The name, "Tactical Intelligence Targeting Access Node" (TITAN), is pretty clever. Peter Thiel's Denver-Based Palantir Technologies, a software-driven data analytics company in the defense and intelligence domain, just won a US$178M contract to build an AI-driven mobile battlefield sensor fusion platform. From Palantir's home page: "AI-Powered Operations, For Every Decision". In this context, TITAN consumes a huge amount of data from remote sensors and tells soldiers what to destroy.
Cool. And absolutely necessary. Soldiers on the battlefield are inundated with information, more than humans can assimilate in the time they have. And even if we didn't build it, our peer adversaries surely will (or more likely, are).
This is the kind of neural network-based AI that's going to mistake a commercial airliner for an enemy bomber and recommend that it be shot down, even if its own cyber-finger isn't on the trigger. Because time is short, and if no other information is forthcoming, someone will pull that trigger.
In the inevitable following Congressional investigation, military officers, company executives, and AI scientists and engineers will be forced to admit that they have no idea why the AI made that mistake, and in fact they can't know, because no one can. When you have an AI with over a trillion - not an exaggeration - variables in its learning model, no one can understand how Deep Learning really works.
Seriously, this is a real problem in the AI field right now. AIs do things their own developers did not anticipate, and cannot explain.
Accidental commercial airliner shoot downs are so common they have their own Wikipedia page. And it's just a matter of time before the cyber-finger is on the trigger, because it can respond so more quickly than its overwhelmed human operators.
The worst thing that could happen is for TITAN be an unqualified success. Someone will get the idea that maybe such a system should have its cyber-finger on the red button for strategic ICBMs.
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