Signaling is the act of conveying meaningful information about oneself to another party. Typically when we talk about signals we refer to intentional behavior on the part of an actor. For example, if the leader of Country A makes a public commitment to defend Country B the leader of Country A is communicating their “type” and, in turn, conveying to other actors that if they attack Country B they will most certainly face retaliation from Country A. The very act of making a public commitment is considered by many to be a reliable signal, since the leader of Country A is putting their reputation on the line (both to domestic and international audiences). Only an actor who was capable and resolved to defend Country B would put their reputation on the line, since backing down afterwards would be very costly.
The problem with behavioral signaling is that actors have incentives to pass themselves off as something they are not (e.g. capable, smart, committed, etc). This has fueled research in economics and political science, with researchers searching for situations and mechanisms that make signals reliable–i.e. the signal can only be sent by actors that have certain characteristics, and therefore are separated from actors that do not.
But what about physiological signals? If behavioral signals are subject to manipulation, why not focus on the physiological signals sent by the human body? For example, if we want to know if an actor plans on following through with a commitment it would be helpful if there were physiological signals given off by the body (e.g. blood pressure, rapid eye movements, body heat, facial movements) that were highly correlated with the act of lying. Dr. Paul Ekman has been conducting breakthrough research in one of these areas for decades, focusing on what he terms “micro-expressions”–physical manifestations of emotions that “leak out” when someone tries to conceal them. (Ekman’s work is the inspiration behind the FOX television series Lie to Me.)
Physiological signals would seem to be more reliable since faking these types of signals is conceivably very difficult, if not impossible. However, there is another concern one mus take into account regarding physiological signals, and their practical application in areas such as transportation security: false positives. While physiological signals might make it difficult for someone (say, an actor intent on hijacking a plane) to hide their intentions, the same physiological signals that indicate ill intent could also be present if someone is generally nervous about flying, being questioned by authorities, etc. The key to using a signal as a diagnostic tool is it’s ability to reliably separate types of actors. If the same signal can be intentionally sent or passively expressed by actors of different types (i.e. hijacker versus nervous flyer), then the signal loses its power.
Fast Company recently profiled some new technology from WeCU Technologies that proposes to reliably diagnose risky airline passengers:
CEO Ehud Givon compares the function of WeCU’s detection system with a doctor’s diagnosis. The technology is relatively simple: a synthesis of electronic sensors and knowledge gleaned from behavioral studies. During a routine act, such as check-in at an airport kiosk, travelers will be subjected to a near-invisible stimulus that will trigger physiological responses among those who are concealing something. Sensors hidden in the kiosk will pick up the cues and alert security officers. WeCU’s boldest claim is that its system can weed out the mal-intentioned from the merely stressed out.
WeCU claims that they’ve developed their measures in such a way as to avoid the problematic false positives that have long provided a barrier to the deployment of these types of systems. It will be very interesting to see how they fair once introduced into a live environment. If the system is able to minimize the number of false positives as well as the number of false negatives (the number of terrorists that evade the system) it will be a big step forward in the practical application of physiological signaling.