Predictive analytics and their effect on careers: a multi-disciplinary analysis

Predictive analytics as part of the broader appearance of artificial intelligence and algorithms on the management scene has made its presence felt also with respect to careers. We take a closer look at machine-learning models (MLMs) as the centrepiece of predictive analytics and analyse their effects on various aspects of careers from a multi-disciplinary perspective, building on psychology, management studies, and sociology. After outlining fundamental, potentially problematic features of MLMs, i.e., correlationism, sociality, and expansionism, we identify and debate three major issues that emerge when applying the respective disciplinary perspectives and look at effects on organisational knowledge production, career decision-making, and organisational performance. Concluding, we outline pathways for future research that focus on predictive analytics’ use as a means to an end (tool view), on the ways users handle and modify this technology (proxy view), and on the social construction of the technology shaped by external contingencies (ensemble view).