Abstract:This session discuses Algorithmic Bias in Human Resources including AI and ML projects. It provides a convincing case that the bias and fairness issues that have been
This session discuses Algorithmic Bias in Human Resources including AI and ML projects. It provides a convincing case that the bias and fairness issues that have been identified are grounded in business strategy decisions. Importantly, the session takes a practitioner perspective, viewing Human Resource technology project implementation from a Project Managers and middle managers point of view. The session starts by identifying the symptoms of the problem that are discussed in public press articles, and then completes a deep dive into the root causes of the issues, by unpacking layers of business and strategy decisions that have led to the issues that have been discovered after system implementation. In this session we also identify strategies and tactics and that can be used by Project Managers and middle management in developing responsible Human Resource algorithms, including AI and ML projects.
What You’ll Learn:
Root causes of bias and fairness issues in Human Resource AI and ML projects
Ushnish Sengupta is an award-winning instructor at the Schulich School of Business at York University, and a PhD candidate at OISE at the University of Toronto. He has an Industrial Engineering and MBA education, worked in various private sector and public sector organizations as an Information Technology Project Manager and Product Manager. Ushnish’s research interests include Entrepreneurship, Blockchain, Artificial Intelligence, Open Data, Diversity, and the Social and Environmental impact of technology projects.
(Tuesday) 2:00 PM - 3:30 PM