13 ms·

GPT detectors are biased against non-native English writers

• skummetmaelk 3y ago
  If anything the opposite should be true. GPT-4 at least has near perfect English. If your sample displays non-native traits probably it wasn't generated by GPT!
  • niel 3y ago
    Speculation on my part, but I believe us non-native English speakers write more formally and with less natural flow. I also wonder which proportion of English writing (in general) is written by non-native speakers, and whether we might be disproportionately represented in training data.
    • Terretta 3y ago
      Yes, I'd speculate along with you that this is not "bias" but just probability space: sampled input, styled output. Had the training cutoff been prior to SEO and "content generation" farms, as well as a shift in balance of academic writing published, the embedding space would be different.
  • janekm 3y ago
    GPT-4 has a bit of a bias towards overly formal, "textbook" English, which could be similar to what many non-native speakers learned.
    • FridayoLeary 3y ago
      I think the real reason is that in order to fully learn a language one has to absorb the culture it's used in. I appreciate because i'm slightly multi lingual. Elegant words in one language have no good parallel in another and an ugly approximation must be used instead. Also, what sounds pleasant in one language can sound artificial and stilted in translation.
      • H8crilA 3y ago
        I recently tried to translate such heavily culture-embedded texts into English so that they stay funny and rich, using GPT-4, and it did an almost perfect job there. Much better than any other translation tools.
    • alex201 3y ago
      You can dictate the style of writing in your prompt, though. For example, I have a few prompts saved in my notes, each for a particular use case. Except for a few comments I write on social media (like this one), none of my English output is generated directly by me, and it never looks or feels generated by AI. All thanks to the writing-style prompts.
  • anothernewdude 3y ago
    GPT-4 picks the most likely words according to the model. It aims for cliche and the most obvious generalisations given the previous context.
    • pmoriarty 3y ago
      "It aims for cliche and the most obvious generalisations given the previous context." Only if your prompts are themselves generic. You can give it examples of a text whose style you wish it to emulate and it will do it. You can also prompt it to alter what it wrote if you don't like something. For example, if you thought some part was too cliche and obvious you can point that out and have it alter that part. If you have a back-and-forth conversation with it about what you like and don't like, what you want or don't want, with examples, the results can be much better than what you'd get with a generic prompt. Incidentally, for creative writing I've found Claude to be much better than GPT4. I have not tried the version of Claude that's been enhanced with a 100k token context length yet, but that should allow you to give it many more examples and hopefully that will translate to even better output. That said, none of these LLMs are perfect, nor do they yet pose a threat to really good (never mind great) human authors, but they're a pretty effective tool.
  • freehorse 3y ago
    I think people here misunderstand the whole point, non-native speakers do not necessarily make more mistakes in general, it is about perplexity of word choices and structure. In a subsequent experiment in the paper, they used chatgpt to increase and decrease perplexity in the original non-native and native texts respectively, and the exact opposite pattern was observed.
    • darkerside 3y ago
      Perplexity?
      • bigbacaloa 3y ago
        Poster was illustrating the point being made.
        • lupire 3y ago
          No, poster was using a word form the linked article. Click the "download PDF" to read past the abstract.
          • freehorse 3y ago
            If half of commenters had skimmed through the article instead of just commenting after reading just the title or, at best, the abstract, they would have answered their comments themselves.
      • olddustytrail 3y ago
        This is a measure of how well the supplied text matches what the model itself would have produced. A low perplexity means the text isn't massively different from what it might have output itself (which might be an indicator that it was produced by a model), whereas a high perplexity suggests it's the kind of semi-random nonsense you'd expect from a student. ;)
• FridayoLeary 3y ago
  >>Our findings reveal that these detectors consistently misclassify non-native English writing samples as AI- generated, whereas native writing samples are accurately identified. Furthermore, we demonstrate that simple prompting strategies can not only mitigate this bias but also effectively bypass GPT detectors, suggesting that GPT detectors may unintentionally penalize writers with constrained linguistic expressions. Essentially ChatGPT writes like a non native english speaker. It has to translate from it's computer language into english. I think it's more likely that humans will adapt to ai "style" then the other way round. Look at the elaborate and often exquisitely constructed language that books used 100 years ago. Does anyone think that the art of good writing has not degenerated?
  • Sharlin 3y ago
    But that does not make sense; ChatGPT writes almost perfect, idiomatic copy, probably at the level of the >95th percentile of native speakers. I guess one could call it too good to be a native – but to get around that, you can just simply ask it to use vernacular and a more casual register. Whatever the difference from "average" English prose that an improperly trained ChatGPT detector has gradient descended upon, it is probably something entirely unintuitive and indescribable that also happens to manifest in non-native writing – a classic case of underfitting due to a lacking training corpus.
    • simion314 3y ago
      >ChatGPT writes almost perfect, But I feel it responses look like a template where it fills the information in and many times fills it with bullshit. This could be the part where they trained the "chat" part on how to respond. Probably better data for training that is needed, and maybe data that would train it to response like a human and not like an LLM.
      • tjpnz 3y ago
        As a large language model created by OpenAI I cannot...
      • 3y ago
• adhesive_wombat 3y ago
  While I don't doubt it, there's probably an uncanny valley too: if a writer's English contains spelling errors, or ungrammatical or unidiomatic constructions, AI won't make the same mistakes. As the English level improves, now the spelling and grammar is correct, but you have a limited repertoire of correct constructions to draw from. This may lead to repetitive structure and wordiness as the meaning is shoehorned into more, simpler, phrases. I imagine this is what sets off the AI detectors. Considering that AI writing standards will probably only increase from here, encroaching on the territory native English speakers operate at, perhaps the best way to mark yourself as not-AI is to start making many errors. This will work for a week or two until someone tunes a model to also do this, and the arms race grinds ever on! It also goes for other languages too, so luckily for me, I have a short period where my dreadful other languages will be an advantage.
  • anothernewdude 3y ago
    AI will make the most common mistakes.
    • adhesive_wombat 3y ago
      I haven't really noticed any grammatical or spelling errors. And if that was a problem, if you also train it using a spelling/grammar checker of the type we've had for decades, it's probably going to be an insignificant amount compared to some non-native writers.
      • ghaff 3y ago
        It's mediocre in a way that's different from how many humans would be mediocre.
    • rpastuszak 3y ago
      Sidenote: from the pov of descriptive linguistics LLMs _seem_ amazing: a fairly true representation of the consensus we call our language. But, this gets more complicated in practice, as the dataset will be always biased. So in a sense the opposite is true: LLMs are prescriptivist as they reflect the biases of the people involved in their creation, thus introducing a "standard" version of the language(s), just not in a completely deliberate way.
• jefftk 3y ago
  The abstract claims, "whereas native writing samples are accurately identified", which is very different from claims I've seen elsewhere about how well these detectors work. The test they're reporting is running the detectors on "88 US 8-th grade essays sourced from the Hewlett Foundation’s Automated Student Assessment Prize (ASAP) dataset", and they got a false positive rate of ~10%.
• iinnPP 3y ago
  If a GPT detector has any false positives at all it will disadvantage people who are already disadvantaged. They are the least likely to be capable of defending themselves and the least likely to be heard if they do try to defend themselves. Not to mention the fact that being called non-human is most definitely going to offend some people. What exactly makes anyone think that they can detect an LLM that is outputting text? The notion seems absurd yet it keeps coming up.
  • mtlmtlmtlmtl 3y ago
    >What exactly ... Probably the fact that if they admit the reality, they have to think about some difficult and profound questions. It's much easier just to posit an imaginary future technology and decide that will solve it.
  • wheybags 3y ago
    > What exactly makes anyone think that they can detect an LLM that is outputting text? When you read LLM output, you can often tell. The source of the notion is that we can do it pretty well ourselves, so if the AIs are so magical then they should be able to do it too (not saying I agree, but it is a pretty clear line of logic).
    • alwayslikethis 3y ago
      I think ChatGPT is trained to speak in a certain tone. I played with other models before, and they seem to not have this issue, and they seem much less distinctive for me.
      • hutzlibu 3y ago
        Also you can just tell ChatGPT to change style.
        • horsawlarway 3y ago
          This is the thing that kills me - people who think they can reliably detect LLM output are fooling themselves. At best - you can look for logical fallacies and false facts in the output, and use that to guess, but realistically - people are fucking bad at detecting it, including all these HN posters who keep claiming they can do it reliably...
• Grustaf 3y ago
  It seems quite natural that it’s easier to interpret correctly written English than language that contains mistakes. Does anyone find this controversial?
  • detaro 3y ago
    I'm not sure how that's relevant to the topic?
• petesergeant 3y ago
  > The detectors demonstrated near-perfect accuracy for US 8-th grade essays I am genuinely confused. It seems that all the test data provided were real human essays. The ones provided to GPT as native English speaker ones are from a prominent machine-learning data set of common essays, that seem likely to have been included in any training data, where the non-English ones were taken from a random forum. Can someone help me understand if I’ve understood the flaws correctly here? If so, does this paper add anything beyond just confirming that there’s at this point of time absolutely no value in GPT detectors?
• CPLX 3y ago
  There is no chance whatsoever that a tool will be able to reliably tell the difference, and I can’t understand how anyone thinks such a thing is possible. It’s not clear how there could be a mechanism of action for such a thing. We’re quite literally talking about an infinite number of monkeys scenario. Consider this thought experiment. We will start with a piece of text that your detector is 100% certain was created by a GPT tool. Now, actually prove that there is no way whatsoever for at least one human being to independently create this piece of text given a reasonably plausible prompt. If you can’t prove that your tool is bullshit.
  • vinyl7 3y ago
    Yea I don't know what happened to the collective conscience but people have totally lost the ability to question things.
• kybernetyk 3y ago
  [flagged]
  • soneca 3y ago
    So you don’t care about the inequalities that it can create or reinforce as a result? Since it wasn’t the intention of the creators, just a limitation of their resources, we should accept and don’t complain if it generates undesired externalities?
    • janalsncm 3y ago
      > just a limitation of their resources I think even this is too generous. These “detectors” are claiming to do something which is impossible from a technical sense. You can’t calculate perplexity without knowing the prior probability distribution, and you can’t know that without knowing which model was used. They’re playing a dangerous game where the consequences for being wrong (which will be borne by innocent 3rd parties) can be extremely dire.
    • gavaw 3y ago
      Non-native English speakers have produced less content in English on the Internet (despite having it easier, since we outnumber native English speakers) and as a result our content is underrepresented. Isn't this the definition of "fucking fair"?
      • soneca 3y ago
        Obviously not a sufficient argument for it to be “fucking fair”. If the consequences of using such technology “overharm” populations underrepresented in the data, it is obviously not fair. Even election polls correct bias due to underrepresented populations among the responders.
  • puika 3y ago
    Easily solved with an AI to detect cats wearing chickens costumes.
  • 3y ago
• janalsncm 3y ago
  If I was a non-native speaker, I would use AI tools to clean up my writing. Does this mean I’m cheating? Of course not, the ideas are still my own. But this might make my writing more likely to be flagged. The fact of the matter is none of these supposed “AI detectors” are reliable. GPTZero claims to be the #1 AI detection system which is a little like claiming to be the world’s best perpetual motion machine. Anyways, that’s why I created this “tool”, hopefully it can get to the top of Google: https://isthiswrittenbyai.surge.sh/ https://isthiswrittenbyai.surge.sh/
  • AdieuToLogic 3y ago
    > If I was a non-native speaker, I would use AI tools to clean up my writing. Does this mean I’m cheating? Of course not, the ideas are still my own. Consider a different moral dilemma: If I had a job which I could not do and used AI tools to clean up my work, does this mean I'm cheating my employer? Even if my ideas might be incorrect, a fact hidden by the "AI clean up", yet are my own?
  • sys_64738 3y ago
    Are you cheating if you use a spell checker, a thesaurus, or one of those word rephrasing recommendations in M$ Word?
    • AdieuToLogic 3y ago
      > Are you cheating if you use a spell checker, a thesaurus, or one of those word rephrasing recommendations in M$ Word? A spell checker does not formulate the word, a thesaurus does not choose which word to use, nor does a word processor predictively generate phrasing.
    • janalsncm 3y ago
      Unless it’s a spelling contest, no.
  • onion2k 3y ago
    If I was a non-native speaker, I would use AI tools to clean up my writing. Does this mean I’m cheating? Of course not, the ideas are still my own. No, the ideas are not your own. They're a combination of yours and the AIs (which is a combination of millions of other people's ideas really), just as they are for anyone who writes a prompt. The fact that you aren't a native English speaker, or that you're using AI for 'good', are irrelevant. If you use AI to produce content of any sort you have to accept that you are not really the author. You just wrote the prompt.
• pylua 3y ago
  I strongly believe that any false positive rate here means they shouldn’t be used at all to detect cheating. It really is morally wrong to potentially fail people that have worked hard to produce something then to question the integrity of it.
  • tgv 3y ago
    There's an awful amount of cheating going on. In certain environments, there's a > 50% chance that an essay was not written by the student.
    • EarthLaunch 3y ago
      Morally wrong? - but there's a crisis! - made up statistics - think of the children
    • pylua 3y ago
      We need to rethink the concept of a term paper and how it is graded. If a machine can produce a paper then why should we be doing it at all? In my opinion, the purpose of producing a paper is to interrogate an issue in depth. I think we should replace/augment papers with oral defenses if the topic and hard questioning . Obviously this is more effort to grade but academia has been quite lax for awhile now.
      • tgv 3y ago
        My more cynical take on the use of papers is that it already was a lax way to assess students. They write stuff, and the teacher skims it. And also important, it gets less complaints than written or oral exams, while you can still maintain the illusion that the students are being tested on the topic. We'll have to go back to sitting in a room, answering questions on paper. Or indeed oral exams, but those are almost everywhere infeasible. A decent exam should take 1 hour or so. Times 100 to 200 students makes anywhere between 2 and 5 weeks of work, excluding the increasing amount of time it takes to handle complaints about the grading. And the TA has to sit in as well, to provide some check. So that's not going to happen, except for very small groups, or very rich institutions.
• alex201 3y ago
  I believe that in a couple of years, people will start looking at writings (any writing) in a very different way than they do now. Apart from the fact that spelling or grammatical mistakes will join history, people will take anything written on a much less serious or personal note. Although the less personal aspect is gratifying, the less serious tone is a huge negative. Writers will move to a new level of writing skills in order to keep relevant and retain their audience. Puns, teasing, and unorthodox expressions will flood the internet. Writing styles will become trademarks! Language itself, especially English, will be much more standardized, as if it's a programming code. The bad will get badder and the good will be gooder.
  • weird-eye-issue 3y ago
    I don't think that's really what's going to happen... People stuffing puns in just to convince you it's human written just sounds silly. Not to mention you can ask GPT to do that too lol What's going to happen is that branding will get more and more important. People simply won't trust anything from random sources anymore like they do now when they search on Google and treat the top pages as the truth They will get most of their info from trusted sources/brands and filter out the rest
  • meindnoch 3y ago
    I think the opposite will happen. People's tolerance of fluff will go to zero, whether it's AI- or human-generated. People will demand straight facts, without any linguistic embellishments. Just pure information, simple.wikipedia.org style.
  • makeitdouble 3y ago
    There was a time a beautiful hand writing was an incredible asset as a person, you'd be writing letters and invitations, and people would look at your script and assert your personality from it. Companies would pass resumes through a mentalist looking mostly at your hand writing. And all of that just went down the drain with the digital world, but we still have people enjoying beautiful writing for the sake of it. Pen and paper addicts still abound. I see stylistic forms analysis going the same route. Nowadays we pay attention to it in many settings, but down the line it should become a niche hobby for people really enjoying it.
• bigbacaloa 3y ago
  I have a strong accent and when I call thebyoical government/bank phone that requires voice responses it typically is hopeless. This is a problem with all such automated systems, although it is often also a problem with people ...
• ballenf 3y ago
  The next step will be students required to "show their work" on writing assignments. That is, some type of edit history or snapshots of the work-in-progress. Of course that could also be faked, but would require quite a bit more work. Just like code is easier to examine and authenticate code if you can see the commit history.
  • caseymarquis 3y ago
    That seems positive, honestly. It forces a focus on the developmental process over the finished product.
  • wildrhythms 3y ago
    Or you could have the student briefly explain their essay in-person, how they came to the conclusion, etc. Explaining the thought process.
• jruohonen 3y ago
  As the referencing is nowhere near solved, LLMs cannot evaluate the reliability of sources, most of science is paywalled, and publishing is continuous while LLMs are forever stuck in the past, I see the educational fears at the university-level completely overblown.
• mensetmanusman 3y ago
  "Biased against" or "non-optimized for" ?
  • deleted 3y ago
    [deleted]
  • lupire 3y ago
    This is a scientific article measuring statistical bias in behavior, not a study of the design process.
• User23 3y ago
  This is a needlessly inflammatory and judging from the comments quite distracting phrasing for the title. The really interesting thing here is that the detectors appear to recognize machine output on account of it is relatively less proficient than fluent writers.
• TallGuyShort 3y ago
  GPT-n detectors are just better trainers / discriminators for GPT-n+1. There's no long term value here.
• AndrewKemendo 3y ago
  They shouldn’t be surprising. You have to remember that all of these things are trained on the Internet, so all of the biases, sentiments that are inherent in the Internet are inherent fundamentally in LLMs trained on common crawl.
• vrglvrglvrgl 3y ago
  [dead]
• aaron695 3y ago
  [dead]
• cpif 3y ago
  The texts in the sample set are too short for this to be meaningful. The human-authored TOEFL tests (which compare unfavorably with the eighth-grader essays) are ~100 words. The longest sample is under 1000 words. GPT detection ought to be optimized for longform texts, so tests of its efficacy should be, too. Perhaps the current detectors on the market are trying to assess writing at the sentence level, but if that's the case then it should be obvious that they will be inaccurate. GMail can write most of a 100-word email for me if I type "Thanks so much" and hit tab. That's a good thing. If GPT is useful as a "productivity" tool, it is for low-level "writing" tasks like this, which aren't really writing at all, just rote responses. Anyone who can access this tool (if they have confidence in its prowess) should use it. Writing proper is about developing ideas, and it's this that people need to be concerned about. It's true that if your college admissions essay is riddled with typos, eyebrows may be raised, but its ultimate significance is whether you can and are willing to reason. If someone is using ChatGPT (or spellcheck, or Grammarly) in order to cultivate the appearance of having "proper English," who cares? But if they're using GPT to avoid thinking altogether, that's a problem. At ~250 words, I guess the only thing you can assess is good formal usage. It's patently obvious that both GPT and non-native English speakers will outperform native speakers on this. Of course, I hope that anyone in the position to assess short-form writing is made aware of this research, and is cautious about GPT detection. On the other hand, it'd be pretty funny if idiosyncratic grammatical choices became the marker of a human hand.
  • ickelbawd 3y ago
    So then generating a term paper becomes a 2+ pass problem then. First have the model generate the outline, then have it generate each paragraph in the outline. Then have it offer suggestions and revisions when you put the whole thing together.
• Gimpei 3y ago
  A close acquaintance of mine just quit her job as a community college writing instructor because of chatGPT. Everybody is using it and it’s difficult to prove so it’s made her job impossible. I think students in general would lose a lot if we “adapted” writing class into prompt engineering class. Writing is as much about organizing your thoughts and assembling an argument as it is about putting words on a page. No amount of prompt engineering training is going to teach that. The only solution I see is making all assessment in class.
  • 13415 3y ago
    I've had arguments about this and don't understand the worries. Although it depends on what people do with it specifically and the context, most uses of LLMs are perfectly reasonable and legitimate, and quite comparable to other tools like spell correction and CAS calculators. In exams, you might not want to allow them, but in almost every other context they make sense and everyone will use them soon anyway. There is one caveat: If the LLM counts as an author, then it needs to receive proper attribution in academia at least as a co-author. But so far I wouldn't say it is possible to create anything of quality solely with an LLM and these models are used for partial content like style and spelling correction software. To put it another way, I see no reason why a writing instructor shouldn't base their assessments on the quality of the writing. Who has written it and how much the LLM can be attributed as an author is another question and doesn't really concern the writing process. Writers will soon use LLMs in all domains, just like they transitioned from typewriter to word processor. They will be integrated into every major word processor anyway.
    • wildrhythms 3y ago
      >Writers will soon use LLMs in all domains You sure about that?
      • crop_rotation 3y ago
        I also think they will, not for the main creative work but that it makes lots of tedious exploring work a lot more easy, even if in the end you discard all GPT output.
• sour-taste 3y ago
  Could you do the stupid thing and have openai et al offer an API that, given text (or a hash of some text) returns whether that hash was generated by the service? Some 3rd party companies specialize in cheat detection and pay for the API then get paid by schools or whoever to detect detect cheaters. Difficulties I can think of: * Getting ai companies to offer this. I don't think it comes with a downside for them really though. You couldn't use it to actually retrieve results in any way, and you wouldn't have prompts. * This only detects exact matches, people changing the output would defeat it. Fixable with some kind of fuzzy search that returns a 'distance to nearest response' but this obviously makes it more expensive and difficult to run, use, etc. * People could still run the model themselves, as models get better and more expensive maybe this becomes less of a problem. Or maybe models get small enough while still generating good output that it becomes more of a problem. Who knows. At least this would avoid AI grading AI issues
  • mkoubaa 3y ago
    Yes but you insert one space and the checksum changes
    • adriancooney 3y ago
      I wonder if comparing embeddings could work here? It might be more resilient to cosmetic changes.
  • dingledork69 3y ago
    Locally ran models exist, and more will come and they'll become cheaper and easier to run.
    • throwaway290 3y ago
      Even if ClosedAI doesn't get government to ban sales of powerful GPUs to the public. Homebrew models will not be of comparable quality in near future. Don't be fooled by how cheap ChatGPT is, it is not profitable.
• fnordpiglet 3y ago
  A solution to preventing cheating by use of calculators on homework is to make people show their work. So, obviously, we should make students turn in written work with their full undo buffer attached.
  • zeroonetwothree 3y ago
    That shouldn’t be too hard to fake with LLMs though
    • fnordpiglet 3y ago
      I dunno - people operate with their own internal models and make fairly regular and distinctive mistake patterns. Until you can fine tune a model with your personal undo histories on prior work (which since I can articulate a solution it can/will be done) it’ll be obvious. But there’s also a crypto point (not to be confused with obfuscation or currencies) I am making is that as LLMs are calculators for language, maybe the goal needs to be to up level the objective. It’s no longer about distinguishing between people with natural facility with written language any more than in the age of calculators is it so damn relevant to be a human computer. Instead novelty of thought and argument is perhaps the more crucial skill, and simply “write an essay about XYZ” is an in class exercise. Am at home exercise should be one that even with a LLM assisting requires primary thought and guidance sufficient to make a body of work that’s an order of magnitude better than if students had to labor against their dyslexia to be understood or bask in their ableism. Maybe the LLM levels the field for language facility and we instead focus on the thoughts of the human, exploring their facility of reasoning, and just accepting LLMs exist. Frankly as a teacher I might find it more interesting to read the specific deepest thoughts of my students rather than wading through their struggles in basic articulation.
• k__ 3y ago
  Snake oil. I tried tools like GPTZero on dozens of my hand written texts and AI texts. Random results all the way. After an editor had their hands on an AI text, you can't tell the difference anymore.
• ineedasername 3y ago
  I’ll be honest, unless there’s a confident but obviously wrong complete factual blunder then I would have very low confidence in any probability of human/ai determination I tried to make. And even then I wouldn’t add many points to my confidence: I’ve made obvious blunders of my own, plenty of them. Right now, and probably for a very limited time only, the primary hallmarks of llm responses like ChatGPT are confident tone and orderly structure, down to using bullet points and ordered lists. Except for the almost overly confident tone that bears a striking similarity to the tone of digests I frequently need to write, and GPT-4 is already much better at not sounding like a reasonably intelligent college sophomore that needs a bit more experience to avoid severe dunning kruger effects. Within a year I’m not sure I’ll have any confidence at all in my ability to detect human/ai, except in areas where much deeper domain knowledge is required, and even that will likely be a rapidly closing window. I doubt it would take much difficulty to train a model out of that confident structured tone as well. If we’re talking about adversarial or malicious use or content farms then I think the barn door is already wide open. As far as content farms go though there’s a reasonable question becoming ever more relevant: apart from the cynical ad revenue cash grab, does it matter that content farms use AI, if it’s accurate and possibly better than, say, the average stack exchange response & threads in 90% of the cases? I’m ambivalent on the question. Deep knowledge and novel insights will be the domain of humans for some time, but I honestly don’t know for how long. As I said before, my work requires succinct output along the lines of OpenAI’s capabilities. Right now it’s not reducing the amount of time it take me to perform some tasks— it’s bootstrapping the process so I can use roughly the same amount of time to produce a better, deeper, more polished result. I am already becoming more of an editor or curator of the end product of projects I work on, where 90% of the work takes place before I get to that point. But especially with GPT 4 I can feed it complex explanations of what I’m doing (not raw data) and ask it for its thoughts to get my own juices flowing. To me, the question of whether something is human/ai produced is becoming not just irrelevant somewhat if a non sequitur. I’m exaggerating a bit to make my point, it’s not as simple as what I can fit into a comment here. But the question “did you use an LLM to produce some/all if this?” Is quickly beginning to sound like “did you spell check this before completing it?”
• simonw 3y ago
  "Furthermore, we demonstrate that simple prompting strategies can not only mitigate this bias but also effectively bypass GPT detectors" Anyone who claims to be surprised by this either isn't thinking very hard - or is deliberately ignoring this because they want to sell you a snake oil detection product.
• JC770 3y ago
  GPT has poor quality in many professional fields, such as IT, biology, and finance, whether for native or non native writers
• crop_rotation 3y ago
  Using AI to detect LLM writing is a fool's errand. You can easily generate text using GPT4 that is absolutely same as how many humans would write it (off course apart from the boilerplate "As an AI language model"). All it will do is penalize some specific writing styles. Ironically it will drive those people to use GPT and ask it to rewrite their work in a different style.
• jwie 3y ago
  ChatGPT detectors don’t work at all. Why would I believe a study about detection needing to be more equitable when the whole thing is bs from the start? Come up with different ways to assess students. Writing samples don’t work anymore get over it.
• wizofaus 3y ago
  That genuinely surprises me, as the sorts or errors made or at least non-idiomatic English used by non-native speakers are not something you typically see from LLM output. Though I don't doubt you could get them to generate text "as though" it were written by a non-native speaker.
  • powersnail 3y ago
    If the detector biases towards the detection of certain qualities of native speakers' writing, using the lack of which as a marker for GPT generated content, it would then logically place an unfair bias on non-native speakers.
• x-complexity 3y ago
  Plagiarism detectors are inherently hard to create because they're trying to detect an amorphous concept right from the start: Originality. Instead, more emphasis should be placed on proper citations & individual short Q&A (< 5 questions) about the writing in question: What they've researched, unexpected hurdles, research methodologies & tools, main references used, etc. Perfect recall of what's been written is not the aim, but rather that the author is able to understand what has been supposedly written by their own efforts, along with the citations used in their works. In fact, as of writing this comment, it could be fun to see what an LLM would produce as questions to such a paper in question, and have the author answer those questions on the spot. This can be used as a teaching lesson on the limits of what an LLM can accomplish, as well as proof that the author can at the very least withstand surface-level examinations from an automated system. Those with (stage fright / social anxiety / vocal disabilities) could be given extra time to come up with answers to said questions, in an attempt to balance out any advantages that could be given to confident authors via this method.
• wraptile 3y ago
  All of these GPT detectors manage to sell snake oil in 2023 - amazing economical example how demand creates supply even though supply is literally impossible.
• zxie 3y ago
  Author of one of the detectors here (Sapling.ai). We try and be clear that the detector output should be used as just one of many possible cues and that there will always be false positives. That said, detectors often do detect bland/generic text, and that can be useful feedback. Open to other suggestions: zxie@sapling.ai
• syngrog66 3y ago
  The obsession with "bias" in general, and with stereotypes, and discrimination, and "representation" and identity-based grievance by a segment of sometimes very vocal people -- both in academia and online in social media -- is a minor theme in a game I've been building [SB: see below.] Also the idea of "Official, Correct, Allowed Opinions", in general. And propaganda and peer pressure. The game is meant to entertain, sure, but also to help educate and influence, and stimulate critical thinking and skepticism. It does this in part via parody but also via other in-world mechanisms like demonstrating cases where "The Emperor wheres no clothes" or via opportunities to have a Socratic dialogue between characters, in-game. Indeed the ability to question, second-guess, test and confirm, is the key behind the success of science and really all major advancements in history. Its important we stay faithful to it, and never let it be corrupted by fraudsters or self-dealing populists. (imo, anyway.) I do believe climate and democracy are the world's top two dangers today. Everything else should be a far lesser priority for us to talk about or try fixing. And that the recent hyped AI breakthroughs, if anything, are more likely to greatly amplify pre-existing dangers to democracy -- to make our world worse, rather than better. One of democracy's dangers, however, is the growing deployment of adversarial propaganda. Another is the increased feeling of an inability to operate on a single, shared mental map of our world. (Both a real gap and an imagined one.) Certain "actors" out there seek to stir our emotions 24x7, to sow tensions where none need be prior, and to enflame hate and trigger violence (eg. stochastic terrorism.). And they do this in part by amplifying certain "annoying" things which many voters can naturally get upset about. Or build a kind of tribal identity upon: Us vs Them. Us Good, Them Evil. Therefore we should all strive to contribute far less to those forces, to give them far less of our precious focus, time and energy. And... build-up personal defenses against whichever bits of this toxic brew that still manages to get through into our info input feeds, daily. Thus my own little project -- to help make a little dent. ---- [SB] - https://synystrongames.itch.io/slartboz https://synystrongames.itch.io/slartboz