Legal Risk Regulation and Improvement Paths for Algorithmic Recommendation
MENG Yidan
YANG Wenli
Abstract：While algorithmic recommendation systems drive digital economy growth,they concurrently manifest negative effects such as privacy violations,intensified discrimination,and inequality.The primary causes of these risks are the improper use of personal information and the opacity inherent in algorithmic recommendation processes.Taking contextual integrity theory as the logical foundation for personal information protection,this study proposes enhancing China's Personal Information Protection Impact Assessment system by drawing on the EU's Data Protection Impact Assessment framework.By establishing the right to algorithmic explanation as the core mechanism,this research aims to dismantle algorithmic black boxes and construct a refined accountability framework and institutional arrangements for algorithmic recommendation systems.
Keywords：algorithmic recommendationalgorithmic black boxcontextual integrity theorydata protection impact assessment systemright to algorithmic explanation
Publication Date：2025-09-30
Online Publishing Date：2025-09-29(First online date of this platform, not the publication date of the document)
Pages：6( 33-38 )