Female perspectives on AI narratives. Seeking Social Justice

Abstract

The rapid expansion of Artificial Intelligence (AI) is reshaping economic, cultural and political spheres in the Global North. Social media and digital news outlets play a key role in co-creating and shaping AI narratives. This reflects public interest and ignites critical debates about its impact on democracy and social justice. This doctoral thesis aims to address the notable lack of empirical research focused on the gender perspective in AI narratives by establishing a user-centric groundwork, enabling more effective contextualization of news outlets’ portrayals and thus fulfilling its dual objectives. The first objective explores social media discussions on gender bias in AI technologies: analysing user profiles, engagement patterns, and the role of under-represented voices in shaping public perceptions. The second objective examines gender representation in AI journalism, categorizing content and analysing authorship to uncover structural inequalities and the narratives influencing technological development. Together, these approaches investigate the intersection of gender, AI and public discourse. This research bridges the gap in the literature by examining 172,041 tweets over 359 days in 2022 on the social media platform formerly known as Twitter; and 1,700 British and Spanish media headlines published in 2023 and 2024 in The Guardian and El País. It also explores the use of Natural Language Processing (NLP) techniques and Machine Learning (ML) models to uncover underlying concepts of gender inequality applied to AI technologies. It employs Computational Grounded Theory (CGT) to evaluate the structural position of women as social media users and in the journalistic workforce. This approach enables the analysis of vast amounts of data sets systematically. It utilizes techniques such as Social Opinion Mining (SOM) and Latent Dirichlet Allocation (LDA) to fully detect ongoing and systemic gender bias mechanisms. Empirical data from various digital sources help us understand the role of female actors in digital media from a practical perspective. Our social media research highlights the role of female micro influencers, who are often everyday individuals facing challenges linked to gender and racial discrimination. They pág. 12 Female perspectives on AI narratives. Seeking social justice. Belen Fraile-Rojas advocate for an intersectional, collaborative and inclusive approach to understanding gender and race in AI. These influencers frequently work independently, bearing the repercussions associated with stigmatized products and services. The findings from AI-related media coverage and content allocation indicate that female journalists experience both horizontal and vertical segregation, limiting their access to leadership positions and leaving them with fewer opportunities to write more valued content. It also suggests that media bias is intentional, sustained, and poses a major threat to democratic values. From a theoretical perspective, the research supports the argument that feminist critical thought is indispensable in developing balanced AI systems and more balance AI narratives. It offers valuable insights that can guide decision-making for both practitioners and researchers, providing a comprehensive understanding of the topic through a critical lens.