Real AI Governance
🎯 AI Governance Architecture™ for Law Firm Leaders 🔥 AI policy ≠ AI governance 🏆 PhD | Technical Fellow | 10 US Patents | 40+ years designing complex technology systems 📌 Identify invisible AI governance failures before they become liability Most AI failures don't begin with AI.
- Indexed videos, last 90 days
- 46
- Latest publication
- Sep 4, 2026
- Audience
- ~1 subscribers
- Earliest in this view
- Jul 8, 2026
Latest videos
Do you have a named human responsible for review (opens the original)
Read excerpt
You might be an AI Governance Cowboy 🤠 if you can tell me there's a human reviewing AI, but you can't tell me which human. “There's a human in the loop.” Great. Who? If nobody can identify the person responsible for reviewing the AI output, then “human oversight” may just be a comforting phrase. Effective oversight requires more than a human somewhere in the process. It requires a named person with defined responsibility and authority. Who reviews it? What are they required to check? What happen
Is a Human in the Loop Your Oversight Strategy (opens the original)
Read excerpt
You might be an AI Governance Cowboy 🤠 if “a human is in the loop” is your entire oversight strategy. Having a human somewhere in the process doesn't automatically create meaningful oversight. Was the human trained to recognize AI failure? Do they know what they're supposed to verify? Do they have enough time to actually review the output? Can they challenge the AI? Can they reject it? Can they stop the workflow? Or are they simply clicking “approve” because the system told them to? A human in t
Is Trust But Verify Your Methodology? (opens the original)
Read excerpt
You might be an AI Governance Cowboy 🤠 if “trust but verify” is your entire AI verification methodology. It sounds responsible. But verify what? The facts? The sources? The citations? The reasoning? The calculations? The completeness? The legal conclusions? “Verify it” isn't a verification standard. It's an instruction to figure it out yourself. Effective AI verification requires defined standards, assigned responsibility, and a repeatable process. Because when the output matters, “trust but ver
Did you verify the content, not just the Citation (opens the original)
Read excerpt
You might be an AI Governance Cowboy 🤠 if you verify that an AI citation exists but never verify what the cited case actually says. The citation is real. The case exists. The reporter volume is correct. So everything must be fine... right? Not even close. An AI can produce a perfectly legitimate citation that does not support the proposition it was cited for. That's why citation verification has two different questions: Does the source exist? And more importantly: Does the source actually say wh
Has anyone opened your AI Policy since it was approved? (opens the original)
Read excerpt
You might be an AI Governance Cowboy 🤠 if your AI policy lives in a folder nobody has opened since it was approved. A policy can be beautifully written. Reviewed by leadership. Signed. Stored in the right folder. And still be completely useless. Because governance isn't the existence of a document. It's whether the organization uses it to make decisions. Does anyone consult it when adopting a new AI tool? Does it guide employee behavior? Does it define who approves what? Does it change when the
Publishing over time
Last 90 days. Choose a month to open its work.
Recurring subjects
Named in the text we hold. One piece can cover several.
Audience
~1 subscribers
Measured Sep 19, 2026
Source's subscribers, not the number who saw an individual piece.
About this data
Counts cover the work we have indexed. Tone needs enough text and a confident classification. Excerpts and episode notes are not full articles or transcripts.
Identity or attribution wrong? Suggest a correction.