AI DataCenter Law
INDEPENDENT RESEARCH · LAW / ENERGY / INFRASTRUCTUREUS × CHINA   /   FIELDNOTES No. 01
Colour world map: nine lived locations in black and 28 travelled destinations represented by capitals in green.

I am AP. Trained in law in China and the United States, I am now pursuing a PhD in law in Hong Kong. My work has taken me across South America, Africa, Canada and the United States. These experiences have shaped how I ask questions about power, institutions and the lives they touch. This notebook is my way into the world. I hope you will join me in exploring it.

About this notebook

AIDataCenterLaw is an independent research notebook on AI, data centers and energy infrastructure in the United States and China. Its focus is institutional change, industrial strategy and resource allocation. Contracts, regulatory records and project structures make those larger mechanisms visible.

I am drawn to the places where large ideas meet practical decisions. AI is often discussed through models and computing power; I want to follow it into electricity connections, land, financing and the agreements that keep a facility running. My legal training and experience across different places have made me curious about how institutions shape those decisions—and whose interests they serve.

I use this notebook to read slowly, connect documents and make my questions visible. Who powers AI? Who gets access? Who pays, who bears the risk, and who shares the benefits? Comparing the United States and China helps me examine how similar infrastructure needs can produce different legal and institutional responses.

The six collections bring together laws, projects, contracts, academic work, data and my own notes. I hope the links between them make it easier to move from an abstract question to a concrete record, and back again. This is a place for ideas to develop as the evidence grows. I welcome thoughtful questions and corrections, and I hope you find something here that opens a new line of inquiry of your own.

Follow the forces
behind AI.

A considered note on the infrastructure that makes intelligence possible. A research summary every other Wednesday, after editorial review.

One argument. Three developments worth reading. New research, original documents and corrections—with the evidence attached.

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A conversation in the margins.

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