IWER April Newsletter: Generative AI and the Future of Work

Generative AI and Worker Productivity

Generative AI and Worker Voice


Emilio Castilla Reflects on the Promise of People Analytics


MIT Sloan Professor Emilio J. Castilla sees tremendous potential in people analytics, which he defines as a data-driven approach to improving people-related decisions in organizations. People analytics, Castilla observed in a presentation at an MIT event not long ago, “promises to help us really identify, attract, retain, develop, and promote talent in organizations in a very scientific way.”

Castilla, who is the NTU Professor of Management and a Professor of Work and Organization Studies at the MIT Sloan School of Management, teaches a course on people analytics at MIT Sloan and is co-director of the MIT Institute for Work and Employment Research (IWER). In his presentation, Castilla explained that people analytics can help companies increase diversity and decrease inequality in the workplace “in a way that is very scientific.”

Part of that scientific process, however, involves evaluating the effectiveness of various approaches that claim to increase workplace diversity and/or decrease inequality—and sometimes those techniques’ effectiveness may be less than managers expect. That was the case in a study Castilla conducted with Hye Jin Rho, an assistant professor at Michigan State University who earned her PhD from the IWER program within MIT Sloan. Castilla and Rho’s study, “The Gendering of Job Postings in the Online Recruitment Process,” was recently published by the journal Management Science. Castilla and Rho found that, contrary to some claims in the business world, removing gendered language in job listings has little effect on diversifying the job applicant pool.

Such findings, Castilla emphasized in his presentation, highlight the overall importance of serious research to identify the best ways for organizations to increase diversity and reduce inequality in the workplace.  Researchers, he noted, need to “be able to…evaluate a lot of these promises or best practices to see if they are really making a difference….Let’s just really investigate this seriously, with real data.” 

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