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Humans are used to being outdone by computers when it comes to recalling facts, but they still have the upper hand in an argument. For now.
It has long been the case that machines can beat us in games of strategy like chess.
And we have come to accept that artificial intelligence is best at analyzing huge amounts of data – sifting through the supermarket receipts of millions of shoppers to work out who might be tempted by some vouchers for washing powder.
But what if AI were able to handle the most human of tasks – navigating the minefield of subtle nuance, rhetoric and even emotions to take us on in an argument?
It is a possibility that could help humans make better decisions and one which growing numbers of researchers are working on.
Until very recently, the creation of machines that can argue was an unattainable goal.
The aim is not, of course, to teach computers how to up the pressure in a feisty exchange over a parking space, or to resolve whose turn it is to take out the bins.
Instead, machines that can argue would inform debate – helping humans challenge the evidence, look at alternatives and robustly draw conclusions.
It is a possibility which could advance decision making on everything from how a business should invest its money, to tackling crime and improving public health.
But teaching a computer how people communicate – and what an argument actually is – is extraordinarily complex.
Think about a courtroom as an example of where arguments are central.
Giving evidence is certainly a part of the process, but social rules, legal requirements, emotional sensitivities, and practical constraints all influence how advocates, jury members, and judges formulate and express their reasoning.
Over the past couple of years, however, researchers have started to think that it might be possible to model some aspects of human arguments.
Work is now underway to capture how such exchanges work and turn them into AI algorithms.
This is a field known as argument technology.
The advances have been made possible by a rapid increase in the amount of data available to train computers in the art of debate.
Some of the data is coming from domains like intelligence analysis; some from specialized online sources and some from broadcasts such as the BBC’s Moral Maze.
New methods to teach computers how arguments work have also been developed.
Researchers in the area draw on philosophy, linguistics, computer science and even law and politics in order to get a handle on how debates fit together.
At the University of Dundee, we have recently even been using 2,000-year-old theories of rhetoric as a way of spotting the structures of real-life arguments.
The rapid advances in the field have led to dozens of research labs around the world applying themselves to the problem, and the explosion in this area of research is like nothing else I have witnessed in 20 years in academia.
‘Why is the sky blue?’
Does this mean that computers will soon be fluent orators on the verge of taking over the world?
No. Let me give you a mundane example.
Until very recently even the most sophisticated AI techniques would have been completely flummoxed by pronouns.
So if you say to your smartphone’s personal assistant: “I like Amy Winehouse. Play something by her,” the software would be unable to work out that by “her” you mean “Amy Winehouse”. Hardly the stuff of robot-apocalypse nightmares.