The US Department of Defense has deployed machine learning algorithms to identify targets in over 85 air strikes on targets in Iraq and Syria this year.
The Pentagon has done this sort of thing since at least 2017 when it launched Project Maven, which sought suppliers capable of developing object recognition software for footage captured by drones. Google pulled out of the project when its own employees revolted against using AI for warfare, but other tech firms have been happy to help out.
The more selective we convince ourselves our weapons are, the more willing we are to use them in conflicts where civilians are put at risk—our use of weapons is constrained by the level of collateral damage we’re willing to take responsibility for, and by distancing ourselves from that responsibility, AI allows us to escalate conflicts until civilians are at even greater risk. It’s the Jevons paradox, with human life instead of gasoline.