Just as factory jobs were eliminated in the twentieth century by new assembly-line robots, Brad and I were the first knowledge-industry workers put out of work by the new generation of ‘thinking’ machines. ‘Quiz show contestant’ may be the first job made redundant by Watson, but I’m sure it won’t be the last.
That was an insightful conclusion. While machines had bested humans at things like chess and solving maths problems – feats we typically associate with genius – they did so by brute force, completing incomprehensible numbers of calculations. Deep Blue assessed 200 million chess positions per second – a colossal number made possible by riding the wave of Moore ’s Law and exponential progress. Those trends have only continued, meaning that today you can download a chess engine programme like Houdini 6 for your home computer and it would beat Deep Blue almost every time.
And yet a paradox has emerged. It has become clear that more ‘processor power’ is actually required for managing what we have historically considered to be low-level tasks for humans, such as motor-sensory coupling, spatial awareness and unanticipated responses. In other words, it is harder to build a machine that can wash the dishes than one that can solve complex mathematical problems. This contradiction is known as Moravec’s Paradox, after the technologist who defined it. From the perspective of technological unemployment it was a hugely important observation, showing how even ‘low-skilled’ jobs, from construction to fruit picking, could remain immune from automation. Even as machines beat chess grandmasters and former supercomputers found their processing power equalled by \$400 games consoles, they could barely walk up a flight of stairs.
For a while this paradox appeared intractable. Even at the turn of the twenty-first century, some fifty years after the
Full Automation
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