Research papers, formal publications, and written thought leadership.
AiSuNe Foundation — registered research and advisory organization
Publications
2026
Governance Twin Framework: Sentinel+Council Architecture for Agentic AI Systems in Digital Twin-Enabled Predictive Maintenance
Presents the Governance Twin framework with Sentinel+Council architecture applied to agentic AI systems operating within digital twin-enabled predictive maintenance environments. Accepted for publication and presentation, co-authored with N. P. Greis and R. Doten.
Conference site → (opens in new tab)Intrinsic Reliability and Robustness for Hyper-Complex Agentic AI Systems: Governance Twin with Sentinels and Council
Extends the intrinsic reliability work by centering the Governance Twin together with Sentinels and Council as the runtime governance architecture for hyper-complex agentic systems.
View paper → (opens in new tab)Delegation Without Living Governance
Argues that governance frameworks built on predefined rules, post-hoc accountability, and static compliance break down once judgment is delegated to agentic AI operating at runtime and machine speed. Introduces runtime governance and the Governance Twin as continuous oversight mechanisms that preserve human relevance during execution.
Read on arXiv → (opens in new tab)Why AI Threats Make Post-Quantum Cryptography Urgent Today
Frames post-quantum cryptography as a coupled governance and security requirement rather than a separate infrastructure upgrade. AI acceleration increases cryptographic risk across model systems, agent communication, and governance infrastructure, making PQC an immediate design concern.
View paper → (opens in new tab)2025
The Governance Twin for Intrinsically Robust and Reliable Agentic AI
Presents the Governance Twin as a parallel runtime architecture for agentic systems whose decisions emerge dynamically. The model separates governance from execution so behavioral drift can be monitored in real time, interventions can happen at system speed, and meaningful human oversight remains possible.
View paper → (opens in new tab)Intrinsic Reliability and Robustness for Hyper-Complex Agentic AI Systems: From Pattern Detection to Collective Intelligence
Addresses the reliability problem created by high autonomy and system complexity. Introduces a Sentinel-Council architecture, together with Minimum Viable Ethics, to monitor evolving behavior, define non-negotiable boundaries, and sustain robust performance under changing conditions.
View paper → (opens in new tab)Ethics, Morals, and Values: A Framework for Real-World Outcomes
Defines ethics as constraints, morals as reasoning, and values as prioritization in order to make ethical language operational inside real systems. The framework aims to translate philosophy into design choices, decision logic, and enforceable governance mechanisms.
View paper → (opens in new tab)AI as Alien Intelligence: A Relational Ethics Framework for Human-AI Co-Evolution
Argues that static ethical frameworks cannot adequately govern advanced AI systems. Proposes a relational ethics approach treating AI as fundamentally alien intelligence, introducing Minimum Viable Ethics as flexible foundational principles for human-AI co-evolution.
Read article → (opens in new tab)From Principles to Relationships: Redesigning Ethics for AI's Alien Cognition
Reframes AI ethics away from static, human-centric rules toward relational ethics. Alien cognition cannot be governed solely through predefined principles; ethics must instead emerge through interaction, adaptation, and ongoing management of the human-AI relationship.
View paper → (opens in new tab)Expert Commentary: Iberian Peninsula Power Outage and Grid Resilience
Expert commentary on the April 2025 Iberian blackout, analysing how poor grid integration — not interconnection — created an energy island vulnerable to cascading failure, with implications for critical infrastructure governance.
Read article → (opens in new tab)DeepSeek and the Future of GenAI
Examines DeepSeek as a signal of where generative AI may be headed, with emphasis on strategic implications for capability development, competition, and governance.
View paper → (opens in new tab)2024
Neurodiversity and Language Skills: The New Superpowers in Generative AI and Prompt Engineering
Explores neurodiversity and language capability as strategic strengths in generative AI and prompt engineering, positioning human cognitive variation as an advantage in shaping effective human-AI interaction.
View paper → (opens in new tab)