Explore the critical considerations of fairness in machine learning development through this insightful ACM talk by Tulsee Doshi, Product Lead for Google's Machine Learning Fairness Effort. Delve into lessons learned from Google's products and research, and discover approaches for evaluating and mitigating common fairness concerns in AI. Learn about the importance of explainability in addressing fairness issues and gain knowledge of available tools and techniques. Examine topics such as AI principles, ML examples and concerns, gender shades, counterfactual fairness, equality of opportunity, and improvements in mitigations. Understand the significance of transparency, industry-wide conversations, and Google's responsibility in promoting fairness in machine learning.