Despite greater awareness of the value of broadening participation in STEM fields and movements to do so, discrimination in hiring remains a problem. The high technology sector is particularly notable for the very low numbers of women, African American, and Hispanic American computer scientists and engineers. A key reason for the low participation is that implicit biases at different stages of recruitment perpetuate the inequitable status quo. To begin to solve this problem, discrimination in recruiting must be understood in detail. This work aims to work toward improving human resources (HR) practices by improving training that uses state-of-the-art technologies to help people avoid unconsciously falling into discriminatory behavior. A potential long-term societal benefit of this work would be more equitable hiring processes. Such an improvement could increase hiring of diverse teams, thus increasing creativity and innovation in the workplace. In addition, more diverse teams can help to reduce stereotype threat, since sterotypes break down as more people from underrepresented groups are included. Toward these goals, the research team plans to conduct an interdisciplinary workshop with industry representatives and experts from HR management, the social sciences, and computer science to identify sources of bias and propose solutions to address them. This workshop is expected to lay the foundation and the research agenda necessary to submit a full Future of Work at the Human-Technology Frontier proposal.
By leveraging the expertise of HR management, psychology, and sociology professionals, in partnership with computer scientists and engineers, this convergent research team plans to gain a deep understanding of where and what kinds of bias occur in the recruitment process for high technology workers. Participants will explore potential interventions to identify or prevent bias through the use of future technologies such as virtual reality, augmented reality, and artificial intelligence-powered tools. The research team will attempt to answer the following questions through this project: What are the standard practices of the technology industry's recruitment process? How much do practices vary from company to company? In what phases of the recruitment process does bias occur, and what types of biases occur? What types of evidence are produced by biased recruiting practices? What technologies are useful for identifying and preventing bias? This project has been funded by the Future of Work at the Human-Technology Frontier cross-directorate program to facilitate convergent research to promote deeper basic understanding of the interdependent human-technology partnership to advance societal needs by advancing design of intelligent work technologies that operate in harmony with human workers.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
