With the widespread application of algorithms and big data, the issue of algorithmic gender discrimination has become increasingly prominent, exacerbating social inequality and hindering the achievement of gender equality goals. This study adopts a dual perspective of technology and society to systematically analyze the endogenous risks and social roots of algorithmic gender discrimination. It proposes a diversified governance framework encompassing data collection, algorithm design, technological innovation, ethical norms, legal refinement, and social supervision to mitigate the risks of algorithmic discrimination. The research aims to promote the healthy development of AI technology, foster a fair (non-discriminatory), just (ethical), and transparent (explainable) algorithmic ecosystem, and provide theoretical foundations and practical pathways for gender equality in digital spaces.

Yating Wang. The Formation Mechanism and Pluralistic Governance of Algorithmic Gender Discrimination in the AI Era. Academic Journal of Humanities & Social Sciences (2025), Vol. 8, Issue 11: 195-200. https://doi.org/10.25236/AJHSS.2025.081128.

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