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DARPA wants to build an AI to find the patterns hidden in global chaos

That most famous characterization of the complexity causality, a butterfly beating its wings and causing a hurricane on the other side of the world, is thought-provoking but ultimately not helpful.

new program at the research agency is aimed at creating a machine learning system that can sift through the innumerable events and pieces of media generated every day and identify any threads of connection or narrative in them.

“The process of uncovering relevant connections across mountains of information and the static elements that they underlie requires temporal information and event patterns, which can be difficult to capture at scale with currently available tools and systems,” said DARPA program manager Boyan Onyshkevych in a news release.

KAIROS, the agency said, “aims to develop a semi-automated system capable of identifying and drawing correlations between seemingly unrelated events or data, helping to inform or create broad narratives about the world around us.”

The military and defense applications are fairly obvious: imagine a system that took in all news and social media posts and informed its administrators that it seemed likely there would be a run on banks, or a coup, or a new faction emerging from a declining one.

Intelligence officers do their best to perform this task now, and human involvement will almost certainly never cease, but they would likely appreciate a computer companion saying, “there are multiple reports of stockpiling, and these articles on chemical warfare are being shared widely, this could point to rumors of terrorist attack”

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This clever AI hid data from its creators to cheat at its appointed task

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