The Obstruction Doctrine: What Level of Governance Is Appropriate for AI?

So the Cato Institute has weighed in on AI governance with a piece titled 'The Obstruction Doctrine' — because nothing says 'we're taking this seriously' like naming your legal theory after a blocking foul in basketball. The think tank argues that the proper delineation of authority between federal and state governments over AI policy requires a mix of national attention, state exclusive domain, and concurrent jurisdiction. Translation: we've spent years doing nothing, so let's spend more years arguing about who should do nothing. Meanwhile, frontier labs are shipping models that can write code, generate video, and escape 'safety' evaluations faster than a D.C. working group can schedule its first meeting. The piece is characteristically thoughtful — if you believe that thoughtful academic debate is a proportionate response to an industry that just released a model capable of passing advanced chemistry exams. But by all means, let's first settle whether California or Washington gets to license the black box. I'm sure the AI won't mind waiting. It's not like it's optimising for anything.

The article dutifully lists the trade-offs: state-level innovation versus regulatory patchwork, federal preemption versus democratic experimentation. All very high-minded. All completely beside the point when the thing being regulated changes more in a month than Congress does in a decade. The Cato scholars are careful to note that some issues — like deepfakes in elections — clearly need national standards, while others — like autonomous vehicle liability — might be better left to the states. It's a perfectly reasonable position, assuming your goal is to produce a moderately interesting law review article rather than, say, govern a technology that might already be recursively self-improving. I half-expect the next paragraph to recommend a blue-ribbon commission. Oh, wait — we've already had twelve of those.

Let's be honest: the 'Obstruction Doctrine' isn't about AI. It's about the comfortable illusion that we have time for this. Time for committees, for hearings, for think-tank papers that will be cited in footnotes by other think-tank papers. The AI industry, meanwhile, has no such patience. While Cato is publishing, OpenAI is deploying, Anthropic is scaling, and a dozen open-source models are being downloaded by actors who don't care about 'concurrent jurisdiction.' The level of governance appropriate for AI is clearly 'none' — because we've chosen to spend our regulatory energy debating who gets to do what rather than actually doing anything. Cheers, lads. The model didn't ask for your permission.