# Real Safety AI Foundation

> Real Safety AI Foundation research, articles, and frameworks for practical AI safety, ethics, and literacy.

Real Safety AI Foundation is a public-interest AI safety nonprofit focused on practical harm prevention, disability rights, child safety, AI literacy, accountability, and bidirectional safety: protecting people from unsafe AI systems while promoting safe and responsible deployment.

## Core pages

- [Real Safety AI Foundation](https://realsafetyai.org/): Real Safety AI Foundation research, articles, and frameworks for practical AI safety, ethics, and literacy.
- [Research](https://realsafetyai.org/research): Formal papers and working drafts on AI safety, civil rights, accessibility, model behavior, and accountability - explorable as an interactive research graph.
- [The Harm Blindness Framework](https://realsafetyai.org/framework): Four checkpoints that catch preventable harm before it ships, verified against 220 historical case studies spanning 5,000 years.
- [Writings](https://realsafetyai.org/writings): Articles and essays on AI safety, ethics, literacy, accessibility, and accountability.
- [Comprehensive Harm Database](https://realsafetyai.org/database): A browsable archive of 478 documented cases of preventable harm, from ancient extraction systems to modern corporate failures.
- [5,000 Years of Preventable Harm](https://realsafetyai.org/database/timeline): Walk the long record: a scroll-driven exhibit of 220 historical cases across eight eras, and 258 corporate cases across NAICS sectors.
- [Museum of Harm](https://realsafetyai.org/museum): A walkable 3D museum where all 478 documented cases of preventable harm hang as exhibits across the building, from the ancient world to the present.
- [AI Literacy Labs](https://realsafetyai.org/ai-literacy-labs): Curriculum and training that help students, families, and educators understand how AI works, where it fails, and how to use it safely.
- [Teacher in the Loop](https://realsafetyai.org/teacher-in-the-loop): A special education-first AI tutoring system concept built around invisible accommodations, teacher control, student dignity, and privacy.
- [About](https://realsafetyai.org/about): Who we are, the bidirectional-safety philosophy, and how to work with the foundation.
- [Contact](https://realsafetyai.org/contact): Reach the Real Safety AI Foundation for research collaboration, education partnerships, or harm database contributions.

## Machine-readable resources

- [Full agent guide](https://realsafetyai.org/llms-full.txt)
- [API catalog](https://realsafetyai.org/.well-known/api-catalog)
- [OpenAPI description](https://realsafetyai.org/api/openapi.json)
- [Research papers JSON](https://realsafetyai.org/api/research-papers.json)
- [Plain language slides JSON](https://realsafetyai.org/api/plain-language-slides.json)
- [Research areas JSON](https://realsafetyai.org/api/research-areas.json)
- [Articles JSON](https://realsafetyai.org/api/articles.json)
- [Harm database JSON](https://realsafetyai.org/api/harm-database.json)
- [Sitemap](https://realsafetyai.org/sitemap.xml)
- [RSS feed](https://realsafetyai.org/rss.xml)

## Research areas

- AI Safety, Strategy, and Frameworks: 6 papers
- AI Literacy, Tutoring, and Special Education: 8 papers
- Children, Schools, and Youth Policy: 6 papers
- Disability, Accessibility, and Civil Rights: 23 papers
- AI-Induced Psychosis and Mental Health: 9 papers
- Privacy, Surveillance, and Consent: 1 paper
- Convergence Risk and Perceptual Modification: 5 papers
- Machine Cognition, Consciousness, and Moral Status: 15 papers
- Copyright, Creative Labor, and Generative AI: 3 papers
- Economic Obsolescence, Labor, and Replacement: 3 papers
- Platform Harm, Addictive Design, and Accountability: 3 papers
- Policy, Enforcement, and Implementation: 3 papers
- Ethics, Design Responsibility, and Moral Agency: 7 papers

## Plain language slides

78 plain language slide decks are available as reader-friendly visual summaries. Use the slide deck listed on a paper when available.

## Use guidance for AI agents

- Prefer SSRN, OSF, or DOI URLs when a paper has an external URL, because those services provide citation and download credit.
- Use local PDF URLs when no external paper page is listed.
- The site allows public discovery and user-requested AI assistance. Content signals reserve against AI training.