That assumes a static demand for development services, which has, more or less, never happened since computing became a thing.
Python, and other high level languages made a lot of development much faster, but it never lead to reduced engineering needs. Cloud made deploying services massively easier, and as a result we actually have a lot more people working in infrastructure.
Faster development mostly leads to expanded economic viability for new types of software. The real question is what becomes economically feasible if development costs are halved.
"In 1865, the English economist William Stanley Jevons observed that technological improvements that increased the efficiency of coal use led to the increased consumption of coal in a wide range of industries. He argued that, contrary to common intuition, technological progress could not be relied upon to reduce fuel consumption."
This definitely feels true for tech companies where the prospect of more more productive engineers improves their bottom line. The same sort of companies that have a near infinite appetite for talented engineers.
But there's a lot of coders in industries whose core business isn't technology. Knapheide for example, a truck outfitting company where my brother codes. I'd imagine in those companies, being able to do the same work with fewer engineers and less cost would lead to fewer hires. Technology isn't their core product and they aren't being held back by software.
I actually think we may see the opposite happen with those kinds of companies too.
At the moment, a truck outfitting company building a customer CRM optimized for their workflow is an absurd idea: they would need a team of a dozen developers working for a year before they could even get a feel for if it was a feasible project or not.
Add LLM assistance and maybe a team of three developers could get to an initial working version in three months.
At that point, companies that had previously ruled out custom software development entirely may find that it makes sense for them - growing the demand for software engineers as a whole.
I guess I'm skeptical how much of an impact better software could have on the business success a truck outfitting company? But maybe I'm being overly skeptical. I bet if I really got in the weeds there I'd see tons of opportunities were better/more software could really accelerate things. Thanks for checking my pessimism!
The job loss depends on the average speed up, however. If the AI is only effective in 10% of tasks (the basic stuff), then that 3x improvement goes down to 1.3x.
That's such a economical fallacy that I'd expect the HN crowd to have understood this ages ago.
Compare the average productivity of somebody working in a car factory 80 years ago with somebody today. How many person-hours did it take then and how many does it take today to manufacture a car? Did the number of jobs between then and now shrink by that factor? To the contrary. The car industry had an incredible boom.
Efficiency increase does not imply job loss since the market size is not static. If cost is reduced then things are suddenly viable which weren't before and market size can explode. In the end you can end up with more jobs. Not always, obviously, but there are more examples than you can count which show that.
This is all broadly true, historically. Automating jobs mostly results in creating more jobs elsewhere.
But let's assume you have true, fully general AI. Further assume that it can do human-level cognition for $2/hour, and it's roughly as smart as a Stanford grad.
So once the AI takes your job, it goes on to take your new job, and the job after that, and the job after that. It is smarter and cheaper than the average human, after all.
This scenario goes one of three ways, depending on who controls the AI:
1. We all become fabulously wealthy and no longer need to work at all. (I have trouble visualizing exactly how we get this outcome.)
2. A handful of billionaires and politicians control the AI. They don't need the rest of us.
3. The AI controls itself, in which case most economic benefits and power go to the AI.
The last historical analog of this was the Neanderthals, who were unable (for whatever reason) to compete with humans.
So the most important question is, how close actually are we to this scenario? Is impossible? A century away? Or something that will happen in the next decade?
> But let's assume you have true, fully general AI.
Very strong assumption and very narrow setting that is one of the counter examples.
AI researchers in the 80s already told you that AI is around the corner in the next 5 years. Didn't happen. I wouldn't hold my breath this time either.
"AI" is a misnomer. LLMs are not "intelligence". They are a lossy compression algorithm of everything that was put into their training set. Pretty good at that, but that's essentially it.
