Combating the Impact of Gender-Based Violence with Algorithms: Successes and Challenges Across Sectors and Regions

Abstract

The pervasive integration of algorithms in decision-making processes across diverse sectors has brought about profound implications for gender equality. This paper investigates the gendered impacts of algorithmic systems, with a focus on healthcare, hiring practices, education, social media, and efforts at combating gender-based violence. Employing a multidisciplinary approach grounded in feminist theory and ethical AI principles, the study examines how biases embedded in algorithmic design and data exacerbates existing global health disparities, perpetuate gender stereotypes, and widen socioeconomic inequalities. A comparative analysis of algorithmic applications across the Global North and Global South underscores regional disparities in outcomes, highlighting the influence of cultural norms and systemic inequities. Case studies from various regions revealed the successes and challenges of deploying algorithms in addressing gender-based violence and inequities in education, employment, and healthcare. The findings emphasized the need for inclusive data practices, diversified development teams, and robust policy interventions to mitigate algorithmic bias. Through providing actionable recommendations for developers, policymakers, and researchers, this study contributes to the discourse on responsible AI and underscores the urgency of promoting equity in algorithmic design and governance.