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New study shows AI could make decisions like humans

A study by British researchers has shown a new machine learning method that enables computers to make decisions in a  more human-like way.

The research, which was published in the May issue of IEEE/CAA Journal of Automatica Sinica, explains how this new method allows machines to render several possible decisions to one specific problem, rather than a single best one.

Human decision-making is not perfect, the study claims, since it relies on variability, the tendency of reaching different decisions even when given the same exact input.

However, this same unpredictability could turn useful if applied to machine learning.

“If the problem domain is such that human experts cannot achieve 100% performance, then we should not expect a computer expert system in this domain to do so, or to put it another way: if we allow human experts to make mistakes, then we must allow a computer expert system to do so”, said Jonathan M. Garibaldi, Head of School of Computer Science at the University of Nottingham, UK and head of the Intelligent Modelling and Analysis Research Group.

The researchers have achieved this by introducing variation into artificial intelligence software through fuzzy inference—a system that adds an ‘if-then’ production of rules where data can be represented on a range between 0 to 1—rather than either 0 or 1.

By doing so, they were able to create a computer system that makes decisions with comparable variability as human experts.

“Exploring variation in the decision making is useful”, Garibaldi explained. “Introducing variation in [a] carefully controlled manner can lead to better performance. Unless we allow computer systems to make the same mistakes as the best humans, we will delay the benefits that may be available through their use.”

Garibaldi’s team intends to provide artificial intelligence with more human-like decision-making skills in order to act as a tool to help physicians avoid the “most wrong” choices among a range of potential options that a trained human doctor might select.

“Computers are not taking over but simply providing more decisions,” Garibaldi said. “This is time- and ultimately life-saving because disasters happen as a result of sub-optimal care.

“Computers can help avoid the glaring mistake that humans make as ‘adjunct experts’ in the room that rule out the wrong decisions and errors by providing a set of alternative decisions, all of which could be correct.”

Image via Pixabay and PXhere.

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