Fairness in Algorithmic Decision Making for Financial Services

Explore the critical issue of fairness in algorithmic decision making for financial services in this 30-minute talk by Talieh Tabatabaei at the Toronto Machine Learning Series (TMLS). Delve into the promises and risks of Artificial Intelligence (AI) and Machine Learning (ML) in banking and financial institutions, covering applications such as process automation, security, underwriting, credit scoring, algorithmic trading, and advisory services. Understand the concept of algorithmic bias and fairness, its importance in the financial sector, and learn techniques for detecting and mitigating bias in organizational algorithms. Gain valuable insights into ensuring ethical and unbiased AI implementation in the rapidly evolving landscape of financial technology.