What are the educational requirements for professionals working on fair and ethical AI systems?

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; ... Jan 21, 2021 ... Identifying Systemic Bias in the Acquisition of Machine Learning Decision Aids for Law Enforcement Applications ... Biased software tools that use ... Feb 21, 2022 ... A model's ability to generalize is influenced by both the diversity of the data and the way the model is trained, researchers report. 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. Model bias, in Machine Learning, refers to the presence of systematic errors in a model that can cause it to consistently make incorrect predictions. Previous research revealed the existence of large near-surface temperature biases (mostly warm) over the Arctic sea ice in the current generation of atmospheric ... According to some futurists, financial markets' automation will substitute increasingly sophisticated, objective, analytical, model-based assessments of, for ... Feb 20, 2024 ... In this review, we present a framework for understanding the balance of opportunities and challenges for minimizing bias in medical imaging. Dec 28, 2018 ... In this paper, we reconcile the classical understanding and the modern practice within a unified performance curve. This "double descent" curve ... May 23, 2016 ... Machine Bias. There's ... The advantage of using a generic statistical learning algorithm is that you KNOW what information goes in.