I agree with you, though proponents will tell you that’s by design. Supposedly, it’s like with high-level languages. You don’t need to know the actual instructions in assembly anymore to write a program with them. I think the difference is that high-level language instructions are still (mostly) deterministic, while an LLM prompt certaily isn’t.
Comment on I Went All-In on AI. The MIT Study Is Right.
AutistoMephisto@lemmy.world 1 day agoThe top comment on the article points that out.
It’s an example of a far older phenomenon: Once you automate something, the corresponding skill set and experience atrophy. It’s a problem that predates LLMs by quite a bit. If the only experience gained is with the automated system, the skills are never acquired. I’ll have to find it but there’s a story about a modern fighter jet pilot not being able to handle a WWII era Lancaster bomber. They don’t know how to do the stuff that modern warplanes do automatically.
ctrl_alt_esc@lemmy.ml 1 day ago
Scubus@sh.itjust.works 21 hours ago
Yep, thats the key issue that so many people fail to understand. They want AI to be deterministic but it simply isnt. Its like expecting a human to get the right answer to any possible question, its just not going to happen. The only thing we can do is bring error rates with ai lower than a human doing the same task, and it will be at that point that the ai becomes useful. But even at that point there will always be the alignment issue and nondeterminism, meaning ai will never behave exactly the way we want or expect it to.
drosophila@lemmy.blahaj.zone 21 hours ago
The thing about this perspective is that I think its actually overly positive about LLMs, as it frames them as just the latest in a long line of automations.
Not all automations are created equal. For example, compare using a typewriter to using a text editor. Besides a few details about the ink ribbon and movement mechanisms you really haven’t lost much in the transition. This is despite the fact that the text editor can be highly automated with scripts and hot keys, allowing you to manipulate even thousands of pages of text at once in certain ways. Using a text editor certainly won’t make you forget how to write like using ChatGPT will.
I think the difference lies in the relationship between the person and the machine. To paraphrase Cathode Ray Dude, people who are good at using computers deduce the internal state of the machine, mirror (a subset) of that state as a mental model, and use that to plan out their actions to get the desired result. People that aren’t good at using computers generally don’t do this, and might not even know how you would start trying to.
For years ‘user friendly’ software design has catered to that second group, as they are both the largest contingent of users and the ones that needed the most help. To do this software vendors have generally done two things: try to move the necessary mental processes from the user’s brain into the computer and hide the computer’s internal state (so that its not implied that the user has to understand it, so that a user that doesn’t know what they’re doing won’t do something they’ll regret, etc). Unfortunately this drives that first group of people up the wall. Not only does hiding the internal state of computer make it harder to deduce it, every “smart” feature they add to try to move this mental process into the computer itself only makes the internal state more complex and harder to model.
Many people assume that if this is the way you think about software you are just an elistist gatekeeper, and you only want your group to be able to use the computer. Or you might even be accused of ableism. But the real reason is what I described above, even if its not usually articulated in that way.
Now, I am of the opinion that the ‘mirroring the internal state’ method of thinking is the superior way to interact with the machine, and the approach to user friendliness I described has actually done a lot of harm to our relationship with computers at a societal level. (This is an opinion I suspect many people here would agree with.) And yet that does not mean that I think computers should be difficult to use. Quite the opposite, I think that modern computers are too complicated, and that in an ideal world their internal states and abstractions would be much simpler and more elegant, but no less powerful. (But elaborating on that would make this comment even longer.) Nor do I think that computers shouldn’t be accessible to people with different levels of ability. But just as a random person in a store shouldn’t grab a wheelchair user’s chair handles and start pushing them around, neither should Windows (for example) start changing your settings on updates without asking.
Anyway, all of this is to say that I think LLMs are basically the ultimate in that approach to ‘user friendliness’. They try to move more of your thought process into the machine than ever before, their internal state is more complex than ever before, and it is also more opaque than ever before. They also reflect certain values endemic to the corporate system that produced them: that the appearance of activity is more important than the correctness or efficacy of that activity. But that is, again, a whole other comment.
Cocodapuf@lemmy.world 18 hours ago
Once you automate something, the corresponding skill set and experience atrophy. It’s a problem that predates LLMs by quite a bit. If the only experience gained is with the automated system, the skills are never acquired.
Well, to be fair, different skills are acquired. You’ve learned how to create automated systems, that’s definitely a skill. In one of my IT jobs there were a lot of people who did things manually, updated computers, installed software one machine at a time. But when someone figures out how to automate that, push the update to all machines in the room simultaneously, that’s valuable and not everyone in that department knew how to do it.
So yeah, I guess my point is, you can forget how to do things the old way, but that’s not always bad. Like, so you don’t really know how to use a scythe, that’s fine if you have a tractor, and trust me, you aren’t missing much.
logicbomb@lemmy.world 1 day ago
It’s more like the ancient phenomenon of spaghetti code. You can throw enough code at something until it works, but the moment you need to make a non-trivial change, you’re doomed. You might as well throw away the entire code base and start over.
And if you want an exact parallel, I’ve said this from the beginning, but LLM coding at this point is the same as offshore coding was 20 years ago. You make a request, get a product that seems to work, but maintaining it, even by the same people who created it in the first place, is almost impossible.
jbloggs777@discuss.tchncs.de 14 hours ago
Indeed… Throw-away code is currently where AI coding excels. And that is cool and useful - creating one off scripts, self-contained modules automating boilerplate, etc.
You can’t quite use it the same way for complex existing code bases though… Not yet, at least…