Well, the problem is you don’t know what you don’t know.

This is true, even recognized in the paper. People that spend more time on writing prompts (probably knowing that this is important) actually did manage to do reasonably well. Which is exactly what I in the previous reply was hinting at.

Because, let’s be honest, this statement is true for everything where someone starts out new. In the past (and probably still) you had people blindly copying code blocks from stackoverflow not understanding what the code or realizing how outdated the answer might be.

So the key is still education of people and making them aware of their limitations. You can try to block the usage of tools like this, some companies actively do so. But people will be people and as long as the tools are available they will try to use them. So the more realistic approach, in my opinion, is to educate them in the usage of these tools.

For LLM training I do wonder if they assigned a weight, but I doubt it.

Given my experience with models I think they might actually do assign a weight. Otherwise, I would get a lot more bogus results. It also isn’t as if it is that difficult to implement some basic, naive, weighing based on the amount of stars/forks/etc.

Of course it might differ per model and how they are trained.

Having said that, I wouldn’t trust the output from an LLM to write secure code either. For me it is a very valuable tool on the end of helping me debug issues on the scale of being a slightly more intelligent rubber ducky. But when you ask most models to create anything more than basic functions/methods you damn well make sure it actually does what it needs it to do.

I suppose there is some role there for seniors to train juniors in how to properly use this new set of tooling. In the end it is very similar to having to deal with people who copy paste answers directly from stack overflow expecting it to magically fix their problem as well.

The fact that you not only need your code/tool to work but also understand why and how it works is also something I am constantly trying to teach to juniors at my place. What I often end up asking them is something along the lines of “Do you want to have learned a trick that might be obsolete in a few years? Or do you want to have mastered a set of skills and understanding which allows you to tackle new challenges when they arrive?”.

Most code on GitHub either is unsecure, or it was written without needing to be secure.

That is a bit of a stretch imho. There are myriads of open source projects hosted on github that do need to be secure in the context where they are used. I am curious how you came to that conclusion.

I’m already getting pull requests from juniors trying to sneak in AI generated code without actually reading it.

That is worrysome though. I assume these people have had some background/education in the field before they were hired?

Would you like me to quote every single one of your lines, line by line, and respond to them?

No, that’s not really what I’m asking for. I’m also not looking for responses that isolate a single sentence from my longer messages and ignore the context. I’m not sure how to make my point any clearer than in my first reply to you, where I started with two bullet points. You seemed to focus on the second, but my main point was about the first. If we do want to talk about standard behavior in human conversation, generally speaking, people do acknowledge that they have heard/read something someone said even if they don’t respond to it in detail.

Again, I’ve been agreeing that AI is causing significant problems. But in the case of this specific tweet, the real issue is with a pay to publish journal where the peer review process is failing, not AI. This key point has mostly been ignored. Even if that was not the case, if you want to have any change of trying to combat the emergence of AI I think it is pretty reasonable to question if the basic processes in place are even functioning in the first place. Where my thesis (again, if this wasn’t a pay to publish journal) would be that this is likely not the case as in that entire process clearly nobody looked closely at these images. And just to be extra clear, I am not saying that AI never will be an issue, etc. But if reviewing already isn’t happening at a basic level how are you ever hoping to combat AI in the first place?

When did anyone say

But by just shouting, “AI is at it again with its antics!” at every turn instead of looking further and at other core issues we will only make things worse”

The context of this tweet, saying “It’s finally happened. A peer-reviewed journal article with what appear to be nonsensical AI-generated images. This is dangerous.”, does imply that. I’ve been responding with this in mind, which should be clear. It is this sort of thing I mean when I say selective reading when you seemingly take it as me saying that you personally said exactly that. Which is a take, but not one I’d say is reasonable if you take the whole context into account.

And in that context, I’ve said:

that doesn’t mean all bullshit out there is caused by AI

Which I stand by. In this particular instances, in this particular context AI isn’t the issue and somewhat clickbait. Which makes most of what you argued about valid concerns. Youtube struggling, SEO + AI blog spam, etc are all very valid and concerning of AI causing havoc. But in this context of me calling a particular tweet clickbait they are also very much less relevant. If you just wanted to discuss the impact of AI in general and step away from the context of this tweet, then you should have said so.

Now, about misrepresenting arguments:

If you are reaffirming somebody else’s comment, you are generally standing behind most if not all of what they said. But nobody here is saying or doing the things you are claiming. You are tilting at windmills.

Have you looked back at your own previous comments when you wrote that? Because while have this, slightly bizarre, conversation I have gone back to mine a few times. Just to check if I actually did mess up somewhere or said things differently that I thought I did. The reason I am asking is that I have been thrown a few of these remarks from you where I could have responded with the above quote myelf. Things like “It’s passing the buck and saying that AI in no way, shape, or form, bears any responsibility for the problem.”

The fact that you specifically respond to this one highly specific thing. While I clearly have written more is exactly what I mean.

shrugs

I feel like this is the third time people are selective reading into what I have said.

I specifically acknowledge that AI is already causing all sorts of issues. I am also saying that there is also another issue at play. One that might be exacerbated by the use of AI but at its root isn’t caused by AI.

In fact, in this very thread people have pointed out that *in this case" the journal in question is simply the issue. https://beehaw.org/comment/2416937

In fact. The only people likely noticed is, ironically, the fact that AI was being used.

And again I fully agree, AI is causing massive issues already and disturbing a lot of things in destructive ways. But, that doesn’t mean all bullshit out there is caused by AI. Even if AI is tangible involved.

If that still, in your view, somehow makes me sound like an defensive AI evangelist then I don’t know what to tell you…

I said clickbait about the AI specific thing. Which I do stand by. To be more direct, if peer reviewers don’t review and editors don’t edit you can have all the theoretical safeguards in place, but those will do jack shit. Procedures are meaningless if they are not being followed properly.

Attributions can be faked, just like these images are now already being faked. If the peer review process is already under tremendous pressure to keep up for various reasons then adding more things to it might actually just make things worse.

I feel like two different problems are conflated into one though.

1. The academic review process is broken.
2. AI generated bullshit is going to cause all sorts of issues.

Point two can contribute to point 1 but for that a bunch of stuff needs to happen. Correct my if I am wrong but as far as my understanding of peer-review processes are supposed to go it is something along the lines of:

1. A researcher submits their manuscript to a journal.
2. An editor of that journal validates the paper fits within the scope and aims of the journal. It might get rejected here or it gets send out for review.
3. When it does get send out for review to several experts in the field, the actual peer reviewers. These are supposed to be knowledgeable about the specific topic the paper is about. These then read the paper closely and evaluate things like methodology, results, (lack of) data, and conclusions.
4. Feedback goes to the editor, who then makes a call about the paper. It either gets accepted, revisions are required or it gets rejected.

If at point 3 people don’t do the things I highlighted in bold then to me it seems like it is a bit silly to make this about AI. If at point 4 the editor ignores most feedback for the peer reviewers, then it again has very little to do with AI and everything the a base process being broken.

To summarize, yes AI is going to fuck up a lot of information, it already has. But by just shouting, “AI is at it again with its antics!” at every turn instead of looking further and at other core issues we will only make things worse.

Edit:

To be clear, I am not even saying that peer reviewers or editors should “just do their job already”. But fake papers have been increasingly an issue for well over a decade as far as I am aware. The way the current peer review process works simply doesn’t seem to scale to where we are today. And yes, AI is not going to help with that, but it is still building upon something that already was broken before AI was used to abuse it.

Oh huh, you are right. I threw that exact prompt in Dall-e and got indeed legible letters.

I totally see why you are worried about all the aspects AI introduces, especially regarding bias and the authenticity of generated content. My main gripe, though, is with the oversight (or lack thereof) in the peer review process. If a journal can’t even spot AI-generated images, it raises red flags about the entire paper’s credibility, regardless of the content’s origin. It’s not about AI per se. It is about ensuring the integrity of scholarly work. Because realistically speaking, how much of the paper itself is actually good or valid? Even more interesting, and this would bring AI back in the picture. Is the entire paper even written by a human or is the entire thing fake? Or maybe that is also not interesting at all as there are already tons of papers published with other fake data in it. People that actually don’t give a shit about the academic process and just care about their names published somewhere likely already have employed other methods as well. I wouldn’t be surprised if there is a paper out there with equally bogus images created by an actual human for pennies on Fiverr.

The crux of the matter is the robustness of the review process, which should safeguard against any form of dubious content, AI-generated or otherwise. Which is what I also said in my initial reply, I am most certainly not waving hands and saying that review is enough. I am saying that it is much more likely the review process has already failed miserably and most likely has been for a while.

Which, again to me, seems like the bigger issue.

This feels like clickbait to me, as the fundamental problem clearly isn’t AI. At least to me it isn’t. The title would have worked as well without AI in the title. The fact that the images are AI generated isn’t even that relevant. What is worrying is that the peer review process, at least for this journal clearly is faulty as no actual review of the material took place.

If we do want to talk about AI. I am impressed how well the model managed to actually create text made up of actual letters resembling words. From what I have seen so far that is often just as difficult for these models as hands are.

Have you tried placing the <br> tag directly after the `` closing tag?

As is often the case there is more nuance to this. As others have pointed out, it is still possible to run your own mailserver if you really want to.

But, there are also other options that aren’t google, microsoft or any other service.

I personally have registered my own domain and have my mail hosted by mailbox.org. If I am ever dissatisfied with them I can simply pick a different mail hosting provider and move my domain there. Other privacy minded providers can be found here: https://www.privacytools.io/privacy-email

And there are also more options if you just want reliable mail and care slightly less about overall privacy. Fastmail for example is a popular choice.

Yes, these are not free. But neither is hosting it yourself as that costs you the VPS/container to host it and a bunch more time and effort.

What it does provide you with is the ability to no longer use big tech while allowing you to mail with people still having their mail hosted there.