Idk why we have to keep re-hashing this debate about whether AI is a trustworthy source or summarizer of information when it’s clear that it isn’t - at least not often enough to justify this level of attention.
It’s not as valuable as the marketing suggests, but it does have some applications where it may be helpful, especially if given a conscious effort to direct it well. It’s better understood as a mild curiosity and a proof of concept for transformer-based machine learning that might eventually lead to something more profound down the road but certainly not as it exists now.
What is really un-compelling, though, is the constant stream of anecdotes about how easy it is to fool into errors. It’s like listening to an adult brag about tricking a kid into thinking chocolate milk comes from brown cows. It makes it seem like there’s some marketing battle being fought over public perception of its value as a product that’s completely detached from how anyone actually uses or understands it as a novel piece of software.
Probably it keeps getting rehashed because people who actually understand how computers work are extremely angry and horrified that basically every idiot executive believes the hype and then asks their underlings to inplement it, and will then blame them for doing what they asked them to do when it turns out their idea was really, unimaginably stupid, but idiot executive gets golden parachute and software person gets fired.
That, and/or the widespread proliferation of this bullshit is making stupid people more stupid, and just making more people stupid in general.
Or how like all the money and energy spent on this is actively murdering the environment and dooming the vast majority of our species, when it could be put toward building affordable housing or renovating crumbling infrastructure.
Don’t worry, if we keep throwing exponential increasing amounts of effort at the thing with exponentially diminishing returns, eventually it’ll become God!
Then why are we talking about someone getting it to spew inaccuracies in order to prove a point, rather than the decision of marketing execs to proliferate its use for a million pointless implementations nobody wants at the expense of far higher energy usage?
Most people already know and understand that it’s bad at most of what execs are trying to push it as, it’s not a public-perception issue. We should be talking about how energy-expensive it is, and curbing its use on tasks where it isn’t anything more than an annoying gimmick. At this point, it’s not that people don’t understand its limitations, it’s that they don’t understand how much energy it’s costing and how it’s being shoved into everything we use without our noticing.
Somebody hopping onto openAI or Gemini to get help with a specific topic or task isn’t the problem. Why are we trading personal anecdotes about sporadic personal usage when the problem is systemic, not individualized?
people who actually understand how computers work
Bit idea for moderators: there should be a site or community-wide auto-mod rule that replaces this phrase with ‘eat all their vegitables’ or something that is equally un-serious and infantilizing as ‘understand how computers work’.
You original comment is posted under mine.
I am going to assume you are responding to that.
… I wasn’t trying to trick it.
I was trying to use it.
This is relevant to my more recent reply to you… because it is an anecdotal example of how broadly useless this technology is.
…
I wasn’t aware the purpose of this joke meme thread was to act as a policy workshop to determine an actionable media campaign aimed at generating mass awareness of the economic downsides of LLMs, which wouldn’t fucking work anyway because LLMs are being pushed by a class of wealthy people who do not fucking care what the masses think, and have essentially zero reason at all to change their course of action.
What, we’re going to boycott the entire tech industry?
Vote them out of office?
These people are on video, on record saying basically, ‘eh, we’re not gonna save the climate, not happening, might as well burn it all down even harder, even faster, for a tiny percentage chance our overcomplicated autocomplete algorithm magically figures out how to fix everything afterward’.
…
And yes, I very intentionally used the phrase ‘understand how computers actually work’ to infantilize and demean corporate executives.
Because they are narcissistic priveleged sociopaths who are almost never qualified, almost always make idiotic decisions that will only benefit themselves and an increasingly shrinking number of people at the expense of the vast majority of people who know more and work harder than they do, and who often respond like children having temper tantrums when they are justly criticized.
Again, in the context of a joke meme thread.
Please get off your high horse, or at least ride it over to a trough of water if you want a reasonable place to try to convince it to drink in the manner in which you prefer.
to fool into errors
tricking a kid
I’ve never tried to fool or trick AI with excessively complex questions. When I tried to test it (a few different models over some period of time - ChatGPT, Bing AI, Gemini) I asked stuff as simple as “what’s the etymology of this word in that language”, “what is [some phenomenon]”. The models still produced responses ranging from shoddy to absolutely ridiculous.
completely detached from how anyone actually uses
I’ve seen numerous people use it the same way I tested it, basically a Google search that you can talk with, with similarly shit results.
Why do we expect a higher degree of trustworthiness from a novel LLM than we de from any given source or forum comment on the internet?
At what point do we stop hand-wringing over llms failing to meet some perceived level of accuracy and hold the people using it responsible for verifying the response themselves?
Theres a giant disclaimer on every one of these models that responses may contain errors or hallucinations, at this point I think it’s fair to blame the user for ignoring those warnings and not the models for not meeting some arbitrary standard.
Why do we expect a higher degree of trustworthiness from a novel LLM than we de from any given source or forum comment on the internet?
The stuff I’ve seen AI produce has sometimes been more wrong than anything a human could produce. And even if a human would produce it and post it on a forum, anyone with half a brain could respond with a correction. (E.g. claiming that an ordinary Slavic word is actually loaned from Latin.)
I certainly don’t expect any trustworthiness from LLMs, the problem is that people do expect it. You’re implicitly agreeing with my argument that it is not just that LLMs give problematic responses when tricked, but also when used as intended, as knowledgeable chatbots. There’s nothing “detached from actual usage” about that.
At what point do we stop hand-wringing over llms failing to meet some perceived level of accuracy and hold the people using it responsible for verifying the response themselves?
at this point I think it’s fair to blame the user for ignoring those warnings and not the models for not meeting some arbitrary standard
This is not an either-or situation, it doesn’t have to be formulated like this. Criticising LLMs which frequently produce garbage is in practice also directed at people who do use them. When someone on a forum says they asked GPT and paste its response, I will at the very least point out the general unreliability of LLMs, if not criticise the response itself (very easy if I’m somewhat knowledgeable about the field in question). This is practically also directed at the person who posted that, such as e.g. making them come off as naive and uncritical. (It is of course not meant as a real personal attack, but even a detached and objective criticism has a partly personal element to it.)
Still, the blame is on both. You claim that:
Theres a giant disclaimer on every one of these models that responses may contain errors or hallucinations
I don’t remember seeing them, but even if they were there, the general promotion and ways in which LLMs are presented in are trying to tell people otherwise. Some disclaimers are irrelevant for forming people’s opinions compared to the extensive media hype and marketing.
Anyway my point was merely that people do regularly misuse LLMs, and it’s not at all difficult to make them produce crap. The stuff about who should be blamed for the whole situation is probably not something we disagree about too much.
