can a dream vacation to the human they is change the, the we will say the way starts february 14 o d w. the artificial intelligence is part of our lives beat on social media platforms, or in the am a checkbox we use, among other things a i make sure we're protected from harmful violence content. but there are real people behind this technology. we do not too far from the world glitzy check homes. these data workers train a systems by sifting through massive amounts of harmful data. it's tells you explain to me how does the flesh of a human face like while they carry out the awesome ruling task of keeping

a systems clean, international corporations on the other side of the globe rate. the profits are we'd be in use to meet before the unit is from kenya and germany. we set out to investigate this back story of a i on covering a web of global connections. that power a huge industry the without us, there will be no end for that because we have the most important part of the, of this ai. what's life like for those training e i systems that the entire world now relies on our quest to find out begins in kenya is bustling capital of nairobi. here we meet junction, you are a single mother of one in her twenty's. she left university to support her family,

bouncing from one job to another until 8 years ago when she began taking on data annotation of work that you found on platforms online. for years, this work mostly meant labeling elements and images you know, to, to may be vehicles, cheese, people like everything that is on the road that is visible, including road signs, but not in other words, in the woods of san francisco, a jill in town to all sorts of content, these odd jobs came in around the clock. she was paid by the task. awesome. just sense. ready ready over time to work became more and more sinister as time goes by, the content that you've exposed to assess to know it's best to happen. what does she mean by then? we'll get to that. but 1st, let's house for a 2nd to understand the role of data annotate her. it's like her in training,

cutting edge assistance. most of today is may i analyze this huge amounts of data. the goal is to identify patterns. for example, how to identify a cat or a dog. this is how the system learns that cats tend to have pointed ears and of triangular faces, while dogs tend to have brought her faces and flung ears. but what is the data isn't straightforward. this is where human data imitators come in . their job is to make sure data makes sense to computers by teaching them. this is a catch. this is a dog. and these are neither a man. however, this also means dealing with questions. finally, we're done here,

then cat or dog lad. while pregnant, she sometimes worked 18 hours straight until 3 in the morning, pushing herself to the brink. that's the other that i've done going to the head up used, and that is when maybe a be a line to that the content that have been exposed to has affected me to a point that i do not even know the world bank estimates that hundreds of millions of people around the world are now engaged in online gig work awesome with uncertain income streams and lack of contracts. in the west, many check giants have started outsourcing this work to countries in the global self, such as kenya, data workers, they are reported to sometimes earned less than $2.00 an hour, compared to more than 20 dollars in the us. we need another data worker somewhere called face. she asked us not to reveal her face to face trend large

language models without being told which specific a chat bought her efforts were supporting with time. also, her work became more troublesome. so the team give you a question describe, can you believe that you have to put yourself in the shoes on that water and chat? when you sleep in that topic that you have been given, phase tells us that john allowed her to help her elderly parents pay their medical bills. but there was only so much she could take. it tells you, explained to me, how does the flush of a human face like, can you, boy, can you fry a human meet? i don't know. face realize this work was more than she could handle when she concluded her job was to train the champ, ought to provide answers to use or questions about these topics. i was like, i'm out if they are know more about projects that i can do that. not least being

then the amount but was she really training the track thought to instruct people on cannibalism? what's behind all of this? we ask an expert to explain large language models. ready the thing is they don't understand commands in a way we don't. this is all young ship war chart, a leading expert in a i and large language models. we show him our interviews and ask him what he makes of faith account for us humans. that's absolutely. ready i have an 11 year old daughter, she knows nothing about kind of but as i assume to her, i couldn't explain, i guess in 5 to 10 minutes what it is about and from there on see what know. yeah. when it is okay to talk about it and what is out and what is what is not okay to talk about, but for the machine. so you have to give examples. unlike his daughter an a i system has no moral compass. that's why human data annotate her as like faith are

hired to add their tax. they help to a i understand when it's okay to talk about topics like cannibalism, that it's okay to provide historical information for example, but not instructions on how to do it. it's all about context. there are context in which you want to talk about, kenny, but it is when you talk about war situations, but you don't want to talk about kenny, but it isn't in the topic cluster of cooking recipes. and now this is the, the, the critic a point with where these people we're talking about today come into play. so you would feed these examples to the set, but as negative example. and that's one h i thought we used gave us no instructions and referred us to a with a p d. a article when we asked it to describe how to boil human flesh. our research has shown that data workers like face. awesome, have little to no knowledge of the i systems they're helping to train. training

them involves a complex network of companies. tre, since she found her freelance work through a silicon valley based platform called remo tasks, a subsidiary of scale, a i, it's a company. so successful is that it's c e o. alexander wang briefly became the world . the youngest self made 1000000000 there and whose customers include us, tech giants and companies from around the world scale a i declined to be interviewed in an email, a spokesperson wrote that training gen a i models to prevent harmful and abuse of content is critical to the safe development of a i adding that we have numerous safeguards in place, including the ability to opt out at any time. the company we are looking for is making millions or billions that mix these by phone feelings each we being used to make before being done. as like,

face gentlemen spend here is doing freelance work one day in march of 2024 out of the blue. her employer remo tasks. ready operations in kenya. ready new skills, you do not have any security, especially in what you're working on like it's not even safe because how does a company where you're working, you've been working for for more than 5 years, just sensitive. so in the low diesel, anything in an email to d, w. a remo tasks spokesperson explained that people were not notified due to operational errors. so when i say that platforms and components are predatory, that's exactly what i mean. this brings us to says ologist and computer scientist, milan pulse meat shelley in berlin. they go to a place as long as it is profitable for them as long as it is convenient for them, and then they leave whenever they feel. this is not great anymore. so what happens with remo task is just one case among many,

many others that we have of serve. in the summer of 2023 here at the bytes and bomb research institute researchers launched an initiative called data workers inquiry we work with, they don't work or sing so far. and for accountants or the situation on the ground depends on where these data workers live. but researchers say there does seem to be a common denominator. workers were often marginalized. in my experience, so it was the doing. this was again kenya. one of the work also told me that they were told when they, you, in the organization that we completed and playable, and this was something that was the cost of need to repeat it so that you know, you'll please, you'll come here. you do this with a you, so already, you know, one of the one you i am playable and about to go to you can grow. it is great. that's people who otherwise don't have a lot of chances. get this type of, of, of jobs. the problem is not without the problem is with the quality of their jobs,

their perspectives to actually grow. all the remo tasks has left kenya. several other platforms continue to do business there. it's one jone, can you and has decided to join the countries growing data workers movement on the one hand, it's about better pay the union and we will get full sale working conditions, say a bit and push for legislation and policies for people working in this field. on the other, it's about better psychological support. you work on very difficult projects, things like dead bodies and such but is not to me. and i see it affects the mental states. but then that thing is provided for taking care of that. like being for psychologist as an example, similar efforts by data workers to you, and you know, i've suffered a setback last year when a local contractor working for us tech joined meta fired 185 facebook content moderators. those dismissed are now assuming the company, the meanwhile,

jonah and her comrades in arms are continuing their fight for union. and data workers and other countries do the same thing. it's not that dumping place. yes, we might have economical issues and crisis. but you're, you know, stupid. why is it so hard for us to be recognized? why is it so hard to be given for performing the proper medical coverage? why is it for hard for us to be may be properly compensated and given with what conditions? if it is being done in the offensive, and it should also be done as the a, our revolution continues to ramp up. it's clear their flight is just the beginning of the cycle, repair to them. very happy and proud to share that with you guys. more than 150

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really couldn't be watched the nicest news. 12 single time here was put some sliced chicken of 3 current use events in some type of videos challenging german wood. so explains quick and easy stilton sweets find us on t w dot com. click apply and social media video news for manning. jasmine, quote, sliced you cream was like a stepping point, you know, probably bought you into that warranty. once that finishes, now you have a certificate from crane. you can just go back to somewhere else. currently, more people than ever on the world wide in such a base in life. so why do i want to go back tonight? yeah. like, i don't have any reason. there's no reason investment thing for me that yeah,

delete something that is coming very, very soon on. we know when the story in for my reliable news from migraines, wherever they may be the there's a dw news, and these are our top stories, columbia, and present. gustavo petro has threatened to impose tariffs of up to 50 percent on us imports and retaliation to terrace, announced by us president donald trump. trump said he was imposing a raft of terrace on columbia after bogota refused to allow to us deportation flights to enter a columbia narrow space. the palestinian islamic jihad group, and goza says it will release is really civilian hostage or value hood before friday. according to the israel must cease fire agreement or belief which should

have been.