And which are these universal human values and preferences ? Or are we talking about silicon valley's executives values ?
Depends how you look at it. I think a brand like Google should vet a mere one level down the supply chain.
to ensure the AI models are more aligned with Google's values and preferences.
FTFY
> "Massive privacy invasion: The core of modern adtech runs on tracking your behavior across different websites and apps. It collects vast amounts of personal data to build a detailed profile about your interests, habits, location, and more, often without your full understanding or consent."
It does not have to have anything ro do with cyberpunk. Corporations are not people, but if they were people, they would be powerful sociopaths. Their interests and anybody elses interests are not the same.
"AI raters at GlobalLogic are paid more than their data-labeling counterparts in Africa and South America, with wages starting at $16 an hour for generalist raters and $21 an hour for super raters, according to workers. Some are simply thankful to have a gig as the US job market sours, but others say that trying to make Google’s AI products better has come at a personal cost."
How this industry managed to not grasp that meaning exists entirely separate from words is altogether bizarre.
I used to point to their reporting as something that my nation’s newspapers should seek to emulate.
(My nation’s newspapers have since fallen even lower.)
Or join an hospital as nurse, but then you are asked to perform surgery as you were a doctor?
There are serious issues outlined in the article.
Or the one about handling disturbing concted with no previous warning and no consueling
How is this not a straight up lie? For this to be true they would have to throw away labeled training data.
It does so indirectly, so it's a true albeit misleading statement.
That's how validation works.
Clearly that does make it hard to measure. I'd think you'd want "equivalent" validation (like changing the SATs every year), though I imagine that's not really a meaningful concept.
This doesn't sound as bad to me as the Facebook moderator job or even a call center job, but it does sound pretty tedious.
That’s sort of what I expect the Guardian’s UK online non-sub readers to make.
Perhaps GlobalLogic should open a subsidiary in the UK?
There are a whole lot of organizations training competent LLMs these days in addition to the big three (OpenAI, Google, Anthropic).
What about Mistral and Moonshot and Qwen and DeepSeek and Meta and Microsoft (Phi) and Hugging Face and Ai2 and MBZUAI? Do they all have their own (potentially outsourced) teams of human labelers?
I always look out for notes about this in model cards and papers but it's pretty rare to see any transparency about how this is done.
Given the number of labs that are competing these days on "open weights" and "transparency" I'd be very interested to read details of how some of them are handling the human side of their model training.
I'm puzzled at how little information I've been able to find.
Time Exclusive: OpenAI Used Kenyan Workers on Less Than $2 Per Hour to Make ChatGPT Less Toxic
https://time.com/6247678/openai-chatgpt-kenya-workers/
Beyond that, I think the reason you haven't heard more about it is that it happens in developing countries, so western media doesn't care much, and also because big AI companies work hard to distance themselves from it. They'll never be the ones directly employing these AI sweatshop works, it's all contracted out.
https://nymag.com/intelligencer/article/ai-artificial-intell...
unwalled: https://archive.ph/Z6t35
Generally seems similar today just on a bigger Scale. And much more focus on coding
Here in the US DataAnnotation seems to be the most marketed company offering these jobs
To counter your question, what makes you think that's not the case? Do you think Mistral/Moonshot/Qwen/etc. are all employing their own data labelers? Why would you expect this kind of transparency from for-profit bodies that are evaluated in the billions?
"what makes you think that's not the case?"
I genuinely do not have enough information to form an opinion one way or the other.
Sure, but the way you're formulating the question is already casting an opinion. Besides, no one could even attempt to answer your questions without falling into the trap of true diligence... one question just asks how all (with emphasis!) LLMs are trained:
> Are all of the LLMs trained using human labor that is sometimes exposed to extreme content?
Who in the world would even be in such a position?
https://www.theverge.com/features/23764584/ai-artificial-int...
it explores the world of outsourced labeling work. Unfortunately hard numbers on the number of people involved are hard to come by because as the article notes:
"This tangled supply chain is deliberately hard to map. According to people in the industry, the companies buying the data demand strict confidentiality. (This is the reason Scale cited to explain why Remotasks has a different name.) Annotation reveals too much about the systems being developed, and the huge number of workers required makes leaks difficult to prevent. Annotators are warned repeatedly not to tell anyone about their jobs, not even their friends and co-workers, but corporate aliases, project code names, and, crucially, the extreme division of labor ensure they don’t have enough information about them to talk even if they wanted to. (Most workers requested pseudonyms for fear of being booted from the platforms.) Consequently, there are no granular estimates of the number of people who work in annotation, but it is a lot, and it is growing. A recent Google Research paper gave an order-of-magnitude figure of “millions” with the potential to become “billions.” "
I too would love to know more about how much human effort is going into labeling and feedback for each of these models, it would be interesting to know.
Is it possible in 2025 to train a useful LLM without hiring thousands of labelers? Maybe through application of open datasets (themselves based on human labor) that did not exist two years ago?
https://finance.yahoo.com/news/surge-ai-quietly-hit-1b-15005...
Their continued revenue growth is at least one datapoint to suggest that the number of people working in this field (or at least the amount of money spent on this field) is not decreasing.
Also see the really helpful comment above from cjbarber, there's quite a lot of companies providing these services to foundation model companies. Another datapoint to suggest the number of people working providing labeling / feedback is definitely not decreasing and is more likely increasing. Hard numbers / increased transparency would be nice but I suspect will be hard to find.
Is it just to dodge labor laws?
The business process outsourcing companies labelling things for AI training are often the same outsourcing companies providing moderation services to facebook and other social media companies.
I need 100k images labelled by the type of flower shown, for my flower-identifying AI, so I contract a business that does that sort of thing.
Facebook need 100k flagged images labelled by is-it-an-isis-beheading-video to keep on top of human reviews for their moderation queues. They contract with the same business.
The outsourcing company rotates workers between tasks, so nobody has to be on isis beheading videos for a whole shift.
Is that an assumption on your side, a claim made by the business, a documented process or something entirely different?
There are some open-weights NSFW detectors [1] but even if your detector is 99.9% accurate, you still need an appeals/review mechanism. And someone's got to look at the appeals.
A lot of these suppliers provide on-demand workers - if you need 40 man-hours of work on a one-off task, they can put 8 people on it and get you results within 5 hours.
On the other hand, if you want the same workers every time, it can be arranged. If you want a fixed number of workers on an agreed-upon shift pattern, they can do that too.
Even when there is a rotation, the most undesirable tasks often pay a few bucks extra per hour, so I wouldn't be surprised if there were some people who opted to stay on the worst jobs for a full shift.
Even if you can afford only a couple of people a month and it takes 5x as long, do it. It's much eaiser to deal with high quality data than to firefight large quantities of slop. Your annotators will get faster and more accurate over time. And don't underestimate the time it takes to review thousands of labels. Even if you get results l in 5 hours, someone has to check if it's any good. You might find that your bottleneck is the review process. Most shops can implement a QA layer for you, but not requesting it upfront is a trap for young players.
Even theoretically.
In that case, how is the notion of truthiness (what the model accepts as right or wrong) affected during this stage , that is affected by human beings vs. it being sealed into the basic model itself, that is truthiness being deduced by the method / part of its world model.
Congratulations, you just described most jobs. And many backbreaking laborers make about the same or less, even in the U.S., not to mention the rest of the world.
These types of articles always have an elitist view of the workers hired. That's a big source of the right (in the US) despising the left. The left don't say it directly, but when they talk about how shitty their town is and how the job they have is exploitative, there's an implicit judgment on the persons who live/work there.
Personally I would love to live in a more rural place, but until I am self sufficient enough, this is not an opportunity I am willing to take.
If you don't want people to ask, don't mention it.
How do I join?
For reference, the median hourly wage is $27/hour.
Honest question: of course, everybody would prefer to work with "lovely" stuff, but I really have difficulties getting what people find so much difficult/hard about jobs where you encounter such content on a screen (the same holds for moderation jobs).
I would claim that I have seen the internet, and I guess many people of my generation have, too (just to be insanely clear: of course not the kind stuff that is hardcore criminal in basically all jurisdictions worldwide - I don't want to get more explicit here).
I wouldn't say I am blunted, but I do think I could handle this stuff without any serious problems as part of my job. I'd thus rather compare it in terms of emotional comfort with a toilet cleaner who sometimes also has to clean very filthy toilets - which is just an ordinary job that some people in society have to do.
Many experts are holding out, and I don't blame them. Why would you want to train AI to replace your job?
Only training the experts should be doing is the ones that is self-hosted or through community of people one trust! Currently none of the big corp qualifies, not sure if the structure of big corp (that it is a person-hood) is capable of creating anything beneficial in the long run.
Why should the big companies benefit from your expertise to build centralize their control?
It has never been a successful strategy to try and fight new technology. Never.
Also im seeing the same trend as you at my company, roles replaced overseas while people only focus on AI taking the jobs i think this is the more sinister thing happening quietly (by that i mean not getting much news coverage)
I’m in-progress on all of this but I’m offering my services to my current employer though my LLC for 20 hours a week at 3X the hourly rate of my old salary. Take it or leave it. They are losing their leverage for me with his move. I no longer need them, they can’t put me in the streets.
So not entirely leaving the industry but will take any work at or above the market rate. High rates mean less waste of my time, as it is more limited with starting a 2nd career.
For doing both, there’s no abusive overtime like in software because it’s double time pay. Which puts you at the pay rate of what would be $240,000 a year. No one wastes your time at that rate. You actually want overtime when it’s fairly compensated like that. You can do both.
It’s sad when you work towards something your entire life, both in school and professionally. And you’ve never done anything wrong. We played by the rules of our society, and our lives were stolen from us. As Steve Bannon famously said once, these American workers deserve reparations. If the situation is ever corrected, I don’t think it would be too hard to jump back in at that point full-time.
Lots of people would do anything to get such work.
Unfortunately, I decided to take software engineering more serious and try to make it my career and then the entire market nosedived, with no signs of recovering anytime soon. Breaking into this market has more or less been impossible for a junior, and dare I say: a junior in their mid 30s. At least within this job I do get to work with code every so often, and I get to do it from home while I'm at it which is a bonus.
It's inconsistent so I'm still learning and looking for software, but for the meantime it's been incredible.
> “At first they told [me]: ‘Don’t worry about time – it’s quality versus quantity,’” she said.
> But before long, she was pulled up for taking too much time to complete her tasks. “I was trying to get things right and really understand and learn it, [but] was getting hounded by leaders [asking], ‘Why aren’t you getting this done? You’ve been working on this for an hour.’”
And:
> Dinika said he’s seen this pattern time and again where safety is only prioritized until it slows the race for market dominance. Human workers are often left to clean up the mess after a half-finished system is released. “Speed eclipses ethics,” he said. “The AI safety promise collapses the moment safety threatens profit.”
Finally:
> One work day, her task was to enter details on chemotherapy options for bladder cancer, which haunted her because she wasn’t an expert on the subject.
Great to see that they have not learned from this experience, and are repeating the mistake with Gemini.
This reminds me of the early voice-to-text start ups in the 00's that had these miraculous demos that required people in call centers to type it all up and pretend it was machine.
RLHF providers:
1. Surge. $1b+ revenue bootstrapped. DataAnnotation is the worker-side (you might've seen their ads), also TaskUp and Gethybrid.
2. Scale. The most well known. Remotasks and Outlier are the worker-side
3. Invisible. Started as a kind of managed VA service.
4. Mercor. Started mostly as a way to hire remote devs I think.
5. Handshake AI. Handshake is a college hiring network. This is a spinout
6. Pareto
7. Prolific
8. Toloka
9. Turing
10. Sepal AI. The team is ex-Turing
11. Datacurve. Coding data.
12. Snorkel. Started as a software platform for data labeling. Offers some data as a service now.
13. Micro1. Also started as a way to hire remote contractor devs
Are there companies that focus on labeling of inputs rather than RLHF of outputs?
Any technology that creates "sysiphian" tasks, is not worth anyones time. That includes LLMs, and "Big Data". The "herculean effort" that never ends is the proof in the pudding. The tech doesnt work.
Its like using machine learning for self driving instead of having an actual working algorythm. Your bust.
kerblang•4mo ago
jkkola•4mo ago
[0] https://youtu.be/0bF_AQvHs1M?si=rpMG2CY3TxnG3EYQ
thepryz•4mo ago
This was one of the first links I found re: Scale’s labor practices https://techcrunch.com/2025/01/22/scale-ai-is-facing-a-third...
Here’s another: https://relationaldemocracy.medium.com/an-authoritarian-work...
lawgimenez•4mo ago
benreesman•4mo ago
But the next paradigm breakthrough is hard to forecast, and the current paradigm's asymptote is just as hard to predict, so it's +EV to say "tomorrow" and "forever".
When the second becomes clear before the first, you turk and expert label like it's 1988 and pray that the next paradigm breakthrough is soon, you bridge the gap with expert labeling and compute until it works or you run out of money and the DoD guy stops taking your calls. AI Winter is cold.
And just like Game of Thrones, no I mean no one, not Altman, not Amodei, not Allah Most Blessed knows when the seasons in A Song of Math and Grift will change.
jhbadger•4mo ago
maltelandwehr•4mo ago
My understanding is they performed work and were paid for it at market rate. So just regular capitalism. Or was there more to it?
jhbadger•4mo ago
intended•4mo ago
Global south nations do not have the same level of Judicial recourse, work safety norms, and health infrastructure as does, say, America. So people doing labelling work who then go ahead and kill themselves after getting PTSD, are just costs of doing business.
This can be put under many labels, to transfer the objectionable portion to some other entity or ideology - in your case "capitalism".
That doesn't mean it is actually capitalism. In this case it's exploitating gaps in global legal infrastructure.
I used to bash capitalism happily, but its becoming a white whale, and catch all. We don't even have capitalism anywhere, since you can get far too many definitions for that term today.