A note on AI policy and the conversations we keep getting wrong
Why the loudest AI commentary often misses the point — and what a more useful conversation looks like.
Placeholder essay. This entry exists so the site has at least one piece of writing on the day it goes live. Replace this content with the first real essay — likely a polished version of the Muganga rebuttal — before launch.
The shape of the argument
There is a particular kind of AI commentary that is loud, confident, and useless. It treats every question as either a hype piece or a panic piece. It does not engage with the actual artifacts. It does not name the specific decision the reader needs to make tomorrow.
That kind of commentary is not harmless. It crowds out the conversations we actually need to be having.
What a better conversation looks like
A better conversation names the system being deployed. It names the population the system will touch. It is specific about who benefits and who bears the cost. It does not confuse “we have a policy” with “we have a working policy.” It is willing to be unfashionable.
What I want to do here
Most of what I will publish in this space is some version of that — work that takes a specific AI policy artifact (a national strategy, a corporate AI use policy, a procurement framework) and asks: does this actually work for the people it claims to serve?
The answer is sometimes yes. More often, it is “almost, but not quite, and here is the gap.” That gap is what I want to write into.
Edmonton, May 2026.
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