... alcohol.

... just use it as a, power wasting, search engine?

It's not like the makers of LLM-based coding tools wouldn't know what the consequences will be, to cite [1]https://www.anthropic.com/rese... [anthropic.com]

> On average, participants in the AI group finished about two minutes faster, although the difference was not statistically significant. There was, however, a significant difference in test scores: the AI group averaged 50% on the quiz, compared to 67% in the hand-coding group—or the equivalent of nearly two letter grades (Cohen's d=0.738, p=0.01). The largest gap in scores between the two groups was on debugging questions, suggesting that the ability to understand when code is incorrect and why it fails may be a particular area of concern if AI impedes coding development. [...] Given time constraints and organizational pressures, junior developers or other professionals may rely on AI to complete tasks as fast as possible at the cost of skill development—and notably the ability to debug issues when something goes wrong.

This is exactly what will happen: More AI-Slop produced faster, with more bugs that never get fixed. And skilled IT personnel being replaced by unskilled prompt-monkeys, because cheaper.

[1] https://www.anthropic.com/research/AI-assistance-coding-skills

I've seen many people comment on other discussion platforms they are using AI simply because the leadership at their employer is requiring it. And many of those comments follow up with how the results of the AI usage are not helpful, or worse, require checking/correcting work and resulting in a net negative for productivity verses if they had just done it themselves.

AI is very good for novices, people who don't know something well.

Executives use it for office tools.

Programmers and engineers use it when working with languages and tools they don't know well. We're all novices at some languages and tools, so AI can be useful to everybody, to some extent.

The big problem is that most of the material on the Internet on programming and engineering is done by novices. Professionals don't have the time to be posting and even if they did they aren't allowed to share their work.

Academics have generally sold their souls to the publish-or-perish system and seldom have professional level skills, so no help there.

AI is basically all about pattern matching, so it matches work done by novices, and in practice people blindly apply that work.

This means people aren't spending time learning how to do it right, which usually involves design time, abstraction, thinking about data structures, experiments, and so forth.

Then one makes the inevitable mistakes, and learns from those mistakes - and ultimately gets better.

With AI, that whole process is short-circuited. You get something the sort-of works, but without the whole learning process.

So it is not that AI is a bad thing, but it can be - people who don't have wisdom or guidance from others aren't going to get the learning experiences they need to get good. They will be condemned to mediocrity. So we're creating a culture of amateurs that don't know how to do anything well.

Really good organizations supplement the learning process with really good mentoring - and that's key to turning the talented amateurs that graduate from colleges into really good professionals.

Unfortunately, really good mentoring is quite rare, because most technical people aren't good enough at either their technical skills or the people skills (or both) to be good mentors, and most organizations don't know how to run a good mentoring program. By that I mean substance, not illusion. Lots of managers can manage the illusion part - we're mentoring, check that box off!

A good mentoring program can help ensure that AI doesn't lead organizations down the wrong paths, and that people develop the genuine high level skills they need to produce high quality products that will generate long term income from repeat customers.

Most organizations don't know how to run such a program, so they rely on patents, trademarks, copyright, and cost-of-entry barriers to make up for all the quality failures in their products that happen because their people don't have the skills they need.

It's another reason to be very suspicious of whether or not IP law is actually providing a genuine benefit to society, as least as it is currently implemented. Basic legal protection from counter-fitting would probably be more efficient and beneficial to society than current IP law.

Some of this is real, no doubt about it, especially if you're a coder or someone whose job is to create spam or shitty advertisements or run chatbots.

But a lot of this is people using ai because its been pushed violently in front of us. Just see how MSFT tried to replace microsoft word with it, or how google has you look at AI before any actual search results. And then there are the employers who mandate it. When you that and then survey the results and find people are using it more, that doesn't translate to it actually being more useful.

I do use LLM-type AI "daily" too. DDG gives an AI answer by default. As that is somewhat useful in, maybe, 50% of all simpler searches, I leave it on. But does that mean I have "integrated AI into my workflow"? Hell, no. That claim would be a direct lie.