Building an Ethical Data Science Practice
Explore the journey of building an ethical data science practice in this 41-minute talk by Cal Al-Dhubaib from Open Data Science. Discover the challenges and solutions in operationalizing ethical AI, including having difficult conversations about bias and risk, transforming ethics from a value to a virtue, and implementing practical tools and processes. Learn how to make a compelling business case for ethical data science, move beyond platitudes to real-world implementation, and incorporate ethics into talent acquisition and development strategies. Gain insights on fostering proactive risk management, building representative data science teams, and improving retention rates while addressing critical issues such as bias in AI, data complexity, and the importance of diversity in the field.