Prompting A Beautiful Young Woman: Gender Stereotypes and the Discursive Power of Image Generative AI

<p><strong>Image generative artificial intelligence (AI) represents a troubling new tool in the social construction of gender. Text prompts, such as an attractive woman with […] perfect anatomy, perfect posture (Midjourney, 2023), create AI images at the rate of 34 million per day (Attie, 2023), indicative of this technology’s ascendant role in the global transmission of gender stereotypes. To investigate and illuminate the extent to which these gender discourses are perpetuated through generative AI platform Midjourney’s text prompts and generated images, I harness the affordances of a linguistic approach. Guided by a critical feminist stance, I utilise corpus linguistic (CL) tools to identify broad discursive patterns across user text prompts. I then perform a social semiotically-informed multimodal analysis (MMA) of AI-generated images, exemplifying and highlighting the CL results. Key findings reveal emerging discourses of normative femininity constructed on a vast scale, alongside those of confinement and hegemonic masculinity – the data analysis of which is deepened through attention to the “mini-narratives” within (Kress & Hodge 1979: 109). Discourses revolve around women as young, white, passive, and epitomising normative beauty standards while men are attributed action and strength-based qualities. Those beyond the binary or who do not align to ‘normative’ representations of appearance are all but erased. In an exciting analytical turn, the emergence of a discourse phenomenon I have labelled ‘algotext’ is discussed, a linguistic strategy platform users employ to evade content filters and elicit explicit images. My research aims to alert current and future image generative AI users to the technology’s sordid training origins, embedded gender biases, and the problematic content it is capable of eliciting and (re)producing. As a result, this research stands to benefit scholars from all linguistic, gender, and media studies fields.</strong></p>