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Algorithmic Bias in Human Resources: Responsible AI and Business Strategy

Toronto Machine Learning Series (TMLS) via YouTube

Overview

Explore the critical intersection of algorithmic bias in human resources, responsible AI, and business strategy in this comprehensive 1-hour 28-minute conference talk from the Toronto Machine Learning Series (TMLS). Delve into the complex issues surrounding AI and ML projects in HR, examining the root causes of bias and fairness problems from a practitioner's perspective. Learn how these challenges are deeply rooted in business strategy decisions and gain valuable insights from the viewpoint of project managers and middle managers. Discover effective strategies and tactics for developing responsible HR algorithms, including AI and ML projects, to address and mitigate bias. Led by Ushnish Sengupta, an award-winning instructor and PhD candidate with extensive experience in IT project management and product management, this session offers a deep dive into the symptoms, causes, and potential solutions for algorithmic bias in HR technology implementations.

Syllabus

Algorithmic Bias in Human Resources, Responsible AI, and Business Strategy

Taught by

Toronto Machine Learning Series (TMLS)

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