A Review of Transparency (seeing-into) Models

Humans often have difficulty accomplishing tasks in correspondence with automation with concealed inner workings. Researchers suggest that allowing humans to see into the inner workings of automation will lead to better understanding, trust in, reliance on, joint task completion with, and better situation awareness of the automation. We identified and compared four transparency models that assist researchers in designing and conducting empirical studies by guiding them on what, how, and when information on or about automation should be disclosed. The results of this review will assist researchers with understanding, identifying, and employing suitable transparency models to their applications.