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| Data Fairness: A New Social Issue in the Era of Digital Economy |
| Huo Chaoguang1,2, Zhao Dongxiang3,4,5,6 |
1.School of Information Resource Management, Renmin University of China, Beijing 100872
2.Institute for AI Governance, Renmin University of China, Beijing 100872
3.School of Information Management, Zhengzhou University, Zhengzhou 450001
4.Research Center for “Double World-Class Project” of Henan Province, Zhengzhou 450001
5.Data Governance Research Center of Henan Province, Zhengzhou 450001
6.Zhengzhou Data Science Research Center, Zhengzhou 450001 |
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Abstract With the rapid advancement of the digital economy and ongoing evolution of data intelligence technologies, data fairness is increasingly emerging as a critical social issue that society cannot avoid, owing to the long-standing concerns over income, education, and healthcare fairness. Unlike traditional factors (e.g., labor, capital, land, and technology), data raise complex and thorny social equity issues. Given that theoretical research on data fairness in Chinese academia lags behind practices driven by digital intelligence development and the evolving digital economy, this paper systematically reviews relevant global multidisciplinary research, proposes a comprehensive data fairness framework system, and analyzes the six basic principles of data fairness. The paper discusses the five main dimensions and four edge dimensions of data fairness, as well as the data fairness issues involved in the three main stages of data collection and acquisition: processing and analysis, sharing, and utilization in the life cycle of data analysis. This paper systematically discusses and proposes a content framework of data fairness for the first time, enriching existing theoretical research on data fairness, expanding the new connotation of social equity in the era of the digital economy, and providing theoretical support for data governance.
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Received: 30 January 2025
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