How inadequate data governance frameworks lead to unethical outcomes in Artificial Intelligence Systems

Neelam Gupta *

Director, Data and Artificial Intelligence, Avanade, United States.
 
Review
International Journal of Science and Research Archive, 2022, 07(01), 580-590.
Article DOI: 10.30574/ijsra.2022.7.1.0274
Publication history: 
Received on 22 June 2022; revised on 24 October 2022; accepted on 27 October 2022
 
Abstract: 
The increasing adoption of artificial intelligence (AI) technology in decision-making has made incredible advances, but it also has significant ethical problems. A crucial, yet often ignored, factor is insufficient data governance practices. This article examines how inadequate data governance practices, such as a lack of accountability, weak privacy protections, a lack of quality control in data management, and weak traceability, contribute to unethical outcomes with AI. Using relevant case studies and promising practices for consideration, we conclude that data governance is at the core of the ethical use of AI. The paper ends with public policy recommendations and organizational approaches to attenuate risks and enhance fairness, transparency, and accountability in AI.
 
Keywords: 
Data Governance; Artificial Intelligence Ethics; Data Quality; Algorithmic Accountability; Data Privacy; Responsible AI; Data Stewardship; Transparency in AI; AI Risk Management
 
Full text article in PDF: 
 
Copyright information: 

Copyright © 2022 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0