It’s said that Henry Ford’s customers wanted a “a faster horse”. If Henry Ford was selling us artificial intelligence today, what would the customer call for, “a smarter human”? That’s certainly the picture of machine intelligence we find in science fiction narratives, but the reality of what we’ve developed is far more mundane.
Car engines produce prodigious power from petrol. Machine intelligences deliver decisions derived from data. In both cases the scale of consumption enables a speed of operation that is far beyond the capabilities of their natural counterparts. Unfettered energy consumption has consequences in the form of climate change. Does unbridled data consumption also have consequences for us?
If we devolve decision making to machines, we depend on those machines to accommodate our needs. If we don’t understand how those machines operate, we lose control over our destiny. Much of the debate around AI makes the mistake of seeing machine intelligence as a reflection of our intelligence. In this talk we argue that to control the machine we need to understand the machine, but to understand the machine we first need to understand ourselves.
Neil has been invited to give the Strachey Lecture in Computing science.
The Strachey Lecture in Computing Science is a termly series of Distinguished Lectures at the University of Oxford named after Christopher Strachey, the first Professor of Computation at Oxford University.
Christopher Strachey was the first leader of the Programming Research Group (PRG), part of the Oxford University Computing Laboratory (OUCL), founded in 1965. He was the first Professor of Computation at Oxford, succeeded by Sir Tony Hoare in 1977 after his untimely death. With Dana Scott he founded the field of denotational semantics, providing a firm mathematical foundation for programming languages.
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