The future of the labor force : higher cognition and more skills

Abstract

Skills can be categorized into two types: social-cognitive and sensory-physical. Sensory-physical skills, governed by explicit rules and transparent rationales, can be effectively executed through meticulous programming, with humans spontaneously trusting machines to perform these skills. In contrast, social-cognitive skills entail open interpretations reliant on personal opinions or intuition and are contextually and problem-dependent. The inherent complexity and subjectivity of social-cognitive skills, underscored by Polanyi’s paradox and algorithm aversion, render machines less capable of replicating these skills. Thus, automation exerts differential impacts on these two skill sets. Moreover, the specialization of machines leads to expensive setup costs when switching tasks, whereas humans switch tasks with much less effort. The versatility in skills enables workers to adapt to a wide array of tasks, making them less prone to automation. Our empirical research, utilizing skill score data from O*NET and employment data from Employment and Wage Statistics (OEWS), validated the attributes of labor resistant to automation: the higher the scores of cognitive skills in a job, the lower its susceptibility to automation; workers endowed with a diverse array of skills experience an increase in their employment share. Conversely, jobs focusing on sensory-physical skills are more likely to be supplanted by machines. Therefore, workers can adopt two strategies to maintain a competitive edge. First, they can enhance cognitive skills, such as creativity and critical thinking. Second, they can develop diverse skills, encompassing both social-cognitive and sensory-physical skills. Specializing in a specific sensory-physical skill does not offer an advantage. Fostering a workforce proficient in cognitive skills and equipped with multifaceted skills, that is, flexible workers, becomes imperative. Our investigation represents the inaugural effort to empirically affirm the differential impact of automation on sensory-physical versus social-cognitive skills, thereby delineating the characteristics of irreplaceable labor. This analysis offers critical insights for individual career development and the strategic planning of national educational systems.