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The flawed Silicon Valley consensus on AI

Serious questions remain about what will happen if we do — and don’t — replicate human intelligence

Oscar Wilde once defined fox hunting as the unspeakable in pursuit of the uneatable. Were he alive today he might describe the quest for artificial general intelligence as the unfathomable in pursuit of the indefinable.

Many hundreds of billions of dollars are currently being pumped into building generative AI models; it’s a race to achieve human-level intelligence. But not even the developers fully understand how their models work or agree exactly what AGI means. 

Instead of hyperventilating about AI ushering in a new era of abundance, wouldn’t it be better to drop the rhetoric and build AI systems for more defined, realisable goals? That was certainly the view at a conference hosted by the University of Southampton and the Royal Society last week. “We should stop asking: is the machine intelligent? And ask: what exactly does the machine do?” said Shannon Vallor, a professor at the University of Edinburgh. She has a point.

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