Presupposing the declarative nature of learning in IP systems is sufficiently similar to knowledge-level learning in humans, IP systems could be augmented with a Cognitive User Interface with the ultimate goal that machines interact like humans, and evaluate whether in this way they can become more intuitive, trustable, familiar, and predictable—including predicting when the system is going to fail.