Explore the complex intersection of privacy governance and explainability in machine learning and artificial intelligence in this 45-minute conference talk from Strange Loop. Delve into the challenges posed by GDPR and other data privacy regulations, particularly in the context of ML and AI systems. Examine methods for enhancing privacy, governing data used in ML/AI, and addressing potential bias in models. Learn about privacy by design, algorithmic fairness, and the role of developers and engineers in ensuring ethical AI practices. Discover techniques such as dynamic sampling, differential privacy, and multidimensional privacy analytics to mitigate privacy risks. Gain insights into building consumer trust and confidence in an increasingly complex technological landscape.