Educational Equity in the Algorithmic Era: Gender Equality Challenges and Strategic Responses in Digital Intelligence-Driven Educational Transformation

This study demonstrates that the deployment of digital intelligence technologies in education has not only fallen short of delivering equitable outcomes but has systematically intensified gender disparities through three fundamental mechanisms: institutionalized algorithmic bias, symbolic monopoly, and the erasure of labor. Within the context of declining birthrates and population aging, technological alienation has further constrained female development—reducing mothers to “education workers” saddled with “digital domestic management” while marginalizing elderly women in digital learning spaces. The research contends that education systems must embrace their “remediation” imperative by deliberately aligning technological frameworks with gender justice principles. Empirical studies confirm that algorithmic auditing can demystify technological black boxes, STEM quota policies can challenge symbolic monopolies, and digital labor quantification can expose hidden exploitation. These reforms carry strategic importance in the context of demographic transitions: reducing maternal burdens to support fertility rates, advancing age-friendly technology democratization to address population aging, and safeguarding algorithmic equity to prevent female exclusion from AI-dominated future workplaces—collectively fostering a lifelong learning environment that supports family formation, embraces all ages, and ensures technological justice.