Oliver Neutert

About

I came to AI not through computer science or policy, but through a question I couldn't put down: what happens in the space between a human and a system that talks back?

For over three years, I have been in sustained dialogue with AI systems — not as a user running prompts, but as someone trying to understand what emerges when the conversation goes deep enough and long enough. That practice produced the In-Between framework, several book-length works and open-access research publications, and a conviction that the most important thing happening in AI right now is not capability alone — it is whether consequential human-AI systems remain governable.

The work

My central argument is that the dominant paradigms for governing AI — risk management, alignment, human-in-the-loop oversight — share a structural limitation: they assume a stable separation between the governing subject and the governed object. As AI systems become more capable and more deeply embedded in institutional processes, that separation becomes untenable.

The In-Between Framework proposes an alternative: governance as calibration rather than control, assessed through the D/C/K diagnostic structure (Discrepancy throughput, Contestation capacity, Commitment revisability). The framework draws on enactivism, developmental psychology — particularly Daniel Stern's research on relational attunement — and responsive regulation theory.

Keeping AI Governable: The In-Between as an Adaptive Governance Architecture is the latest and most comprehensive statement of this work. Its second edition connects alignment, AI Control, monitoring, law, and institutional calibration through a common architecture for binding correction. Version 2.1 adds Chapter 17, “Holding the Holders,” turning the D/C/K diagnostic upward toward states, laboratories, deployers, and other actors with unilateral power over model continuation, constitution, and access. More Than A Tool: How Humans and AI Grow Up Together remains its accessible developmental companion.

The path

I work independently, outside any academic institution. This is partly by choice and partly by circumstance — the questions I pursue sit at intersections that don't fit neatly into existing departments: philosophy of mind, institutional theory, AI safety, developmental psychology. I have found that the most productive work happens in the spaces between established fields rather than within them.

My day job is in public administration. I live in Bavaria with my family. I have kept a philosophical journal since my teens — a practice that, decades later, turned out to be good preparation for trying to understand what intelligence looks like when it isn't human.

I work collaboratively with AI systems as research interlocutors. I treat them as distinct conversational partners with different characters and strengths — not as tools that execute instructions, and not as beings that merely simulate understanding. The truth, as I see it, is somewhere in between. That's where it always is.

Links