Even if this convergence across models is just an artifact of RLHF or common training data, there's a lot of truth to it. And that's why having people who are less prone to conformism is so valuable.
Humans are social and emotional creatures. Its not hard to imagine a relentless pursuit of truth that leads to misery and suffering.
Have you ever had an argument with a loved one and realized youd rather be happy then right? Or a scenerio where you withhold the truth because it was not useful and would cause harm?
Nevermind the clear bias nearly everyone shows when they weigh in on world events.
Maybe the new meta should be reviewing new code at the end of the week/month rather than at each merge? But even that might be too much of a bottleneck. The alternative is to talk to your agent to understand changes at a high level without reading every line of code.
Is there evidence that overall software developer positions are declining relative to other jobs? It wouldn't surprise me if Jevons paradox applied here.
There is mixed evidence on the impact of AI on developer jobs, but on the balance it seems that to the extent AI is impacting dev jobs, it is mostly the junior roles that are being affected.
There is even some evidence that suggests senior roles are more in demand (and getting correspondingly higher pay too) which gels with the common observation that senior workers are more effective at managing the AI which is doing the work of (and hence displacing) junior workers.
Asking a chatbot or Google AI overviews should surface relevant studies.
It’s really hard to get a good read on it because of the state of the post-COVID economy and job market.
Like the mass layoffs the last couple of years seemed to be primarily driven by the goofy hiring spree every company went on during the pandemic and the AI reasoning was only partly true and mostly a coverup for their mistakes in hiring in previous years.
On the other hand, the amount of garbage level devs that were being churned out of bootcamps and such in the years leading up to COVID was also due for some kind of correction and AI may be the catalyst for that correction.
I’ve been around devs making an easy 6 figures that did nothing but copy/paste code from the internet or other parts of the codebase and spew jank into the repo because management needs the work done yesterday.
Thanks! I've heard numerous examples of this. E.g. paint rollers, and later paint sprayers, made painting so much more efficient and cheaper that people wanted their houses and apartments painted more often, ultimately increasing house painter employment. But I didn't realize the phenomenon had a name.
The broader topic of marginal utility is worth looking into if this is interesting to you.
The reason why AI induces more demand is more interesting than simply observing a correlation. At the root of the paradox is the dissatisfaction with AI as it raises the bar for human work. In that sense, AI functions like training wheels more than actually doing anything useful on its own. More people can ride the bike well as a result.
This is the "law of diminishing marginal utility". In other words, LLMs are an NLP-powered google search 2.0. That sums up pretty well why AI hit a plateau a couple of years ago. There's only so much training data and humans become more efficient and creative once exposed to the exact information they were always looking for, but could never find in the past.
