The 2023 MB HR Talks, hosted by the School of Human Resources Management, is pleased to announce Dr. Piers Steel as our distinguished speaker. Dr. Steel will present his latest research on harnessing the power of big data in personnel selection. Following his presentation, there will be an engaging discussion on the far-reaching implications of automating personnel selection. Join us for an insightful evening of exploration and discourse on this transformative topic.
Looking forward to seeing you there!
Dr. Piers Steel is an eminent academic and expert in the application of meta-analysis and systematic reviews in organizational psychology. Holding a Ph.D. in Industrial-Organizational Psychology, he is a tenured professor at the University of Calgary where he leads groundbreaking research in meta-analytic techniques. Dr. Steel is the architect behind the HubMeta platform, an innovative tool designed to facilitate the systematic collection, analysis, and interpretation of research data across studies. His platform has been instrumental in revolutionizing the way meta-analyses are conducted and disseminated, influencing both academic research and organizational practices.
His scholarly contributions in synthetic validity and meta-analysis have been published in top-tier academic journals, setting the benchmark for quality and methodological rigor in the field. These works have garnered numerous awards and are often cited as seminal contributions to our understanding of personnel selection processes. In today’s talk, Dr. Steel will unpack the transformative potential of synthetic validity in the realm of personnel selection. Drawing upon his extensive experience with the HubMeta platform, he will explore the ethical and practical implications of these advancements, setting the stage for a robust academic discourse on this groundbreaking subject.
Abstract:
In an era where technological advancements are monthly reshaping organizational processes, this talk delves into the revolutionary impact of synthetic validity and Big Data analytics on personnel selection. Drawing on six decades of research in synthetic validity and emerging methodologies in Big Data, this discussion offers an interdisciplinary exploration of how meta-analytic techniques and machine learning algorithms are enabling the near full automation and optimization of selection systems. In short, we can allocate human capital far more perfectly. After showing that the technical aspects of automated selection have been addressed, it behooves us to ask: “What is the impact of this?” Taking a Responsible Research and Innovation (RRI) lens, which emphasizes the anticipation of scientific outcomes, we find these systems offer substantial benefits, including the optimized allocation of human capital, the enhancement of job satisfaction, and incentives for improving organizational cultures. They also hold the promise of significantly boosting national wealth, providing an approximate 15% bump (i.e., in the trillions of dollars). However, these innovations are not without risks. If not carefully integrated, they could exacerbate workforce commodification and virtualization, leading to potential political destabilization and disenfranchisement. The urgency for nuanced and thoughtful responses to these transformative changes in the labor market is escalating.