Feminist Perspectives on AI: Ethical Considerations in Algorithmic Decision-Making

Abstract

Artificial intelligence (AI) is increasingly shaping human experiences, yet its design and implementation often reflect entrenched gender biases, raising ethical concerns about algorithmic decision-making. Feminist perspectives on AI critique the opaque and biased nature of algorithmic systems, advocating for a more inclusive and ethical approach to technological development. This paper explores the ethical implications of AI decision-making from a feminist standpoint, examining issues such as data bias, discrimination in automated systems, and the underrepresentation of women in AI development. Algorithmic bias disproportionately affects marginalized groups, reinforcing societal inequalities in areas such as hiring, healthcare, and law enforcement. A feminist ethical framework emphasizes transparency, fairness, and inclusivity, challenging the patriarchal and corporate-driven narratives that dominate AI research and policy. Moreover, feminist scholars argue that AI ethics must extend beyond technical fixes to address systemic power imbalances and cultural biases embedded in data. Ethical AI requires interdisciplinary collaboration, including insights from gender studies, sociology, and critical data science. By integrating feminist ethics into AI governance, policymakers and technologists can work towards equitable and accountable AI systems. This study underscores the importance of participatory AI design and calls for greater diversity in the AI workforce to mitigate bias and ensure ethical algorithmic decision-making. Ultimately, feminist perspectives offer a crucial lens for rethinking AI development, urging a shift from exclusionary practices to inclusive, socially responsible innovation.