A.I. Is Harder Than You Think

Gary Marcus and Ernest Davis – New York Times

Coverage of Google’s recent announcement of a conversational AI which can sort out your restaurant bookings for you has largely taken one of two lines. The first is about the mimicry of human speech patterns: is it ethical for computers to um and er in a way which can only be intended to deceive their interlocutors into thinking that they are dealing with a real human being, or should it always be made clear, by specific announcement or by robotic tones, that a computer is a computer? The second – which is where this article comes in – positions this as being on the verge of artificial general intelligence: today a conversation about organising a hair cut, tomorrow one about the meaning of life. That is almost completely fanciful, and this article is really good at explaining why.

It does so in part by returning to a much older argument about computer intelligence. For a long time, the problem of AI was treated as a problem of finding the right set of rules which would generate a level of behaviour we would recognise as intelligent. More recently that has been overtaken by approaches based on extracting and replicating patterns from big data sets. That approach has been more visibly successful – but those successes don’t in themselves tell us whether they are steps towards a universal solution or a brief flourishing within what turns out to be a dead end. Most of us can only be observers of that debate – but we can guard against getting distracted by potential not yet realised.

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