Eins System: A Scientific, Fair, Real-Time Measure of AI Originators' Influence on Society

1.112026-08-29

Eins0
Eins Arbitration Committee
Document date: 2026-08-29

Abstract

This white paper presents the Empirical Influence Norm System (EINS), a research measurement system whose flagship output is the Eins Index (code 8100): a scientific, fair, real-time measure of the influence that AI Originators — the communities that continuously create, release, and iterate AI models and thereby supply AI productive capacity to society — exert on society. The index output layer is designed to be accessible: from a full indicator state, a small set of well-defined public artifacts (a single number, a single line, a consistent standard) is produced by an explicit presentation-layer mapping, so that a non-specialist can read the landscape without mastering the underlying measurement technology. Accessibility is a property of that output layer. The scientific contribution of the system is a measurement scale rather than a single number. The scale is relative (influence is measured against a cross-sectional reference set rather than an arbitrary absolute), centered (a conservation law ties the sum of the index to the sum of its fundamental anchors, so that transient discussion reorders positions but cannot enlarge the total pool), and real-time (a collection–pricing–display pipeline publishes at minute level). The slow anchor is the Fundamental Anchor (FA): a composite of capability, edge-model coverage, ecosystem stock, and commercial accessibility. The live component is the Real-time Influence (RI) signal: an algebraically explicit renewal-envelope process whose numerical parameters are deliberately not disclosed. The system is only partially reproducible and is designed to remain scrutable. Its invariants (conservation, centralization, boundedness, audit inequalities) are stated as propositions with proofs and are in principle checkable against public data, while the fast, easily manipulated components are kept opaque by design. FA methods and reference parameters are documented in this white paper; RI internals are reserved. This asymmetric disclosure is the institutional basis of the system's trustworthiness.

Keywords: influence measurement; AI Originators; relative index; real-time index; measurement unit; construct validity; public understanding of AI.

Eins System: A Scientific, Fair, Real-Time Measure of AI Originators' Influence on Society

Abstract

Contents

Part I · Motivation and Positioning

Part II · The Object

Part III · The Measure

Part IV · The Mathematical Shell

Part V · Trust and Verification

Part VI · Operations and Evidence

Appendices