When Are Models of Technology in Psychology Most Useful?

Abstract

In industrial-organizational (I-O) psychology, much like in the organizational sciences more broadly (Hambrick, 2007), we have a bit of an addiction to theoretical models. It is commonly assumed that developing new theory is the most valuable way to solve pressing research problems and to drive our field forward (Mathieu, 2016). However, this assumption is untested, and there is growing awareness among organizational scientists that this hardline approach, which is unusual among both the natural sciences and other social sciences, may even be damaging the reputation and influence of our field (Antonakis, 2017; Ones, Kaiser, Chamorro-Premuzic, & Svensson, 2017). As Hambrick (2007) describes, the requirement for theory first “takes an array of subtle, but significant, tolls on our field” (p. 1348). As we will describe in this article, Morelli, Potosky, Arthur, and Tippins’ (2017) suggestions, if taken at face value, will likely create such tolls by encouraging the creation of new theories of dubious value. To be clear, we agree with Morelli et al. that better theory is needed for technology's impact on I-O psychology broadly and talent assessment in particular. We disagree, however, that creating new technology theories using the approaches that I-O psychology typically employs is likely to accomplish this broader goal. Rather, it will ultimately only isolate research on I-O technologies even further from both mainstream I-O research and technology research. Given that we are already quite isolated, this would be a disastrous path.