SenseTime's Xu Li: Recommend promoting public professional training for AI tools to foster diversified employment development

The value of AI lies not in replacing humans, but in amplifying human creativity.

On February 4th, Xu Li, member of the Shanghai Municipal Committee of the Chinese People’s Political Consultative Conference, Chairman and CEO of SenseTime, stated during the Fourth Session of the 14th Shanghai CPPCC that breakthroughs in model capabilities continue to drive the rise of “super individuals.” The super individual model is most suitable for scenarios that maximize the collaborative advantages of “single person + AI,” such as office work, short film creation, marketing, coding, and more.

In an interview with a reporter, Xu Li further explained the strategic significance of super individuals in the global AI competition landscape. He pointed out that current large model innovations in the U.S. are dominated by a “superstar” model, controlled by a few teams with substantial computing power and capital investment. China should instead consider how to build its own super individual ecosystem. “If large models are only used as cost-cutting and efficiency-boosting management tools, commercialization is difficult to close the loop; but once they are delivered as process-based solutions that empower individuals to complete tasks, the productivity explosion is very obvious.”

Xu Li noted that current tools generally face issues such as high application barriers, large learning costs, and limited widespread use of efficiency. The lack of a public professional training system has limited people’s utilization of these tools, preventing true technological “popularization,” creating a technological information gap, and becoming a key bottleneck in transforming creativity into actual productivity.

On the other hand, the enhancement of model capabilities heavily depends on scenario-driven needs, requiring customized solutions for specific industries or niche fields. The scarcity of high-quality scenario data limits the accuracy, generalization, and adaptability of models, making it difficult to meet the advanced needs of super individuals in practical work.

In response, Xu Li proposed two systemic suggestions during the Shanghai Two Sessions.

First, recommend the government to lead the development of a public professional training system for AI tools application.

He pointed out that current online courses in the market generally face two major issues: first, a lack of standardized qualifications and content; second, an overemphasis on profit, making it difficult to benefit the broad labor force. Therefore, it is necessary to systematically promote public, standardized AI tool usage training at the societal level. Taking Shanghai as an example, it is recommended that the Municipal Human Resources and Social Security Bureau lead, in cooperation with educational institutions and enterprises, to design and implement training programs covering scenarios such as office work, creation, marketing, and programming, helping workers master AI tools, expand their professional capabilities, enhance employment competitiveness, and promote diversified employment development.

Second, fully leverage Shanghai’s diverse application scenario advantages, promote “scenario first and trial first,” and encourage the development of super individuals through diverse exploration and practice.

Xu Li stated that Shanghai has rich and high-value application scenario resources in finance, trade, manufacturing, consumption, urban governance, and cultural creativity. It is recommended that the government organize special initiatives to solicit AI application scenarios from society, focusing on areas such as smart office, education, healthcare, and financial services. Through mechanisms like “unveiling the list and open scenarios,” guide and support super individuals to conduct diverse explorations and practices in real and cutting-edge environments, cultivating a batch of application results with demonstrative and scalable value.

Xu Li also emphasized in the interview that a large number of “one-person companies” (OPC) are emerging, whose practitioners generally have a deep understanding of AI and strong tool usage skills. However, these super individuals face two major challenges in development: first, those with AI technical understanding may lack deep industry knowledge; second, early native AI tools pose potential systemic risks and security hazards during use.

Therefore, Xu Li believes it is necessary to build an effective support service system around super individuals. This includes establishing systematic training and cultivation mechanisms to quickly popularize the underlying logic of AI tools among industry practitioners, thereby accelerating industry productivity. At the same time, safety boundaries should be established early in application, with forward-looking guidance to avoid future risks exposure that could force a passive governance model of “develop first, regulate later, and start over.”

(Source: The Paper News)