Generative AI, Equality, and Public Administration: The Need for Inclusive Criteria in the Creation of Institutional Advertising

Abstract

Generative Artificial Intelligence (AI) has transformed digital content production and institutional communication, including within the public administration. Proposal/Objective: To analyze the impacts of using generative AI in the creation of institutional advertising, focusing on the reproduction of algorithmic biases and the need for inclusive criteria. Research Method: This is a qualitative study based on a critical literature review regarding generative AI, algorithmic bias, algorithmic racism, public communication, and constitutional principles. Results: The study finds that generative AI, by utilizing data marked by historical inequalities, can reproduce stereotypes, render social groups invisible, and reinforce exclusion, thereby undermining institutional representation and legitimacy. Risks such as algorithmic racism, tokenism, diversity washing, and the erosion of public trust are identified, alongside the need for greater transparency and regulation. Final Considerations: The effective use of AI in public administration requires ethical governance, critical human oversight, and the adoption of inclusive criteria. The importance of *alterity* (recognition of the other) as a guiding principle is highlighted, ensuring that public communication reflects social diversity and that technological innovation contributes to equity and social justice.