Mirroring the bias: gender and artificial intelligence

Abstract

Following COVID-19, there has been an increase in digitization and use of Artificial Intelligence (AI) across all spheres of life, which presents both opportunities and challenges. This commentary will explore the landscape of the gendered impact of AI at the intersections of Science and Technology Studies, feminist studies (socialist feminism), and computing. The Global Dialogue on Gender Equality and Artificial Intelligence (2020) organized by UNESCO highlighted the inadequacy of AI normative instruments or principles which focus on gender equality as a “standalone” issue. Past research has underscored the gender biases within AI algorithms that reinforce gender stereotypes and potentially perpetuate gender inequities and discrimination against women. Gender biases in AI manifest either during the algorithm’s development, the training of datasets, or via AI-generated decision-making. Further, structural and gender imbalances in the AI workforce and the gender divide in digital and STEM skills have direct implications for the design and implementation of AI applications. Using a feminist lens and the concept of affective labor, this commentary will highlight these issues through the lenses of AI in virtual assistants, and robotics and make recommendations for greater accountability within the public, private and nonprofit sectors and offer examples of positive applications of AI in challenging gender stereotypes.

Keywords:

• Gender
• artificial intelligence
• bias
• algorithms

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes on contributors

Ardra Manasi is a development practitioner based in New York City, with expertise in gender policy, migration, and technology for development. She works as a Senior Program Coordinator for Advocacy & Partnerships at the Center for Women’s Global Leadership (CWGL), where she specializes in gender, labor and human rights.

Subadra Panchanadeswaran, PhD is a Professor at Adelphi University School of Social Work. Dr. Panchanadeswaran studies female sex workers and sexual minorities’ experiences around gender-based violence and HIV/AIDS. She also studies immigrant South Asian women in the U.S. who experience violence.

Emily Sours (she/her) is a master's student in Women’s, Gender, and Sexuality Studies at Rutgers University. With experience working with NGOs, Emily brings theory and praxis together to advance the rights of women, LGBTQ+ persons, and marginalized groups.

Seung Ju Lee is a doctoral student at Adelphi University in the School of Social Work. Her primary research interest is intimate partner violence, with a specific focus on women's financial independence, and culturally relevant assistance, programs, and policy for communities of color, including immigrant populations.