Kill Decision(7)
“Pentagon says it wasn’t our drone.”
“We both know that hardly matters. So you tell me: Are drones helping us or hurting us, Colonel?”
The colonel seemed familiar with this sort of intense debate with his subordinates. He remained calm. “Like it or not, Sergeant, fifty other nations are developing their own drones as fast as they can.” He paused. “Which is, in fact, why I’ve called you here.”
Odin frowned in confusion.
“Are you familiar with the term lethal autonomy?”
Odin nodded. “Autonomous combat drones.”
“Yes. Drones that fly themselves and make a kill decision without direct human involvement.”
Odin considered this with some dismay. “That’s a major RMA, sir.”
“Tell me why it’s a revolution in military affairs.”
“Because it would combine all the worst aspects of cyber war—anonymity and scalability—with the physical violence of kinetic war. A successful design could be stolen and cheaply punched out by the tens of thousands in offshore factories, then sent anonymously against anyone without fear of retribution.”
The colonel regarded Odin then nodded to himself, apparently having made a decision. “I have a mission for your team, Master Sergeant. A mission that requires someone who, as you so aptly put it, can think for himself, both strategically and tactically. I’m adding you to the BIGOT list for a highly compartmentalized SAP, code-named Project Ancile. You’ll be one of only three people who know it exists, and you are to report to me and only me.”
“What’s my objective?”
The colonel closed his laptop and focused his gaze on Odin. “You are to discover the source of the drone attacks on the continental United States.”
“You’re referring to the terror bombings, sir?”
“That’s a cover story. The truth is more worrisome. We think whoever was behind the Karbala attack is also behind the CONUS attacks.”
Odin considered the implications.
“One more thing.” The colonel paused for emphasis. “You are to pursue your mission no matter where it leads you—even if you are commanded to stop. You must continue, and you must succeed. Do you understand me, Master Sergeant?”
Odin nodded. “Yes, I believe I do, sir.”
CHAPTER 3
Raconteur
“Good afternoon, ladies and gentlemen. My name is Joshua Strickland, team lead for visual intelligence development here at the Stanford Vision Lab. I’d like to thank you all for coming today.”
Strickland stood at the head of a darkened, windowless lecture hall in the basement of the Gates Computer Science Building. Beside him the camera-eye logo of the Vision Lab filled a large projection screen. In the PowerPoint afterglow he saw familiar and unfamiliar faces among a small audience seated primarily in the front two rows. He focused on the serious faces seated just before him.
“An especially warm welcome to our distinguished guests from the Transformational Convergence Technology Office. Thanks also to our faculty advisor, Doctor Lei Li, without whose support we would not be presenting to you today.”
There was timid applause from somewhere in the darkness.
Strickland paused to collect his thoughts. So much was riding on this. He took a breath then began, “What you’re about to see is a visual intelligence technology we call Raconteur.” A click of his wireless remote, and the slide changed to an animation of dozens, then hundreds, and then thousands of individual video insets, swarming. It was a vast stream of graphic data. “Visual intelligence is often confused with ‘computer vision’—but it’s much more than that. Visual intelligence means giving machines the ability not merely to identify objects in images—which has been possible for years—but the cognitive ability to discern what’s occurring in a scene. Concept detection, integrated cognition, interpolation— prediction. What could have happened, and what might happen next. It means giving machines not only the ability to see but to understand what they see.”
He searched the faces of those front and center. “Why is this important?”
He clicked the remote, and the slide changed to surveillance images of London subway bombers moving through stations and standing in railcars. “In an increasingly dangerous world, video surveillance represents society’s best hope to detect threats before they materialize. But this flood of visual imagery means an exponential increase in the volume of surveillance video that must be analyzed—and analyzed real-time if it is to be of use not just in reviewing criminal acts after the fact but in preventing criminal acts.”