Governance of Fair Data Usage and Value Distribution: From a Comparative Perspective

Enter The Age of Surveillance Capitalism by Professor Shoshana Zuboff, companies feature the collection of vast amounts of personal data, accumulating substantial private power. This power enables companies to extract “behavioral surplus” from data without offering corresponding benefits to users or considering social benefits. Such data concentration raises concerns about individual privacy loss, economic exploitation, structural inequality and the erosion of democratic values. In response, the European Union emphasizes the fair distribution of the data value by granting users rights over data processing and usage, the United States prioritizes a market-based data transaction approach, while China establishes new property rights. However, existing legal frameworks inadequately address the behavioral issues affecting consumers in data usage and fail to mitigate market failures associated with informational asymmetry. These frameworks overlook the data relations that exacerbate social inequality. Against this backdrop, this study conducts a comparative critical analysis of data privacy laws in the European Union, the United States, and China. It examines the underlying reasons for their differing principles. As data should be harnessed for the benefit of both individuals and society adhering to basic notions of equality, this paper also tries to explores a more equitable path for data governance and value distribution.

Authors

Institutions

Publication Details

Journal
California Digital Library
Published
2026-07-25
DOI
https://doi.org/10.48321/d1117fb66d
Primary Topic
Privacy, Security, and Data Protection
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Governance of Fair Data Usage and Value Distribution: From a Comparative Perspective

博辉 苏
California Digital Library
Privacy, Security, and Data Protection
article

Governance of Fair Data Usage and Value Distribution: From a Comparative Perspective

博辉 苏
article en

Abstract

Enter The Age of Surveillance Capitalism by Professor Shoshana Zuboff, companies feature the collection of vast amounts of personal data, accumulating substantial private power. This power enables companies to extract “behavioral surplus” from data without offering corresponding benefits to users or considering social benefits. Such data concentration raises concerns about individual privacy loss, economic exploitation, structural inequality and the erosion of democratic values. In response, the European Union emphasizes the fair distribution of the data value by granting users rights over data processing and usage, the United States prioritizes a market-based data transaction approach, while China establishes new property rights. However, existing legal frameworks inadequately address the behavioral issues affecting consumers in data usage and fail to mitigate market failures associated with informational asymmetry. These frameworks overlook the data relations that exacerbate social inequality. Against this backdrop, this study conducts a comparative critical analysis of data privacy laws in the European Union, the United States, and China. It examines the underlying reasons for their differing principles. As data should be harnessed for the benefit of both individuals and society adhering to basic notions of equality, this paper also tries to explores a more equitable path for data governance and value distribution.

California Digital Library
Chinese University of Hong Kong (HK)
Reduced inequalities
Openalex Percentile: Top 3%
Privacy, Security, and Data Protection
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.