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WHY THIS MATTERS IN BRIEF

An AI capable of monitoring the whole world for threats, of any kind, is a huge undertaking and could become the world’s first “global” intelligence platform.

 

DARPA already has a reputation as the mad scientist lab of the US military, thanks to a range of projects that include uploading knowledge directly to people’s brains, using brainwaves to control fleets of advanced F-35 fighter jets, and turning animals and plants into giant living sensor networks, and that’s just for starters. But now their latest project raises the bar yet again – to create an Artificial Intelligence (AI) that can monitor the entire world for threats. And for those of you thinking of something that one day could resemble the infamous Terminator Skynet system, well, that’s already shown up, so you can consider this newest project as the “cherry on the cake” so to speak.

 

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In short DARPA want to create an AI that finds the original butterfly so often referred to in the infamous Chaos Theory – the butterfly that flaps its wings on one side of the world that causes a hurricane on the other. In Or in DARPA’s case the event in one place that eventually causes everything from terrorist bombings to revolutions in another place.

The new program is aimed at creating an AI capable of sifting through the innumerable events and pieces of media generated every day to identify any threads of connection or narrative in them, and the program is called KAIROS, short for Knowledge-directed Artificial Intelligence Reasoning Over Schemas.

“Schema” in this case has a very specific meaning. It’s the idea of a basic process humans use to understand the world around them by creating little stories of interlinked events. For example, when you buy something at a store, you know that you generally walk into the store, select an item, bring it to the cashier, who scans it, then you pay in some way, and then leave the store. This “buying something” process is a schema we all recognise, and could of course have schemas within it itself or even be part of another schema, such as giving a gift.

Although these are easily imagined inside our heads they’re surprisingly difficult to define formally in such a way that a computer system would be able to understand. They’re familiar to us because of our experience and the way our brains work, but they’re not immediately obvious or rule based. And the more data there is the more difficult they are to define.

 

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Buying something is comparatively simple, but how do you create a schema for recognising a cold war, or a bear market? That’s what DARPA wants to look into.

“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.”

How? Well, they have a general idea but they’re looking for expertise. The problem, they note, is that schemas currently have to be laboriously defined and checked by humans. At that point you might as well inspect the information yourself. So the KAIROS program aims to have the AI teach itself, much ion the same way that elsewhere Google DeepMind’s Alpha Zero AI platform is now self-learning and “producing its own knowledge.”

At first the system will be limited to ingesting data in massive quantities to build a library of basic schemas. By reading books, watching news reports, and so on it should be able to create a laundry list of suspected schemas, like those mentioned above. It might even get a hint of larger, more hazy schemas that it can’t quite put its virtual finger on — love, racism, income disparity, and so on — and how others might fit into them and each other. Next it will be allowed to look at complex real-world data and attempt to extract events and narratives based on the schemas it has created.

 

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The military and defense applications are fairly obvious. Imagine a system that can take in all news and social media posts and inform its administrators that it looks likely there’ll be a run on the 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 rumours of terrorist attack,” or the like.

Of course at this point it is all purely theoretical, but that’s why DARPA is looking into it – the agency’s raison d’etre is to turn the theoretical and crazy into the practical and every day, or failing that, at least find out why they can’t. Given the extreme simplicity of most AI systems these days it’s hard to imagine one as sophisticated as they clearly want to create, but never-the-less that hasn’t stopped them turning science fiction into science fact before, and my bet is that one day KAIROS will be everything they wanted it to be… that is until it tries to run the world, something that even Elon Musk is worried about.

About author

Matthew Griffin

Matthew Griffin, award winning Futurist working between the dates of 2020 and 2070, is described as “The Adviser behind the Advisers” and a “Young Kurzweil.” Regularly featured in the global press, including BBC, CNBC, Discovery and RT, Matthew’s ability to identify, track, and explain the impacts of hundreds of revolutionary emerging technologies on global culture, industry and society, is unparalleled. Recognised for the past six years as one of the world’s foremost futurists, innovation and strategy experts Matthew is an international speaker who helps governments, investors, multi-nationals and regulators around the world envision, build and lead an inclusive, sustainable future. A rare talent Matthew sits on several boards and his recent work includes mentoring Lunar XPrize teams, building the first generation of biological computers and re-envisioning global education with the G20, and helping the world’s largest manufacturers ideate the next 20 years of intelligent devices and machines. Matthew's clients include three Prime Ministers and several governments, including the G7, Accenture, Bain & Co, BCG, BOA, Blackrock, Bentley, Credit Suisse, Dell EMC, Dentons, Deloitte, Du Pont, E&Y, HPE, Huawei, JPMorgan Chase, KPMG, McKinsey, PWC, Qualcomm, SAP, Samsung, Sopra Steria, UBS, and many more.

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