The weapons that will be used to fight tomorrow’s wars will need to address a very old problem: friendly fire. Researchers think complex algorithms can help by telling soldiers where to shoot, and where not to. But how much trust should soldiers place in a machine that helps them to decide who to kill?
“The reality is that soldiers are doing a very difficult task under very difficult circumstances,” Greg Jamieson, a researcher at the University of Toronto’s Cognitive Engineering Laboratory (CEL), told me over the phone. “So, if you can provide some kind of tool to help people make better decisions about where there’s a target or who this target is or the identity of that target, that’s in the interest of the civilian or non-aligned people in the environment.”
The problem is that the tool Jamieson is referring to, called automated target detection (ATD), doesn’t really exist in any sort of ready-to-deploy form for individual soldiers. So, in partnership with Defence Research and Development Canada (DRDC), Jamieson and the other researchers at CEL are tackling the research backwards: instead of testing new tech to see how soldiers respond, they’re testing soldiers to understand what they need out of new tech.