3. How can we use the combination of these approaches?
This innovative pipeline can be used to design decision-support systems that are safe, adaptive and actionable. More specifically,
it provides insight into the type and amount of information to present people, given their operational context. It does this by learning
models of how people encode and fuse information to form beliefs, and how that information needs to be updated across context. Moreover, it does
NOT use operator preferences to select information, as that can result in perpetuating or even amplifying biases.
Any other ways this can be used?
Since we are leveraging simulation data to train our low-fidelity models, we can begin to evaluate the risk associated with introducing new
technology into the operational setting at the concept stage of development. Normally, these data aren't available until after the technology has
been deployed, so this saves a great deal of time and money and assures only the safest and most effective technology is developed.