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 …
A survey on bias and fairness in machine learning
With the widespread use of artificial intelligence (AI) systems and applications in our
everyday lives, accounting for fairness has gained significant importance in designing and …
everyday lives, accounting for fairness has gained significant importance in designing and …
Artificial intelligence in human resources management: Challenges and a path forward
P Tambe, P Cappelli… - California Management …, 2019 - journals.sagepub.com
There is a substantial gap between the promise and reality of artificial intelligence in human
resource (HR) management. This article identifies four challenges in using data science …
resource (HR) management. This article identifies four challenges in using data science …
The measure and mismeasure of fairness
The field of fair machine learning aims to ensure that decisions guided by algorithms are
equitable. Over the last decade, several formal, mathematical definitions of fairness have …
equitable. Over the last decade, several formal, mathematical definitions of fairness have …
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 …
Algorithmic bias: Senses, sources, solutions
S Fazelpour, D Danks - Philosophy Compass, 2021 - Wiley Online Library
Data‐driven algorithms are widely used to make or assist decisions in sensitive domains,
including healthcare, social services, education, hiring, and criminal justice. In various …
including healthcare, social services, education, hiring, and criminal justice. In various …
Simulation intelligence: Towards a new generation of scientific methods
The original" Seven Motifs" set forth a roadmap of essential methods for the field of scientific
computing, where a motif is an algorithmic method that captures a pattern of computation …
computing, where a motif is an algorithmic method that captures a pattern of computation …
Algorithmic fairness
An increasing number of decisions regarding the daily lives of human beings are being
controlled by artificial intelligence (AI) and machine learning (ML) algorithms in spheres …
controlled by artificial intelligence (AI) and machine learning (ML) algorithms in spheres …
Causal conceptions of fairness and their consequences
Recent work highlights the role of causality in designing equitable decision-making
algorithms. It is not immediately clear, however, how existing causal conceptions of fairness …
algorithms. It is not immediately clear, however, how existing causal conceptions of fairness …
Interventional fairness: Causal database repair for algorithmic fairness
Fairness is increasingly recognized as a critical component of machine learning systems.
However, it is the underlying data on which these systems are trained that often reflect …
However, it is the underlying data on which these systems are trained that often reflect …