What is the role of interpretability in ensuring fairness in AI models?

Nov 10, 2017 ... Machine learning can perpetuate and even amplify behavioral biases. By design, a social-media site filtering news based on user preferences ... Jun 2, 2022 ... This article will discuss the use of AI and ML in cancer care and provide a framework for mitigating bias to achieve cancer equity. Mar 15, 2022 ... In this article, we will cover bias concerning ML modeling, types of biases involved in developing machine learning models, methods to detect biases, and their ... Feb 8, 2024 ... We developed a unified transformer-based machine learning framework ImmuBPI that comprised three tasks and achieved state-of-the-art performance. The bias–variance trade-off implies that a model should balance underfitting and overfitting: Rich enough to express underlying structure in data and simple ... Feb 4, 2019 ... Bias can creep in at many stages of the deep-learning process, and the standard practices in computer science aren't designed to detect it. Jul 15, 2024 ... As institutions of higher education turn to AI machine learning and data-driven algorithms to make their work more efficient, a new study ... The biases include those related to missing data and patients not identified by algorithms, sample size and underestimation, and misclassification and ... Jul 19, 2021 ... ... bias in artificial intelligence was identified and the ethical risk mitigated. ... We can build a machine-learning model that works well at ... Oct 16, 2023 ... AI bias, also referred to as machine learning bias or algorithm bias, refers to AI systems that produce biased results that reflect and ...