Welcome to my AI Lab Notebook

This is where I study AI not as a product, but as a system shaping human life.

Over time, three themes have defined my work:

1. AI Governance as Architecture: I build frameworks like the AI OSI Stack, persona architecture, and semantic version control because AI needs scaffolding, not slogans.

2. The Human Meaning Crisis in Machine Time: I explore how AI destabilizes identity, trust, and authenticity as machine speed outpaces human comprehension.

3. Power, Distribution, and Responsibility: I examine who benefits from AI, who is displaced, and how governance, economics, and control shape outcomes.

These pillars guide everything I write here. AI’s future won’t be determined by capability alone, it will be determined by the structures, meanings, and power dynamics we build around it.

Thanks for reading.

Dan 11/5/25 Dan 11/5/25

Quiet on the Outside, Building on the Inside

In October, I went a little quiet. The lab went quiet. But that quiet was full of motion. What began as loose sketches of AI philosophy solidified the AI OSI Stack: a structured architecture linking human judgment, governance logic, and technical standards like ISO 42001 and NIST’s AI RMF. Now it has a few formal papers and a Github repo. Alongside it, a new agent prototype, GERDY, began reasoning through compliance tasks autonomously, showing that governance can be both automated and transparent.

Dan 9/15/25 Dan 9/15/25

Why You Should Care About AI

AI is already part of daily life. It screens job applications, shapes news feeds, and powers therapy tools. The question is not whether AI matters but whether it is trustworthy. Trust rests on four loops. How AI reasons. How it treats people. How it is governed. How it shapes meaning. When these loops are weak, AI becomes invisible yet unaccountable. When they are strong, AI can become infrastructure we rely on. Caring about AI is not optional. It is already shaping choices that define who we are.

Dan 9/13/25 Dan 9/13/25

Preserving Trust in Language in the Age of AI

AI generates language faster than humans can absorb. The risk is not only misinformation but erosion of meaning itself. Words like sustainable or net zero can be bent quietly until they no longer serve their original purpose. To protect meaning, I propose the idea of a transparent tool called Semantic Version Control. Language must be treated as shared infrastructure, with its evolution logged and visible. The goal is not to freeze words. The goal is to keep their meaning contested in public, not captured in silence.

Dan 9/11/25 Dan 9/11/25

The Irony of AI Governance: When the Tool Helps Write Its Own Rules

I often use AI to help draft policies meant to regulate AI itself. The recursion may seem absurd, but it is honest. Governance is already entangled with the systems it oversees. This does not weaken legitimacy. It clarifies it. Authorship does not lie in generation but in judgment. By acknowledging the paradox, we stop pretending governance is external. We see it as a practice shaped by the very tools it regulates. That honesty builds trust more than distance ever could.

Dan 9/9/25 Dan 9/9/25

The AI OSI Stack: A Governance Blueprint for Scalable and Trusted AI

AI is often spoken of as a single entity, a black box that contains everything. This collapse hides differences and invites monopoly. The AI OSI Stack provides a layered alternative. Like the OSI model did for the internet, it separates hardware, models, APIs, and governance. The result is interoperability, clarity, and embedded trust. The point is not only technical soundness but institutional stability. AI should not be a monolith. It should be a system of layers that can be trusted piece by piece.

Dan 9/8/25 Dan 9/8/25

AI Governance as a Living Practice

Static governance cannot keep pace with AI. Frameworks written once soon become irrelevant. What leaders need are tools for live trade-offs. Dynamic governance treats rules as living practice. Personas, decision briefs, and transparent reasoning make choices visible. The aim is not compliance for its own sake but trust that adapts. Governance must be usable in real time, grounded in philosophy and tested in practice. That is how it becomes credible.

Dan 9/6/25 Dan 9/6/25

Beyond Compliance: Personas as a Reasoning Layer for AI Governance

Compliance frameworks set a floor. They define what organizations must do, but when crises hit, compliance is rarely enough. Leaders need fast reasoning that can withstand pressure and still hold up to audit. Persona architecture provides one path. By simulating structured perspectives such as legal, equity, truth-seeker, and feasibility, leaders can explore diverse angles without losing accountability. Each persona generates options that are resilient in conflict and traceable to evidence. The result is not a replacement for compliance but a complement. Governance becomes adaptive in the moment while still auditable afterward. The power lies in combining philosophy with practice, so that decisions are not only defensible but also credible.

Dan 8/21/25 Dan 8/21/25

A Pivotal Conversation: Learning from Dominique Shelton Leipzig on AI Governance

I had the privilege of a long conversation with Dominique Shelton Leipzig, a leading authority on privacy and AI governance. The exchange offered insights, resources, and guidance that I could not have accessed otherwise. It marked a turning point in my work, clarifying how governance must blend law, ethics, and lived context. For me, it underscored the importance of mentorship in a field that too often moves faster than reflection. Progress is not only technical. It is also relational.