Could artificial neural networks make our public services smarter?

A few weeks ago, Google DeepMind’s AlphaGo beat the world’s highest-ranked Go champion, Lee Sedol, in a feat of machine intelligence that until recently many thought was still a decade away. This achievement is, at the very least, thought provoking. Unlike chess, the possibilities on a board of Go are virtually endless. It cannot be “brute-forced”, the strategy that the Deep Blue chess computer took in 1997 against Grandmaster Garry Kasparov, by processing every permutation. In this case the artificial intelligence does some extensive decision tree searching, but after that relies on something much more akin to — for lack of a better word —intuition. So how does this depart from traditional machine learning? And, more importantly, what does this approach mean for those of us looking to improve digital…


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