2024, Vol. 5, Issue 1, Part A
Data diversity and its impact on machine learning fairness
Author(s): Abdulaziz Alruwaili and Malek Alsalim
Abstract: Machine learning algorithms are increasingly deployed across various domains, influencing critical decisions in finance, healthcare, education, and criminal justice. As these systems impact more aspects of human life, ensuring their fairness has become imperative. Data diversity, a crucial element in achieving fairness, encompasses the inclusion of varied data points representing different demographics, socio-economic backgrounds, and scenarios. This research article explores the importance of data diversity in machine learning, examines its impact on model fairness, and discusses strategies for fostering diversity in datasets to enhance the equitable performance of machine learning systems.
DOI: 10.33545/27075907.2024.v5.i1a.60Pages: 38-41 | Views: 67 | Downloads: 33Download Full Article: Click Here
How to cite this article:
Abdulaziz Alruwaili, Malek Alsalim.
Data diversity and its impact on machine learning fairness. Int J Cloud Comput Database Manage 2024;5(1):38-41. DOI:
10.33545/27075907.2024.v5.i1a.60