[Scientists Are Disappearing] ⑤ Korea Lacks Structures for Long-Term Researcher Growth… What Is the Solution?

Editor’s NoteThe declare that scientists are disappearing might sound exaggerated. After all, the variety of graduate college students in science and engineering and funding in analysis and improvement (R&D) have, statistically, remained regular. However, the actuality in analysis settings may be very totally different: unfilled graduate applications, extended postdoctoral positions, and analysis labs in provincial areas that stay eerily silent. Through this collection, The Asia Business Daily has sought to reply the query, “Why are scientists disappearing?” We have explored what modifications in coverage and apply are wanted to create a Korea the place scientists can stay and proceed their analysis over the long run.

“The problem facing Korea’s science and technology sector today is not a lack of talent. We’ve trained people, but we have not created a system in which researchers can stay and grow over time.”

KiBeom Park, Senior Research Fellow at the Science and Technology Policy Institute (STEPI) (pictured), provided this analysis of the present disaster in science and engineering throughout an interview with The Asia Business Daily on May 20. Since the Nineteen Nineties, Korea has persistently elevated its pool of science and expertise expertise, however has didn’t construct a analysis ecosystem and labor market able to absorbing and nurturing these people. He pressured, “Now is the time to move beyond quantitative expansion and shift policy direction to structures that enable researchers to grow in the long term.”

Senior Research Fellow Kibum Park of the Science and Technology Policy Institute (STEPI) is being interviewed by The Asia Business Daily on the twenty second. Provided by STEPI

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“The Real Issue is Not a Lack of STEM Talent, but a Lack of Research Jobs”

Senior Research Fellow Park additionally identified at a latest joint discussion board hosted by the National Assembly, the Korean Federation of Science and Technology Societies (KOFST), and the Korean Academy of Science and Technology that the expertise improvement coverage centered on increasing graduate faculty capability has already reached its restrict. He believes the core drawback is now a mismatch between provide and demand, not a scarcity of expertise. He mentioned, “In the past 30 years, Korea has essentially never lacked science and engineering talent in quantitative terms,” and advised, “From now on, policy efforts should focus on creating high-quality R&D jobs and long-term career structures, rather than simply expanding headcount.”

Senior Research Fellow Park sees the weakening of regional analysis ecosystems as a national-level disaster. He mentioned, “If the current trend of concentration in the Seoul metropolitan area continues, some regional universities may struggle even to recruit graduate students,” and added, “Once a regional research ecosystem collapses, it is difficult to restore it in the short term simply by injecting funding.”

He additional analyzed that whereas not all non-metropolitan areas are affected concurrently, the focus of analysis personnel and college students in choose universities and fields is quickly widening inner disparities inside areas. He emphasised, “So far, policy has centered on increasing research funding and graduate school capacity, but going forward, a national strategy is needed to determine which universities and research fields should be sustained over the long term.”

Regarding the short-term challenge construction and extended postdoctoral durations, Park famous, “The current system places excessive uncertainty on young researchers,” and noticed, “Paradoxically, the more talented individuals are, the more likely they are to leave research early.” He advised, “It is time to move beyond evaluation based on paper count and short-term achievements, and build career safety nets that enable young researchers to grow into independent scientists in the long run.”

Can AI Replace Empty Research Labs?

In excessive environments the place fewer folks should course of extra papers and knowledge, there may be growing dialogue about whether or not synthetic intelligence (AI) can function a practical various to keep up analysis productiveness. This is as a result of generative AI is quickly permeating all facets of analysis, from literature search and summarization to experiment design, knowledge evaluation, and code writing. In the subject, some even say, “AI can easily perform the equivalent work of a skilled graduate student.”

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Experts additionally agree that in the analysis subject, utilizing generative AI for drafting papers, exploring experimental circumstances, and visualizing knowledge is more and more accelerating the tempo of analysis.

Cha Miyeong, Director of the Max Planck Institute for Security and Privacy (MPI-SP) in Germany, mentioned, “AI can reduce a significant portion of repetitive tasks such as data analysis, literature search, and basic code writing. Tasks that once took a graduate student days to complete can now often be handled by AI in just a few hours.” She added, “Just like a one-person startup, research labs may be reorganized into small, highly efficient teams. We can expect to see the emergence of entirely new scientific professions that combine AI technology.”

However, she asserts that AI can’t absolutely change researchers. Director Cha acknowledged, “Orchestrating the overall direction and complexity of research will remain a core human domain. While AI can improve efficiency, the philosophical questions and value definitions—such as ‘why is this research necessary?’—will ultimately be left to humans.”

Senior Research Fellow Park drew an analogous line, stating, “AI cannot fully replace researchers.” He emphasised, “The crucial issue is what questions we choose to ask. In the AI era, the value of researchers with long-accumulated experience and a keen sense of the problems is likely to become even more important.” He left open the chance that the analysis ecosystem could possibly be reorganized via the use of AI. The elementary construction of analysis labs may shift from a ‘labor-intensive’ mannequin, the place many graduate college students conduct prolonged, repetitive experiments, to an ‘clever’ mannequin, the place a small variety of core researchers collaborate with AI and automatic techniques.

Kibeom Park, Senior Research Fellow at the Science and Technology Policy Institute (STEPI), is being interviewed by The Asia Business Daily on the twenty second. Provided by STEPI

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Senior Research Fellow Park famous, “If AI replaces a significant portion of repetitive tasks such as literature search, data processing, and code writing, the very structure of staffing in research labs may change. In the era of AI, it will be increasingly important to have researchers who can define problems and design new research directions, rather than simply perform repetitive research.”

He added, “Scientists are not made overnight. Science and technology talent policies must be redesigned—not around how many are produced, but around how long each researcher can grow and whether they can nurture the next generation.”

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