As DARPA put it:
ITM is taking inspiration from the medical imaging analysis field, where techniques have been developed for evaluating systems even when skilled experts may disagree on ground truth. For example, the boundaries of organs or pathologies can be unclear or disputed among radiologists. To overcome the lack of a true boundary, an algorithmically drawn boundary is compared to the distribution of boundaries drawn by human experts. If the algorithm's boundary lies within the distribution of boundaries drawn by human experts over many trials, the algorithm is said to be comparable to human performance.
On a practical level, the program is focused on medical treatment in the field, and has two phases: part one involves small-unit triage, and part two is triage involving mass casualties.
Matt Turek, ITM's program manager, said the plan is for an algorithmic decision-maker and human experts to both choose how to act in a situation. Those decisions are handed blindly to a pool of triage professionals, who then have to say which of the decision makers they would delegate to.
That's just the testing phase. Ultimately, ITM aims to take humans out of the decision-making loop by building AIs that people will trust to make the same sorts of decisions an expert would.