What is the ARC Principle?

The ARC Principle, formulated by Michael Darius Eastwood, is a conjecture that a system's cumulative capability U scales as the product of its intelligence I and its recursion R. Formally, U = I x R raised to the exponent alpha, with alpha proposed as a ceiling of about two. It is a design lens for how self-improving processes compound in biological, artificial and cosmic systems, and the framework is positioned as a complement to E = mc squared, not a competing physical law.

The framework was first placed on the public evidentiary record in a self-emailed manuscript timestamped by Google's servers at 02:45:18 UTC on 8 December 2024, where the U = I x R equation appears at line 9 of the version-2 essay. The specific named framing 'ARC Principle - Artificial Recursive Creation' also dates to that anchor. The book Infinite Architects (2 January 2026, ISBN 978-1806056200) presents the full published treatment; Paper I on the Open Science Framework (17 January 2026, DOI 10.17605/OSF.IO/6C5XB) formalises the conjecture for peer distribution.

Empirical work on the recursive-scaling exponent is bounded and honestly reported. An initial sequential exponent estimate of about 2.24 was formally retracted; the current robust estimate from Paper II is approximately 0.49 (sub-linear); the parallel-recursion exponent is approximately zero; the alpha > 1 case is treated as an open pre-registered prediction. Recursion as a structural principle has extensive prior art, notably in evolutionary theory, self-modifying computation and quantum error correction. The priority is over the specific named framing and cross-domain application under the label 'ARC Principle', not over recursion as a concept.