How can biased credit scoring models perpetuate financial inequality?

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' ... This review will discuss the relevant ethical and bias considerations in AI-ML specifically within the pathology and medical domain. Sep 5, 2022 ... This article aims to examine some of the ways in which racial bias gets included in AI and touch upon what can be done to mitigate these biases. 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. Jun 1, 2023 ... In this review article, we discuss the implicit bias in training neural networks using gradient-based methods. Mar 10, 2025 ... PhyloFrame is an equitable machine learning method that creates signatures of disease based on population genomics data and disease-relevant ... Apr 18, 2017 ... Princeton University-based researchers have found that machine-learning programs can acquire the cultural biases embedded in the patterns of wording. Previous research revealed the existence of large near-surface temperature biases (mostly warm) over the Arctic sea ice in the current generation of atmospheric ... This paper postulates that the root causes of bias are the prior decisions that affect- (a) what data was selected and (b) the labels assigned to those ... What is machine learning bias (AI bias)? ... Machine learning bias, also known as algorithm bias or AI bias, is a phenomenon that occurs when an algorithm ...