "fair sharing of development achievements". She believes that the impact of artificial intelligence on social equity can be divided into two categories: one is the sustained impact on existing fairness balance, including large enterprises strengthening their market dominance through data, computing power, and algorithm advantages, squeezing the living space of small and medium-sized enterprises, etc; The second is the disruptive challenge brought by the inherent characteristics of technology, such as the "increasing returns to scale" and "emerging capabilities" of artificial intelligence large models. The larger the model, the higher the optimization iteration efficiency, and after breaking the threshold, it generates cognitive and problem-solving abilities that small models cannot possess, forming a "crushing" competitive advantage.

        Jiang Xiaojuan believes that to evaluate the social value of artificial intelligence, it is necessary to go beyond a single efficiency dimension and establish a multidimensional indicator system that covers intergenerational fairness, group fairness, and opportunity fairness, ensuring that the achievements of technological progress are shared by all members of society.

        Collaborate strong and weak rules to build a dynamically balanced AI governance framework. Jiang Xiaojuan proposed that the governance of artificial intelligence should draw on the logic of the synergy between "endogenous market rules" and "government regulatory rules" in economics, and form an organic governance system that combines "weak rules" and "strong rules". Weak rules are the fundamental constraints of market games and social coordination, while strong rules are the bottom line guarantee of government regulation and legal constraints. For example, implementing negative list control, strengthening transparency requirements, and protecting the rights and interests of digital vulnerable groups. She specifically pointed out that the impact of the artificial intelligence technology revolution on employment is different from the historical situation of "more new jobs than old ones", and it is necessary to establish a more forward-looking social security and vocational training system to avoid social imbalances where "winner's gains" cannot offset "loser's losses".

        Artificial intelligence governance is not a simple rule making process, but a systematic engineering involving economic efficiency, social equity, and technological innovation. Jiang Xiaojuan stated that the core value of an economic perspective lies in providing quantifiable, comparable, and actionable analytical tools to transform governance goals from a "beautiful vision" to a "practical path". Only by adhering to the unity of efficiency and fairness, the coordination between the market and the government, and the equal emphasis on technological innovation and humanistic care, can we lay a sustainable institutional foundation for the development of artificial intelligence and truly achieve the ultimate goal of "technology benefiting humanity".