Trust Issues at 35,000 Feet: Assuring AI Digital Twins Before They Fly
Trust Issues at 35,000 Feet: Assuring AI Digital Twins Before They Fly Airspace is a bad place to discover that your simulation was “mostly right.” That sentence is obvious enough to sound useless, but it points to the real issue. For an AI-enabled digital twin of air traffic control, being “accurate” is not one property. It is a stack of claims. The data must be representative. The software representation must preserve the right details. The trajectory predictor must handle uncertainty rather than pretending aircraft behave like obedient geometry. The AI agents using the twin must receive, act on, and explain information without corrupting the control problem on the way. ...