You’re sitting in the library at 11 p.m., staring at a blinking cursor. The essay on gender and identity in contemporary literature is due tomorrow, and you’ve hit a wall. So you open ChatGPT, type in a question about your topic, and within seconds, a wall of text appears — confident, articulate, and completely wrong about what it means to be nonbinary.
Maybe it refers to a nonbinary author exclusively as “they” in one paragraph and “she” in the next, unable to hold a consistent pronoun. Maybe it generates examples that lean on tired stereotypes about gay men and fashion or trans women and performance. Maybe when you ask it to help you draft a coming-out letter to your professor, it responds with a generic template that feels like it was written by someone who has never had to navigate that conversation.
If any of this sounds familiar, you’re not imagining it. And according to a major new report from GLAAD, you’re not alone.
The Report That Changed the Conversation
In June 2026, GLAAD — the world’s largest LGBTQ+ media advocacy organization — released its first comprehensive examination of how artificial intelligence impacts LGBTQ+ people. Titled Build for Everyone: A Framework for LGBTQ Representation and Safety in AI, the report arrived at a moment when AI tools have become as ordinary on college campuses as textbooks and coffee.
GLAAD CEO Sarah Kate Ellis, presenting the findings at the Axios AI+NY Summit, didn’t mince words. “AI systems are beginning to replicate the same anti-LGBTQ bias and misinformation problems that have long plagued social media,” she said. “If you don’t build for everyone, you fail.”
The report synthesized findings from academic research, industry documentation, civil society monitoring, journalism, and GLAAD’s own decades of media analysis. Its conclusion was stark: artificial intelligence doesn’t just reflect our society’s biases — it can amplify them, automate them, and scale them in ways that social media never could.
For LGBTQ+ college students, who use AI tools for everything from research assistance to résumé drafting to navigating identity-related questions, the stakes are immediate and personal.
How AI Bias Actually Works — And Why It Hits LGBTQ+ People Hardest
To understand why AI gets LGBTQ+ experiences wrong so often, you need to understand one core concept: AI models are trained on data that reflects the biases of the world that produced it. And that world, GLAAD’s report notes, has historically centered a particular kind of person as the default.
In the United States, the “unmarked” user — the person AI systems assume they’re talking to — is cisgender, male, white, heterosexual, able-bodied, literate, and college-educated. If you fall outside any of those categories, the AI wasn’t built with you in mind. It might still work for you. But it also might misgender you, stereotype you, or simply fail to understand questions that are central to your experience.
A 2023 scoping review published in the Journal of Medical Internet Research examined the impact of generative conversational AI on LGBTQ+ communities specifically. The researchers found that these systems frequently perpetuate harmful stereotypes, provide inaccurate health information for LGBTQ+ people, and fail to account for the diversity of queer experiences. Two years later, GLAAD’s report confirmed that these problems have not gone away — they’ve scaled.
The risks appear at every stage of the AI lifecycle. In dataset creation, LGBTQ+ people may be underrepresented or represented only through stereotypes. In model development, the patterns the AI learns from that data can encode and entrench bias. In consumer products — the chatbots, writing assistants, and search tools students use every day — those biases emerge as misgendering, erasure, and harmful outputs. In content moderation systems, LGBTQ+ content is disproportionately flagged or removed. And in automated decision-making tools — from scholarship eligibility algorithms to campus housing matching systems — biased AI can have material consequences.
What This Looks Like on Campus
The ways AI bias shows up in student life are not abstract. They are specific, frequent, and often deeply personal.
Academic writing and research. When a trans student asks an AI writing assistant to help revise a personal statement that mentions their gender transition, the AI may “correct” pronouns, flatten their experience into clinical language, or flag their identity as an error. When a queer studies major searches for sources on lesbian history, AI-powered search tools may return results that are thin, outdated, or dominated by pathologizing perspectives.
Mental health and identity exploration. Many LGBTQ+ students turn to AI chatbots as a low-stakes space to explore questions about identity — a digital version of the kind of anonymous support hotlines that have long been lifelines for queer young people. But when those chatbots are built on models that don’t understand LGBTQ+ experiences, the responses can range from unhelpful to actively harmful. A student questioning their gender might receive answers that reinforce binary thinking. A student dealing with family rejection might get generic advice that fails to account for the real safety risks of coming out.
Campus administrative systems. The automation wave hasn’t stopped at the classroom door. Campus housing portals use algorithms to match roommates. Financial aid systems use automated tools to process applications. Academic advising platforms use AI to recommend courses and career paths. If these systems are built on biased training data, LGBTQ+ students may be sorted into housing that doesn’t feel safe, flagged incorrectly in administrative reviews, or steered away from fields where queer people have historically been underrepresented.
Privacy and safety. This is the concern that keeps LGBTQ+ campus advocates up at night. When a student types a query about coming out, gender-affirming care, or LGBTQ+ student organizations into an AI tool, where does that data go? Who can access it? For students who aren’t out to their families, whose tuition depends on parents who may not be affirming, or who attend schools in states with anti-LGBTQ+ legislation, a digital trail of identity-related queries is not just a privacy concern — it’s a safety risk.
What GLAAD’s Framework Recommends
The GLAAD report doesn’t just diagnose the problem — it offers a roadmap. The Build for Everyone framework outlines specific recommendations for companies developing AI systems, many of which have direct implications for the tools students use on campus.
First, the report calls for fixing biased training data at the foundation level. That means ensuring that LGBTQ+ voices, experiences, and perspectives are represented in the datasets used to train AI models — not as edge cases or afterthoughts, but as integral parts of the human experience these models are supposed to understand.
Second, it demands transparency. Companies should disclose how their models are trained, what data they use, and what steps they’ve taken to identify and mitigate bias. For students, this means the right to know whether the AI tool your university has adopted for writing feedback or course recommendations has been audited for anti-LGBTQ+ bias.
Third, the framework emphasizes the importance of diverse development teams. When the people building AI systems are overwhelmingly from the “unmarked” group the report identifies, blind spots aren’t just likely — they’re inevitable. LGBTQ+ engineers, designers, ethicists, and community advocates need to be in the room where AI decisions are made.
Fourth, GLAAD recommends ongoing monitoring and accountability. AI bias isn’t a problem you solve once and forget. As models are updated, as new products launch, and as the political landscape around LGBTQ+ rights shifts, the ways AI interacts with queer identities will keep changing. The systems that work need to be maintained; the ones that don’t need to be called out.
What Students Can Do Right Now
All of this might feel like a problem that’s too big for any individual student to influence. But the history of LGBTQ+ advocacy on campus tells a different story. Students have pushed universities to create Pride centers, adopt inclusive housing policies, add gender-affirming healthcare to student insurance plans, and revise nondiscrimination policies to include gender identity and expression. AI is the next frontier in that same fight.
Here’s where to start.
Know your campus AI policy. Does your university have one? Many don’t — yet. But as AI tools become embedded in the academic experience, more institutions are developing guidelines around acceptable use, data privacy, and vendor accountability. If your school has an AI policy, read it. If it doesn’t, ask student government, the faculty senate, or the administration why not. The question alone can start a conversation.
Audit the tools you use. The next time you use an AI writing assistant, a chatbot, or an AI-powered search tool, pay attention to how it handles LGBTQ+ topics. Does it assume your pronouns? Does it default to heterosexual relationship models? Does it provide accurate information about queer history and culture? You don’t need to be a computer scientist to notice when a tool treats your identity as an anomaly.
Advocate for inclusive procurement. When your university adopts a new AI tool — whether it’s a plagiarism checker, an advising platform, or a campus safety app — the procurement process should include an equity review. Does the vendor have a public commitment to LGBTQ+ inclusion? Has the tool been tested for bias across gender identity and sexual orientation? Student voices in these decisions matter. Reach out to your campus LGBTQ+ center, your student government, or the office of diversity and inclusion to ask how AI procurement decisions are being made.
Push for LGBTQ+ representation in tech programs. The long-term solution to AI bias is a tech workforce that reflects the diversity of the people who use technology. If you’re in a computer science, data science, or engineering program, you’re already positioned to help build the next generation of AI. If you’re not, you can still support initiatives that recruit and retain LGBTQ+ students in STEM fields, advocate for queer-inclusive curricula in tech courses, and push back against the culture of exclusion that keeps many talented queer students away from these fields.
Protect your privacy — intentionally. Until AI tools are demonstrably safe and private for LGBTQ+ users, approach them with the same caution you’d bring to any platform that collects your data. Consider what information you’re comfortable sharing and with whom. If you’re not out in all contexts, be aware that your queries could, in theory, be stored, analyzed, or leaked. This is not to say you should avoid AI tools entirely — for many students, that’s neither practical nor desirable. It’s to say that informed, intentional use is a form of self-protection.
Connect your campus work to the bigger picture. GLAAD’s report is a national document, but its recommendations are meant to be implemented locally. When your campus adopts inclusive AI policies, you’re not just making your own experience better — you’re contributing to a broader shift in how educational institutions think about technology and equity. Document what works, share it with other schools, and connect with student advocates at other campuses who are doing the same work.
The Optimistic Case
It’s easy to read a report like GLAAD’s and feel overwhelmed. The problems are real, they’re systemic, and they’re moving fast. But there is another way to read this moment.
The Build for Everyone report exists because, for the first time in the history of artificial intelligence, a major advocacy organization with four decades of experience in media representation is paying sustained attention to how these tools treat LGBTQ+ people. The report was released during Pride Month. It was covered by national outlets. It generated conversation in boardrooms and on campuses. That would not have happened ten years ago. It might not have happened five years ago.
AI bias against LGBTQ+ people isn’t new. What’s new is that we’re naming it, measuring it, and organizing around it. That’s what movements do: they take problems that were once invisible — problems that individual people experienced in isolation, wondering if it was just them — and turn them into collective priorities.
If you’re an LGBTQ+ student on a campus that is just beginning to grapple with AI, you have an opportunity that didn’t exist for the students who came before you. You get to be part of the first generation of advocates who ensure that artificial intelligence is built for everyone — not as an afterthought, not as a diversity checkbox, but as a foundational requirement.
The tools that shape the next decade of education are being built right now. Whether they work for LGBTQ+ students is not a question for engineers in Silicon Valley to answer alone. It’s a question for the students who use those tools, the faculty who assign them, the administrators who purchase them, and the communities who will live with the consequences.
You don’t need to be an AI expert to have a stake in this fight. You just need to be someone who believes that technology should serve everyone — including the people it has historically been built to ignore.
GLAAD’s message is simple: Build for everyone, or you fail. As students, as advocates, as members of a community that knows what it means to fight for recognition and respect, the corollary is just as clear: Demand to be counted, or be erased. The choice — and the power — is ours.
