How can bias affect the performance of recommender systems?

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 ... 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 ... 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 ... Aug 18, 2023 ... Here, we apply machine learning (ML) to produce a blended TROPOMI+GOSAT product that uses GOSAT to correct biases in the TROPOMI data and ... Jul 25, 2022 ... Machine learning bias is sometimes called algorithm bias or AI bias. Predictive models may be trained on data containing human decisions or ... Aug 29, 2022 ... One of the main areas for concern is bias in AI systems. Bias can inappropriately skew the output from AI in favor of certain data sets; ... Jun 28, 2022 ... 'It's not going to work': Keeping race out of machine learning isn't enough to avoid bias ... As more machine learning tools reach patients, ... May 22, 2019 ... The private and public sectors are increasingly turning to artificial intelligence (AI) systems and machine learning algorithms to automate ... The biases include those related to missing data and patients not identified by algorithms, sample size and underestimation, and misclassification and ...