America's Data-Swamped Spy Agencies Pin Their Hopes On AI (phys.org)

An anonymous reader quotes Phys.org: Swamped by too much raw intel data to sift through, US spy agencies are pinning their hopes on artificial intelligence to crunch billions of digital bits and understand events around the world. Dawn Meyerriecks, the Central Intelligence Agency's deputy director for technology development, said this week the CIA currently has 137 different AI projects, many of them with developers in Silicon Valley. These range from trying to predict significant future events, by finding correlations in data shifts and other evidence, to having computers tag objects or individuals in video that can draw the attention of intelligence analysts. Officials of other key spy agencies at the Intelligence and National Security Summit in Washington this week, including military intelligence, also said they were seeking AI-based solutions for turning terabytes of digital data coming in daily into trustworthy intelligence that can be used for policy and battlefield action.

Comments

Re:What could possibly go wrong?

[ShanghaiBill]

Expert systems are subject to "mistakes" like identifying all rainy pictures as "Tank!" because all the training pictures of tanks were taken on a rainy day.

That is a weakness of neural nets, not "expert systems". Expert systems (popular in the 1980s) and neural nets are opposite approaches. Neural nets are trained on raw data, and use machine learning to automatically extract important features. Expert systems encode knowledge and decision making of human experts, and are generally manually constructed.

Re:What could possibly go wrong?

[phantomfive]

Note that neural networks still frequently use a tagged system to learn to recognize things, but they detect features on their own........whereas in expert systems, all potential features are hard-coded.