Reporter Meng Xiaoxiao

He is known as the scientist who caught the "Schrödinger's cat" in the game of chasing light; He and his collaborators were awarded the Nobel Prize in Physics in 2012 for "discovering breakthrough experimental methods for measuring and controlling individual quantum systems".

Recently, during the annual meeting of the 81 Zhongguancun Forum, Serge Haroche, a 0-year-old academician of the French Academy of Sciences, accepted an exclusive interview with China Science News. "I'm too old to catch up with the AI bandwagon," he laughs. ”

"In basic science, we should not build walls that hinder the transfer and sharing of knowledge," Arosh called for at the meeting. Research of all kinds must be carried out internationally so that scientists can freely communicate and share. ”

Young researchers are more like "entrepreneurs"

China Science News: It has been more than 10 years since you won the Nobel Prize in Physics, do you think the research environment has changed?

AroshNowadays, young researchers are more like "entrepreneurs" who have to spend a lot of time writing proposals and securing funding. Early in a career, these jobs can be detrimental to the healthy development of basic science.

In fact, young scientists are being pushed into a highly competitive work environment and are expected to be able to achieve results quickly at an early stage. This means that research efforts will be more focused on short-term topics rather than "ambitious" long-term projects. This competition has led young researchers to eagerly pursue publications, which backfires because they may exaggerate the results of their research.

China Science News: How to get out of the "if you don't publish, you're out" dilemma?

Arosh: When I was younger, computer data analysis was not as developed as it is today, and I didn't need to answer quantitative data questions, but only needed to publish a qualitative report of my research work and provide it to my peers in related fields. The current situation is that a scientific research result is judged on the basis of quantitative data, numbers and rankings. In my opinion, rather than relying on quantitative indicators, it is better to have in-depth assessments by peers.

Whereas the current scientific community's over-reliance on the number of papers and publication records in high-impact journals forces young people to choose short-term, low-risk topics, quantitative metrics have replaced qualitative judgment. To change the status quo, it is necessary to establish an evaluation mechanism that is more focused on the quality of research and to make long-term projects more inclusive.

Scientific inquiry should come from the bottom up

China Science News: What do you think are China's strengths and room for improvement in basic research?

Arosh: Every time I visit a university or research institute in China, I am impressed by the financial support and the investment in equipment. China's scientific progress in the past 10 years is also remarkable, which is a positive phenomenon.

But I don't think there is enough freedom for young researchers in China to develop their own projects. The real big scientific breakthroughs often come from bottom-up exploration by scientists, who are free to choose unexplored areas of research and conduct open-ended research.

China Science News: You have a wealth of academic experience in different countries, can you share a little bit about other countries?

AroshIn the United States, Israel, and some European countries, young scientists have greater academic autonomy. If a young researcher shows outstanding potential, they are often given full trust and are allowed to freely choose their research direction. Usually, five or six years are given to evaluate whether they have achieved something and whether they are awarded tenure. The situation in France is somewhere in between, our scientific research system does not give such freedom, and we may be more respectful of seniority.

Be cautious about the application of artificial intelligence

China Science News: In recent years, artificial intelligence has developed rapidly, have you tried to use AI tools for research?

Arosh: Actually, I don't use artificial intelligence for research, I think I'm too old.

Artificial intelligence as a translator is very useful. When reading an Iranian paper, I use artificial intelligence to translate it; When I speak at a conference, AI can translate instantly. Artificial intelligence also plays an important role in research areas that need to process massive amounts of data. For example, in accelerator physics research, researchers need to analyze huge data sets; In the pharmaceutical industry, AI can help elucidate complex molecular or protein structures to accelerate the development of new drugs.

China Science News: Have you talked to young academics about how to use AI tools? Nowadays, some students even use AI tools to write essays.

Arosh: We have to make sure that doesn't happen. In the field of education, there are people who use AI to write essays, and there are people who try to use AI to cheat on exams, which is a serious problem. Therefore, we need tools to detect whether a paper is written by a human or generated by an artificial intelligence.

I think AI is an excellent tool if consumers have a solid background in the subject matter and can use it with critical thinking. But if you just copy text mechanically, or generate something you don't understand, you'll end up wasting time and not really learning.

China Science News: What specific advice do you have for researchers who are just starting their academic careers?

Arosh: Young researchers should recognize what their passions are and think about how they want to contribute to them. As soon as you find out that a field is undergoing a revolution and has the potential to lead to a major breakthrough, you should not hesitate to jump into it.

As far as I'm concerned, laser technology was in its infancy when I started my research career. I immediately realized that laser technology would open up completely new possibilities for the study of atomic physics. At the time, I had no way of foreseeing the technological changes and the impact that would follow in the next 60 years. Perhaps, artificial intelligence is one of the transformative technologies of the moment, and there are similar breakthroughs in the field of life sciences.

(Reporter Shen Chunlei also contributed to this article)