As the gap between human and machine shrinks, it becomes increasingly important to develop computer systems that incorporate or enhance existing Situation Awareness. However, these tend to focus on raw quantitative parameters, such as position and speed of objects. When these situations are governed by human actors, such parameters leave significant margins of uncertainty. In this paper, we discuss the potential of applying the characteristics intrinsic to the human actors that comprise a given situation to Situation Awareness, and the capacity that these concepts have to improve situation-aware systems. We argue that intention-aware based systems offer an advantage over situation-aware based systems in that they reduce the informational burden on humans without limiting effectiveness. We argue that computational analysis and tracking of semantic and affective information associated with human actors' intentions are an effective way to minimize miscommunication and uncertainty, particularly in time-sensitive and information-saturated situations.
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