Michael Wu

Explore the root causes of AI biases, including data collection and choice architecture. Learn strategies to identify and mitigate these biases for more accurate and ethical AI systems.

Explore how emergent biases arise during machine learning training, even with unbiased data. Understand their origins, detection challenges, and strategies to mitigate their impact on AI models.

Explore how biases in training data affect AI systems and learn strategies to identify and mitigate these inherited biases for more ethical and accurate machine learning models.

Discover how AI biases emerge, why they matter, and how to address them. Learn about biased data, explainable AI, and the steps to mitigate AI bias effectively.