Google DeepMind co-founder says AI will end work-from-home (Image for representation: Freepik)
Artificial intelligence (AI) is not confined to pop culture trends such as Studio Ghibli, Nano Banana, and others. AI has now taken over several industries as it continues to roll out smarter tools that often boost efficiency and clarity in work, further enhancing its users’ experience. However, Shane Legg, Chief AGI Scientist and co-founder of Google DeepMind, recently stated that AI might end work-from-home, killing all remote jobs.
Speaking to Professor Hannah Fry in an interview, Legg explained how AI could wipe out large parts of remote work and cognitive skills. Emphasising human intelligence is far from what machines can do, Legg said, “Jobs that are purely cognitive and done remotely via computer are particularly vulnerable.” He added that companies will reduce teams as AI tools can give better or the same results as human minds.
“If you can do the job remotely over the internet just using a computer, then that job is potentially at risk,” he said.
Adding that AI will gradually reach professional-level capability and beyond in areas such as mathematics, coding, and complex knowledge work, Legg said, “My expectation is over a number of years these things will all get addressed.”
Legg further noted that there will be visible changes in software engineering, with teams of 100 engineers dramatically reducing as AI does major chunk of the workload, as machines can perform a significant part of cognitive work. “In a few years, where prior you needed 100 software engineers, maybe you need 20, and those 20 use advanced AI tools,” he said.
Comparing the growing use of AI to early 2020, Legg warned that ignoring these signals would be a mistake. “People find it very hard to believe that a really big change is coming,” he said, adding that major changes are foreseen when fundamental forces are in play.
However, Legg believes that AI could unlock a “real golden age” by boosting productivity, reducing human force assigned for work that machines can perform better, and advancing science. But, the real challenge, she stated, can be distribution, ensuring that people are not left without purpose or support and how societies share the wealth created by AI machines.