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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.
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