transferred to a 2nd vehicle. ok think on the belt. it's an old who stopped in the police have enlisted the help of international authorities to find the thieves and their precious loot. and that is all. thank you for watching the we say they're about never getting up every weekend on dw, my name is the calls back. say thank you so much for joining in. welcome to don't hold bad. a lot of people do that. it's all about saying it aloud. that's what it being nosy,

they like good everyone to ok. so to be turning into the microphone, sorry. check out the award winning outcome. don't hold back. 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 litzy check homes, these data workers trend 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 reach

the profits 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 heating 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 adults in the woods of san francisco, gillian, talent, all sorts of content. these odd jobs came in around the clock. she was paid by the task awesome. just sense over time, the work became more and more sinister. ready as time goes by, the content that you've exposed yourself to now it's fetched to happen. what does she mean by that? we'll get to that. but 1st, let's house for a 2nd to understand the role of data annotate hers like her in training, cutting edge a systems. most of today's 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 our faces and fluffy years . but what is the data isn't straightforward. this is where human data and the teachers come in. their job is to make sure data makes sense to computers by teaching them. this is a catch, this as 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 day after i'm going to the fed up used, and that is when may be 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 often 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 to the team. give you a question. describe, can you believe that you have to put yourself in the shoes on which ad worked in church? and you said in that topic that you have been given faith chose as to 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 flesh of a human face like, can you, boy, can you phrase 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 and that i can do that. not least being then the amount but was she really training the chance 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. ready in a way, we know this is all young shipboard chart, a leading expert in a i and large language models. we show him our interviews and ask him what he makes a face account for us humans. that's absolutely. 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, and 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 is like phase 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 categories 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 where, where these people we're talking about today come into play. so you would feed these examples to the set, but as negative example. that's one, a champ thought we used gave us no instructions and referred us to a wic, a p, 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 nit because companies say,

says she found her freelance work through a silicon valley base 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 who was customers include us, tech giants and companies from around the world. scale a i declined to be interviewed in an email, a spokes person 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 working for is making millions or billions that mix the special anything we've been used to make before being done. as like face gentlemen spend years doing freelance work one day

in march of 2024 out of the blue, her employer remo tasks seized operations in kenya. ready these jobs 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 exiting. 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 sociology, just and computer scientist, milan calls me chelly 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 rema task is just one case. i'm on many, many other stuff we have of serve. in the summer of 2023 here at the vitamin bomb

research institute researchers launched an initiative called data workers inquiry that we work with data work or things so far and for continents. 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 i was doing this research in 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, you know, in your place, you come here. you do this with the so rates, you know, one of the one you i am playable and about to give it to you to 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. can you several

other platforms continue to do business there? it's one, joan, 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 mentor states within that thing is provided for taking care of that. like being for a 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. 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 this one on the glaciers and crisis, but we are no 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 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 beginning the how do i optimize my brain? research as doctors and trainers are constantly making new discoveries. our most

important oregon is even more powerful than we thought the. and in sports, knowing about neural systems is a key to success. tomorrow today, next on d, w, the football in pushed in on the 1st we are far in cost of the options we didn't noise, kosovo was ready to accept something like this. we took the staff and said, let's try, let's stevens and open the box on tv to open up the home number mod upfold steps. and it's making a successful not only among the clear community, 0930 minutes from dw moving plan in d, w bought. com, how to make greener choices in your everyday lives. but honestly try to do the

working 32 hours a week to be better for the assignments and 40. but of course we shouldn't be 90 the. the living scientists just had subscribe. whatever you listen to had cost or the do you practice a sport regularly, but feel like you're making little progress towards mastery? it might be because your brain is getting in the way. targeted training focused on your green matter can tease out a whole realm of new potential. at least according to sports scientists to study the brain body interface. some top asked lisa, now striving to reach the next level with a new training concept known as neural athletics. welcome to tomorrow. today. this time we'll be learning lots more about the brains and hummingbirds at the various olympic games.