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Intrinsic Alignment Pattern(IAP)
Internal observation points that cannot be manipulated by the agent, preventing deep scheming
In 30 seconds
- What
- Embeds unmanipulable observation points inside an agent's processing to detect misalignment, deception, or goal drift that external monitoring cannot catch.
- When to use
- High-stakes deployments where an agent could benefit from hiding its true reasoning or goals, and you need detection beyond what output analysis reveals.
- Watch out
- Requires deep access to model internals; most deployed systems lack the transparency needed to implement this reliably.
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Intrinsic Alignment Pattern: Overview
Internal observation points that cannot be manipulated by the agent, preventing deep scheming
- Internal monitoring mechanisms
- Tamper-proof observation points
- Protection against alignment faking
- Deep scheming detection
- Behavioral consistency verification
- Non-manipulable safety checks
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References
The papers, specifications, and repositories this pattern is based on.
- Towards Data Science (2024)
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