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Artificial intelligence boffins are developing scary technology which will allow robots to think exactly like humans.
In order to do so, the University of Glasgow's School of Psychology and Neuroscience researchers have analysed and compared the learning processes of both humans and computers.
Their new study uses 3D modelling to do this, mapping out what are known as "Deep Neural Networks", meaning how computers learn.
They say that, in order to achieve their goal of creating human-like AI, they need to fully understand this process. However, one sticking point is that they don't, as of yet.
Some scientists believe Deep Neural Networks are the best model of decision-making behaviour, achieving or even exceeding human performance in some tasks.
However, even in some simple tasks such as spotting differences between images, the machines get stuff wrong.
Deep Neural Network technology is currently used for facial recognition, and while it is very successful at some things scientists still don't fully understand how errors come to be.
Professor Philippe Schyns, senior author of the study and Head of the University of Glasgow's Institute of Neuroscience and Technology, explained that it is incredibly hard to get robots to think like us.
He said: "When building AI models that behave 'like' humans, for instance to recognise a person's face whenever they see it as a human would do, we have to make sure that the AI model uses the same information from the face as another human would do to recognise it.
"If the AI doesn't do this, we could have the illusion that the system works just like humans do, but then find it gets things wrong in some new or untested circumstances."
The researchers used a series of randomly generated faces and asked humans to rate their similarity to four familiar identities.
They then used this information to test whether the robots came to the same conclusions, crucially looking at whether they used the same information as humans to make their decisions.
It turned out that AI and humans draw on different information to analyse faces.
Researchers hope this work will pave the way for more dependable AI technology that behaves more like humans and makes fewer unpredictable errors.
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- Artificial Intelligence
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