The Ethics of Data and Its Governance: A Discourse Theoretical Approach

Stahl, Bernd Carsten

Abstract

The rapidly growing amount and importance of data across all aspects of organisations and society have led to urgent calls for better, more comprehensive and applicable approaches to data governance. One key driver of this is the use of data in machine learning systems, which hold the promise of producing much social and economic good, but which simultaneously raise significant concerns. Calls for data governance thus typically have an ethical component. This can refer to specific ethical values that data governance is meant to preserve, most obviously in the area of privacy and data protection. More broadly, responsible data governance is seen as a condition of the development and use of ethical and trustworthy digital technologies. This conceptual paper takes the already existing ethical aspect of the data governance discourse as a point of departure and argues that ethics should play a more central role in data governance. Drawing on Habermas’s Theory of Communicative Action and using the example of neuro data, this paper argues that data shapes and is shaped by discourses. Data is at the core of our shared ontological positions and influences what we believe to be real and thus also what it means to be ethical. These insights can be used to develop guidance for the further development of responsible data governance.

Citation

Stahl, B. C. (2025). The Ethics of Data and Its Governance: A Discourse Theoretical Approach. Information, 16(6), Article 497. https://doi.org/10.3390/info16060497

• Journal Article Type: Article
• Acceptance Date: Jun 12, 2025
• Online Publication Date: Jun 15, 2025
• Publication Date: 2025-06
• Deposit Date: Jun 17, 2025
• Publicly Available Date: Jun 18, 2025
• Journal: Information
• Electronic ISSN: 2078-2489
• Publisher: MDPI
• Peer Reviewed: Peer Reviewed
• Volume: 16
• Issue: 6
• Article Number: 497
• DOI: https://doi.org/10.3390/info16060497
• Public URL: https://nottingham-repository.worktribe.com/output/50441693
• Publisher URL: https://www.mdpi.com/2078-2489/16/6/497