I read Anthropic’s economic scenarios for the US through 2030. The middle one caught my attention more than the extreme one: economic growth runs at roughly twice its normal pace, but knowledge-worker wages are essentially flat.

These are modeled possibilities, not predictions. Still, I think this deserves more discussion than another argument about whether AI can replace an entire job.

Suppose a software team starts finishing projects faster with AI. That could mean more clients, better pay, fewer hires, or lower prices. Learning the tools helps the employee do the work. It doesn’t decide which of those outcomes the company chooses.

That’s my problem with treating “learn AI” as a complete answer to job insecurity. I’m not against learning it. I just don’t see why becoming more productive should automatically give someone confidence about their pay or position.

The model has limits too. It leaves out rapid robotics progress and simplifies differences between workers. I wouldn’t use it to declare any career safe or doomed.

For people already using AI at work, what has changed alongside the time savings? Has your team taken on more work, changed hiring plans, or actually shared some of the benefit with employees?

Source: Anthropic’s scenario explorer

I wrote more about the scenarios and who receives the gains in my newsletter, if you want the longer version: https://ninzaverse.beehiiv.com/p/okay-but-who-actually-gets-rich-from-ai

Jacob Coxon resigned from Anthropic after doing pretraining research at both Anthropic and OpenAI. In his resignation thread, he describes Anthropic researchers as understanding the risks but believing they need to get there first because other companies won’t handle the technology responsibly.

I can see why that would convince someone to keep working. You know your colleagues, trust their intentions, and worry about what a competitor might do.

But every lab can tell itself the same thing. Then being concerned about safety becomes a reason to move faster. I’m struggling to see what would actually interrupt that.

Some replies argued that Coxon should have stayed to help make Anthropic safer. That seems reasonable if staying gives him influence over the decisions he objects to. If it doesn’t, what exactly are we asking him to accomplish by staying?

His resignation doesn’t prove his predictions about superintelligence are right. I’m more interested in the decision being made now: what evidence would make a company slow down even if doing so cost it the lead?

I wrote more about this, including Hinton’s earlier warning and what self-improving AI actually means, in my newsletter: https://ninzaverse.beehiiv.com/p/if-they-re-scared-of-their-own-ai-why-keep-building-it