How can we ensure that the benefits of AI are distributed equitably across all members of society?

Feb 7, 2024 ... The landscape is overrun with “neutral” analysts using some kind of sentiment analysis to lazily label something as right or left. This MIT ... Aug 13, 2018 ... This paper argues that algorithmic biases explicitly and implicitly harm racial groups and lead to forms of discrimination. The purpose of this study is to illustrate the harmful effects of learned human-like biases in MLAGs, to highlight how improper algorithm training leads to ... In linear regression analysis, bias refers to the error that is introduced by approximating a real-life problem, which may be complicated, by a much simpler ... 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 ... Sep 3, 2024 ... AI bias occurs when an AI system produces systematically prejudiced results due to erroneous assumptions in the machine learning process. These ... 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. Mar 5, 2019 ... Reports of successful applications of machine learning (ML) methods in structure-based virtual screening (SBVS) are increasing. 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 19, 2010 ... A bias value allows you to shift the activation function to the left or right, which may be critical for successful learning.