0009-0008-1993-9022 About
Erickson Katz — Scholar-Practitioner | Founder, AiSEON Research Initiative
I develop planning architectures, diagnostics, and governance frameworks for artificial intelligence adoption, deployment, and survivability.
Through the AiSEON Research Initiative, my work focuses on a central question:
How can organizations preserve meaningful human judgment as amplification, semantic drift, and acceleration increase?
This work has evolved into the AiSEON Pathways Foundation, a unified theoretical architecture integrating decision admissibility, enterprise semantic integrity, and thermodynamic constraint into a coherent planning science for AI-intensive systems.
The foundation is organized around three interdependent conditions:
Implementation — ensuring decisions remain admissible before amplification occurs.
Endurance — preserving semantic integrity and organizational coherence after amplification.
Temporality — understanding how entropy, drift, and collapse velocity constrain long-term survivability.
The resulting body of work includes the Cognitive-Semantic Integrity Diagnostics for Adoption, Deployment, and Lifecycle (CSID-ADL), Enterprise Semantic Integrity (ESI), Knowledge Thermodynamics, Conversational Thermodynamics, and related governance models examining human anchoring, externalized centers, and semantic survivability.
AiSEON is grounded in a simple principle:
Knowledge need not be perfect to be productive. It must remain recoverable, interpretable, and governable.
Modern institutions rarely fail because they lack information. They fail when amplification outpaces interpretation, correction arrives too late, or meaning can no longer remain coherent across people, systems, and time.
My research therefore focuses on the conditions under which organizations can adopt, deploy, and sustain AI systems without surrendering the causal effectiveness of human judgment.
Field-testing precedes canonization.
Theory is expected to survive contact with implementation.
Areas of Focus
AI Adoption, Deployment, and Governance
Assessment of AI initiatives using decision-admissibility and governance frameworks.
AI Risk, Ethics, and Governance
Governance architecture, oversight design, human anchoring, and externalized-center analysis.
Executive Advisory and Thought Partnership
Strategic analysis, executive decision support, governance advisory, and complex decision systems.
Education, Learning, and AI Integration
AI adoption in education, guided-learning architectures, semantic integrity in learning systems, and institutional readiness.
📩 [email protected]
🌐 https://aiseon.net/
ORCID: 0009-0008-1993-9022
Employment
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Education
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Publications (55)
- Agentic AI: When Machines Decide Faster Than We Can Be Held Accountable Save
- When Meaning Becomes Accountable: Why Institutions Resist Thermodynamic Constraints on Semantic Systems Save
- The Thermodynamics of Temporal Endurance: Why "Built to Last" Wasn't Built to Endure Save
- The Thermodynamics of Advisory Dominance Save
- THE MIRAGE OF CERTAINTY: A Distributed Semantic Governance Demonstration Save
- Knowledge Thermodynamics: A Planning and Risk Model for AI Save
- Airplanes Don't Flap: Why AI Governance Keeps Asking the Wrong Question Save
- When the Envelope Is the Product's Refusal: Vibe-Coding and the Coming Reckoning in AI Governance Save
- When the Question Has Borders: Task Envelope Failure and a Failure-Mode Typology of Externalized Centers in Politically Sensitive AI Dialogue Save
- Made Simple, Made Inadmissible: A Triangulated CSID-ADL Decision-Admissibility Audit of McKinsey's "The AI Assembly Line" Save