[Hidden-tech] Question about ChatGPT and machine learning

Sun Mar 12 15:57:09 UTC 2023

I agree with Marcia. ChatGPT is to a skilled writer as clip-art is to
graphics. It's adequate for basic needs but is no substitute for a designer
working specifically to convey your idea.

I recently landed on a site that I could tell used a chatbot to write its
copy. I was repelled and left quickly--and crossed that consultant off my
list of people I'd ever hire, because she didn't disclose that a bot wrote
the site. Ugh!

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On Sat, Mar 11, 2023 at 9:45 PM Marcia Yudkin via Hidden-discuss <
hidden-discuss at lists.hidden-tech.net> wrote:

> I'm not sure I would call its output "well-written," though,  It's
> competently written, well-organized and with proper grammar, but stodgy in
> style and unimaginative, unless you've given it instructions like "write in
> the style of ____."
>
>
>
>
>
>
> On Saturday, March 11, 2023 at 04:22:19 PM HST, Alan Frank <
> alan at 8wheels.org> wrote:
>
>
>
>
>
> I would use it for composing text, but not for facts at all.  And if I
> asked it "How would you introduce George Takei at a political
> convention"," I would expect well-written text, but would also
> fact-check everything.
>
>
> -------- Original Message --------
> Subject: Re: [Hidden-tech] Question about ChatGPT and machine learning
> Date: 2023-03-11 15:55
> From: Marcia Yudkin via Hidden-discuss
> <hidden-discuss at lists.hidden-tech.net>
> To: Rob Laporte <rob at 2disc.com>
>
> Rob,
>
> Those are very interesting examples.  It's a mixed track record,
> though.  Based on your experience, what would you say ChatGPT should and
> shouldn't be used for, or how it should or shouldn't be used?
>
> For example, based on the errors in bios you saw, would you still use it
> for those artist bios given that you'd have to meticulously fact check
> everything it wrote?
>
> Marcia Yudkin
>
>
>
>
>
>
> On Saturday, March 11, 2023 at 10:19:20 AM HST, Rob Laporte
> <rob at 2disc.com> wrote:
>
>
>
>
>
> I've noticed that humans simplify complex, especially threatening, new
> things, by using dichotomies of good and evil, red and blue, etc, and
> that conviction is often inversely proportionate to knowledge. I've
> worked in search marketing for 28 years, have digested a lot about the
> kind of tech and processes underlying chatGPT (gpt), and I have no sound
> basis for strong conviction on any of the issues broached here. But this
> I can tell you from my mere 6 hours novice use so far:
>
>     * In under an hour it solved a complex HR-financial legal question,
> and provided the letter the plaintiff should write to the corporation's
> HR department, with quality of writing, sensitivity to workplace
> politics, and effective brevity way better than anything I can recall in
> my 50 years of adulthood, decade teaching college lit and writing, and 3
> decades in search marketing. Truly stunning. Save at least $2000 in
> legal fees that might have gone to a local law firm.
>     * A few times over the years I researched best email spam blocking
> solutions, and considered an aggressive form of it. gpt explained the
> problem with that solution, and did so way faster than my past and still
> inclusive Google searches, saving me a few hundred dollars in IT
> consulting.
>     * It completely conflated my semi-famous lawyer grandad's bio with
> that of his stellar but less accomplished son of the same name. Both are
> years deceased (most gpt data ends Sept '21), yet totally wrong.
>     * So too it got the bio of a decade-deceased famous scholar of Roman
> architecture (friend's dad) wrong on a few points, most notably that
> most his career was at Smith college, not Princeton as gpt said.
>     * It produced strikingly eloquent spreadsheet solutions for two
> different complex purposes. I asked it for the actual spreadsheet, and
> cell references were off, but in a second half hour of work, I'm sure it
> wold have gotten it right or I could correct it myself. A few hours of
> work time saved there, and one of the two tasks was billable.
>     * My firm had a prospective writing project for a client, involving
> bios of famous and notable painters sold by the client. I say "had"
> because now gpt or its structuring within services like NeuroFash will
> cut both client and my firm's copywriter time substantially.
>     * I've not tried but viewed a YouTube of good, arguably very good,
> graphic design for a marketing campaign done in well under half a day.
> Outside of broad ideological judgements, there's much to consider in how
> gpt will change work and incomes.
>
> The current version 3.5 will be upgraded to 4.0 within weeks. Think of
> gpt like the web in 1994 or personal PCs in 1981, with advancements
> happening 10x faster.
>
> Best Regards,
>
> Rob Laporte
> CEO  |  R&D Manager
> DISC - Making Web Sites Make Money
> Rob at 2disc.com, 413-584-6500
> www.2disc.com
>
> NOTE: Emails can be blocked by spam filters throughout the web. If you
> don’t get a reply within an expected span of time, please call.
>
>
>
> ---- On Fri, 10 Mar 2023 20:36:26 -0500 Marcia Yudkin via Hidden-discuss
> <hidden-discuss at lists.hidden-tech.net> wrote ---
>
> > David,
> >
> > Some great points there.  I especially like this one:
> >
> >>> it is *ALL* made up.<<
> >
> > That helps me to dimly understand that everything the chat says is
> > simply plausible, no more than that.
> >
> > Maybe we should think of it as no more authoritative than the cocktail
> > party chatter of someone who reads indiscriminately and can't shut up
> > until they've spewed five paragraphs.
> >
> > Marcia
> >
> >
> >
> >
> >
> >
> >
> >
> > On Friday, March 10, 2023 at 12:34:46 PM HST, R. David Murray via
> > Hidden-discuss <hidden-discuss at lists.hidden-tech.net> wrote:
> >
> >
> >
> >
> >
> > From what I understand (admittedly from only a *basic* understanding of
> > machine learning), it is not so much that ChatGPT is "making errors",
> > but rather that it is "making stuff up", and does not admit that it is
> > making stuff up.
> >
> > I'm going to brain dump what I think here, but I'm not an expert in
> > this
> > by any stretch, so don't take me as an authority.  Perhaps this can
> > help
> > you reason about ChartGPT until you find a better expert to consult ;)
> >
> > One thing to understand is that this is a *trained* model.  That means
> > that it was given a set of questions and answers and told "these are
> > good, these are bad", probably with a rating of *how* good or bad.
> > Then
> > it was given a lot of other data (and how exactly this gets turned into
> > questions and answers is *way* beyond my knowledge level).  Then a team
> > of model trainers started asking questions.  The trainers would look at
> > the answers it came up with and rate them, thus adding to the "trained"
> > data set.  When you tell ChatGPT that its answer was good or bad, you
> > are also potentially adding to that training data, by the way.
> >
> > I'm guessing that the way the system works there is actually no way for
> > it to "know" that it has made something up.  The output that it
> > produces
> > is generated based on what you can think of as a very advanced version
> > of statistical language modelling:  given a certain input, what are the
> > most likely kinds of things that would follow as a response?  And like
> > any statistical model, when you get enough standard deviations out,
> > things get weird.  At no point in the model output are things tagged as
> > "made up" or "not made up":  it is *ALL* made up.
> >
> > In the middle of the bell curve the made up things are *much* more
> > likely to be "correct" than out at the edges of the bell curve.  But
> > oh those edges...
> >
> > It is of course more sophisticated than a statistical model, but the
> > same principle applies:  if there are few examples of *exactly* the
> > kind
> > of data your input contains, then it is going to draw from stuff that
> > is
> > a lot less closely related to your input for its response.  But, and
> > here is the important part, it is going to make up *something* to
> > answer
> > with.  If a source is mentioned multiple times in the context of your
> > input, it will use it.  If there are no sources mentioned in the
> > context
> > of your input, it will generate an output that looks like the *kind of
> > thing* that would be a response to that *kind of input*.  In this case
> > that included a list of articles.  It generated at least one of them
> > from an author whose name was probably mentioned in the context of your
> > input, but never with an actual article name attached.  Or maybe that
> > author was mentioned in the context of conversations containing a
> > subset of the *words* in your input (rather than logically formed
> > sentences), depending on just how fuzzy the match was.  Then it
> > effectively made up a plausible sounding article name to go with the
> > author name, because that's what responses to other similar questions
> > in
> > its training data looked like (not similar in content, but similar in
> > *form*).
> >
> > So while I agree that making up all the sources seems like an extreme
> > example of this, ChatGPT is what Science Fiction calls an "Artificial
> > Stupid" (something that can't actually *reason*), and thus I think my
> > explanation is plausible.  It just depends on how fuzzy the match was
> > that it made on the input.  If the match was very fuzzy, then it would
> > have come back with material from its data that generally followed at
> > least some of your input, and then since responses the trainers
> > considered "good" to questions like that usually included some sources,
> > it made some up based on how the answers to other, less related,
> > questions looked.
> >
> > Anyone want to bet that four sources was the average number that was
> > accepted as "a good answer" by the people who did the training?  I know
> > I've seen "four things" in a couple of ChatGPT answers, and I haven't
> > asked it very many questions :)
> >
> > Given all this, there are only two things you can do, one of which is
> > exactly what you did: ask it for the sources.  Given *that* input, it
> > should be able to come up with the most likely response being the
> > actual
> > source.  If it can't, then it has probably made up the source (note: I
> > have not tested this technique myself, but it follows logically from
> > how
> > I think the system works).
> >
> > The second thing you can do (which you probably also already did) is to
> > rephrase your input, giving it different amounts and kinds of context,
> > and see how the output changes.  If your altered input results in a
> > less
> > fuzzy match, you will get better answers.
> >
> > The big takeaway, which you clearly already know, is to never trust
> > anything ChatGPT produces.  Use it as a rough draft, but verify all the
> > facts.
> >
> > My fear is that there are going to be a lot of people who aren't as
> > diligent, and we'll end up with a lot of made up information out on the
> > web adding to all of the maliciously bad information that is already
> > out
> > there.  I have read that the ChatGPT researchers are worried about how
> > to avoid using ChatGPT's output as input to a later ChatGPT model, and
> > I
> > have no idea how they are going to achieve that!
> >
> > And keep in mind that that maliciously bad information *is part of
> > ChatGPT's data set*.  Some of it the people who did the training will
> > have
> > caught, but I'm willing to bet they missed a lot of it because *they*
> > didn't know it was bad, or it never came up during training.
> >
> > --David
> >
> > On Fri, 10 Mar 2023 03:14:21 +0000, Marcia Yudkin via Hidden-discuss
> > <hidden-discuss at lists.hidden-tech.net> wrote:
> >> Yes, I know that people have been pointing out "ridiculous factual
> >> errors" from ChatGPT.   However, to make up sources that sound
> >> completely plausible but are fake seems like it belongs in a whole
> >> other category.
> >>
> >>
> >>
> >>
> >>
> >>
> >> On Thursday, March 9, 2023 at 04:10:43 PM HST, Alan Frank
> >> <alan at 8wheels.org> wrote:
> >>
> >>
> >>
> >>
> >>
> >> ChatGPT is a conversation engine, not a search engine.  It is designed
> >> to provide plausible responses based on similarity of questions and
> >> answers to existing material on the internet, without attempting to
> >> correlate its responses with actual facts.  Pretty much every social
> >> media space I follow has had multiple posts from people pointing out
> >> ridiculous factual errors from ChatGPT.
> >>
> >> --Alan
> >>
> >>
> >> -------- Original Message --------
> >> Subject: [Hidden-tech] Question about ChatGPT and machine learning
> >> Date: 2023-03-09 15:29
> >> From: Marcia Yudkin via Hidden-discuss
> >> <hidden-discuss at lists.hidden-tech.net>
> >> To: "Hidden-discuss at lists.hidden-tech.net"
> >> <Hidden-discuss at lists.hidden-tech.net>
> >>
> >> This question is for anyone who understands how the machine learning
> >> in
> >> ChatGPT works.
> >>
> >> I've been finding ChatGPT useful for summarizing information that is
> >> widely dispersed around the web, such as questions like "what are the
> >> most popular objections to X?"  However, the other day for a blog post
> >> I
> >> was writing I asked it "What are some sources on the relationship of X
> >> to Y?"  It gave me four sources of information, including the article
> >> title, where it was published and who wrote it.
> >>
> >> This looked great, especially since I recognized two of the author
> >> names
> >> as authorities on X.  However, when I then did a Google search, I
> >> could
> >> not track down any of the four articles, either by title, author or
> >> place of publication.  I tried both in Google and in Bing.  Zilch!
> >>
> >> Could ChatGPT have totally made up these sources?  If so, how does
> >> that
> >> work?
> >>
> >> I am baffled about the explanation of this.  One of the publications
> >> involved was Psychology Today, so we are not talking about obscure
> >> corners of the Internet or sites that would have disappeared recently.
> >>
> >> Thanks for any insights.
> >>
> >> Marcia Yudkin
> >> Introvert UpThink
> >> Introvert UpThink | Marcia Yudkin | Substack
> >>
> >>
> >>
> >>
> >>
> >> Introvert UpThink | Marcia Yudkin | Substack
> >>   Marcia Yudkin
> >>   Exploring how introverts are misunderstood, maligned and
> >> underappreciated in our culture - yet still thrive. Cli...
> >>
> >>
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