Social Implications of Bias in Machine Learning

This course aims to explore the social implications of bias in machine learning, highlighting the power individuals working on ML tools have in shaping the future. The learning outcomes include understanding how datasets and algorithms reflect societal biases, the potential inaccuracies and discrimination they can cause, and methods to assess impact and drive positive change. The course covers topics such as social bias, statistical bias, and the human condition in relation to machine learning. The teaching method involves real-world examples, discussions on potential solutions, and exploring the relationships between technology and society. The intended audience includes anyone interested in leveraging technology for social justice and equality, regardless of their background in data science.