CBM-I training and its effect on interpretations of intent, facial expressions, attention and aggressive behavior

There is abundant evidence suggesting that attention and interpretation biases are powerful precursors of aggression. However, little is known how these biases may interact with one another in the development and maintenance of aggression. Using cognitive bias modification of interpretation (CBM-I), the present study examined whether training more pro-social or hostile intent attributions would affect attention bias, interpretation bias of facial expressions, aggression and mood. University students (17–48 years) were assigned to either a positive training (n = 40), negative training (n = 40), or control training (n = 40). Results showed that the positive training successfully changed measures of intent attributions in a pro-social direction compared to the control training. The negative training changed measures of intent attributions in a hostile direction but not more so than the control training. We found no generalization of the training effects to relevant other outcomes. Possible explanations underlying these findings are discussed.

Detection of Hostile Intent by Spatial Movements

Objective The ability of people to infer intentions from movement of other vessels was investigated. Across three levels of variability in movements in the path of computer-controlled ships, participants attempted to determine which entity was hostile. Background Detection of hostile intentions through spatial movements of vessels is important in an array of real-world scenarios. This experiment sought to determine baseline abilities of humans to do so. Methods Participants selected a discrete movement direction of their ship. Six other ships’ locations then updated. A single entity displayed one of two hostile behaviors: shadowing, which involved mirroring the participant’s vessel’s movements; and hunting, which involved closing in on the participant’s vessel. Trials allowed up to 35 moves before identifying the hostile ship and its behavior. Uncertainty was introduced through adding variability to ships’ movements such that their path was 0%, 25%, or 50% random. Results Even with no variability in the ships’ movements, accurate detection was low, identifying the hostile entity about 60% of the time. Variability in the paths decreased detection. Detection of hunting was strongly degraded by distance between ownship and the hostile ship, but shadowing was not. Strategies employing different directions of movement across the trial, but also featuring some runs of consecutive movements, facilitated detection. Conclusions Early identification of threats based on movement characteristics alone is likely to be difficult, but particularly so when adversaries employ some level of uncertainty to mask their intentions. These findings highlight the need to develop decision aids to support human performance.

Vulnerable Civilians: Coalition Checkpoints and the Perception of Hostile Intent

This chapter examines civilian casualties at coalition checkpoints in Afghanistan and Iraq, focusing on the decision to use lethal force against individuals considered to be hostile. Drawing on the testimony of American soldiers, this chapter argues that the decision to use lethal force can be seen as an affective judgement, with soldiers often resorting to ‘muscle memory’ as they sought to identify potential threats amidst the chaos and confusion of war. It will argue that these affective judgements do not occur within a cultural vacuum but are animated and informed by a set of background assumptions that mark certain populations as dangerous, threatening and hostile before they even arrive on the scene. To understand what made civilians so vulnerable to death and injury at coalition checkpoints, it will be necessary to inquire into the affective schemes of intelligibility that render certain lives disposable and certain bodies profoundly injurable in war.

Rules of Engagement and Self-Defence

This chapter discusses the interaction between (the law of) self-defence and the rules of engagement (ROE), and how they play out against the military, and subsequently the political objectives of governments. It analyses the various forms of self-defence, from a national to individual perspective, including unit self-defence and force protection, and examines the legal basis and framework for each type of self-defence. The chapter goes on to analyse how these frameworks interact with, and influence, the ROE for military operations, discussing the concepts and applications of Hostile Act and Hostile Intent as followed by the North America Treaty Organization and the European Union in specific detail.

Dangerous feelings: Checkpoints and the perception of hostile intent

Between 2006 and 2007 an average of one Iraqi civilian was killed or injured at a coalition checkpoint each day. In many cases, civilians were shot because soldiers had misinterpreted their behaviour as hostile or as a demonstration of hostile intent. In other words, the soldiers responsible thought that they were acting in self-defence against an imminent threat. Some analysts have argued that these killings can be explained by ambiguities in the rules of engagement, but such explanations wrongly assume that the decision to kill is a purely rational calculation. Drawing upon the work of Sara Ahmed, William Connolly and George Yancy, I will argue that the interpretation of hostile intent and the decision to use lethal force are affective judgements rather than purely conscious decisions and, as such, are shaped by feelings, moods and intuitions. Moreover, I will argue that these judgements are never entirely neutral but clouded by a set of pre-existing assumptions that mark certain bodies as dangerous before they even have a chance to act. Drawing upon an archive of incident reports filed in the aftermath of these shootings and interviews with former soldiers, this article will show how seemingly innocuous behaviours were so readily mistaken for hostile acts with decidedly deadly consequences for the local population.