westcoast49

I’m not concerned because I consider my skills as a software developer to not be based upon my ability to write code, but my ability to analyze problems. In my mind, as a developer, AI tools are just like a higher form of abstraction in a way, which will enable mathematicians and software developers alike to do much more in a shorter amount of time than they used to be able to. It fills me with optimism, more than dread.

What would fill me with dread was if I considered my skills to be tied directly to my ability to write code. Then I would find myself in a similar situation as manual “scribes” probably found themselves in at the time when the printing press was invented.

The main concern I have, personally, is the speed with which all this is happening. It seems that the speed itself is likely to lead to some level of chaos, because it is happening faster than people, institutions and constitutions are able to cope, and it will leave the door open for opportunists of many kinds, including rogue players.

The deeper question is why we register it as bad.

It has the "same voice" you say. But that is also, kind of, the same as saying that there is no humanity behind it, no identity, no "mind".

For lexical articles, like text given as an answer to a single prompt or question, AI writing can be excellent. Because, there we do want an answer that represents the average or combination of all human knowledge about the topic. We're not looking for personality, or another mind.

When we read long-form text, on the other hand, what we are engaging in, is mind-transfer. We then expect there to be a recognizable mind at the other end. And this is, in my opinion, what typically falls apart when we ask an AI to write a complete long-form text.

> we readers shouldn’t be expected to labor to understand a sentence that the writer themselves didn’t work to create.

What about answers that an LLM gave to a question that we ourselves asked? Should we “labor” to understand that answer?

I think the argument, as presented in this and other similar pieces of critique, is too simplistic.

I do understand the criticism, but I think it should be framed in a different manner. The problem, when we read a long form piece by an author, is that we imagine that there’s another “mind” at the other side. We imagine that we are following the reasoning within the mind of a fellow human being, the writer. There’s an implied sort of “intimacy” to it. And the breach is when we are fooled into thinking that we are engaged in human communication, only to discover that there is a machine on the other side.

When we ask questions to an AI, this problem does not exist, because we are fully aware that the entity on the other side is not a human being.

Yet there is no doubt that the reply from an AI can contain information that is very much worthy of our time, and of our “labor” and effort to understand it.

So I think this ultimately will be about disclosure. As long as we are being made aware of the percentage of AI use in a text, explicitly or implicitly, I think we will actually grow to accept it.

I got a slight flashback to Blue Max, just because of the graphics.

It is possible though, to unify those things, and to see those other effects also as second or third order effects of the same underlying deficiencies that cause problems in social interaction. I believe, for instance, that our super power as neurotypicals is our ability to see, process, model and make sense, especially in real-time, of what's inside the minds of other people. In a way, we are wired to be comfortable with multiple worlds or perspectives around us, because we can see them, process them, and make sense of them. It makes sense to me that a person who is less good at this, will end up seeking a model of the world that is more rigid. If the worlds of other people around you seem chaotic to you, and uncomprehensible, then you will seek an environment and an understanding of the world that is more static, rigid or fixed. So, I think, at least on a conceptual level, it's possible to link the root causes of social problems to the root causes of the need for rigidity and stability.

I’m sure it does. If you ask a question, it forces you to think the problem through, which has a similar effect as the kind of therapeutic writing that is mentioned in this article.

I think you're right. I'm on the opposite side of it, but I have a colleague who routinely writes functions that are hundreds of lines long, with 30-40 local variables inside each function. I've come to realize that he does so because his brain allows him to do it. He has a brain that is more detail-oriented than my brain. Where I naturally see a problem as a "tree" of sub-problems with their own details, he naturally sees one large problem with 100 details. He naturally writes code to accommodate his own cognitive style, while I write code to accommodate my own cognitive style.

Moreover, I've come to realize that my colleague is not adverse to using abstractions if they are well established, and if they already exist. But he is (much) less inclined to invent or write new abstractions than I am. As you have concluded, I have also concluded that this is actually a matter of cognitive style, more than it's a symptom of "slop" or "cargo-culting of best practices".

> Knowing At a high level what needed to happen to accomplish what the code did, I know for a fact it could have and should have been broken down more. However, because of the complexity of what he wrote, no one had the patience to go through it. When he left, the code got thrown away.

And today an LLM could probably have refactored it fairly well, automatically.

Kalman filtering is what's used in GPS navigation apps, is it not, to smooth out imperfections in the raw GPS signal?

> If you could always do it over, an infinite redo so to say, nothing would matter. Every choice and outcome would become insignificant, because you could just redo it until it was just right.

The movie Groundhog Day comes to mind.

Or:

(e) because it’s subjective.

I'm just arguing that there has been no qualitative shift. The skills you need to produce pop music today are different than the skills that you needed before. Now you need to be able to operate a MIDI sequencer or a program like Ableton, which is not necessarily easier in and off itself, than for instance learning how to play a guitar. I think it's the same with AI tools and programming. We're just talking about a different set of skills that you need in order to be competitive. I don't think there has been any real shift from "skill needed" to "judgement needed". I think this relationship remains the same, both for pop music and programming, but also for the example of playing an instrument in a symphony orchestra.

Music was never an issue of skill. You might have needed skill in order to get to the point where you could use your judgement, but skill was never the deciding factor. So, I don't agree with Brian Eno's point that there has been some kind of seismic shift when it comes to this. Rather, it's just a matter of a shift in the type of skill that you need to have. The same is probably true when it comes to AI tools within the field of programming.

So this is WYSINWYG.