Transparent automation for assessing and designing better interactions between operators and partly-autonomous interactive systems

Human Automation Interaction deals with finding the best balance for the allocation of tasks and functions between operators and the systems being operated. Automation is typically addressed at a very high level i.e. at the procedures or tasks that have to be performed to reach a goal. When these automations are not adequately designed (or correctly understood by the operator), they may result in so called automation surprises [30], [36] that degrade, instead of enhance, the overall performance of the operations. However, such previous work on automation surprises have overlooked the importance of automation in order for the operator to trigger these tasks and the fact that an interactive command and control system has to be used. This interactive system usually integrates low level automation that might also result in automation surprises. The paper proposes a stepwise approach for identifying, describing and analyzing the automation level of interaction techniques in an explicit way. This approach provides support for analyzing potential automation surprises that can arise from the interaction technique but also for identifying how to modify them in order to reduce performance degradations due to automation surprises at the interaction level. Based on a classification of interaction techniques we demonstrate that a model-based approach can support the design and assessment of the automation that interaction techniques feature and that is usually hidden from the users.