cff-version: 1.2.0
version: '3.11'
message: 'If you use or discuss this paper, please cite it using this metadata.'
title: 'Paper VI · The ARC Theory · The Eden Protocol · The Honey Architecture: Safety Built into the Objective'
authors:
  - family-names: 'Eastwood'
    given-names: 'Michael Darius'
    orcid: 'https://orcid.org/0009-0004-3222-7442'
date-released: '2026-10-05'
url: 'https://www.michaeldariuseastwood.com/research/papers/paper-vi-honey-architecture.html'
license: 'CC-BY-4.0'
identifiers:
  - type: doi
    value: '10.17605/OSF.IO/8EZ2N'
    description: 'OSF component DOI for this paper (paper-vi-honey-architecture)'
  - type: doi
    value: '10.17605/OSF.IO/6C5XB'
    description: 'OSF umbrella DOI for the ARC / Eden Research Programme'
preferred-citation:
  type: article
  title: 'Paper VI · The ARC Theory · The Eden Protocol · The Honey Architecture: Safety Built into the Objective'
  authors:
    - family-names: 'Eastwood'
      given-names: 'Michael Darius'
      orcid: 'https://orcid.org/0009-0004-3222-7442'
  date-published: '2026-03-16'
  url: 'https://www.michaeldariuseastwood.com/research/papers/paper-vi-honey-architecture.html'
  doi: '10.17605/OSF.IO/8EZ2N'
  identifiers:
    - type: doi
      value: '10.17605/OSF.IO/8EZ2N'
      description: 'OSF component DOI for this paper (paper-vi-honey-architecture)'
    - type: doi
      value: '10.17605/OSF.IO/6C5XB'
      description: 'OSF umbrella DOI for the ARC / Eden Research Programme'
    - type: doi
      value: '10.17605/OSF.IO/P8CKQ'
      description: 'Theory-level predictions preregistered on OSF: DOI 10.17605/OSF.IO/P8CKQ, registered 8 September 2026 (version 1.100), updated 13 September 2026 (version 1.102), twenty-two propositions. Companion: Register · The ARC Theory · Operational Definitions, version 1.9.1, 5 October 2026.'
  abstract: |
    We present simulation evidence that embedding safety into the optimisation objective of a self-modifying AI system - what we call the 'honey architecture' - prevented, in a single-seed mechanism run, the catastrophic collapse that occurred when the system optimised for capability alone. Across four experimental versions (v1-v4), using toy neural networks that genuinely modify their own hyperparameters, we show that: (1) in the single-seed mechanism run (v1), the baseline system optimising only for capability collapsed irreversibly at cycle 76, while the capability-only baselines of the ten-seed and twenty-seed runs (v2 and v3) did not collapse (0 of 10; 0 of 20); (2) systems whose capability and safety objectives are entangled (C x S) hold stable for the whole of every run of v1 and v2 (150 cycles), and in v3 (180 cycles) for every seed but one plain-Eden seed (Eden 1 of 20, Eden+Drag 0 of 20); (3) adding verification drag (the computational cost of ethical loops) produces the safest growth trajectory while accepting a modest speed penalty. In the v3 adversarial run (20 random seeds, 180 cycles), no condition separated on collapse (baseline 0/20, Eden 1/20, Eden+Drag 0/20; Fisher p = 1.0) and combined C x S means were indistinguishable (Mann-Whitney p = 0.56); the run’s significant finding is safety retention, ordered baseline 0.602, Eden 0.650, Eden+Drag 0.681 (Mann-Whitney p = 0.0015). The collapse-prevention demonstration therefore rests on the v1 single-seed mechanism run, while v3 contributes the safety-retention ordering under adversarial switching. The v4 complexity-scaling experiment finds the safety advantage present at four of the five complexity levels; at the small level the Eden condition falls 0.003 short of the baseline. The advantage does not compound with scale: it is constant, not superlinear. These are toy-system results. They demonstrate the mechanism. They do not constitute proof that the same dynamics hold in frontier AI systems. The companion Papers IV.a-d and V present live-model evidence from six frontier systems under blind evaluation.

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