Algorithmic Fairness and Bias in Machine Learning Systems

Algorithmic Bias in Autonomous Systems

Algorithms play a key role in the functioning of autonomous systems, and so concerns have periodically been raised about the possibility of algorithmic bias. However, debates in this area have been hampered by different meanings and uses of the term, “bias.” It is sometimes used as a purely descriptive term, sometimes as a pejorative term, and such variations can promote confusion and hamper di...

Algorithmic Aspects of Machine Learning

Algorithmic Statistics, Prediction and Machine Learning

Algorithmic statistics considers the following problem: given a binary string x (e.g., some experimental data), find a “good” explanation of this data. It uses algorithmic information theory to define formally what is a good explanation. In this paper we extend this framework in two directions. First, the explanations are not only interesting in themselves but also used for prediction: we want ...

Appendix : Machine Learning Bias Versus Statistical Bias

is if and 0 if. This high variance may help to explain why there is selection pressure for weak (machine learning) bias when the (machine learning) bias correctness is low. The reason that statisticians are interested in (statistical) bias and variance is that squared error is equal to the sum of squared (statistical) bias and variance. Therefore minimal (statistical) bias and minimal variance ...

Appendix : Machine Learning Bias Versus Statistical Bias

is if and 0 if. This high variance may help to explain why there is selection pressure for weak (machine learning) bias when the (machine learning) bias correctness is low. The reason that statisticians are interested in (statistical) bias and variance is that squared error is equal to the sum of squared (statistical) bias and variance. Therefore minimal (statistical) bias and minimal variance ...