One of the last overseas trips I undertook before Covid-19 shut our borders was to San Francisco to watch a supercomputer take on one of the world’s top debaters. Hundreds of us sat in an auditorium watching on as debate champion Harish Natarajan took to the stage across from a rectangular blue screen, IBM’s Project Debater. Both human and machine were given 15 minutes to prepare to debate whether preschool education should be subsidised.
While Natarajan scribbled down some notes, Project Debater’s massive brain trawled millions of newspaper articles and Wikipedia entries related to the topic. The machine’s comments in favour of the resolution, delivered in a measured female voice, were coherent, factual and compelling.
Natarajan ultimately won the debate by audience vote, with a more, well, human performance. His wit and emotion beat out logic and facts. But the spectacle was a reminder of how far artificial intelligence has come since IBM’s Deep Blue supercomputer outplayed Russian chess champion Garry Kasparov in a six-game match in May 1997.
In research labs around the world, teams of scientists are making important advances towards developing artificial general intelligence (AGI). If achieved, this wouldn’t just make it easier for us to converse with information-dispensing machines, a sort of supercharged Siri or Alexa, but allow AI systems to think like we do, tackling complex, wide-ranging problems, learning as they go.
With the advent of AGI, it becomes more efficient to outsource much of our problem-solving to the machines, as our human capabilities are rendered increasingly inferior. A parallel field of research in brain-machine interfaces could allow us to use that superintelligence to augment our own brain functions.
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