Posts by tiotasram@kolektiva.social
 (DIR) Post #AvOpSjUPG5l9eB55yS by tiotasram@kolektiva.social
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       #AI and "productivity", some thoughts:Edit: fixed some typos.Productivity is a concept that isn't entirely meaningless outside the context of capitalism, but it's a concept that is heavily inflected in a capitalist context. In many uses today it effectively means "how much you can satisfy and/or exceed your boss' expectations." This is not really what it should mean: even in an anarchist utopia, people would care about things like how many shirts they can produce in a week, although in an "I'd like to voluntarily help more people" way rather than an "I need to meet this quota to earn my survival" way. But let's roll with this definition for a second, because it's almost certainly what your boss means when they say "productivity", and understanding that word in a different (even if truer) sense is therefore inherently dangerous.Accepting "productivity" to mean "satisfying your boss' expectations," I will now claim: the use of generative AI cannot increase your productivity.Before I dive in, it's imperative to note that the big generative models which most people think of as constituting "AI" today are evil. They are 1: pouring fuel on our burning planet, 2: psychologically strip-mining a class of data laborers who are exploited for their precarity, 3: enclosing, exploiting, and polluting the digital commons, and 4: stealing labor from broad classes of people many of whom are otherwise glad to give that labor away for free provided they get a simple acknowledgement in return. Any of these four "ethical issues" should be enough *alone* to cause everyone to simply not use the technology. These ethical issues are the reason that I do not use generative AI right now, except for in extremely extenuating circumstances. These issues are also convincing for a wide range of people I talk to, from experts to those with no computer science background. So before I launch into a critique of the effectiveness of generative AI, I want to emphasize that such a critique should be entirely unnecessary.But back to my thesis: generative AI cannot increase your productivity, where "productivity" has been defined as "how much you can satisfy and/or exceed your boss' expectations."Why? In fact, what the fuck? Every AI booster I've met has claimed the opposite. They've given me personal examples of time saved by using generative AI. Some of them even truly believe this. Sometimes I even believe they saved time without horribly compromising on quality (and often, your boss doesn't care about quality anyways if the lack of quality is hard to measure of doesn't seem likely to impact short-term sales/feedback/revenue). So if generative AI genuinely lets you write more emails in a shorter period of time, or close more tickets, or something else along these lines, how can I say it isn't increasing your ability to meet your boss' expectations?The problem is simple: your boss' expectations are not a fixed target. Never have been. In virtue of being someone who oversees and pays wages to others under capitalism, your boss' game has always been: pay you less than the worth of your labor, so that they can accumulate profit and thus more capital to remain in charge instead of being forced into working for a wage themselves. Sure, there are layers of management caught in between who aren't fully in this mode, but they are irrelevant to this analysis. It matters not how much you please your manager if your CEO thinks your work is not worth the wages you are being paid. And using AI actively lowers the value of your work relative to your wages.Why do I say that? It's actually true in several ways. The most obvious: using generative AI lowers the quality of your work, because the work it produces is shot through with errors, and when your job is reduced to proofreading slop, you are bound to tire a bit, relax your diligence, and let some mistakes through. More than you would have if you are actually doing and taking pride in the work. Examples are innumerable and frequent, from journalists to lawyers to programmers, and we laugh at them "haha how stupid to not check whether the books the AI reviewed for you actually existed!" but on a deeper level if we're honest we know we'd eventually make the same mistake ourselves (bonus game: spot the swipe-typing typos I missed in this post; I'm sure there will be some).But using generative AI also lowers the value of your work in another much more frightening way: in this era of hype, it demonstrates to your boss that you could be replaced by AI. The more you use it, and no matter how much you can see that your human skills are really necessary to correct its mistakes, the more it appears to your boss that they should hire the AI instead of you. Or perhaps retain 10% of the people in roles like yours to manage the AI doing the other 90% of the work. Paradoxically, the *more* you get done in terms of raw output using generative AI, the more it looks to your boss as if there's an opportunity to get enough work done with even fewer expensive humans. Of course, the decision to fire you and lean more heavily into AI isn't really a good one for long-term profits and success, but the modern boss did not get where they are by considering long-term profits. By using AI, you are merely demonstrating your redundancy, and the more you get done with it, the more redundant you seem. In fact, there's even a third dimension to this: by using generative AI, you're also providing its purveyors with invaluable training data that allows them to make it better at replacing you. It's generally quite shitty right now, but the more use it gets by competent & clever people, the better it can become at the tasks those specific people use it for. Using the currently-popular algorithm family, there are limits to this; I'm not saying it will eventually transcend the mediocrity it's entwined with. But it can absolutely go from underwhelmingly mediocre to almost-reasonably mediocre with the right training data, and data from prompting sessions is both rarer and more useful than the base datasets it's built on.For all of these reasons, using generative AI in your job is a mistake that will likely lead to your future unemployment. To reiterate, you should already not be using it because it is evil and causes specific and inexcusable harms, but in case like so many you just don't care about those harms, I've just explained to you why for entirely selfish reasons you should not use it.If you're in a position where your boss is forcing you to use it, my condolences. I suggest leaning into its failures instead of trying to get the most out of it, and as much as possible, showing your boss very clearly how it wastes your time and makes things slower. Also, point out the dangers of legal liability for its mistakes, and make sure your boss is aware of the degree to which any of your AI-eager coworkers are producing low-quality work that harms organizational goals.Also, if you've read this far and aren't yet of an anarchist mindset, I encourage you to think about the implications of firing 75% of (at least the white-collar) workforce in order to make more profit while fueling the climate crisis and in most cases also propping up dictatorial figureheads in government. When *either* the AI bubble bursts *or* if the techbros get to live out the beginnings of their worker-replacement fantasies, there are going to be an unimaginable number of economically desperate people living in increasingly expensive times. I'm the kind of optimist who thinks that the resulting social crucible, though perhaps through terrible violence, will lead to deep social changes that effectively unseat from power the ultra-rich that continue to drag us all down this destructive path, and I think its worth some thinking now about what you might want the succeeding stable social configuration to look like so you can advocate towards that during points of malleability.As others have said more eloquently, generative AI *should* be a technology that makes human lives on average easier, and it would be were it developed & controlled by humanists. The only reason that it's not, is that it's developed and controlled by terrible greedy people who use their unfairly hoarded wealth to immiserate the rest of us in order to maintain their dominance. In the long run, for our very survival, we need to depose them, and I look forward to what the term "generative AI" will mean after that finally happens.
       
 (DIR) Post #B6QdM68zpxzGxDeATY by tiotasram@kolektiva.social
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       @Hex I wonder if it would be valuable to run a split scenario where 2/3 of the team thinks you're running "interpersonal conflict" while only 1/3 know that it's really "sexual abuse within the org" and see if things get handled well. Could also do a version with "infiltrator is making false accusations of sexual abuse" but you'd need to be really careful about how to balance things (plus get active consent from SV/DV survivors in group first; ideally let them run things).
       
 (DIR) Post #B9f9zIn0adOpP4HmG8 by tiotasram@kolektiva.social
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       @Rairii love it. I've been meaning to write up a more offensive worm-style version of this but haven't had the time yet.
       
 (DIR) Post #B9vHlHqjYQLJidOqBM by tiotasram@kolektiva.social
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       @skjeggtroll @freshstart @neil it's worse than this actually.We know that LLM code sometimes includes fragments of training data verbatim. We know much training data is licensed such that verbatim copies requires attribution. So we know that LLM code sometimes violates these attribution requirements.There is no practical way to check whether a given section of LLM produced code violates an attribution requirement. How are you going to search against all lines of code in the training database? Do you run that search for each line of code?Even worse: two different people using the same LLM, even with different prompts, may generate the same or substantially similar code. Whoever tries to slap a license on that code second is in violation of the first person's license, assuming a world in which such code is licensable at all. These people probably don't know of each others' existence at first. This has already happened, see:https://blog.terrygodier.com/2026/08/09/mea-culpa-dark-hours.htmlTo accept any LLM-generated code or documentation is to say that you are fine with license violations. If, as Debian did, you try to thrust the impossible burden of ensuring license violations do not occur onto each contributor, I'm not sure what you're saying, but your policy isn't sincere.
       
 (DIR) Post #B9wBlkMb8QZPaQ6Fs0 by tiotasram@kolektiva.social
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       @lxo @skjeggtroll @freshstart @neil Okay, that's what the law says, but how is the second person going to fare against a lawsuit if the first person claims infringement?If the second person succeeds on an argument that "using an LLM is like a clean-room implementation" then open-source is non-functional, legally, as anyone can easily ignore any license by asking an LLM to duplicate relevant functionality and then claiming plausibly that they hadn't seen the other work before.If, as you're suggesting, there's an "I came up with it independently" defense, does the burden of proof fall on the accuser or the accused? Normally burden always falls on the accuser, but if we assume open-source development on both sides, the accuser can trivially prove (if they published faster) that they came up with the idea first and that their code was theoretically accessible to the accused when the accused was developing their version, and that the accused used lines of code verbatim which are in their version. The accuser can probably even show that their code was likely in the training data of any LLM that the accused used.I don't actually know the law here, but if that's not enough to throw a presumption onto the accused and the accuser actually has to prove intent or something, it again seems like open-source licenses offer negligible protections against infringement (maybe this is actually the case). If the accuser on the basis of showing that the accused used verbatim copies of their public code can shift the burden of proof onto the accused, how is the accused going to prove they actually came up with the idea independently, especially when they used an LLM so it's not really their idea?Maybe some kind of twisted precedent *will* be established that this situation is fine actually and anyone accused of copyright infringement who is using an LLM can just claim their invention is independent despite having literal copies of another work in it... I don't want to be the person testing that legal theory against a startup with a 6-figure legal budget, let alone a big tech firm. The big tech firms regularly do patent software, after all.On the other side of things out it turns out that legally LLM-generated code cannot be licensed or patented at all, then it can't be open source and this should not be acceptable to Debian.But let's think about the moral level too. Do I want to be using the sometimes-steals-code machine and then get into a situation where it looks like I stole someone's code? No. What actually happened in this case was not that the slower sloperator mounted an arcane legal defense and everyone was okay to let the two apos coexist. Instead he backed off, apologized to everyone, deleted the project and promised never to use LLMs to generate code again. That seems like the best case for reputational damage. So even if the legal reality permits some really gross stuff (let's face it, this is the norm actually) unless you're a massive corporation who doesn't care about reputation, a legal technicality doesn't make this situation all good.