Just like a toddler might be confused when they first see a box with legs walking towards it. Or mistake a hand puppet for a real living creature when they first see it. I've seen this first hand with my son (the latter).
AI tooling is already capable of identifying whatever it's trained to. The DARPA team just hadn't trained it with varied enough data when that particular exercise occurred.
For example, detecting the possible presence of a cavity inside an object X, and whether that cavity is large enough to hide another object Y. Learning generic geospatial properties like that can greatly improve a whole swath of downstream prediction tasks (i.e., in a transfer learning sense).
I take it you don't have any hands-on knowledge of the field. Because I've created systems that detect exactly such properties. Either directly, through their mathematical constructs (sometimes literally via a single OpenCV function call), or through deep classifier networks. It's not exactly rocket science.
That's a weird way to spell "murders"