Re: Stupidity plus arrogance
What makes you think that? Perhaps read my comment again.
2107 publicly visible posts • joined 9 Jul 2009
I did my postgrad (Maths Tripos Part III) at Cambridge – my money (what there was of it – I got there on a scholarship) – was neither Old nor New. Funnily enough, while there I got to know a greatn grandson of Charles Darwin (his surname was Darwin). A toff, certainly, an Old Etonian IIRC, but a thoroughly nice and extremely smart guy, and not at all arrogant/entitled/ignorant – quite the opposite. I also met some appalling human beings of both the Old and New Money persuasion.
Interesting, a lot of downvotes there.
The hallmarks of a communist society are (obviously I'm not talking about the American usage – "kind of to the left" – here):
* A classless society
* Common ownership of the means of production, distribution and allocation
* Allocation of commodities/products according to need
* No private ownership of property
How many of these apply to modern-day China?
> … but that just drives home how hopelessly, laughably they've fallen behind.
Perhaps, just perhaps, falling behind in a race to … where? Oblivion? Financial/operational meltdown? The bottom? … is not that laughable?
Wariness about US and Chinese AI tech sounds like a pretty sound attitude to me.
Nice summary.
Further to that, the wartime British authorities were perfectly well aware of the "Final Solution" and the death camps pretty much from the start. Of course they had spies and people on the ground in Germany and further afield in occupied Europe. They deliberately withheld this knowledge from the British population, apparently on the grounds that it might undermine the war effort; sympathy for Jews and other "others" was not exactly thick on the ground in Britain.
Having said which, the British did (up to a point) accept or aid Holocaust refugees, especially children.
In almost all of Europe, also probably Australia, New Zealand, Canada and beyond, the US Democrats would be considered a centre-right party, perhaps like the Tories in the UK (who would be genuinely bemused at being referred to as "socialists").
The centrist parties in these places tend to be "social democrats" – not the same thing. Social democrats espouse a mixture of state vs private ownership and production, particularly in areas such as health/social care and basic services (e.g., water, transport infrastructure, …). In practice, ideology takes second place to pragmatism.
Well, in the context of socio-political stances, "reality" is the distribution (i.e., "frequency of patterns") of those stances in the population. The question, as the article makes clear, is the extent to which the population distribution is reflected in the input datasets…
“I’m having trouble finding any high-quality right-wing equivalent that would drive the models in the other direction,”…especially if filtered by "quality" (which, you'd have to say, may also be in the eye of the beholder).
Okay, that's a little bit disingenuous, and not what people mean by the cliche "reality has a left-wing bias". If, for example, you are inclined to argue that the "best" global economic model is unregulated free-market capitalism, you might want to look around you, and have a hard think about what "best" means there. But of course that's just my socio-political stance talking :-)
So one incident I had with a (good) PhD student, is that I was reviewing some of her simulation code, at her request (which was fine). I came across a section of code which seemed to be doing… nothing – in a very complicated way. It didn't really impact the simulations, which in a way was almost worse. She rather sheepishly admitted that she'd been in a rush and used some LLM to generate the code. I had to explain that I didn't actually mind her using LLMs – either for coding or to help with surveying the existing literature in some area – but it was absolutely essential that she reviewed (and understood) the generated code, and always chased up references in the literature. And, of course, so long as using LLMs (in either case) was effective and efficient; i.e., useful. Which, after all the requisite reviewing, may or may not have been the case.
Sure, I was speaking about my personal experience.
The way it works at my (UK) higher-education institution, and probably quite generally in the UK (although not necessarily in Europe or other parts of the world) is that an undergraduate degree course teaches familiarity with a field of study up to a certain (sub-research) level. I don't personally teach at undergraduate level.
The idea of a Masters degree is to take you up to research level in the subject, and in particular to teach how to research. There will usually be some kind of final-term dissertation or project where you get to demonstrate your level of familiarity with the field, and that you have taken on board what research involves; this will not necessarily (or even generally) be expected to involve original research.
For a PhD you are expected to delve deeply into your chosen field and perform original research, under the guidance of your supervisor.
Getting accepted for a place on a Masters course will require an undergraduate degree with a high enough grade (e.g., a First). There may well also be an interview process; places will be limited, and competition strong. And Masters courses ain't cheap! Now if you cheated with AI to gain the requisite grade for a Masters, you will likely be found wanting and rejected in the interview process, or, if you make it onto the course you will simply flounder and fail. You will not get away with cheating with AI on your Masters; the degree of oversight is higher. Apart from hand-in coursework, you will at various stages be required to actually demonstrate your knowledge, be it in supervisions, study groups, or whatever. As a supervisor, I will spot it immediately (this has happened on some very rare occasions).
To be accepted for a PhD, you will require a very high standard Masters degree. You will be interviewed, possibly several times. Competition will be fierce – very fierce (you'll be competing against the best of the best internationally). You will need funding, which itself may well require demonstrating your suitability for research. You will not get away with cheating. No chance.
As a Research Fellow in academia, I supervise MSc and PhD students. I can assure you that fake research ("fake" as in not valid, that is) is not at all hard to detect if you're familiar with the field. "Fake" as in plagiarised research may be harder—well, at least more work—to detect. At that level of study, however, it really isn't in the student's interest to produce fake work in either sense; and if they're stupid enough not to realise that, chances are they wouldn't have made it to the MSc/PhD level in the first place.
It's obviously not the same as the student actually doing them.
However, the end product may well be virtually indistinguishable from that produced by an averagely-competent student. That's a problem for teachers (but see my later posts).
An acquaintance lectures in law at a well-known UK university. She says the easiest way to spot AI-generated essays tends to be that the grammar, spelling and language construction are simply too good, given her knowledge of the linguistic skills, or rather lack thereof, of the student. (Many of her students are not native English-speakers, although, depressingly, this applies too to many who are.) That, plus the bland, generic style, as well as the odd hallucinated reference (although this seems to be becoming less prevalent).
If there are sufficient grounds for suspicion, the student may be called in for a live examination; most own up at this point.
Sure. Nonetheless it is the study of the past, as best we can parse it through whatever records do exist, and (with best practice) taking into account the perspectives, agendas and biases inherent in those records.
A thoroughly honourable and worthwhile enterprise to be sure, but not, of course, to be confused with science.
My argument was precisely that this is not what will happen. That this will, rather, just nudge us further towards idiocracy.
(And no, I don't give a stuff about damage to LLM providers either.)
> I don't have concerns about misleading users because LLMs are already unreliable and likely always will be.
More of a Bad Thing is not just a Bad Thing – it's a Worse Thing.
Isn't a concern here that the LLM doesn't "know" it's ingesting garbage, and will happily tokenise away, increasing the probability that regurgitation generates nonsense.
Hooray, you may say, this will make people more cautious about trusting LLM output, and they will be more inclined to cross-check sources or reject the technology altogether. Except I sincerely doubt that'll be what actually happens. Do we really want more idiots filling their heads with plausible- (or even implausible-)sounding nonsense? Some of these people may even have a vote.
> Local (relatively speaking) LLMs specialised for a certain use-case (e.g. aiding medical research) …
In the longer run, valid and actually useful applications of AI (ML if you're easily triggered) in scientific/medical domains are, IMHO unlikely to be LLMs at all – recall what that second 'L' stands for.
LLMs are not the only game in town.
Not a problem, there's a dedicated head gesture for ordering 600kg of Red Leicester (although admittedly it is uncomfortably close to the one for posting naked selfies to your local Freecycle group).
The real problem is when humming along to 90s R&B where all the female singers do that weird lateral head-slide thing. Anything could happen…
To expand a little, I think what those marketing people are handing down are not "design specifications" at all – they are desiderata, and unrealistic and unrealisable ones at that.
If some tech-bro droid orders his team to design and implement a cold-fusion reactor, then sorry, I'm not going to blame their failure to do so on the poor sods who found themselves landed in that crock.
> Thanks for that, but I don't think it's making the case that I should shut up …
Not you personally; I was just having a pop at what to me comes across as a circle-jerk of angry old men1 competing to see who can be the angriest, and adding nothing of interest to the discussion.
> I will treat the advertising as the spec and hold the designers accountable if they are complicit with that advertising.
I guess we'll have to agree to disagree on who to blame for the mis-selling; personally, I'm not inclined to conflate design and advertising.
1I am by all accounts an old man myself, although not a particularly angry one in real life. I do enjoy a robust debate, but a bunch of people endlessly, repetitively and loudly agreeing with each other doth not a debate make.
Unfortunately, that genie has long left the bottle, and is aided and abetted by publish-or-perish science culture, and the junk/predatory/parasitic journals that it engenders.
Speaking as a research scientist myself, the grim truth is that it places a heavy burden on those of us who take science seriously. There are no easy solutions that I am aware of.
Having said which, there are still reputable journals out there who take peer review seriously, as well as some interesting moves to challenge the current academic publishing/review model.
> The issue with AI is that it can easily be used to write what are effectively "junk" papers which look plausible at first viewing.
Most certainly, and it is a plague in many disciplines.
However, as I mention in a previous comment, the article seems ambivalent about whether it is talking about AI-created research, or just the writing-up (no, those are not the same thing!) The latter, I argued, is more nuanced.
Lazy, certainly (and probably highly error-prone), but to be fair it doesn't necessarily follow that the research was performed/assisted by AI.*
And to be honest, given the quantity of horrendously badly-written and incoherent papers I have to plough through, or even <shudder> review, this may not always be entirely a bad thing, especially for non-native language speakers. Provided, of course, that the actual research is by humans, and that due diligence is exercised to ensure that the AI write-up accurately reflects the research (hardly a given1).
1You might well ask how the reader can tell. But this goes as much for humans as for AI. If an author misrepresents their work (and some will), ultimately you have no way of knowing short of you or someone else replicating their study. This is endemic to science, a feature not a bug. But dishonesty (deliberate or inadvertent through AI) is a career-stopper – the proof tends to come out in the wash…
[I fully expect the usual torrent of downvotes here for failing to express the Reg-standard sneering contempt for anything and everything under the banner of AI, but before jerking that knee, consider that there is a valid point here: AI may turn out turgid and inaccurate prose, but at least—in comparison to a depressing number of humans—those prose tend to be grammatically correct, correctly spelled and, in contrast to the linguistic horrors I am forced to endure, actually comprehensible. Every academic, lecturer and teacher knows this all too well.]
*EDIT: Having re-read the article, I am honestly not sure whether they are talking about research conducted by AI, or just the write-up. Just to be clear, my comment refers strictly to writing-up, not actual research.