How can we update and retrain models to maintain fairness over time?

Aug 12, 2020 ... What are Bias and Variance? · Bias: it's the difference between average predictions and true values. · Variance: it's the variability of our ... Jun 1, 2023 ... In this review article, we discuss the implicit bias in training neural networks using gradient-based methods. Tackling issues of bias and fairness when building and deploying machine learning and data science systems has received increased attention from the research ... We argue that algorithmic bias evolves with human interaction in an iterative manner, which may have a long-term effect on algorithm performance and humans' ... Sep 1, 2022 ... Bias – A significant imbalance in the input data or model predictions across different facet values. What constitutes “significant” depends on ... Mar 15, 2022 ... This document uses terms such as AI technology, AI system, and AI applications inter- changeably. Terms related to the machine learning pipeline ... As promising as machine-learning technology is, it can also be susceptible to unintended biases that require careful planning to avoid. Jan 21, 2021 ... Identifying Systemic Bias in the Acquisition of Machine Learning Decision Aids for Law Enforcement Applications ... Biased software tools that use ... May 22, 2019 ... The private and public sectors are increasingly turning to artificial intelligence (AI) systems and machine learning algorithms to automate ... Detecting bias in your ML model can be done proactively or reactively, and depending on your specific case, either one is viable. Reactive bias detection ...