A review on fairness in machine learning
An increasing number of decisions regarding the daily lives of human beings are being
controlled by artificial intelligence and machine learning (ML) algorithms in spheres ranging …
controlled by artificial intelligence and machine learning (ML) algorithms in spheres ranging …
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 …
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 …
Fairness in machine learning: A survey
When Machine Learning technologies are used in contexts that affect citizens, companies as
well as researchers need to be confident that there will not be any unexpected social …
well as researchers need to be confident that there will not be any unexpected social …
[HTML][HTML] From what to how: an initial review of publicly available AI ethics tools, methods and research to translate principles into practices
The debate about the ethical implications of Artificial Intelligence dates from the 1960s
(Samuel in Science, 132 (3429): 741–742, 1960. https://doi. org/10.1126/science. 132.3429 …
(Samuel in Science, 132 (3429): 741–742, 1960. https://doi. org/10.1126/science. 132.3429 …
From ethical AI frameworks to tools: a review of approaches
E Prem - AI and Ethics, 2023 - Springer
In reaction to concerns about a broad range of potential ethical issues, dozens of proposals
for addressing ethical aspects of artificial intelligence (AI) have been published. However …
for addressing ethical aspects of artificial intelligence (AI) have been published. However …
Algorithmic recourse: from counterfactual explanations to interventions
As machine learning is increasingly used to inform consequential decision-making (eg, pre-
trial bail and loan approval), it becomes important to explain how the system arrived at its …
trial bail and loan approval), it becomes important to explain how the system arrived at its …
[ΒΙΒΛΙΟ][B] Fairness and machine learning: Limitations and opportunities
An introduction to the intellectual foundations and practical utility of the recent work on
fairness and machine learning. Fairness and Machine Learning introduces advanced …
fairness and machine learning. Fairness and Machine Learning introduces advanced …
[PDF][PDF] Counterfactuals in explainable artificial intelligence (XAI): Evidence from human reasoning.
RMJ Byrne - IJCAI, 2019 - researchgate.net
Counterfactuals about what could have happened are increasingly used in an array of
Artificial Intelligence (AI) applications, and especially in explainable AI (XAI) …
Artificial Intelligence (AI) applications, and especially in explainable AI (XAI) …
Counterfactual fairness
Abstract Machine learning can impact people with legal or ethical consequences when it is
used to automate decisions in areas such as insurance, lending, hiring, and predictive …
used to automate decisions in areas such as insurance, lending, hiring, and predictive …