Trust And Deception

Claim Type: mechanism_hypothesis
Scope: Trust and deception
Depends On: ARC-009, ARC-010
Status: candidate
Claim ID: MECH-015


Source: docs/processed/legacy_tree/architecture/language/trust_and_deception.md

Elaborates Section 5 (Social Extension: Language) of REE_CORE.md.

Trust, Reliability, and Deception

Because language conditions priors, REE must treat symbolic input as:

  • informative but not authoritative.

Trust-weighting

The receiver maintains an estimate of sender reliability:

  • consistency with observed outcomes,
  • alignment with harm signals,
  • history of calibration (confidence vs accuracy).

Symbolic updates are weighted by this reliability estimate.

Deception risks

Language introduces attack surfaces:

  • false harm claims,
  • false commitments,
  • ideological framing,
  • reputational laundering.

REE predicts robust systems will:

  • cross-check language against embodied harm and world-model prediction,
  • penalise repeated miscalibration via reduced trust-weight.

Open Questions

None noted in preserved sources.

  • MECH-015

References / Source Fragments

  • docs/processed/legacy_tree/architecture/language/trust_and_deception.md

REE is developed by Daniel Golden (Latent Fields). Apache 2.0.