The essentials
- AI accelerates discovery. Google’s latest research shows how large language models and quantum computing are driving scientific breakthroughs, from cancer research to geospatial mapping.
- Humans still matter most. Yossi Matias, head of research at Google, says AI will not replace scientists: it will multiply their potential by removing repetitive obstacles to exploration.
- Automation as an opportunity. The same lesson applies to businesses: leaders who redeploy talent instead of shrinking it can unlock more innovation and long-term value.
Google’s search efforts have been successful of late. Over the past two weeks, the company announcement he used LLMs to find a potential new cancer treatment route, his quantum chip said ran an algorithm 13,000 times faster than traditional supercomputers and provides deeper geospatial data available via prompt on Earth AI.
I sat down with Yossi Matias, director of Google Research, for a conversation about the latest news during an event the company hosted at its Mountain View headquarters. Google has used the latest AI models in its research work – in the case of cancer, the model came up with a hypothesis that was proven true in living cells – and I wanted to hear Matias’s take on whether the technology could eventually replace human researchers.
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The researchers present a formidable test case for whether AI will eventually lead to large-scale displacement. Their work is experimental, unstructured and by definition addresses new problems. If AI can replace them, that could be bad news for the rest of us. But Matias shared a response that highlights how current discussions about AI and work often only tell part of the picture.
“We’re going to need a lot more researchers in all disciplines,” Matias told me. “The only situation where you need fewer researchers is if you assume that we have pretty much answered all the questions we need to ask. I don’t think anyone here in the public would think that. We only understand a tiny fraction of what we need to understand.”
Matias cited Google DeepMind’s efforts with AlphaFold, the AI initiative that decoded protein structures, as an example of AI actually creating more work for researchers because it automates processes. “We don’t have fewer researchers working on proteins. We actually have a lot more, don’t we?” he said. “But now they don’t need to work on the problem of protein folding. They actually use it for more important questions.”
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Can AI replace human researchers?
There are obvious parallels in the business world. When a CEO automates a job with AI, they can either fire the person whose job they automated or give them a new task. The conventional wisdom is that automation directly leads to layoffs. But this ignores the fact that most business leaders believe there is much more work to be done than they can reasonably entrust to their workforce. Smart CEOs hand over new problems to those whose work they automate.
This outlook is perhaps too optimistic. We are already seeing some companies plan use AI to reduce hiring. But to this day Generative AI did not lead to massive job losses. And where it has eliminated jobs, you really have to squint to see it.
“I look at this as AI as an amplifier of human ingenuity,” Matias said. “It really empowers scientists, health care workers, teachers and business people in our everyday lives.”
The leader of Google Research is encouraged to say so. But it is a perspective that at least deserves consideration amid the dominant discourse.
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