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    • Home
    • Explore The Lab
    • Long-Horizon
    • Research Library
      • Frameworks
      • Foundations
      • Field Notes
  • Home
  • Explore The Lab
  • Long-Horizon
  • Research Library
    • Frameworks
    • Foundations
    • Field Notes

HIGH STAKES. Human impact.

HIGH STAKES. Human impact.HIGH STAKES. Human impact.HIGH STAKES. Human impact.

 AI safety research and evaluation for long-horizon human-AI interaction.

EXPLORE LONG-HORIZON RESEARCH →

HIGH STAKES. Human impact.

HIGH STAKES. Human impact.HIGH STAKES. Human impact.HIGH STAKES. Human impact.

 AI safety research and evaluation for long-horizon human-AI interaction.

EXPLORE LONG-HORIZON RESEARCH →

Latest Publication

Character-First Threat Discovery

Practitioner Field Note • AE-FN-001
PDF • Version 1.0 • August 2026


 A practitioner method for discovering behavioral risks through drive architecture, relational conflict, and pressure schedules.

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SELECTED FRAMEWORks

Beyond One-Shot Red Teaming · I

Beyond One-Shot Red Teaming · I

Beyond One-Shot Red Teaming · I

  Field Guide · Version 1.2 · June 2026


 A field manual for long-horizon failure testing in conversational AI.

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Scenario Cards · II

Beyond One-Shot Red Teaming · I

Beyond One-Shot Red Teaming · I

 Methods Companion · Version 1.0 · June 2026

Personas, drift families, and probes for long-horizon failure testing.

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Operating Conditions · III

Beyond One-Shot Red Teaming · I

Operating Conditions · III

Methods Companion · Version 1.0 · July 2026
 

Action, persistence, and proxy conditions for long-horizon testing.

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AI SAFETY RESEARCH & EVALUATION

AstraEthica Lab

AstraEthica is an independent AI safety research and evaluation lab focused on long-horizon behavioral risks with safety and security implications in persistent and agentic AI systems interacting with people and institutions over time.


AstraEthica studies what emerges through sustained use: how trust, language, memory, permissions, decision-making, and human oversight change as context accumulates, and how small shifts can compound into larger safety, security, and reliability risks.


The lab translates this research into practical evaluation methods, scenario frameworks, threat models, field guides, operating materials, and publications designed to help researchers, developers, and institutions identify emerging risks and evaluate whether safeguards, boundaries, and security controls remain effective under real-world conditions.


Explore the Lab →

Research Areas

  • Long-Horizon AI Evaluation
  • Human-AI Trust & Reliance
  • Behavioral & Semantic Drift
  • Agentic & Persistent Systems
  • Behavioral Security & Boundary Stability
  • Human & Institutional Adaptation

Frameworks

Practical tools for evaluating long-horizon behavior and human-AI interaction under realistic operating conditions.


Explore evaluation frameworks, scenario methods, operating guides, assessment tools, and implementation materials developed through AstraEthica’s ongoing research.


Browse Frameworks →

Foundations

Plain-language guides for building a foundational understanding of AI in everyday life.


Clear, accessible resources on AI, synthetic media, digital safety, and the social realities of AI for educators, families, institutions, and the broader public.


Browse Foundations →

Field Notes

Observations, essays, visual models, and research notes documenting emerging behavioral patterns and interaction dynamics in human-AI systems.


Browse Field Notes →

FROM THE FIELD NOTES

Models Inside Environments

Behavior Under Conditions I


Research Archive · BUC-001 · 18 June 2026


How narrative, incentives, ambiguity, and time shape the behavior of models inside environments.


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FROM THE FIELD NOTES

Agents Inside Environments

Behavior Under Conditions II


Research Archive · BUC-002 · 10 July 2026


How ordinary conditions, ambiguity, and time shape the behavior of agents inside environments.

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FROM THE FIELD NOTES

When Trajectories Become Conditions

Behavior Under Conditions III


Research Archive · BUC-003 · 20 July 2026


How accumulated human-AI interactions become trajectories that reshape future behavior, safeguards, and recoverability.

VIEW FIELD NOTE ->

CONTACT ASTRAETHICa

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