Why your AI might be biased (and what you can do about it)
Explains the causes of bias in AI systems, focusing on training data and proxy variables, and offers practical steps for developers to mitigate it.
Explains the causes of bias in AI systems, focusing on training data and proxy variables, and offers practical steps for developers to mitigate it.
Explores the critical challenge of bias in health AI data, why unbiased data is impossible, and the ethical implications for medical algorithms.
Announcement for a lecture series on machine learning, covering topics like Weka, deep learning, algorithmic fairness, and sparse supervised learning.