The Need for a Feminist Approach to Artificial Intelligence

Abstract

Artificial intelligence (AI) presents immense potential and significant challenges concerning algorithmic bias. This paper explores how feminist theory provides a criti-cal lens for understanding and addressing algorithmic bi-as’s root causes and impacts. The historical context of systemic discrimination reveals how power imbalances have shaped data collection and analysis, leading to bi-ased datasets that perpetuate inequalities through AI sys-tems. The "black box" problem further obscures these bi-ases, amplifying discriminatory outcomes in various domains. Feminist interventions, particularly intersec-tional feminism, offer a framework for uncovering how algorithmic bias interacts with multiple forms of oppres-sion. Feminist data science challenges traditional meth-odologies and advocates for transparency, accountabil-ity, and diversity in AI development. Critiques of tech-no-solutionism highlight the need for broader societal change alongside technical fixes. By embracing a feminist approach, we can envision and work toward a future where AI technology is used for social justice, inclusivi-ty, and collective liberation.