Encoded Sexism: The Erasure of Women in Artificial Intelligence Systems

Authors : Muhammed Ramazan Demirci

Pages : 98-114

View : 81 | Download : 168

Publication Date : 2025-12-31

Article Type : Research Paper

Abstract :This study offers a theoretical and critical examination of the systematic erasure of women in artificial intelligence (AI) systems through the concept of “encoded sexism.” Situated at the intersection of political science and gender studies, the research is grounded in feminist epistemology and critical technology studies. Encoded sexism refers to the embedded gender biases that permeate all stages of AI processes—from data collection and algorithm design to user interaction. By challenging the myth of algorithmic neutrality, the study problematizes the assumption that AI is an objective and impartial tool, emphasizing instead that these systems are inherently shaped by their socio-political and ideological contexts. Utilizing feminist critical discourse analysis, the research conducts case studies in facial recognition, recruitment algorithms, and natural language processing to reveal patterns of algorithmic gender bias. The findings demonstrate that AI systems not only reproduce existing gender inequalities but also contribute to the invisibilization of women. By engaging with the implications of technological development for democratic equality and knowledge politics, the study concludes with policy recommendations for a more just and inclusive AI ecosystem.
Keywords : Kodlanmış Cinsiyetçilik, Algoritmik Önyargı, Yapay Zekâ, Toplumsal Cinsiyet, Feminist Epistemoloji

ORIGINAL ARTICLE URL