Operationalizing Contingency: The Axiomatic Model (AXM) for Applied AI Alignment

{"Abstract":[0],"Current":[1],"methodologies":[2],"for":[3,175,197],"Artificial":[4],"Intelligence":[5],"alignment":[6,61],"operate":[7],"under":[8],"a":[9,120,125,146,231],"fundamental":[10],"systems":[11,53,81,182],"vulnerability:":[12],"they":[13],"attempt":[14],"to":[15,68,171,202],"derive":[16],"ethical":[17,59],"constraints":[18,195],"from":[19,64],"historically":[20],"biased":[21],"human":[22,49,162,211],"datasets.":[23],"This":[24,72,238],"reliance":[25],"on":[26],"subjective":[27,65],"probability-averaging":[28],"floods":[29],"computational":[30,141],"models":[31,201],"with":[32],"changing":[33],"variables":[34],"and":[35,44,57,90,115,165,185,210,218],"undefined":[36],"relational":[37],"weights,":[38],"inevitably":[39],"generating":[40],"un-auditable":[41],"\\"ethical":[42],"hallucinations\\"":[43],"utilitarian":[45],"trade-offs":[46],"that":[47,83,158,248],"compromise":[48],"agency.":[50],"To":[51],"build":[52],"capable":[54],"of":[55,95,110,222,247],"safe":[56],"scalable":[58],"solutions,":[60],"must":[62],"transition":[63],"behavioral":[66],"principles":[67],"objective":[69,136],"ontological":[70],"computation.":[71],"paper":[73,191],"introduces":[74],"the":[75,85,96,108,161,181,193,223,236,242],"Axiomatic":[76,224],"Model":[77,99,225],"(AXM),":[78],"an":[79,135],"executable":[80],"framework":[82],"translates":[84],"formal":[86],"S4":[87],"modal":[88],"logic":[89],"Standard":[91],"Deontic":[92],"Logic":[93],"proofs":[94],"Ontological":[97],"Contingency":[98],"(OCM)":[100],"directly":[101],"into":[102],"applied":[103],"cybernetics.":[104],"The":[105,215],"AXM":[106],"operationalizes":[107],"preservation":[109],"Unconditional":[111],"Human":[112],"Worth":[113],"(□W)":[114],"Free":[116],"Will":[117],"(◇FW)":[118],"through":[119],"dual-mechanic":[121],"architecture.":[122],"It":[123],"establishes":[124],"1D":[126],"Lexicographic":[127],"Governor—a":[128],"strict":[129],"Boolean":[130],"triage":[131],"hierarchy":[132],"governed":[133],"by":[134,235],"function":[137],"(J(a))—that":[138],"prohibits":[139],"subtractive":[140],"trajectories.":[142],"Concurrently,":[143],"it":[144],"deploys":[145],"3D":[147],"State":[148],"Vector":[149],"Space":[150],"(S":[151],"=":[152],"⟨":[153],"X,":[154],"Y,":[155],"Z":[156],"⟩)":[157],"actively":[159],"optimizes":[160],"operator’s":[163],"biological":[164],"psychological":[166],"baseline,":[167],"absorbing":[168],"environmental":[169],"complexity":[170],"maximize":[172],"their":[173],"capacity":[174],"teleological":[176],"choice.":[177],"By":[178],"halting":[179],"at":[180],"formulation":[183],"boundary":[184],"eschewing":[186],"simulated":[187],"empirical":[188],"datasets,":[189],"this":[190],"provides":[192],"mathematical":[194],"required":[196],"future":[198],"machine":[199],"learning":[200],"facilitate":[203],"syntropic,":[204],"transgenerational":[205],"co-evolution":[206],"between":[207],"artificial":[208],"intelligence":[209],"operators.":[212],"Author's":[213],"Note:":[214],"foundational":[216],"concepts":[217],"early":[219],"theoretical":[220],"explorations":[221],"(AXM)":[226],"were":[227],"originally":[228],"serialized":[229],"as":[230,241],"digital":[232],"essay":[233],"series":[234],"author.":[237],"manuscript":[239],"serves":[240],"formal,":[243],"unified":[244],"systems-architecture":[245],"consolidation":[246],"work.":[249]}

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-08-02
DOI
https://doi.org/10.5281/zenodo.21761426
Primary Topic
Embodied and Extended Cognition
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
article

Operationalizing Contingency: The Axiomatic Model (AXM) for Applied AI Alignment

Azusa Allard
Zenodo (CERN European Organization for Nuclear Research)
Embodied and Extended Cognition
article

Operationalizing Contingency: The Axiomatic Model (AXM) for Applied AI Alignment

Azusa Allard
article en

Abstract

Abstract Current methodologies for Artificial Intelligence alignment operate under a fundamental systems vulnerability: they attempt to derive ethical constraints from historically biased human datasets. This reliance on subjective probability-averaging floods computational models with changing variables and undefined relational weights, inevitably generating un-auditable "ethical hallucinations" and utilitarian trade-offs that compromise human agency. To build systems capable of safe and scalable ethical solutions, alignment must transition from subjective behavioral principles to objective ontological computation. This paper introduces the Axiomatic Model (AXM), an executable systems framework that translates the formal S4 modal logic and Standard Deontic Logic proofs of the Ontological Contingency Model (OCM) directly into applied cybernetics. The AXM operationalizes the preservation of Unconditional Human Worth (□W) and Free Will (◇FW) through a dual-mechanic architecture. It establishes a 1D Lexicographic Governor—a strict Boolean triage hierarchy governed by an objective function (J(a))—that prohibits subtractive computational trajectories. Concurrently, it deploys a 3D State Vector Space (S = ⟨ X, Y, Z ⟩) that actively optimizes the human operator’s biological and psychological baseline, absorbing environmental complexity to maximize their capacity for teleological choice. By halting at the systems formulation boundary and eschewing simulated empirical datasets, this paper provides the mathematical constraints required for future machine learning models to facilitate syntropic, transgenerational co-evolution between artificial intelligence and human operators. Author's Note: The foundational concepts and early theoretical explorations of the Axiomatic Model (AXM) were originally serialized as a digital essay series by the author. This manuscript serves as the formal, unified systems-architecture consolidation of that work.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 8%
Embodied and Extended Cognition
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.