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Bias, Fairness and Accountability with Artificial Intelligence and Machine Learning Algorithms.
- Source :
-
International Statistical Review . Dec2022, Vol. 90 Issue 3, p468-480. 13p. - Publication Year :
- 2022
-
Abstract
- Summary: The advent of artificial intelligence (AI) and machine learning algorithms has led to opportunities as well as challenges in their use. In this overview paper, we begin with a discussion of bias and fairness issues that arise with the use of AI techniques, with a focus on supervised machine learning algorithms. We then describe the types and sources of data bias and discuss the nature of algorithmic unfairness. In addition, we provide a review of fairness metrics in the literature, discuss their limitations, and describe deābiasing (or mitigation) techniques in the model life cycle. [ABSTRACT FROM AUTHOR]
- Subjects :
- *ARTIFICIAL intelligence
*SUPERVISED learning
*MACHINE learning
*FAIRNESS
Subjects
Details
- Language :
- English
- ISSN :
- 03067734
- Volume :
- 90
- Issue :
- 3
- Database :
- Academic Search Index
- Journal :
- International Statistical Review
- Publication Type :
- Academic Journal
- Accession number :
- 160029287
- Full Text :
- https://doi.org/10.1111/insr.12492