Algorithmic fairness in artificial intelligence for medicine and healthcare
In healthcare, the development and deployment of insufficiently fair systems of artificial
intelligence (AI) can undermine the delivery of equitable care. Assessments of AI models …
intelligence (AI) can undermine the delivery of equitable care. Assessments of AI models …
[HTML][HTML] Explainable ai: A review of machine learning interpretability methods
Recent advances in artificial intelligence (AI) have led to its widespread industrial adoption,
with machine learning systems demonstrating superhuman performance in a significant …
with machine learning systems demonstrating superhuman performance in a significant …
A survey on datasets for fairness‐aware machine learning
As decision‐making increasingly relies on machine learning (ML) and (big) data, the issue
of fairness in data‐driven artificial intelligence systems is receiving increasing attention from …
of fairness in data‐driven artificial intelligence systems is receiving increasing attention from …
Trustworthy LLMs: A survey and guideline for evaluating large language models' alignment
Ensuring alignment, which refers to making models behave in accordance with human
intentions [1, 2], has become a critical task before deploying large language models (LLMs) …
intentions [1, 2], has become a critical task before deploying large language models (LLMs) …
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 …
Trustworthy ai: A computational perspective
In the past few decades, artificial intelligence (AI) technology has experienced swift
developments, changing everyone's daily life and profoundly altering the course of human …
developments, changing everyone's daily life and profoundly altering the course of human …
Explainable deep learning: A field guide for the uninitiated
Deep neural networks (DNNs) are an indispensable machine learning tool despite the
difficulty of diagnosing what aspects of a model's input drive its decisions. In countless real …
difficulty of diagnosing what aspects of a model's input drive its decisions. In countless real …
User-oriented fairness in recommendation
As a highly data-driven application, recommender systems could be affected by data bias,
resulting in unfair results for different data groups, which could be a reason that affects the …
resulting in unfair results for different data groups, which could be a reason that affects the …
Retiring adult: New datasets for fair machine learning
Although the fairness community has recognized the importance of data, researchers in the
area primarily rely on UCI Adult when it comes to tabular data. Derived from a 1994 US …
area primarily rely on UCI Adult when it comes to tabular data. Derived from a 1994 US …
Bias in data‐driven artificial intelligence systems—An introductory survey
Artificial Intelligence (AI)‐based systems are widely employed nowadays to make decisions
that have far‐reaching impact on individuals and society. Their decisions might affect …
that have far‐reaching impact on individuals and society. Their decisions might affect …