May 30 marks the 10th "National Science and Technology Workers' Day." The establishment of this day inspires scientific and technological workers to forge ahead on the path of building a world-leading technological power.
Young people are the hope of innovation and the future of science and technology. How can young researchers practice the spirit of innovation—scaling new heights and daring to lead? How can they leverage AI to improve research? How should they choose their professional directions? Regarding these topics, Xinhua Net interviewed Academician Mei Hong, a member of the Chinese Academy of Sciences and a professor at the School of Computer Science, Peking University.
Under the New AI for Science Research Paradigm
How Can Young Researchers Better Conduct Scientific Research?
AI technology is booming and is being deeply applied to scientific research. "Accelerating the exploration of new AI-driven scientific research paradigms and technology R&D models" has been written into the 15th Five-Year Plan outline. Under the new paradigm of AI for Science, how can young researchers use AI tools properly to enhance their research work?
"This wave of AI provides an automatic and effective means to process and analyze massive, multi-modal, high-dimensional data, which is extremely useful for our research." Speaking of AI for Science, Mei Hong believes its essence lies in applying artificial intelligence to research—i.e., AI-driven science.
Following experiments and theoretical deduction, the invention of computers made computation another crucial method for scientific research. In the past, computers helped scientists enhance computational abilities based on existing rules and formulas. Today, AI dramatically improves data processing capacity, and a significant part of scientific research involves processing and analyzing data.
Now AI is used not only for data processing but potentially in every step of the scientific process. Mei Hong hopes young researchers will actively embrace AI and use it well, but not blindly trust AI, nor neglect human agency in research. "Personally, I treat AI and computers as tools; they cannot replace humans in decision-making or analysis. We should not completely trust the results given by AI either. Researchers themselves must judge the final results."
AI offers data processing capabilities far beyond humans', but one thing cannot be ignored: where does scientific data come from? AI cannot generate genuine new data.
"We need more researchers to put in painstaking, diligent work—through experiments and observation—to obtain new scientific data." Mei Hong believes that on the basis of steadily accumulating new scientific data, we can use AI tools to analyze and utilize the data well.
AI Deeply Integrated into Education & Teaching
How Should Young People Choose Their Majors?
Against the backdrop of deep AI integration into education, how should young people who aspire to serve the country through scientific research choose their professional directions?
In Mei Hong's view, "Every discipline is necessary and needs people to work on it." He reminds parents and students that chasing hot majors is unnecessary; it's not advisable for everyone to crowd into the same track.
Taking computer science as an example, Mei Hong says: "This discipline mainly provides tools that empower other fields and sectors. It must be closely integrated with domain knowledge in various areas. For instance, in aerospace and space science, a large amount of scientific and engineering computing requires computers. After accumulating vast data, deep learning methods are needed to exploit that data. But where does the data come from? It comes from researchers in different fields through experiments and their dedicated work."
As science and technology develop, the boundaries of many disciplines gradually expand. Interdisciplinary research has become an inevitable trend. The empowerment of new technological tools like AI is giving rise to more cutting-edge interdisciplinary fields. Interdisciplinary areas are often where breakthroughs occur, and many universities are actively establishing frontier interdisciplinary research institutes.
Mei Hong argues that for research universities, undergraduate education should focus primarily on foundational knowledge and general education, while graduate students can choose specialized disciplines for further study. "No matter which major you choose, I believe that in the future, you must learn to use computers and artificial intelligence tools effectively."
While AI profoundly affects traditional disciplines, it also impacts the existing education system. How to cultivate innovative talents is a new challenge for universities.
"With AI, college students can learn on their own and no longer need teachers"—Mei Hong disagrees with this view circulating online. "Education is not merely about acquiring knowledge from teachers. For students, interpersonal communication, interaction, and mutual inspiration between teachers and students are also very important." He says, "AI will not completely replace teachers, nor will it completely overturn the existing higher education system. However, the education system needs to adapt accordingly. What can be done with tools and what must be done by humans requires continuous research, practice, and exploration. Historically, the education system has always adjusted along with the development of educational technology."
How Can Young Researchers Practice the Innovative Spirit of
"Scaling New Heights and Daring to Lead"?
The development of any field relies on generational inheritance and continuity—the field of scientific innovation is no exception.
"We stand on the shoulders of giants and do things that surpass our predecessors. This is the inexhaustible driving force of human social progress and an eternal pattern. It means the next generation must possess an innovative and critical spirit. Standing on the shoulders of predecessors, we can take one step further, doing what predecessors never did or dared to do, and doing what peers never do or dare to do. That is the essence of daring to lead." Mei Hong says.
Today, the construction of Digital China is accelerating. Amid the great tide of the digital era, how can young researchers practice the innovative spirit of "scaling new heights and daring to lead"?
Mei Hong indicates that the current wave of AI is essentially a breakthrough brought by machine learning and deep learning. If researchers merely use machine learning and deep learning to process data, such purely applied work can hardly produce original or even disruptive results.
"We need more young researchers who, on the basis of understanding the underlying logic of their own disciplines, use existing tools well and choose more forward-looking or even less popular topics." Mei Hong calls on researchers to remain calm amidst the hype, avoid blindly chasing hot trends, be daring to lead, and brave the "uncharted territories" of science and technology.
"Young people are the future of our country, and young researchers are the future of our scientific enterprise." On the occasion of the 10th National Science and Technology Workers' Day, Mei Hong shares three messages with researchers:
[Editor: Chen Tingyu]
