What are the ethical considerations surrounding the use of AI in sensitive domains like criminal justice?

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. 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 ... Jul 13, 2021 ... In this survey, we investigated different real-world applications that have shown biases in various ways, and we listed different sources of ... Bias in deep learning: A case study · Missing Data and Patients Not Identified by Algorithms: They occur due to known or unknown gaps in datasets used to train ... Mar 20, 2023 ... Debiasing ML refers to the process of mitigating or removing the effects of bias from the model or the data used to train the model. Apr 18, 2017 ... Princeton University-based researchers have found that machine-learning programs can acquire the cultural biases embedded in the patterns of wording. 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 ... 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' ... Nov 10, 2017 ... Machine learning can perpetuate and even amplify behavioral biases. By design, a social-media site filtering news based on user preferences ... 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 ...