How can we foster greater collaboration and knowledge sharing in this interdisciplinary field?

Sep 3, 2024 ... AI bias occurs when an AI system produces systematically prejudiced results due to erroneous assumptions in the machine learning process. These ... May 23, 2016 ... Machine Bias. There's ... The advantage of using a generic statistical learning algorithm is that you KNOW what information goes in. Apr 3, 2025 ... Bias Variance Tradeoff. If the algorithm is too simple (hypothesis with linear equation) then it may be on high bias and low variance condition ... Aug 18, 2021 ... We demonstrate that state-of-the-art scheduling systems cause the black patients in our data set to wait about 30% longer than nonblack patients. Jul 27, 2023 ... Bias is an additional parameter in a neural network that is used to adjust the output along with the weighted sum of the inputs to the neuron. May 1, 2022 ... It is the difference between the average estimator value (averaged over random samples) and the true value of the parameter. Mar 3, 2021 ... In this paper we make three contributions. First, we assess the compatibility of fairness metrics used in machine learning against the aims and purpose of EU ... Jan 31, 2018 ... This post assumes some familiarity with machine learning, and reinforcement learning in particular. If you are new to RL, I'd recommend ... May 31, 2022 ... Additionally, ML algorithms tend to overfit to the data on which they are trained, which entails the learning of spurious relationships present ... Aug 8, 2023 ... Encord Active offers features to help reduce bias in datasets, allowing you to identify and address any potential biases in your data workflow.