• The Pursuit of Fairness in Artificial Intelligence Models🔍
• Machine Learning Ethics🔍
• Fairness and Bias in Artificial Intelligence🔍
• Fairness in machine learning🔍
• Inherent Limitations of AI Fairness🔍
• Toward Fairness🔍

The Pursuit of Fairness in Artificial Intelligence Models: A Survey

Working towards making AI models fair can also enhance user experience. In this paper, we discuss the impact of biased models on users and ...

Machine Learning Ethics: Understanding Bias and Fairness

Ethical considerations have become increasingly crucial in the rapidly advancing field of machine learning (ML).

Fairness and Bias in Artificial Intelligence: A Brief Survey of Sources ...

Counterfactual fairness is a more recent concept that aims to ensure that AI systems are fair even in hypothetical scenarios. Specifically, counterfactual ...

(PDF) Ethical Considerations in AI Addressing Bias and Fairness in ...

This paper explores the ethical implications of bias in AI systems and the importance of ensuring fairness in ML models.

Fairness in machine learning: Regulation or standards?

ML fairness—and AI fairness more broadly—is a complex and multidimensional concept, and there are several definitions and metrics used to ...

Inherent Limitations of AI Fairness - Communications of the ACM

Fundamentally, solutions toward ethical AI have a limited effect if a deviation from ethics has no consequences. The sheer complexity of ...

Fairness: from the Ethical Principle to the Practice of Machine ...

This paper clarifies why bias cannot be completely mitigated in Machine Learning (ML) and proposes an end-to-end methodology to translate the ethical principle ...

Toward Fairness, Accountability, Transparency, and Ethics in AI for ...

Machine learning (ML) algorithms have become pervasive in today's world, influencing a wide range of fields, from governance and financial decision-making to ...