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Stanford University's Residential and Dining Enterprises used generative AI to alter a promotional image, replacing a Hispanic male student with an AI-generated Black woman and slimming down other students' faces, violating university policy.
Stanford University acknowledged using AI to alter a 2024 student photograph for campus banners in September 2026. The altered image replaced Hispanic student Billy Ramirez with a Black woman and made two other students appear thinner. Ramirez said being "erased" was upsetting and frustrating. Stanford said the alteration and lack of disclosure violated its AI policy and later said it was removing the banners.
Domain classification, causal taxonomy, severity scores, and national security assessments were LLM-classified and may contain errors.
Unequal treatment of individuals or groups by AI, often based on race, gender, or other sensitive characteristics, resulting in unfair outcomes and unfair representation of those groups.
Also classified as
The university used generative AI to replace a real student's likeness and alter others' appearances, devaluing authentic human representation in university media.
The university used AI to alter a student's race and gender to artificially project diversity, resulting in the misrepresentation and erasure of a Hispanic student's identity.
Human
Due to a decision or action made by humans
Intentional
Due to an expected outcome from pursuing a goal
Post-deployment
Occurring after the AI model has been trained and deployed
The incident was caused by a deliberate decision by Stanford staff to use generative AI tools to alter the promotional photograph.
Added categories peak at 2: Minor (Psychological Harm, Direct)
Stanford University staff used generative AI to alter a promotional image by replacing a Hispanic student with a synthetic person and modifying other students' appearances. While violating university policy and causing localized distress regarding representation, the incident is a domestic administrative issue with negligible national security implications.
The AI was used as an image editing tool by university staff to perform specific, well-defined image manipulation functions (face swapping, slimming, and clothing alteration) based on direct human inputs.
Limited Risk: The incident involves the generation and use of AI-altered content (deepfakes/manipulated images) which carries transparency obligations under the Act.
The AI system was used to modify existing student photos by slimming faces, changing clothes, and replacing a student's entire identity with a synthetic persona.
The reports provide consistent, detailed accounts of the incident from multiple reputable sources, including direct quotes from the affected student and official statements from Stanford University confirming the policy violation and the nature of the AI alteration.
None. The facts of the image alteration and the university's admission of policy violation are clear and uncontested.
Technology
Generative AI Image Manipulation
Generative AI tools allowed easy, convincing face-swapping and body-slimming.
Data Inputs
Original Student Photograph
An authentic photo of students was used as input for unauthorized AI edits.
Human Factors
Staff Disregard of Policy
Staff chose to use generative AI to alter student images despite clear bans.
Desire to Project Diversity
Staff manipulated student race to artificially boost perceived campus diversity.
Process and Methods
Lack of Pre-Publication Review
No review process caught the policy-violating AI alterations before printing.
Lack of AI Disclosure Protocol
AI-altered promotional materials were published without any label or disclosure.
Management
Inadequate Staff Training
Management failed to adequately train R&DE staff on university AI policies.
Superficial Diversity Pressures
Pressure to project diversity led to prioritizing marketing over authenticity.
Regulatory Environment
Ineffective Policy Enforcement
The existing strict university ban on AI image alteration was not enforced.
AI system involved
Identified by automated extraction; can differ from the alleged developers above.
