Inherent Limitations of AI Fairness
Inherent Limitations of AI Fairness - Communications of the ACM
AI fairness should not be considered a panacea: It may have the potential to make society more fair than ever, but it needs critical thought and outside help ...
Inherent Limitations of AI Fairness | Communications of the ACM
Abstract. AI fairness should not be considered a panacea: It may have the potential to make society more fair than ever, but it needs critical ...
[2212.06495] Inherent Limitations of AI Fairness - arXiv
Many technical solutions for measuring and achieving AI fairness have been proposed, yet their approach has been criticized in recent years for ...
(PDF) Inherent Limitations of AI Fairness - ResearchGate
powered by machine learning are increasingly rare, so long as enough data of sufficient quality is available. ... [26]. At the same time, fairness ...
inherent limitations of ai fairness - arXiv
We consider eight inherent limitations of this prototypical fair AI system, which each affect its different components and levels of abstraction ...
Navigating the Challenges of AI Fairness, Bias and Robustness
In response to these issues, researchers began to investigate bias, discrimination, and robustness in AI algorithms and to develop techniques ...
[PDF] Inherent Limitations of AI Fairness | Semantic Scholar
AI fairness should not be considered a panacea: It may have the potential to make society more fair than ever, but it needs critical thought and outside ...
Faizan J. on LinkedIn: Inherent Limitations of AI Fairness
To improve the efficacy of such systems, the cited article highlights limitations of technical AI fairness systems: 1) Lack of ground truth: AI ...
Inherent limitations of AI fairness - Ghent University Library
Though many technical solutions for measuring and achieving AI fairness havebeen proposed, their model of AI fairness has been widely criticized in recentyears ...
The Fairness Frontier: Ethical Challenges in AI Development
Given the mathematical constraints highlighted by impossibility theorems such as that exemplified in Sidebar 2, AI developers face ethical ...
The possibilities and limits of algorithmic fairness (Part 1) - Office of ...
However, the disadvantage of sufficiency is that it allows an AI / ML model to embed forms of discrimination within its features, so long as the ...
Inherent Limitations of AI Fairness - OUCI
AI fairness should not be considered a panacea: It may have the potential to make society more fair than ever, but it needs critical thought and outside ...
6.3: Fairness | AI Safety, Ethics, and Society Textbook
There are several problems with trying to create fair AI systems. While we can try to improve models' adherence to the many metrics of fairness, the three ...
It may have the potential to make society more fair than ever, but it ...
Inherent Limitations of AI Fairness: AI fairness should not be considered a panacea: It may have the potential to make society more fair than ever, but it ...
Policy advice and best practices on bias and fairness in AI
Fairness in AI (or simply, fair-AI) aims at designing methods for detecting, mitigating, and controlling biases in AI-supported decision making ...
February 2024 CACM: Inherent Limitations of AI Fairness - YouTube
Maarten Buyl discusses "Inherent Limitations of AI Fairness," a Research Article in the February 2024 CACM.
Inherent limitations of AI fairness - UGent Biblio - Universiteit Gent
Buyl, Maarten, and Tijl De Bie. 2024. “Inherent Limitations of AI Fairness.” COMMUNICATIONS OF THE ACM 67 (2): 48–55. doi:10.1145/3624700.
Fairness and Bias in Artificial Intelligence: A Brief Survey of Sources ...
While fairness and bias are closely related concepts, they differ in important ways, including that fairness is inherently a deliberate and intentional goal, ...
Communications of the ACM on X: "“Inherent Limitations of AI ...
Inherent Limitations of AI Fairness,” by Maarten Buyl @UGent and @TijlDeBie, estimates how far technical approaches can go in measuring and ...
Addressing issues of fairness and bias in AI - Thomson Reuters
Old or incomplete data sets are another source of potential bias, both in the development and implementation of algorithmic models, she said, ...