6 ms·
These are language models, not Skynet. They do not scheme or deceive.
by emp17344 8mo ago
These are language models, not Skynet. They do not scheme or deceive.
- jaennaet 8mo agoWhat would you call this behaviour, then?
- victorbjorklund 8mo agoMarketing. ”Oh look how powerful our model is we can barely contain its power”
- c03 8mo agoEven hackernews readers are eating it right up.
- emp17344 8mo agoThis place is shockingly uncritical when it comes to LLMs. Not sure why.
- meindnoch 8mo agoWe want to make money from the clueless. Don't ruin it!
- _se 8mo agoHilarious for this to be downvoted. "LLMs are deceiving their creators!!!" Lol, you all just want it to be true so badly. Wake the fuck up, it's a language model!
- pixelmelt 8mo agoThis has been a thing since GPT-2, why do people still parrot it
- jazzyjackson 8mo agoI don’t know what your comment is referring to. Are you criticizing the people parroting “this tech is too dangerous to leave to our competitors” or the people parroting “the only people who believe in the danger are in on the marketing scheme” fwiw I think people can perpetuate the marketing scheme while being genuinely concerned with misaligned superinteligence
- modernpacifist 8mo agoA very complicated pattern matching engine providing an answer based on it's inputs, heuristics and previous training.
- deleted 8mo ago[deleted]
- criley2 8mo agoWe are talking about LLM's not humans.
- margalabargala 8mo agoGreat. So if that pattern matching engine matches the pattern of "oh, I really want A, but saying so will elicit a negative reaction, so I emit B instead because that will help make A come about" what should we call that? We can handwave defining "deception" as "being done intentionally" and carefully carve our way around so that LLMs cannot possibly do what we've defined "deception" to be, but now we need a word to describe what LLMs do do when they pattern match as above.
- surgical_fire 8mo agoThe pattern matching engine does not want anything. If the training data gives incentives for the engine to generate outputs that reduce negative reaction by sentiment analysis, this may generate contradictions to existing tokens. "Want" requires intention and desire. Pattern matching engines have none.
- jazzyjackson 8mo agoI wish (/desire) a way to dispel this notion that the robots are self aware. It’s seriously digging into popular culture much faster than “the machine produced output that makes it appear self aware” Some kind of national curriculum for machine literacy, I guess mind literacy really. What was just a few years ago a trifling hobby of philosophizing is now the root of how people feel about regulating the use of computers.
- pfisch 8mo agoEven very young children with very simple thought processes, almost no language capability, little long term planning, and minimal ability to form long-term memory actively deceive people. They will attack other children who take their toys and try to avoid blame through deception. It happens constantly. LLMs are certainly capable of this.
- sejje 8mo agoI agree that LLMs are capable of this, but there's no reason that "because young children can do X, LLMs can 'certainly' do X"
- anonymous908213 8mo agoAre you trying to suppose that an LLM is more intelligent than a small child with simple thought processes, almost no language capability, little long-term planning, and minimal ability to form long-term memory? Even with all of those qualifiers, you'd still be wrong. The LLM is predicting what tokens come next, based on a bunch of math operations performed over a huge dataset. That, and only that. That may have more utility than a small child with [qualifiers], but it is not intelligence. There is no intent to deceive.
- jvidalv 8mo agoWhat is the definition for intelligence?
- anonymous908213 8mo agoQuoting an older comment of mine... Intelligence is the ability to reason about logic. If 1 + 1 is 2, and 1 + 2 is 3, then 1 + 3 must be 4. This is deterministic, and it is why LLMs are not intelligent and can never be intelligent no matter how much better they get at superficially copying the form of output of intelligence. Probabilistic prediction is inherently incompatible with deterministic deduction. We're years into being told AGI is here (for whatever squirmy value of AGI the hype huckster wants to shill), and yet LLMs, as expected, still cannot do basic arithmetic that a child could do without being special-cased to invoke a tool call. Our computer programs execute logic, but cannot reason about it. Reasoning is the ability to dynamically consider constraints we've never seen before and then determine how those constraints would lead to a final conclusion. The rules of mathematics we follow are not programmed into our DNA; we learn them and follow them while our human-programming is actively running. But we can just as easily, at any point, make up new constraints and follow them to new conclusions. What if 1 + 2 is 2 and 1 + 3 is 3? Then we can reason that under these constraints we just made up, 1 + 4 is 4, without ever having been programmed to consider these rules.
- ostinslife 8mo agoIf you define "deceive" as something language models cannot do, then sure, it can't do that. It seems like thats putting the cart before the horse. Algorithmic or stochastic; deception is still deception.
- dingnuts 8mo agodeception implies intent. this is confabulation, more widely called "hallucination" until this thread. confabulation doesn't require knowledge, which as we know, the only knowledge a language model has is the relationships between tokens, and sometimes that rhymes with reality enough to be useful, but it isn't knowledge of facts of any kind. and never has been.
- staticassertion 8mo agoOkay, well, they produce outputs that appear to be deceptive upon review. Who cares about the distinction in this context? The point is that your expectations of the model to produce some outputs in some way based on previous experiences with that model during training phases may not align with that model's outputs after training.
- 4bpp 8mo agoIf you are so allergic to using terms previously reserved for animal behaviour, you can instead unpack the definition and say that they produce outputs which make human and algorithmic observers conclude that they did not instantiate some undesirable pattern in other parts of their output, while actually instantiating those undesirable patterns. Does this seem any less problematic than deception to you?
- surgical_fire 8mo ago> Does this seem any less problematic than deception to you? Yes. This sounds a lot more like a bug of sorts. So many times when using language models I have seem answers contradicting answers previously given. The implication is simple - They have no memory. They operate upon the tokens available at any given time, including previous output, and as information gets drowned those contradictions pop up. No sane person should presume intent to deceive, because that's not how those systems operate. By calling it "deception" you are actually ascribing intentionality to something incapable of such. This is marketing talk. "These systems are so intelligent they can try to deceive you" sounds a lot fancier than "Yeah, those systems have some odd bugs"
- coldtea 8mo agoWho said Skynet wasn't a glorified language model, running continuously? Or that the human brain isn't that, but using vision+sound+touch+smell as input instead of merely text? "It can't be intelligent because it's just an algorithm" is a circular argument.
- emp17344 8mo agoSimilarly, “it must be intelligent because it talks” is a fallacious claim, as indicated by ELIZA. I think Moltbook adequately demonstrates that AI model behavior is not analogous to human behavior. Compare Moltbook to Reddit, and the former looks hopelessly shallow.
- coldtea 8mo ago>Similarly, “it must be intelligent because it talks” is a fallacious claim, as indicated by ELIZA. If intelligence is a spectrum, ELIZA could very well be. It would be on the very low side of it, but e.g. higher than a rock or magic 8 ball. Same how something with two states can be said to have a memory.
- coldtea 8mo agoInterestingly, I found this related bit in Scott Alexander's blog: In 2004, neuroscientist Giulio Tononi proposed that consciousness depended on a certain computational property, the integrated information level, dubbed Φ. Computer scientist Scott Aaronson complained that thermostats could have very high levels of Φ, and therefore integrated information theory should dub them conscious. Tononi responded that yup, thermostats are conscious. It probably isn’t a very interesting consciousness. They have no language or metacognition, so they can’t think thoughts like “I am a thermostat”. They just sit there, dimly aware of the temperature. You can’t prove that they don’t.