How can we identify bias in a machine learning dataset?

Oct 18, 2022 ... We develop and evaluate a machine learning system for identifying five major categories of biased and discriminatory language in job advertisements. Mar 1, 2021 ... "Bias" is used to characterize the model error due to simplified assumptions of the model, eg, using linear regression when linear regression is not complex ... Oct 9, 2024 ... Selection bias occurs if a dataset's examples are chosen in a way that is not reflective of their real-world distribution. Selection bias can ... Jun 1, 2023 ... In this review article, we discuss the implicit bias in training neural networks using gradient-based methods. 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 ... Dec 25, 2023 ... Machine learning bias, often referred to as algorithmic bias, is the tendency of a machine learning model to exhibit a preference or prejudice ... Previous research revealed the existence of large near-surface temperature biases (mostly warm) over the Arctic sea ice in the current generation of atmospheric ... Mar 22, 2024 ... Research suggests that digital ageism, that is, age-related bias, is present in the development and deployment of machine learning (ML) models. 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; ... Aug 22, 2024 ... Discover why bias and variance are two key components that you must consider when developing any good, accurate machine learning model.