• Korhaka@sopuli.xyz
    link
    fedilink
    English
    arrow-up
    0
    ·
    4 months ago

    I just use it to write emails, so I declare the facts to the LLM and tell it to write an email based on that and the context of the email. Works pretty well but doesn’t really sound like something I wrote, it adds too much emotion.

  • lalala@lemmy.world
    link
    fedilink
    arrow-up
    0
    ·
    4 months ago

    I think that AI has now reached the point where it can deceive people ,not equal to humanity.

  • balderdash@lemmy.zip
    link
    fedilink
    arrow-up
    0
    ·
    4 months ago

    Deepseek is pretty good tbh. The answers sometimes leave out information in a way that is misleading, but targeted follow up questions can clarify.

  • Showroom7561@lemmy.ca
    link
    fedilink
    arrow-up
    0
    ·
    4 months ago

    If it’s being designed to answer questions, then it should simply be an advanced search engine that points to actual researched content.

    The way it acts now, it’s trying to be an expert based one “something a friend of a friend said”, and that makes it confidently wrong far too often.

      • Meltdown@lemmy.world
        link
        fedilink
        arrow-up
        0
        ·
        4 months ago

        With all due respect, Wikipedia’s accuracy is incredibly variable. Some articles might be better than others, but a huge number of them (large enough to shatter confidence in the platform as a whole) contain factual errors and undisguised editorial biases.

        • It is likely that articles on past social events or individuals will have some bias, as is the case with most articles on those matters.

          But, almost all articles on aspects of science are thoroughly peer reviewed and cited with sources. This alone makes Wikipedia invaluable as a source of knowledge.

      • A_norny_mousse@feddit.org
        link
        fedilink
        arrow-up
        0
        ·
        4 months ago

        TBF, as soon as you move out of the English language the oversight of a million pair of eyes gets patchy fast. I have seen credible reports about Wikipedia pages in languages spoken by say, less than 10 million people, where certain elements can easily control the narrative.

        But hey, some people always criticize wikipedia as if there was some actually 100% objective alternative out there, and that I disagree with.

        • Fair point.

          I don’t browse Wikipedia much in languages other than English (mainly because those pages are the most up-to-date) but I can imagine there are some pages that straight up need to be in other languages. And given the smaller number of people reviewing edits in those languages, it can be manipulated to say what they want it to say.

          I do agree on the last point as well. The fact that literally anyone can edit Wikipedia takes a small portion of the bias element out of the equation, but it is very difficult to not have some form of bias in any reporting. I more use Wikipedia as a knowledge source on scientific aspects which are less likely to have bias in their reporting

      • PeterisBacon@lemm.ee
        link
        fedilink
        English
        arrow-up
        0
        ·
        4 months ago

        Idk it says Elon Musk is a co-founder of openAi on wikipedia. I haven’t found any evidence to suggest he had anything to do with it. Not very accurate reporting.

        • grrgyle@slrpnk.net
          link
          fedilink
          arrow-up
          0
          ·
          4 months ago

          Isn’t co-founder similar to being made partner at a firm? You can kind of buy your way in, even if you weren’t one of the real originals.

          • PeterisBacon@lemm.ee
            link
            fedilink
            English
            arrow-up
            0
            ·
            4 months ago

            That is definitely how I view it. I’m always open to being shown I am wrong, with sufficient evidence, but on this, I believe you are accurate on this.

    • glimse@lemmy.world
      link
      fedilink
      arrow-up
      0
      ·
      4 months ago

      What topics are you an expert on and can you provide some links to Wikipedia pages about them that are wrong?

      • Meltdown@lemmy.world
        link
        fedilink
        arrow-up
        0
        ·
        4 months ago

        I’m a doctor of classical philology and most of the articles on ancient languages, texts, history contain errors. I haven’t made a list of those articles because the lesson I took from the experience was simply never to use Wikipedia.

    • OsrsNeedsF2P@lemmy.ml
      link
      fedilink
      arrow-up
      0
      ·
      4 months ago

      There’s an easy way to settle this debate. Link me a Wikipedia article that’s objectively wrong.

      I will wait.

      • Meltdown@lemmy.world
        link
        fedilink
        arrow-up
        0
        ·
        4 months ago

        There are plenty of high quality sources, but I don’t work for free. If you want me to produce an encyclopedia using my professional expertise, I’m happy to do it, but it’s a massive undertaking that I expect to be compensated for.

      • PeterisBacon@lemm.ee
        link
        fedilink
        English
        arrow-up
        0
        ·
        4 months ago

        Because some don’t let you. I can’t find anything to edit Elon musk or even suggest an edit. It says he is a co-founder of OpenAi. I can’t find any evidence to suggest he has any involvement. Wikipedia says co-founder tho.

    • Ms. ArmoredThirteen@lemmy.zip
      link
      fedilink
      English
      arrow-up
      0
      ·
      4 months ago

      If this were true, which I have my doubts, at least Wikipedia tries and has a specific goal of doing better. AI companies largely don’t give a hot fuck as long as it works good enough to vacuum up investments or profits

      • Meltdown@lemmy.world
        link
        fedilink
        arrow-up
        0
        ·
        4 months ago

        Your doubts are irrelevant. Just spend some time fact checking random articles and you will quickly verify for yourself how many inaccuracies are allowed to remain uncorrected for years.

    • imblue@slrpnk.net
      link
      fedilink
      arrow-up
      0
      ·
      2 months ago

      Well yes but also no. Every text will be potentially wrong because authors tend to incorporate their subjectivity in their work. It is only through inter-subjectivity that we can get closer to objectivity. How do we do that ? By making our claims open to scrutiny of others, such as by citing sources, publishing reproducible code and making available the data we gathered on which we base our claims. Then others can understand how we came to the claim and find the empirical and logical errors in our claims and thus formulate very precise criticism. Through this mutual criticism, we, as society, will move ever closer to objectivity. This is true for every text with the goal of formulating knowledge instead of just stating opinions.

      However one can safely say that Chatgpt is designed way worse then Wikipedia, when it comes to creating knowledge. Why ? Because Chatgpt is non-reproducible. Every answer is generated differently. The erroneous claim you read in a field you know nothing about may not appear when a specialist in that field asks the same question. This makes errors far more difficult to catch and thus they “live” for far longer in your mind.

      Secondly, Wikipedia is designed around the principle of open contribution. Every error that is discovered by a specialist, can be directly corrected. Sure it might take more time then you expected until your correction will be published. On the side of Chatgpt however there is no such mechanism what so ever. Read an erroneous claim? Well just suck it up, and live with the ambiguity that it may or may not be spread.

      So if you catch errors in Wikipedia. Go correct them, instead of complaining that there are errors. Duh, we know. But an incredible amount of Wikipedia consists not of erroneous claims but of knowledge open to the entire world and we can be gratefull every day it exists.

      Go read “Popper, Karl Raimund. 1980. „Die Logik der Sozialwissenschaften“. S. 103–23 in Der Positivismusstreit in der deutschen Soziologie, Sammlung Luchterhand. Darmstadt Neuwied: Luchterhand.” if you are interested in the topic

      Sorry if this was formulated a little aggressively. I have no personal animosity against you. I just think it is important to stress that while yes, both may have their flaws, Chatgpt and Wikipedia. Wikipedia is non the less way better designed when it comes to spreading knowledge then Chatgpt, precisely because of the way it handles erroneous claims.

  • DicJacobus@lemmy.world
    link
    fedilink
    English
    arrow-up
    0
    ·
    4 months ago

    I have frequentley seen gpt give a wrong answer to a question, get told that its incorrect, and the bot fights with me and insists Im wrong. and on other less serious matters Ive seen it immediatley fold and take any answer I give it as “correct”

  • jsomae@lemmy.ml
    link
    fedilink
    arrow-up
    0
    ·
    4 months ago

    ChatGPT is a tool. Use it for tasks where the cost of verifying the output is correct is less than the cost of doing it by hand.

    • qarbone@lemmy.world
      link
      fedilink
      English
      arrow-up
      0
      ·
      4 months ago

      Honestly, I’ve found it best for quickly reformatting text and other content. It should live and die as a clerical tool.

      • ArchRecord@lemm.ee
        link
        fedilink
        English
        arrow-up
        0
        ·
        4 months ago

        Which is exactly why every time I see big tech companies making another stupid implementation of it, it pisses me off.

        LLMs like ChatGPT are fundamentally word probability machines. They predict the probability of words based on context (or if not given context, just the general probability) when given notes, for instance, they have all the context and knowledge, and all they have to do it predict the most statistically probable way of formatting the existing data into a better structure. Literally the perfect use case for the technology.

        Even in similar contexts that don’t immediately seem like “text reformatting,” it’s extremely handy. For instance, Linkwarden can auto-tag your bookmarks, based on a predetermined list you set, using the context of each page fed into a model running via Ollama. Great feature, very useful.

        Yet somehow, every tech company manages to use it in every way except that when developing products with it. It’s so discouraging to see.

    • tacobellhop@midwest.social
      link
      fedilink
      English
      arrow-up
      0
      ·
      4 months ago

      Youre still doing it by hand to verify in any scientific capacity. I only use ChatGPT for philosophical hypotheticals involving the far future. We’re both wrong but it’s fun for the back and forth.

      • jsomae@lemmy.ml
        link
        fedilink
        arrow-up
        0
        ·
        edit-2
        4 months ago

        It is not true in general that verifying output for a science-related prompt requires doing it by hand, where “doing it by hand” means putting in the effort to answer the prompt manually without using AI.

        • tacobellhop@midwest.social
          link
          fedilink
          English
          arrow-up
          0
          ·
          4 months ago

          You can get pretty in the weeds with conversions on ChatGPT in the chemistry world or even just basic lab work where a small miscalculation at scale can cost thousands of dollars or invite lawsuits.

          I check against actual calibrated equipment as a verification final step.

          • jsomae@lemmy.ml
            link
            fedilink
            arrow-up
            0
            ·
            4 months ago

            I said not true in general. I don’t know much about chemistry. It may be more true in chemistry.

            Coding is different. In many situations it can be cheap to test or eyeball the output.

            Crucially, in nearly any subject, it can give you leads. Nobody expects every lead to pan out. But leads are hard to find.

            • tacobellhop@midwest.social
              link
              fedilink
              English
              arrow-up
              0
              ·
              4 months ago

              I imagine ChatGPT and code is a lot like air and water.

              Both parts are in the other part. Meaning llm is probably more native at learning reading and writing code than it is at interpreting engineering standards worldwide and allocation the exact thread pitch for a bolt you need to order thousands of. Go and thread one to verify.

              • jsomae@lemmy.ml
                link
                fedilink
                arrow-up
                0
                ·
                4 months ago

                This is possibly true due to the bias of the people who made it. But I reject the notion that because ChatGPT is made of code per se that it must understand code better than other subjects. Are humans good at biology for this reason?

  • Kane@femboys.biz
    link
    fedilink
    arrow-up
    0
    ·
    4 months ago

    Exactly this is why I have a love/hate relationship with just about any LLM.

    I love it most for generating code samples (small enough that I can manually check them, not entire files/projects) and re-writing existing text, again small enough to verify everything. Common theme being that I have to re-read its output a few times, to make 100% sure it hasn’t made some random mistake.

    I’m not entirely sure we’re going to resolve this without additional technology, outside of ‘the LLM’-itself.

  • PartiallyApplied@lemmy.world
    link
    fedilink
    arrow-up
    0
    ·
    4 months ago

    I feel this hard with the New York Times.

    I feel 99% of the time I feel it covers subjects adequately. It might be a bit further right than me, but for a general US source, I feel it’s rather representative.

    Then they write a story about something happening to low income US people, and it’s just social and logical salad. They report, it appears as though they analytically look at data, instead of talking to people. Statisticians will tell you, and this is subtle: conclusions made at one level of detail cannot be generalized to another level of detail. Looking at data without talking with people is fallacious for social issues. The NYT needs to understand this, but meanwhile they are horrifically insensitive bordering on destructive at times.

    “The jackboot only jumps down on people standing up”

    • Hozier, “Jackboot Jump”

    Then I read the next story and I take it as credible without much critical thought or evidence. Bias is strange.

    • Lady Butterfly @lazysoci.al
      link
      fedilink
      English
      arrow-up
      0
      ·
      4 months ago

      Can you give me an example of conclusions on one level of detail can’t be generalised to another level? I can’t quite understand it

      • PartiallyApplied@lemmy.world
        link
        fedilink
        arrow-up
        0
        ·
        edit-2
        4 months ago

        Perhaps the textbook example is the Simpson’s Paradox.

        This article goes through a couple cases where naively and statically conclusions are supported, but when you correctly separate the data, those conclusions reverse themselves.

        Another relevant issue is Aggregation Bias. This article has an example where conclusions about a population hold inversely with individuals of that population.

        And the last one I can think of is MAUP, which deals with the fact that statistics are very sensitive in whatever process is used to divvy up a space. This is commonly referenced in spatial statistics but has more broad implications I believe.


        This is not to say that you can never generalize, and indeed, often a big goal of statistics is to answer questions about populations using only information from a subset of individuals in that population.

        All Models Are Wrong, Some are Useful

        • George Box

        The argument I was making is that the NYT will authoritatively make conclusions without taking into account the individual, looking only at the population level, and not only is that oftentimes dubious, sometimes it’s actively detrimental. They don’t seem to me to prove their due diligence in mitigating the risk that comes with such dubious assumptions, hence the cynic in me left that Hozier quote.

      • PartiallyApplied@lemmy.world
        link
        fedilink
        arrow-up
        0
        ·
        4 months ago

        “Wet sidewalks cause rain”

        Pretty much. I never really thought about the causal link being entirely reversed, moreso that the chain of reasoning being broken or mediated by some factor they missed, which yes definitely happens, but now I can definitely think of instances where it’s totally flipped.

        Very interesting read, thanks for sharing!

  • Alloi@lemmy.world
    link
    fedilink
    arrow-up
    0
    ·
    4 months ago

    i mainly use it for fact checking sources from the internet and looking for bias. i double check everything of course. beyond that its good for rule checking for MTG commander games, and deck building. i mainly use it for its search function.