Detecting Concealed Information on a Large Scale: Possibilities and Problems

There is an increasing demand for deception detection at scale. In situations in which larger numbers of people need to be tested, traditional deception-detection methods are limited because they often require extensive testing sessions or are limited in their flexibility to novel contexts. The aim of this chapter is to discuss the potential for large-scale applications of several deception-detection methods. Specifically, we evaluate the theoretical foundations of the methods, the potential for quick data-collection procedures, and the flexibility of implementing the methods in different contexts. Each method (behavioral observation, reaction times, speech analysis, verbal content, thermal imaging) is outlined, evaluated, and discussed on the suitability for large-scale purposes. There is no substantial evidence to support the validity of behavioral observation nor of speech analysis. Reaction times and verbal content analysis are promising for future of large-scale applications. To reach their full potential, for both methods the key challenges are a fast data-collection process (e.g., remote online testing) and a near real-time assessment of the data. We close this chapter with an outlook on possible new applications including the integration of methods (i.e., multimodal approaches).