You don't need AI to replace whole jobs 1:1 to have massive displacement.

If AI can do 80% of your tasks but fails miserably on the remaining 20%, that doesn't mean your job is safe. It means that 80% of the people in your department can be fired and the remaining 20% handle the parts the AI can't do yet.

That's exactly the point of the essay though. The way that you're implicitly modeling labor and collaboration is linear and parallelizable, but reality is messier than that:

> The most important thing to know about labor substitution...is this: labor substitution is about comparative advantage, not absolute advantage. The question isn’t whether AI can do specific tasks that humans do. It’s whether the aggregate output of humans working with AI is inferior to what AI can produce alone: in other words, whether there is any way that the addition of a human to the production process can increase or improve the output of that process... AI can have an absolute advantage in every single task, but it would still make economic sense to combine AI with humans if the aggregate output is greater: that is to say, if humans have a comparative advantage in any step of the production process.

Also, you don’t need AI to replace your job, you need someone higher up in leadership who thinks AI could replace your job.

It might all wash out eventually, but eventually could be a long time with respect to anybody’s personal finances.

I'd you team bought the latest IDE for $200/mo and was able to finish tickets, you 50% of your team be laid off?

Or would you just do more stuff?

I feel like most software projects have an endless backlog.

Better IDEs, programming languages, packages, frameworks, etc have increased our productivity, reduced bugs -- but rarely reduced headcount.

Ever hard anyone migrate from php+jQuery to react+node and reduce head count due to increased productivity?

I sometimes reminiscent about the LAMP stack being super productive. But at the time I didn't write tests :)

Wasn't that the point of mentioning Jevon's Paradox though? Like they said in the essay, these things are quite elastic. There's always more demand for software then what can be met, so bringing down the cost of software will dramatically increase the demand for it. (Now, if you don't think there's a ton of demand for custom software, try going to any small business and ask them about how they do bookkeeping. You'll learn quite quickly that custom software would run much better than sticky notes and excel, but they can't afford a full time software developer as a small business. There's literally hundreds of thousands of places like this.)

In reality that would probably mean that something like 60% of the developer positions would be eliminated (and, frankly, those 60% are rarely very good developers in a large company).

The remaining "surplus" 20% roles retained will then be devoted to developing features and implementing fixes using AI where those features and fixes would previously not have been high enough priority to implement or fix.

When the price of implementing a feature drops, it becomes economically viable (and perhaps competitively essential) to do so -- but in this scenario, AI couldn't do _all_ the work to implement such features so that's why 40% rather than 20% of the developer roles would be retained.

The 40% of developer roles that remain will, in theory, be more efficient also because they won't be spending as much time babysitting the "lesser" developers in the 60% of the roles that were eliminated. As well, "N" in the Mythical Man Month is reduced leading to increased efficiency.

(No, I have no idea what the actual percentages would be overall, let alone in a particular environment - for example, requirements for Spotify are quite different than for Airbus/Boeing avionics software.)

The problem is, you won’t necessarily know which 20% it did wrong until it’s too late. They will happily solve advanced math problems and tell you to put glue on your pizza with the same level of confidence.

Why do people make arguments like this?

"Work" isn't a finite thing. It's not like all the people in your office today had to complete 100% of their tasks, and all of them did.

"Work" is not a static thing. At least not in positions of many knowledge-worker careers.

The idea of a single day's unit of "work" being 100%, is really sophomoric.

Also, If 100% of a labor force now has 80% more time...wouldn't it behoove the company to employ the existing workforce in more of the revenue generating activities? Or find a way to retain as much of the institutional knowledge?

Doom, fear-mongering and hopelessness is not a sustainable approach.

We are already in low-hire low-fire job market where while there aren't massive layoffs to spike up unemployment there also aren't as many vacancies.

What happens if you lay off 80% of your department while your competitors don't? If AI multiplies each developer's capabilities, there's a good chance you'll be outcompeted sooner or later.

That's an oversimplification. Work is rarely so simply divisible like this.

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