Data Centers in Space Are a Futuristic Alibi
The newest argument: the AI-governance failures we choose, carried into the fight over where and how the infrastructure itself gets built. The “alibi” isn’t only in the decision — it’s in the story we tell about the hardware.
Read on LinkedIn →The Missing Layer
A six-part series on why AI accountability starts before the output — written in public, one piece at a time, as the case for what Equal Standard Project is building. Each article names one part of the problem. Read in order, they make the whole picture.
The Missing Layer
Why AI Governance Starts With Input, Not Output
The piece that names the problem: governance has been pointed at what AI produces, while what it takes in goes unwatched. Where the failures actually start, and why the window to build the missing accountability layer is open now.
Read on LinkedIn →The Pipeline
What Governing AI Inputs Actually Looks Like
Input governance isn’t surveillance — it’s quality control, the way you test water along the whole pipeline and not just at the tap. What that looks like in practice, and why it makes a system more trustworthy rather than less free.
Read on LinkedIn →The Alibi
AI Isn’t Predatory. It’s Poorly Trained.
The threat was never the technology. It’s the missing accountability around it. People make the choices and use the system as the delivery mechanism, or the cover. There’s a named address on that negligence. There always is.
Read on LinkedIn →The Excuse
AI Isn’t Making Layoffs Inevitable. Leadership Is.
The decision gets blamed on the system, but a person signed it. A look at who actually carries responsibility when an automated call costs someone their job — and why “the data decided” is the oldest excuse in a new coat.
Read on LinkedIn →The Ally
It Isn’t Throwing Anyone Under the Bus. It’s Installing a Seat.
The turn from problem to answer: accountability built for the people these systems judge, not just the institutions running them. Not blame — a seat at the table where the decision gets made.
Read on LinkedIn →The Playbook
What It Looks Like When Someone Actually Builds
The series closes by naming AEGIS publicly for the first time and turning the argument into an invitation — for the municipalities, researchers, and organizations who want to help author the standard rather than inherit it.
Read on LinkedIn →More writing is on the way. Follow along on LinkedIn.
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