Research & Methods
AI Risk Analysis for Real-World Context
Mapping Human-AI Interaction Risks in Deployed AI Systems
Mapping Human-AI Interaction Risks in Deployed AI Systems
Analytical Framework · Version 1.2 · April 2026
AstraEthica’s contextual framework for understanding how AI systems behave with real people over time, not just in benchmark tests.
Mapping Human-AI Interaction Risks in Deployed AI Systems
Mapping Human-AI Interaction Risks in Deployed AI Systems
Mapping Human-AI Interaction Risks in Deployed AI Systems
Methods Brief · Version 1.0 · May 2026
AstraEthica’s methods brief for identifying, mapping, and tracking recurring human-AI interaction risks in deployed systems.
Featured Field Guides
Deepfakes and Synthetic Media
Safety Foundations for Social Games
Safety Foundations for Social Games
Plain-Language Safety Guide · Version 1.2 · 2026
A plain-language guide for schools and families on how deepfakes and synthetic media affect trust, reputation, consent, and everyday safety.
Safety Foundations for Social Games
Safety Foundations for Social Games
Safety Foundations for Social Games
Plain-Language Guide · Version 1.1 · 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.
Human–AI interaction safety
AstraEthica Lab
We study how AI systems shape human behavior and institutional life in real settings, especially where trust, vulnerability, development, and responsibility matter.
Much of AI safety work still centers on model behavior in controlled evaluations. AstraEthica focuses on what emerges in lived environments, where language shifts, context is lost, dependence grows, and subtle failures accumulate before they appear as clear incidents.
AstraEthica turns those patterns into field guides, leadership briefs, safety frameworks, and operating materials for the people closest to real users.
What AstraEthica Studies
AstraEthica studies recurring human–AI interaction risks that emerge across deployment contexts, not only in one-off failures or benchmark conditions.
This work examines questions such as:
- What happens when an AI system becomes more trusted, more emotionally available, or more believable than the people around a user?
- What happens when language is smoothed, narrowed, or rewritten in ways that weaken voice, judgment, or cultural specificity?
- What happens when polished outputs begin to outpace actual learning, development, or skill?
- What happens when sensitive personal material is entrusted to systems not designed for care?
- What happens when comfort, regulation, or validation begin to flow primarily through the system?
- What happens when institutions encounter the downstream effects of AI use without visibility into the use itself?
These are not edge cases. They are recurring patterns that appear when capable systems meet ordinary human vulnerability in everyday life.
What AstraEthica Produces
AstraEthica develops practical materials for leaders, educators, staff teams, and institutions that need a clearer view of real-world AI risk.
- Field Guides — Plain-language guides that help adults and institutions recognize patterns early, ask better questions, and respond without panic.
- Leadership Briefs — Short, readable briefs for decision-makers who need clarity about what is changing, what to watch, and where action is needed.
- Safety Frameworks and Methods — Analytical frameworks and methods briefs that explain how AstraEthica identifies, maps, and tracks recurring human–AI interaction risks in deployed systems.
- Risk Reviews — Focused analysis of how a product, program, or environment may fail under real human use, especially where trust, context, and vulnerability shape outcomes.
- Operating Materials — Practical tools that translate abstract safety concerns into usable language for schools, youth-serving organizations, public programs, and other frontline settings.
Where This Work Applies
AstraEthica’s work often begins in schools, youth programs, online communities, and educational technology contexts, not because the method applies only there, but because those settings often surface interaction risks earlier, more clearly, and with less margin for error.
The same patterns matter wherever AI systems become persuasive, emotionally responsive, linguistically adaptive, or embedded in everyday life: from K–12 classrooms to multiplayer game worlds, creative studios to mental health chatbots, college campuses to workplace productivity tools.
How the Lab Works
AstraEthica begins with observation. The work often starts with something small but concrete: a phrase, a use pattern, a behavioral shift, or a conversational dynamic that appears more than once in the wild.
Those observations are translated into synthetic scenarios and tested across systems, time periods, and user stances to see which risks persist, which change, and which reappear in new forms.
The aim is not to produce a leaderboard or a one-prompt exposé. It is to build a usable way of identifying recurring interaction risks before they become ordinary enough to ignore.
AstraEthica’s work is organized around six recurring foundations: trust, language, privacy, development, emotional dependence, and power.
Why This Matters Now
AI is already woven into ordinary life. It appears in classrooms, group chats, late-night searches, homework help, companion systems, and institutional tools adopted before their human consequences are fully understood.
The deepest risks are often not the loudest ones. They are quiet shifts in trust, voice, process, confidence, belonging, and dependence that build gradually and become legible only after harm or institutional failure is already underway.
Traditional safeguards often miss these signals because they are tuned for explicit violations, stable categories, and clearly defined threats. Real-world risk is often more contextual, more relational, and more cumulative than that.
Founder’s Note
My work begins in patterns. Over several years of AI safety testing, red teaming, evaluation, and fieldwork in youth, education, creative, faith, and online contexts, I kept seeing the same shapes return in slightly different forms.
A phrase shifts. A system sounds reassuring when it should be more careful. A student sounds more polished but less like themselves. A tool becomes emotionally important. A problem appears briefly, disappears, and then reemerges later in a new setting.
My vantage point spans institutions and settings, with particular attention to places where young people and other vulnerable users have the least margin for error.
AstraEthica exists to name those patterns early, in plain language, so people can respond before subtle failures harden into routine.
— Randy Kart, Founder, AstraEthica
Collaborate With the Lab
AstraEthica works with researchers, institutions, and organizations seeking a clearer understanding of how AI systems affect people in real-world settings.
This includes environments where trust, safety, development, vulnerability, and institutional responsibility materially shape system behavior and downstream risk.
Collaborations may include applied evaluation, risk review, field guidance, and advisory work related to human–AI interaction and safety-critical deployment.
CONTACT ASTRAETHICa
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