I used an expense App that claimed to use AI for its smart scanning and OCR but I always suspected it was using real people as often it would take hours or a day to ‘process’ the scan - and each time it would be a very different length of time for what were very similar scans.

Name one multi billion dollar industry that isn't partly outsourced to foreign workers.

Underpaid? By American standards, absolutely, but not by their local standards. Is it wrong? Yeah, on multiple levels, but it's legal and the cheapest way to get shit done.

Tech is not alone in this, and especially not AI in particular.

Your shoes, pants, shirt, watch, phone, laptop, car, and practically everything in your house has at least components that come from outside your country. Sure, some things are locally sourced and produced, but I guarentee you anything electronic isn't.

[removed]

The biggest tech companies in the world imagine a future where AI will replace a lot of human labor. But this vision ignores the fact that much of what we think of as “AI” is actually powered by tedious, low-paid human labor.

A.I is misused..it’s hoverboards all over again!

Right, some of these firms are paying over 50% above the average wage in the developing world to do simple content moderation.

So same like any other industry or innovation since the dawn of colonialism.

If a factory worker in Africa would cost like the one in New York why would anyone hire the one in Africa?

But is the claim of AI not that it can produce outcomes on its own through some sort of machine learning using different input? If it requires a team people anyway, then what is the point in calling it AI?

What an INANE headline. Ever since the initiation of free trade, this has been true for every singe industry and sector of the economy.

I dunno - if you look at Fiverr its few thousand people competing for a buck. Its appalling.

AI..??? Should have said EV

Yes, and no. Data labeling is a manual human task, yes. It’s tedious and low-paid because anyone can do it sitting at their computer with literally no background training at all. It is literally just labeling objects you see so the computer knows them. It’s also used often by universities and small startups, not just big tech, because that’s just what the future of technology in AI requires. It’s not being hidden or ignored, it’s being acknowledged to the point where you’re literally reading an article about Amazon offering a service for it. This is half an ad.

“Howson can’t say for sure whether tech companies are intentionally obscuring human AI laborers, but that doing so certainly works in their interests.” Cool, get back to me when there’s evidence.

This is not what the article is about. Humans are involved in the data labeling process prior to the deployed AI model, not during or after.

AI does not operate independently of people. That has never been the goal. The goal is to use what we know about intelligence to make new tools that help us take society in a more productive and automated direction. In this case, humans still need to be the ones who train AI to begin with. A developed AI only needs an operator/maintainer.

I used to do some work on mTurk (Amazon) many years ago. At one point I was working on the Kinect project for Microsoft. Training it to recognize heads, shoulders, elbows, hands, hips, knees and feet. I had no idea the what the work was for until after the project was released and I saw the videos of how it’s tracking worked. They paid something like .36c (usd) per frame and there were tens of thousands of images to tag. Each image would have 1-4 shadowy outlines of people in it. I made a quick macro that would click around to give me the basic shape I needed and then all I had to do was line up the all the joints for whatever poses they happened to be in. Guess I was kind of cheap human ai teaching skynet how to track our movements for the future.

Almost everything is being done by the underpaid

[removed]

Fiver is independent people, though. I suppose they could be in some sort of company that farms out work to fiver, but generally it's an individual placing a value on their own work and time. That's like the purest form of free and fair competition.

> but generally it's an individual placing a value on their own work and time.

Hence the name Fiverr - five bucks or less. How they're still in business given the shady practices I have no clue.

"AI" is just a buzzword for machine learning algorithms that take large, large, large data sets and run over then multiple times to create an interactive algorithm based on what it was taught. The people in the article are the ones doing trivial tasks for the data sets, like labeling images so a neural network could learn what a bird is, or something along those lines.

Your comment seems to have not read the article?

ChatGPT is just a dude in India let’s be real

[removed]

MNCs aren't outsourcing content moderation to Fiverr.

I've seen companies like ByteDance, PWC, Deloitte, and Atos paying people about $1,000 - 1,300 a month throughout Southeast Asia when the average salary is only around $500-600 a month.

Doesn’t make it inane. Exporting exploitation is a huge problem and one that I’m sure many, many people don’t associate with AI and machine learning. We know children make Nike shoes in slave factories, many people are unaware of how that same level of exploitation is prevalent in something like software development, something that’s not physically manufactured.

Neo colonialism baby, let's goooo

Eyooo, an article about me

Edit: ok maybe not sadge

Because there aren’t a limitless supply of New York factory workers? Lmfao come on

Yeah with current approaches you need *someone* to categorise and tag whatever training data you're using at some point. Unfortunately most bits of data don't come with convenient pre-categorisations

You are misreading the article yourself slightly. The article says that AI needs labeled data yes and sometimes non AI work like content moderation for objectionable photos is PTSD inducing hard rote work for outsourced workers on a regular basis. If Meta outsources this to a contractor company Sama who then exploits its own local labor force to accomplish the tasks ( not even paying them regular wages), it is no different than Nike employing workers in sweat shops to build shoes or blood cobalt and diamonds.

The article discusses the politics of this. Companies hide the fact that all of these content moderation and labeling occurs by poorly paid and managed workers elsewhere and this would need better contractual oversight than just outsourcing and looking the other way which is the norm today. Your university may employ a bunch of guys on Fiverr to do it is a different issue. So here the problem is just how unethical sourcing and manufacturing is in other domains too and AI is no different. But a consumer today can ask about shoes and sweat shops, it has no clue that AI model data is another Nike shoe.

Interesting.

I think Fiverr was there before Uber and the rest, correct? If that's true, I think they might've influenced gig economy quite a bit, but I never heard anyone tying them with Uber, Lyft etc

It's not exporting exploitation, it's just that US standards are way too high for underdeveloped countries. So much so that your minimum wage would already place someone on the top 10% earners in their respective countries.

Really. We would like to earn more? Sure, who doesn't. But the salaries they offer are already high by our standards, so I'm very thankful. If they can also profit from that, good for them.

No, it’s exporting exploitation. American Industry has had constant “cheap/free” labor supply issues since the abolition of slavery and through the years have always been seeking a replacement in that loss of profit. This is why we moved to Chinese Labor (railroads), Child Labor (factories), Female Labor (pay gap), etc. Now our solution is to export that exploitation to the 3rd world where most Americans don’t see it day-to-day and therefore don’t have an emotional connection to it enough to protest against it like we did for civil rights, and workers rights, and child labor rights, and women’s rights. This is a problem America has been fighting since the late 1800’s.

In other words, another case of the same shit, people are exploited literally everywhere in every form of industry. That is literally what today's corporations are based on, save as much on the people at the bottom so the CEO can get 50 mil yearly bonus and a new Ferrari on top.

Listen, the labor is cheap by your standards. It's definitely good enough for us. And those children end up in factories not because companies want to profit more with cheap labor, after all they're not nearly as smart or strong as adults and they get involved in more accidents. The reason there were children in factories was that their parents' income was not enough. Also pay gap? Really? Debunked at every turn and people still have the gall to use that argument.

Companies exporting labor is a direct consequence of the cost of labor laws. There comes a point where it just becomes a lot cheaper to bring the whole production chain to another country and ship the result back home. That is not by any stretch detrimental to said country, in fact it's quite the opposite. It is only indirectly detrimental to US workers, who will find it harder to find jobs. Then comes the government to apply tax on the shipping to try and make the outsourcing more expensive, and thus encourage companies to stay in the US. This is called protectionism. This is a bad thing because it artificially inflates prices in trade for saving US job positions.

mmm, skynet. AI will be powered by 3rd world Dickensian programmers...it is poetic.

[deleted]

Those workers are now making themselves obsolete in future.

Hopefully someday you learn to view all humans as equal people and not fodder for the consumerist capitalistic machine… If you think the wage gap through all of American history is “debunked at every turn,” you are grossly misinformed and I implore you to actually research the history of women’s pay in the American workforce.

I have. I know for a fact that it is a gross manipulation of the facts. The research authors just blindly gathers all women and all men and see that there is a difference in income, while completely ignoring underlying factors like job areas, occupational risks, hours worked, willingness to move, willingness to humor unreasonable requests, life priorities, etc. And this is true even in Scandinavian countries, where they supposedly have more equality. But this is already digressing from the original topic of the post. I suggest you take your own advice and do a little search around the topic.

Again, your explanation is a gross oversimplification of a systemic issue that has been an evolving problem for the better part of a century. Do you think secretaries in the ‘60s were adequately compensated for their labor when compared to equivalent male roles at the time, and if so I would love a single example.

This isn’t really being hidden, consumers just don’t care. The article itself cites authorities saying so.

From Facebook’s public content policy from their own website regarding their use of AI: “Sometimes, a piece of content requires further review and our AI sends it to a human review team to take a closer look. In these cases, review teams make the final decision, and our technology learns and improves from each decision. Over time—after learning from thousands of human decisions—the technology gets better.” They are not hiding the need for human labor behind AI. This is from a source in the article. This is different already than companies using sweatshops they try to hide and disavow knowledge of.

And these outsourcing companies proudly advertise big tech as their clients: https://www.sama.com/Others are using the very popular and frequently used MTurk service for this promoted publicly by Amazon, such that universities are aware of this and use it to advance academia, with these services being described in their methodology. This is all available information that’s being actively marketed.

This article’s headline and much of its content make it sound like a conspiracy specific to AI instead of “by the way, issues with the global labor markets apply to the labor behind AI too.” The transparency or lack thereof isn’t even the problem, because people don’t care. American consumers enjoy cheap products, people in foreign countries consider the American outsourcing better than jobs in their localities (and data labeling and content moderation are significant improvements to physical labor- the article itself cites someone saying as much), and the countries that accept Americans outsourcing their labor benefit politically and economically.

I don’t like exploitation and I think all content moderators should have readily available mental health access, but this is what a global liberal marketplace looks like, and I’m wary of blaming AI and the companies behind it for this instead of examining the economic systems we have that promote these issues. The technology and its needs aren’t the issue. It’s not as if big tech is marketing a camera with a child inside who quickly draws what they see and gives it to you. They need a tough job done cheaply that Americans don’t want to do. Not unlike how that’s a big reason Americans allow immigrants to come in in the first place.

Also worth noting that the author doesn’t actually have experience in technology, but is rather an artist who also writes about AI ethics. I do apply extra scrutiny to what narratives are being painted by that kind of author.

It often works exactly as OP described. “Automated” products will use humans for cognitive tasks up until machines can be trained on their results.

That seems unlikely for a basic OCR task. Doesn’t that come equipped with every smartphone these days anyways? It seems more likely to me that it’s possibly just some poorly designed app that sends images to some remote server for analysis, but has terrible response times or is frequently down for maintenance without notifying OP. We are definitely past the point where humans need to intervene for OCR.

If it was for something important like eg depositing checks, it doesn’t seem odd that they’d have a human verification process

That’s fair, though I imagine their use of AI then is to flag specific images for human verification if there are concerns.

converted call centers

Just because it's publicly available information doesn't mean it isn't undisciplined in nearly every article about new ML models. I think you took the work "hidden" too literally

When drawing a comparison to Nike and other companies with a history of literally hiding their labor abuses, what “hidden” literally means does matter in terms of accountability. There isn’t a point to mentioning what humans are doing to train new ML models in most articles. The data labeling and content moderation angles are not really relevant to what the model’s own impact and application is, and those processes really don’t change. This isn’t new information at all.

Yeah, the name indicates the original languages before it supported English: Gujarati, Punjabi, Tamil.

I completely made this up.

Do those workers overseas have better opportunities? Do they overdrive themselves as being underpaid, and if yes, by what measure?

The one who wrote this article is a Chinese and highly skeptical on AI in every article she writes. What I’d say is, she’s a dog for CCP

AI stands for Aman and Imran…

Isn’t the entire world powered by underpaid workers at this point?

Someone needs to work on that.

Lets also not forget that people are fighring corporations which are given the same rights as people. However corporations never die due to old age and continue to accumulate wealth.

Also by captcha and people training AI for free… or you can always guess the image used to sort data and try to select the wrong one and pass. It’s a fun game.

[removed]

The big thing these days is "self-supervised" learning.

You do the bulk of the training on a simpler task, like predicting missing parts of images or sentences. You don't need labels for this, and it allows the model to learn a lot about the structure of the data. Then you fine-tune the model with a small amount of labeled data for the specific task you want it to do.

Not only does this require far less labeled data, it also lets you reuse the model - you don't have to repeat the first phase of training, just the fine-tuning. You can download pretrained models on huggingface and adapt them to your specific task.

For example, England developed because of India. This isn't new at all.

my attempt to "TLDR" for folks / personal interpretation:

1. Commercialized AI is often powered by low-paid workers in foreign countries who perform tasks such as labeling images and annotating objects in videos.
2. These tasks, which are outsourced to gig workers and data training companies, are important for training AI systems.
3. Many tech companies imagine a future where AI will replace human labor, but the reality is that much of what is considered "AI" is actually powered by human labor.
4. The people performing these tasks often do not have insight into what their work will ultimately be used for.
5. The use of low-paid labor in the development of AI raises ethical questions about the treatment of workers and the accuracy of the data they provide.
6. Amazon's Mechanical Turk platform allows businesses to hire workers to perform tasks for compensation, including training AI projects.
7. Many of these tasks are outsourced to gig workers and data training companies, often in developing countries.
8. Turkopticon, a platform created by workers, aims to address the power imbalance between workers and requesters on Mechanical Turk.
9. Poor working conditions and low pay on gig work platforms like Mechanical Turk can lead to lower quality work for clients.

​

Pros of using low-paid labor to develop AI:

1. Cost savings: Outsourcing tasks to workers in developing countries can be less expensive for companies than hiring in-house workers to perform the same tasks.

2. Access to a large labor pool: Crowdsourcing platforms like Mechanical Turk allow companies to access a large pool of workers from around the world.

3. Efficiency: Using large numbers of workers to label data or perform other tasks can be a quick and efficient way to train AI systems.

Cons of using low-paid labor to develop AI:

1. Ethical concerns: There are concerns about the treatment of workers on crowdsourcing platforms, including low pay, poor working conditions, and lack of job security.

2. Quality of work: Poor working conditions and low pay can lead to lower quality work, which can impact the accuracy of the data being used to train AI systems.

3. Lack of transparency: Workers may not have insight into what their work is being used for, raising questions about accountability and transparency in the development of AI.

There are a few alternatives to using low-paid labor to perform tasks such as data labeling for machine learning operations (industry term for this arduous process):
Automation: One possibility is to develop automated tools that can perform tasks such as data labeling without human intervention. This can be more efficient and cost-effective, but it also has its own limitations and may not be suitable for all types of tasks.

In-house teams: Companies can also choose to hire in-house teams to perform tasks such as data labeling. This can help ensure better working conditions and higher pay for workers, but it may also be more expensive and may require more resources to manage.

Volunteer efforts: Some companies have also turned to volunteer efforts to gather data or perform other tasks. For example, the Zooniverse projectrelies on volunteers to classify and label images and other data for use in scientific research. This can be a cost-effective option, but it may also be less reliable and may not be suitable for all types of tasks.

[removed]

This is a net good though. If companies seek cheap labor, they move their industrial investments to the poorest places. This has resulted in prosperity for places like singapore, taiwan, japan, south korea, china, india, and vietnam, among others.

Yes this is actually what I think happened - they needed more high quality training data and humans were the way to achieve it until the ocr was good enough.

I agree with many of your points, but oftentimes the reason that labor is cheaper in other countries is because they don’t have worker or environmental protections that more developed countries have. This makes the work much more dangerous, worse for the environment and workers. It’s not always black & white.

>There are a few misconceptions in the sentiment you mentioned. First, it is true that most data does not come with convenient pre-categorizations. However, this does not necessarily mean that someone needs to manually categorize and tag the data for it to be used in unsupervised learning.
>
>Unsupervised learning is a type of machine learning where the model is not given any labeled data or supervision. Instead, the model must learn to identify patterns and relationships in the data on its own. This is in contrast to supervised learning, where the model is given labeled data and is trained to predict a specific outcome based on this data.
>
>In unsupervised learning, the model does not need to be told what categories or tags to look for in the data. Instead, it can use techniques like clustering to group similar data points together and identify patterns in the data. This allows the model to discover and learn about the underlying structure of the data without the need for explicit categorization or tagging.
>
>Therefore, while it is often helpful to have some level of human annotation or labeling of data, it is not always necessary in unsupervised learning. The model can still learn and make useful predictions or discoveries even if the data is not explicitly labeled or categorized.

Written for you by an AI powered by unsupervised learning...

That doesn’t make any sense. Plenty of countries developed without colonies. Germany, for example.

I can confirm this as TRUE, I previously worked for a popular voice assistant where I do voice to text transcription. I was paid as low as 1.20$ per hour.

Thank God that they haven’t gotten around to teaching them what a stoplight looks like yet…

Vice is the Debbie Downer of digital news sources. What'd you expect?

If worker supply in NY is running out wages will rise. And if it has to rise the same amount in Africa then still no one will hire them.

Is there anything that’s not built on the shoulders of underpaid foreign workers?