Artificial intelligence: the role of evolution in decision-making

Published in The Telegraph 

As far as decision-making mechanisms go, there is no better example than the human brain, so artificial intelligence must evolve to emulate it. Sally Percy reports

Strategy matters in war. But behind every good strategy is good data. Take Korean War veteran and US Air Force officer John Boyd as an example.

He was tasked with analysing the outcome of dogfights – aerial battles between fighter planes conducted at close range – and come up with a way to save the lives of more American pilots. He did.

What Boyd created was a framework for decision-making that is known as the OODA loop. OODA refers to the recurring cycle of four actions: observe, orient, decide and act. He discovered that the pilots who came out of dogfights most successfully were those who had processed the loop as quickly and as often as possible.

Their experience of reacting to lots of different situations meant they could best adapt their battle strategies to unfolding events.

“What Boyd was telling us was that surviving, learning and adapting were key to winning,” says Antoine Blondeau, the co-founder and co-chairman of Sentient Technologies and the inventor of the natural language technology behind Siri, Apple’s intelligent personal assistant. “Since then, that framework has been pervasive within the US armed forces. If you train, train and train, you go through that loop as often as possible.”

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