The 2026 AI report flags risks for LGBTQ communities, including biased design, automated discrimination, misinformation, and privacy violations that affect access to information, services, and safety.

Start with the foundation: train AI on inclusive LGBTQ datasets, involve diverse LGBTQ stakeholders, and implement responsible AI practices with guardrails, privacy protections, ongoing testing, and transparency.

Engage civil society through ongoing safety evaluations and red-teaming with affected communities, increase transparency, give independent researchers access to data and models, and fairly compensate consultants integrated into workflows.

Maintain human oversight with nuanced content moderation to preserve legitimate expression, avoid over-reliance on automation, invest in diverse safety reviewers, and require clear labeling for AI-generated content to curb harassment.

The recommendations are presented in a progression from data foundation to governance and civil society collaboration.

Transparency and privacy-by-design are essential: minimize data collection, clarify data practices, enable user control, and embed security and retention limits from development through deployment.

The report follows GLAAD’s established approach to evaluating safety on platforms, building on previous assessments of major companies.

GLAAD seeks to influence AI developers early, noting the ecosystem is currently shaped by a few foundation models from major players that power wider apps.

Responsible AI is beneficial for society and business competitiveness, and GLAAD invites collaboration with industry leaders as a resource.

Designing responsibly is not just ethical—it’s essential for future-proofing AI companies and sustaining long-term trust.

An accompanying analysis highlights broader concerns about colonialism in AI data practices.

Broader AI concerns include model hallucinations, ideological bias in language models, environmental and labor impacts from data centers, and psychosocial effects of prolonged chatbot use.