It is no longer new to say that artificial intelligence (AI) is changing the speed and methods of scientific research. Thanks to AI, calculations have become faster, predictions more precise, and designs so complex that it is hard for people to keep up by hand. The stronger the technology becomes, the clearer the questions: "Will AI really take the place of researchers?" and "If so, what should researchers do going forward?"
David Baker, a 2024 Nobel Prize in chemistry laureate and professor at the University of Washington, said in an interview with ChosunBiz at Yonsei University in Seodaemun-gu, Seoul, on the 6th, "AI has completely transformed protein design research," but drew a line, saying, "AI is a tool, after all." It is true that AI has made it possible to solve more difficult problems, but it cannot take over the responsibility of setting the direction of research and discerning the meaning of the results.
Professor Baker is a figure who expanded the horizons of life sciences by designing new proteins that do not exist in nature using AI. He is still continuing his research by using AI for protein design with the goal of developing and commercializing medicines.
He advised that Korea should prioritize talent and research culture over computing resources or infrastructure as elements to build competitiveness in AI bio and protein design. He said that in the AI era, research competitiveness comes not from one better model, but from an environment that can gather and connect good researchers. The following is a Q&A.
◇ "AI is a powerful tool, but choosing the questions is up to humans"
-What share does AI account for in protein design research?
"Our lab began focusing in earnest on developing AI-based methodologies around 2018–2019. We are still building the next generation of AI to design more complex proteins. From the perspective of methodology development, it is no exaggeration to say we have used AI in almost everything we have done over the past six years."
-What role will AI play in science and technology research? Will it replace researchers?
"No. It cannot replace them. AI is just a very powerful tool. In the past, sequencing itself felt like a major research project, but now it is routine analysis where you put in a sample and get the result the next day. I think AI will ultimately become that kind of tool."
-What are AI's limitations?
"What is harder than designing a protein with AI and validating it in the lab is turning it into an actual medicine and getting it through clinical trials. At this stage, public data is insufficient and our understanding of biology and medicine is still incomplete. So it is an area where AI cannot easily achieve immediate breakthroughs. AI can play a supporting role in designing proteins that will work better in manufacturing processes, but it is still far too early for it to dramatically shorten clinical development as a whole."
-As AI becomes better at protein design, what abilities matter for human researchers?
"The crux is still the questions. It is important to determine what problems are important, plan how to test design results, and judge how far we can trust AI's outputs. In the end, the fundamental questions of science do not change."
-Korea is also investing heavily in AI bio and protein design. Among computing resources, talent, experimental infrastructure, and data, what is most important for Korea to build world-class competitiveness?
"Talent is the most important. Competitiveness ultimately comes from securing good researchers and supporting them so they can dig into interesting problems for a long time. That said, protein design is not a field that grows just by promoting it in isolation. Because fundamental research in basic science, bio, chemistry, and computing must be strong together, I think it is desirable for Korea to support a diverse research base and grow protein design on top of that."
-What advice would you give to young researchers and graduate students in Korea?
"Rather than overcalculating the future, grab the problem that is most interesting and that you feel passionate about in that moment. Science often opens new paths not by following a set plan, but through the process of digging deeply into questions of interest. I, too, started from an interest in protein folding and structure prediction and came to protein design. What matters, in the end, is thinking long and hard about the problems you truly care about and working with people who are a good fit."
◇ A lab that becomes a "communal brain"… "Future interests include nanomachines and agriculture"
-How do you create an environment where researchers can collaborate freely and dig into interesting problems?
"I place importance on an environment where people naturally gather and talk continuously in the lab. We prepare free food in the lab every day so anyone can come and converse. We also share everything without secrets. That is because I believe difficult problems are solved better together than separately. I call this the 'communal brain.' Each researcher should be connected and interact like neurons. That is why I am almost always in the lab. Only then can I immediately see who is struggling and where a breakthrough has emerged, and help."
-You must have had more lectures and outside engagements after the Nobel Prize. How do you keep balance?
"I turn down most invitations. This visit to Korea happened exceptionally because I wanted to come with my wife, and because of my strong ties with Korean students. I still spend a lot of time in the lab as I used to."
-Beyond your current work, what topics would you like to take on in 5–10 years?
"It is hard to predict exactly. But I see great potential in nanomachines. Nanomachines are ultra-miniature mechanical systems designed to perform specific functions at the molecular or protein level, and they have broad application potential not only in medicine but across technology. Agriculture is also interesting. As the Earth warms, we can use protein design to create more stable plants at higher temperatures. What is clear is that I will not be doing the same kind of research as now."
-Why do you keep seeking new subjects?
"I tend to get bored easily. I do not like repeating the same work, and when a problem interests me, I keep holding on to it and thinking about it. Then, naturally, I move into new areas different from what others are already doing."
-What is your ultimate goal as a scientist?
"There is not a single ultimate goal in particular. I enjoy the very process of discovering new things while working with students and postdoctoral researchers in the lab. Of course, there are many big problems to solve, such as neurodegenerative diseases, but rather than setting a single goal, I prefer the process itself of tackling important problems together."