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[HTML][HTML] Fairness, Accountability, Transparency, and Ethics (FATE) in Artificial Intelligence (AI) and higher education: A systematic review
B Memarian, T Doleck - Computers and Education: Artificial Intelligence, 2023 - Elsevier
Abstract Background The use of Artificial Intelligence or AI is rising in higher education. With
this rise, the morality of AI programs is being questioned. There is, as such, a need to …
this rise, the morality of AI programs is being questioned. There is, as such, a need to …
Bias mitigation for machine learning classifiers: A comprehensive survey
This article provides a comprehensive survey of bias mitigation methods for achieving
fairness in Machine Learning (ML) models. We collect a total of 341 publications concerning …
fairness in Machine Learning (ML) models. We collect a total of 341 publications concerning …
Fairness in deep learning: A survey on vision and language research
Despite being responsible for state-of-the-art results in several computer vision and natural
language processing tasks, neural networks have faced harsh criticism due to some of their …
language processing tasks, neural networks have faced harsh criticism due to some of their …
[PDF][PDF] Towards guaranteed safe ai: A framework for ensuring robust and reliable ai systems
Ensuring that AI systems reliably and robustly avoid harmful or dangerous behaviours is a
crucial challenge, especially for AI systems with a high degree of autonomy and general …
crucial challenge, especially for AI systems with a high degree of autonomy and general …
An evaluation of synthetic data augmentation for mitigating covariate bias in health data
Data bias is a major concern in biomedical research, especially when evaluating large-scale
observational datasets. It leads to imprecise predictions and inconsistent estimates in …
observational datasets. It leads to imprecise predictions and inconsistent estimates in …
Machine vision combined with deep learning–based approaches for food authentication: An integrative review and new insights
C Shen, R Wang, H Nawazish, B Wang… - … Reviews in Food …, 2024 - Wiley Online Library
Food fraud undermines consumer trust, creates economic risk, and jeopardizes human
health. Therefore, it is essential to develop efficient technologies for rapid and reliable …
health. Therefore, it is essential to develop efficient technologies for rapid and reliable …
Multi-task learning with dynamic re-weighting to achieve fairness in healthcare predictive modeling
The emphasis on fairness in predictive healthcare modeling has increased in popularity as
an approach for overcoming biases in automated decision-making systems. The aim is to …
an approach for overcoming biases in automated decision-making systems. The aim is to …
Debiasing methods for fairer neural models in vision and language research: A survey
Despite being responsible for state-of-the-art results in several computer vision and natural
language processing tasks, neural networks have faced harsh criticism due to some of their …
language processing tasks, neural networks have faced harsh criticism due to some of their …
Addressing bias in bagging and boosting regression models
As artificial intelligence (AI) becomes widespread, there is increasing attention on
investigating bias in machine learning (ML) models. Previous research concentrated on …
investigating bias in machine learning (ML) models. Previous research concentrated on …
FATE in MMLA: A Student-Centred Exploration of Fairness, Accountability, Transparency, and Ethics in Multimodal Learning Analytics
Multimodal Learning Analytics (MMLA) integrates novel sensing technologies and artificial
intelligence algorithms, providing opportunities to enhance student reflection during …
intelligence algorithms, providing opportunities to enhance student reflection during …