About
Christopher M. Graziul, PhD
Computational sociologist. Independent advisor on AI governance durability.
What I do
I'm a computational sociologist who works on a single problem: how long does AI governance last before something breaks. Most frameworks measure compliance at a moment. I measure durability — how governance survives model cycles, vendor shifts, regulatory change, and staff turnover.
My background is structural analysis of high-stakes data systems. PhD in sociology from the University of Chicago; applied math and physics undergrad at Virginia Tech; postdoctoral work at Brown. Before launching this practice I was a research assistant professor and data scientist at the University of Chicago. I have nineteen peer-reviewed publications and a position paper accepted at ICML 2025 on AI governance.
Most people in AI governance are either philosophers who can't touch code or engineers who can't think structurally about power. I do both. I write governance frameworks and build decision-process architectures that survive institutional change. The gap between what NIST AI RMF and ISO 42001 ask organizations to do, and what actually happens when models update or the team that wrote the policy leaves — that gap is where the work lives. I call it governance shelf-life.
I also founded the Illinois Data Equity Project, a 501(c)(3) whose founding governance is designed to fold itself into community leadership over time. It is the methodology applied to its own institution. Read the case study →
Selected work
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ICML 2025 — position paper on AI governance
Accepted submission on the structural durability of AI governance frameworks across model and regulatory transitions.
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Nineteen peer-reviewed publications
Computational social science, urban sociology, social-network analysis, and applied NLP. Google Scholar.
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Research Assistant Professor & Data Scientist, University of Chicago (2018–2025)
Computational social science, including translational AI work and methodological infrastructure for structured data systems.
Full academic record at graziul.github.io.
How I work
What you can expect from working together.
Specific over abstract. Roles are paired with named people. Triggers are quantified ("when vendor pricing changes by more than 20 percent"), not vague. Everything has a date or an owner.
Concession over salesmanship. I will tell you when this methodology does not apply, when a competitor is better positioned for your specific situation, or when you don't need an engagement at all.
Productized where it makes sense. Tier 2 has fixed prices, fixed scope, fixed timelines. Hours aren't a useful unit when the work is structured analysis.
Slow on purpose where slow earns its place. The diagnostic delivers in seven to ten business days because a real human reads it. Same-day reports are impressive but they're not what this is.
Curious whether this applies to your situation? Start with the diagnostic.