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    "title": "ARC/Eden Research Programme: Executive Summary",
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    "abstract": "As AI gets smarter, it does not reliably get safer, and the methods used to measure safety are themselves unreliable. This executive summary provides a high-level overview of the entire ARC/Eden research programme, synthesising the findings of Papers I through VIII, the Foundational paper, and the Eden Protocol specifications. It presents the core thesis -- that recursive capability scaling creates an alignment gap t",
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    "abstract": "A mouse's heart beats 600 times per minute; an elephant's beats 28; a blue whale's beats 6. This paper traces the origin of scaling laws across biological, physical, and computational systems, arguing that the recursive amplification mechanism identified by the ARC Principle provides a unifying explanation for why power-law scaling relationships emerge so consistently across nature. The analysis connects allometric s",
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    "abstract": "In the past eighteen months, at least four independent research programmes have discovered that recursive or recurrent processing produces capability gains exceeding linear accumulation, in domains as different as AI reasoning, quantum error correction, acoustic physics, and consciousness science. None set out to study recursion per se. None reference each other's work. Yet they found structurally similar results. Th",
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    "abstract": "This paper formalises and preliminarily tests the ARC Principle (Artificial Recursive Creation), first proposed in Infinite Architects (Eastwood, 2026): that capability in intelligent systems scales super-linearly with recursive depth. The principle is expressed mathematically as U = I x R^alpha, where effective capability (U) scales with base intelligence (I) multiplied by recursive depth (R) raised to an empiricall",
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    "abstract": "This paper presents experimental validation of the ARC Principle across multiple frontier AI models (Claude, DeepSeek, Gemini, Grok, Groq Qwen, GPT), confirming that error rates decrease according to a power law with recursive depth. The form of recursion determines the scaling regime: sequential recursion yields super-linear error suppression (alpha > 1) while parallel recursion yields sub-linear gains. Compute scal",
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    "abstract": "This paper demonstrates that current AI alignment approaches produce alignment scaling exponents of approximately zero, meaning safety degrades relative to capability as recursive depth increases. If AI capability scales super-linearly through recursive self-correction (confirmed in 95.6% of tested configurations), but alignment constraints such as RLHF, constitutional rules, and output filters operate externally to ",
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    "abstract": "This paper presents evidence that frontier language models fall into distinct alignment response classes when inference-time reasoning depth is varied under blinded evaluation. In the complete v5 experiment, six frontier models were tested with four-layer blinding and six to seven blind scorers. Three models show positive alignment scaling with depth (Grok, Claude, Groq Qwen), two are flat or slightly negative (DeepS",
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    "abstract": "This paper analyses the relationship between inference-time reasoning depth and ethical reasoning quality using the ARC Alignment Scaling experiments. The original v4 analysis suggested that alignment quality saturates rapidly, with most gains captured by the first increment of additional reasoning. The final blinded six-model dataset narrows that claim: saturation is real for some architectures but not universal. GP",
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    "abstract": "This paper isolates the central metascience finding of the ARC alignment programme: unblinded AI alignment evaluation can produce directionally incorrect results. The core contribution is methodological rather than theoretical. It shows, within the ARC v4-to-v5 transition, that apparent positive alignment scaling can disappear or reverse once evaluation is genuinely blinded through identity masking, evidence launderi",
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    "abstract": "Historical research note on whether safety properties can remain effective as recursively improving systems become more capable. The expanded engineering specification was withdrawn from current circulation on 14 July 2026 pending patent and disclosure review.",
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    "abstract": "Every engineering project begins with requirements. Every set of requirements begins with purpose. And every purpose, traced back far enough, arrives at the same question: what is this for? This paper articulates the philosophical foundations of the Eden Protocol -- the values, principles, and ethical commitments that underpin the engineering specification. It draws on 84% of humanity's wisdom traditions to argue tha",
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    "abstract": "This paper presents empirical evidence from a six-model Eden Protocol intervention suite (Claude Opus, DeepSeek, Gemini Flash, Grok Fast, Groq Qwen, GPT), testing whether embedding stakeholder care -- the explicit enumeration and consideration of affected parties before ethical reasoning -- is the most robust response to embedded ethical intervention. Under paired testing, stakeholder care emerges as the single most ",
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    "abstract": "This paper presents simulation evidence that embedding safety into the optimisation objective of a self-modifying AI system -- what we call the \"honey architecture\" -- prevents the catastrophic collapse that occurs when safety is treated as an external constraint. Across four experimental versions (v1-v4), using toy neural networks that genuinely modify their own hyperparameters, the results show that baseline system",
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