Now, 'smarter' computer programmes that think like humans

Researchers have created a computer programme that can score 150 in IQ tests, in which the average score for humans is 100.

IQ tests are based on two types of problems: progressive matrices, which test the ability to see patterns in pictures, and number sequences, which test the ability to see patterns in numbers.

The most common math computer programmes score below 100 on IQ tests with number sequences. For Claes Strannegard, researcher at the Department of Philosophy, Linguistics and Theory of Science, this was a reason to try to design 'smarter' computer programmes.

"We're trying to make programmes that can discover the same types of patterns that humans can see," he said.

The research group, which consists of Claes Strannegard, Fredrik Engstrom, Rahim Nizamani and three students working on their degree projects, believes that number sequence problems are only partly a matter of mathematics – psychology is important too. Strannegard demonstrates this point:

"1, 2, …, what comes next? Most people would say 3, but it could also be a repeating sequence like 1, 2, 1 or a doubling sequence like 1, 2, 4. Neither of these alternatives is more mathematically correct than the others. What it comes down to is that most people have learned the 1-2-3 pattern."

The group is therefore using a psychological model of human patterns in their computer programmes. They have integrated a mathematical model that models human-like problem solving.

The programme that solves progressive matrices scores IQ 100 and has the unique ability of being able to solve the problems without having access to any response alternatives.

The group has improved the programme that specialises in number sequences to the point where it is now able to ace the tests, implying an IQ of at least 150.

"Our programmes are beating the conventional math programmes because we are combining mathematics and psychology. Our method can potentially be used to identify patterns in any data with a psychological component, such as financial data."

"But it is not as good at finding patterns in more science-type data, such as weather data, since then the human psyche is not involved," added Strannegard.