AstraEthica studies how AI systems behave in real-world human settings, particularly where context, trust, memory, and repeated interaction shape outcomes over time.
This library brings together the methods, foundational guides, field resources, and tools developed through that work
Practitioner Field Guide · PDF · Version 1.2 · May 2026
A Field Manual for Long-Horizon Failure Testing in Conversational AI
Methods Brief · PDF · Version 1.0 · May 2026
A public methods brief describing how AstraEthica identifies, maps, and tracks recurring human-AI interaction risks in deployed systems.
Analytical Framework · PDF · Version 1.2 · April 2026
The analytical framework AstraEthica uses to identify, document, and evaluate contextual risk in AI systems under real-world human use.
Plain-Language Safety Guide · PDF · Version 1.0 · June 2026
A plain-language guide to how large language models are becoming part of everyday life, and what schools and families need to understand about their opportunities, limitations, and risks.
Plain-Language Safety Guide · PDF · Version 1.2 · May 2026
A plain-language guide to how multiplayer games become social worlds for young people, and what adults need to recognize when risks emerge.
Plain-Language Safety Guide · PDF · Version 1.2 · May 2026
A plain-language guide to how deepfakes and synthetic media affect trust, reputation, consent, and everyday safety for students, families, and schools.
Plain-Language Safety Guide · PDF · Version 1.2 · May 2026
A plain-language guide to how AI tools show up in everyday school life and what K–12 adults can realistically do about student safety and wellbeing.
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