Artificial Intelligence · Theory, Methodology, Practice, Training
What will become of the human —
and how will it be narrated?
That is my research question for the age of artificial intelligence. AI is not just a tool entering the workplace. It is a new informational environment — and my scholarship argues that environments write themselves into people. AI will reshape what counts as work, what work is worth, and therefore what people believe they are worth. It will participate in the narration of the human. Narration, my framework holds, is how environments reach the body. Which makes artificial intelligence an inscribing actor — a force that writes itself into who we become — and makes the question of who holds the pen the most important question in the room.
Since the beginning
Hooked before the hype
I've been in this since the public beginning — playing with DALL·E when image generation first dropped, then ChatGPT in late 2022 — hooked from the first prompt, and not as a spectator. By 2023 I was publishing on AI and the conditions that shape human expression. By 2024 I had published the Basquiat Pedagogy Framework — a culturally responsive, AI-assisted approach to teacher preparation — and was teaching prompt-engineering workshops to educator networks. By 2025 I was hosting a 12-episode podcast season on AI in education and had built a custom AI module for my own preservice teachers. Today I work daily across the full toolchain — Claude, Cursor, Codex, Gemini, ChatGPT, Perplexity, NotebookLM, Antigravity — not loyal to a brand, loyal to the practice.
I am a theorist of this moment and a practitioner in it — and I intend to help shape the culture of artificial intelligence, not just use its products.
The theory
AI is an environment, and environments write people
My framework, Epigenetic Consciousness, names four modes of environment that write themselves into bodies and minds: material, structural, relational, and informational. Artificial intelligence is the most powerful informational environment ever built — and it is rapidly becoming structural (deciding access), relational (talking with our children), and economic (re-pricing human labor). When the economy renames what work is worth, it renames people. That renaming is narration. And narration, from sociogeny forward, is the mechanism by which environments become flesh.
So the questions I bring to AI are not "which model is best." They are: What will become of the human, and how will it be narrated? Who authors that narration — and will the people most often narrated about finally hold the pen? History already shows us what happens when a powerful narrating system writes a people without their consent. I study that history. I refuse the rerun.
The line I build by, and the line I teach: the human narrates; the machine carries. Sovereignty is not a setting. It is the architecture.
The methodology
An original research method, built on AI — with the human as the pen
Agentic Nkwaethnography
My dissertation's methodology: AI-mediated autoethnography under carrier supervision, extending the endarkened research tradition. The unit of field data is the whole conversation — 5,400+ of them and counting. The carrier narrates; the medium carries; the carrier keeps every judgment that matters.
AMRI — AI-Mediated Reflective Inquiry
The protocol inside the method: structured reflective dialogue with AI in which internalized voices become audible as voices — so the human can re-author them. Reflection at machine patience, judgment at human depth.
One voice at machine scale
I developed a reproducible technique — assembled rules, definitions, and standards every agent loads before working — that lets many parallel AI agents write as one human voice, and lets separate AI systems share one mind about a project. It is citable, teachable, and it transfers to any organization.
The practice
I ship what I theorize
Five working AI platforms, all built from scratch, all carrying the same soul: GoodCatch (recognition-first school behavior), ECHO (whole-child tutoring intelligence), Giovanna (zero-knowledge support for families of neurodivergent children), the EC Research Platform (the dissertation's living artifact), and the NBPTS Living Evidence Repository (national standards work). Plus ED 319GPT for my preservice teachers, published frameworks, workshops, and the podcast. Every one of them draws the same line in code: no child's data leaves the family's hands; no machine interprets a child; the human stays the author of their own story.
The training
Bring this to your people
AI training for educators, leaders, and organizations — hands-on, sovereignty-first, taught by someone who builds with these tools every day, studies learning for a living, and thinks about what AI is doing to the human at the level the moment demands.
eli@4blackcenturies.com Speaking & consulting