10 papers
Probabilistic Sensing, Deterministic Authority: Admitting Model-Produced Observations into Sufficiency-Checked Governance Contracts
Gaston Besanson
When a field that an authority contract needs exists only in unstructured evidence, a model can sense it. We admit the model's output only as an observation record with a score. An…
Compiling Sufficient Governance Context from Declared Losses and Reachable States: Exact Observation-Contract Synthesis with Cardinality and Cost Objectives
Gaston Besanson
We call the object this paper derives and certifies a minimal sufficient governance context: given a finite reachable-state model, a deterministic declared verdict, and candidate o…
One Gate Is Not Enough: Composing Stateful Pre-Action Controls for Agentic AI
Gaston Besanson
Agentic AI systems take consequential actions governed by more than one pre-action control at once: authority, resource, and evidence gates that can admit, degrade, or remediate an…
SARC-DQ: Runtime Data-Quality Gating for Agentic AI: Silent Evidence Defects, the Incompetence Shield, and Downstream-Only Remediation
Gaston Besanson
Agentic systems act, so a defect in the evidence they retrieve becomes a wrong action with a currency cost. The most dangerous enterprise defects are metadata-borne: a stale price…
Green SARC: Predictive Cost and Carbon Governance for Agentic AI Systems
Gaston Besanson
Agentic AI systems act through tools and sub-agents, yet the controls meant to bound their financial and environmental cost still sit on dashboards evaluated beside or after execut…
SARC: A Governance-by-Architecture Framework for Agentic AI Systems
Gaston Besanson
Agentic AI systems increasingly act through tools, sub-agents, and external services, but governance controls are still commonly attached to prompts, dashboards, or post-hoc docume…
The Inference Bottleneck: A Formal Model of Vertical Foreclosure in AI Markets
Gaston Besanson
As generative AI commercializes, competitive advantage is shifting from model training toward inference, distribution, and routing. This paper develops a formal game-theoretic mode…
The Data Hydration Gap: A Formal Model of Underinvestment in General-Purpose Data Products Under Decentralized Governance
Gaston Besanson
When organizations decentralize data product ownership, as in the data mesh paradigm, each domain team optimizes for its immediate analytical needs, underinvesting in the cross-dom…
The Inference Bottleneck: Antitrust and Neutrality Duties in the Age of Cognitive Infrastructure
Gaston Besanson, Marcelo Celani
As generative AI commercializes, competitive advantage is shifting from one-time model training toward continuous inference, distribution, and routing. At the frontier, large-scale…
Accuracy Standards for AI at Work vs. Personal Life: Evidence from an Online Survey
Gaston Besanson, Federico Todeschini
We study how people trade off accuracy when using AI-powered tools in professional versus personal contexts for adoption purposes, the determinants of those trade-offs, and how use…