AI(); Creativity(); Diversity(); TTI and Feminism in Gen Z Thesis Work

Generative artificial intelligence is transforming visual design while raising critical questions about gender representation, algorithmic bias, and the reproduction of cultural stereotypes. Text-to-image systems offer new creative possibilities but frequently reinforce established conventions concerning femininity, beauty, sexuality, and power. Recent feminist research highlights these limitations while suggesting opportunities for critical intervention through design. This paper examines two practice-based bachelor thesis projects conducted at Macromedia University Hamburg in 2026, exploring complementary feminist strategies in AI-assisted image generation. An exploratory analysis of 805 bachelor thesis title entries submitted across the university identified 85 (10.6%) explicitly referencing AI, while only two (0.25%) combined AI with feminist concepts, suggesting that this intersection remains an uncommon explicitly articulated research focus within the cohort. Laura Orlinski's The New Muse employs generative AI to reinterpret patriarchal visual narratives in Renaissance and Mannerist paintings. Through iconographic analysis and systematic prompting, she develops alternative representations emphasising female agency while exposing algorithmic biases and content moderation constraints. Lotte Liebich's project explores the cultural repositioning of women's football through a premium editorial magazine featuring AI-generated imagery. Using intentional prompting and critical image selection, she develops a visual language emphasising athletic competence, authenticity, and collective identity rather than conventional gender stereotypes. The comparison identifies critical deconstruction and intentional reconstruction as complementary feminist design strategies. While Orlinski challenges inherited visual conventions, Liebich constructs alternative representations through deliberate creative decisions. Both projects demonstrate the importance of human judgment, cultural awareness, and critical visual literacy in AI-assisted design. As an exploratory, practice-based investigation, the study does not establish the effectiveness of these interventions or their ability to eliminate structural algorithmic bias. Instead, it illustrates how designers can critically negotiate and challenge established visual conventions, highlighting the need to integrate feminist perspectives into AI-assisted design practice and education.