Social Engineering Blogs

An Aggregator for Blogs About Social Engineering and Related Fields

Raising Awareness about Active Shooter Incidents

Active shooter incidents are incredibly frightening events that often have deadly consequences for individuals, and dire consequences for organizations. The term “active shooter” describes a “situation in which a shooting is in progress and an aspect of the crime may affect the protocols used in responding to and reacting at the scene of an incident” (Blair & Schweit, 2014, p. 4). Most government agencies in the U.S. define “active shooter” as an “individual actively engaged in killing or attempting to kill people in a confined and populated area” (Blair & Schweit, 2014, p. 5). Since they have been studied, active shooter incidents have been steadily increasing over the years (Figure 1), causing increasing numbers of casualties, including many who have been killed or wounded (Blair, Martaindale, & Nichols, 2014; Blair & Schweit, 2014).

Figure 1: Active Shooter Events by Year

Image retrieved from https://leb.fbi.gov/2014/january/image/figure-1.-active-shooter-events-by-year.jpg/image_preview.

 

Unsurprisingly, most of these events have occurred at businesses (Figure 2). Because these data are cause for grave concern for any organization, private or public, it is no wonder that many organizations are coming to grips with the reality of considering ways of dealing with, managing, and preventing these kinds of incidents to occur.

Figure 2: Locations of Active Shooter Incidents

Image retrieved from (Blair et al., 2014).

Obviously there are multitude of ways to approach this very important problem for security professionals. The first step is often raising awareness of this important issue, as many security professionals and organizations unfortunately remain in the dark about the frequency and/or severity of these types of events. Raising awareness alone is not enough; what is equally if not more important is to actively consider, implement, monitor, and refine a comprehensive security plan in order not only to deal with these incidents when they occur – as well as their aftermath – but also how to prevent them in the first place.

By now many security professionals have heard of the current rendition of the “best” response to an active shooter incident, involving the mantra “Run, Hide, Fight.” But let’s dive deeper into how this may actually occur in an active shooter situation. In reality, data on active shooter incidents have shown that 70% of such incidents ended in five minutes or less, with 37% ending in two minutes or less (Blair & Schweit, 2014). At the same time, the average (median) response time by law enforcement officers to the scene is about three minutes. These statistics indicate that civilians often have to make life and death decisions in a very short time, and in a very emotional situation. How to do so?

My many years of training athletes in Olympic judo competition gives us clues about how to approach the problem. These are also highly charged situations in which split second decisions need to be made when one is hyper aroused. In fact we have clocked athletes’ heart rates in competition upwards of 200 beats/minute. Given that that is what is occurring in real life, it becomes very clear very quickly that training in what to do in a very neutral, calm environment (e.g., a classroom lecture or workshop) has little or no bearing on making constructive changes to behaviors in the hyper charged situation. While classroom workshops on active shooter incidents are great for raising awareness, their potential in producing effective behaviors in a hyper charged situation is extremely limited. What is needed is training that simulates, as close as possible, the actual environment in which the desired behaviors need to take place. The most effective training will be that which produces that simulation well.

There are many ways to think about prevention as well. Research has increasingly documented the signs and signals of impending violence (Matsumoto, Frank, & Hwang, 2015; Matsumoto & Hwang, 2013, 2014; Matsumoto, Hwang, & Frank, 2013, 2014a, 2014b, 2016), much of which can be transformed into proactive detection capabilities to intervene before things escalate. Moreover, recent research on lone actors and other actors who perform violent acts against others has documented that many – upwards of 80 – 90% of these individuals – leak their plans and intentions in some way, shape, or form to others (Meloy & Gill, 2016; Meloy, Roshdi, Glaz-Ocik, & Hoffman, 2015). Heightened awareness of these signs and signals, and procedures for reporting these to security professionals may be of interest.

These are just some of the many ways to consider how to deal with, manage, and prevent active shooter incidents. Perhaps the most important factor to consider, however, and perhaps the most difficult, is to find the courage and conviction to truly deal with them in the first place.

References Cited

Blair, J. P., Martaindale, H., & Nichols, T. (2014). Active Shooter Events from 2000 to 2012. FBI Law Enforcement Bulletin, January. Retrieved from https://leb.fbi.gov/2014/january/active-shooter-events-from-2000-to-2012 website:

Blair, J. P., & Schweit, K. W. (2014). A study of active shooter incidents in the United States between 2000 and 2013. Washington, D.C.: Texas State University and Federal Bureau of Investigation. U.S. Department of Justice.

Matsumoto, D., Frank, M. G., & Hwang, H. C. (2015). The role of intergroup emotions on political violence. Current Directions in Psychological Science, 24, 369-373. doi: 10.1177/0963721415595023.

Matsumoto, D., & Hwang, H. C. (2013). The language of political aggression. Journal of Language and Social Psychology, 32, 335-348. doi: 10.1177/0261927X12460666.

Matsumoto, D., & Hwang, H. C. (2014). Facial signs of imminent aggression. Journal of Threat Assessment and Management, 1, 118-128. doi: 10.1037/tam0000007.

Matsumoto, D., Hwang, H. C., & Frank, M. G. (2013). Emotional language and political aggression. Journal of Language and Social Psychology, 32, 452-468. doi: http://dx.doi.org/10.1177/0261927X12474654.

Matsumoto, D., Hwang, H. C., & Frank, M. G. (2014a). Emotions expressed by leaders in videos predict political aggression. Behavioral Sciences of Terrorism and Political Aggression, 6, 212-218. doi: 10.1080/19434472.2013.769116.

Matsumoto, D., Hwang, H. C., & Frank, M. G. (2014b). Emotions expressed in speeches by leaders of ideologically motivated groups predict aggression. Behavioral Sciences of Terrorism and Political Aggression, 6, 1-18. doi: 10.1080/19434472.2012.716449.

Matsumoto, D., Hwang, H. C., & Frank, M. G. (2016). The effects of incidental anger, contempt, and disgust on hostile language and implicit behaviors. Journal of Applied Social Psychology. doi: 10.1111/jasp.12374.

Meloy, J. R., & Gill, P. (2016). The lone-actor terrorist and the TRAP-18. Journal of Threat Assessment and Management, 3, 37-52. doi: http://dx.doi.org/10.1037/tam0000061.

Meloy, J. R., Roshdi, K., Glaz-Ocik, J., & Hoffman, J. (2015). Investigating the individual terrorist in Europe. Journal of Threat Assessment and Management, 2, 140-152. doi: http://dx.doi.org/10.1037/tam0000036.

Out of the Corner of Your Eye

The role of peripheral vision in emotional recognition is crucial to our perception of the world.

This is the conclusion of exciting research by Dr. Fraser Smith of the University of East Anglia. Dr. Smith and his team looked at the ways in which our peripheral vision manages to capture expressions of fear, tying this with central questions related to the evolution of emotional recognition and basic emotions.

In an admittedly small study of fourteen participants, researchers displayed images of various emotions from either directly in front of faces to orientations to the left or right of their face. These images contained a baseline neutral expression as well as images of people demonstrating six basic emotions, and participants were asked to identify the emotion shown.

This set up was intended to see if participants were able to first detect an emotion and then recognize which one it was. Interestingly, there were significant differences between each emotion. Fear was easily detected but less easily recognized, while happiness and surprise were generally well identified.

Moreover, they found that rates of recognition differed significantly when images were moved to peripheral vision. The authors emphasized the implications for individuals who struggle to recognize emotions, such as autism, as this research seeks to better understand those relevant neurological pathways.

Dr. Smith summarized how the paper importantly related to social interactions, stating “We show that it is not just being able to recognise expressions that is important, but being able to detect them in the first place. This gives us a different picture of which underlying systems may be impaired, which has potential implications for treatment of conditions where perception of emotions is affected.”

Moreover, this research furthers our understanding of the evolutionary roots of emotions and emotional recognition. For instance, in a past blog we outlined how our subtle emotional processes creates a type of emotional “landscape.” This is the result of us synthesizing impressions of emotions, such as fear and disgust, and creating a general map of the world as it relates to those emotions.

These sorts of landscapes are fundamental in allowing us to navigate the world around us and are present in many animals besides humans. Similarly, the very notion of universal emotions can be seen as tied into our evolutionary experience with the world around us, and they are certainly shared by many apes and other non-human animals.

Dr. Smith’s research helps tap into these fundamental questions, in addition to questions of social interaction. If we implicitly recognize certain emotions and identify others, our brain is doing some very focused work based on that emotion, and this is likely rooted in the evolutionary importance of each emotion.

Similarly, it is not possible to separate these evolutionary questions from those relevant to social interaction, as Dr. Smith emphasized the fundamental nature of social interaction to our daily lives.

Certainly, we are hardwired to detect and recognize emotions, but these instincts are far from perfect. This is where Humintell comes in: to harness those processes and make you better able to read people and their emotions!

Universal or Just Deceptive Emotions?

We spend a fair amount of this blog discussing the role of universal emotional expressions, but not everyone agrees.

Some emerging research, such as a recent study by Drs. Carlos Crivelli and Alan Fridlund, has begun to challenge some fundamental ideas related to the concept of basic emotions. This research questions whether facial expressions reflect emotions at all but instead reflect intentional social action.

For example, Dr. Crivelli has spent months interacting with indigenous groups like the Trobrianders of Papua New Guinea and the Mwani of Mozambique. When many of these people are shown basic emotion expressions, Dr. Crivelli found that they declined to identify those expressions with emotions.

Instead, a smile was described as “laughing” or as a feeling of being in “raptured enchantment.” Dr. Crivelli noticed that these referred not to emotions as much as to behaviors and actions. He found similar results when replicating these analyses among the Himba people of Namibia or the Hadza in Tanzania.

Moreover, a 2017 meta-analysis found that often facial expressions are not representing the emotion we would thing they should be, based on basic emotion theory. Instead, co-author Dr. Rainer Reisenzein suggested that openly expressing one’s emotions could “[put] us at a disadvantage” in an evolutionary sense.

Dr. Fridlund emphasized a similar point, stressing that emotions have strategic social motivations. Perhaps individuals are not revealing inner states but are trying to convey a specific state to you, so that you will act accordingly.

While many would see this research as a challenge to the idea of basic emotions, this isn’t really the case. Instead, it just underscores the importance of both incorporating microexpression analysis and deception detection. Microexpressions are actually just basic emotional expressions that are displayed almost instantaneously.

These microexpressions are the key to seeing through the sort of deceptive expressions that the aforementioned studies discuss. Certainly, your peer may be using a facial expression in a way that doesn’t just display the emotion in question, but their emotion is not completely concealed. It comes out in the form of a microexpression.

Still, this new cultural research helps elaborate on two complexities. First, many researchers may take for granted that the presence of expressions as showing underlying emotions. Such perceptions must take into account the possibility that others’ expressions are being used instrumentally.

Second, we must revisit the perennial issue of how to contextualize basic emotions into the admittedly distinctive manifestations that we see across cultures. Instead of speaking in terms of underlying emotions, some indigenous groups can simply describe the behaviors. What does this say about deception in those cultures? About emotional openness?

These are even more reasons to see what Humintell can do to better let you read microexpressions and to allow us to incorporate cultural differences into our people reading.