this story takes place behind the scenes of those businesses who are working to invent our future with. for now, it's hardly this wonderful world where machines are working entirely for mankind. in fact, you could say is exactly the opposite. humans are involved in every step of the process when you're using anything online. but we're sold as this miracle of automation. google, facebook, amazon, goober, these digital giants are using a completely invisible workforce to keep their applications running with technology to actually find them, pay them a tiny amount of money. um and then get rid of them when you don't need them anymore. a workforce that is disposable and underpaid. on a very good day. i could do $5.00 now. at

a really bad day. i could do $0.10 now. i mean it, is it possible for you to be less than the american minimum wage? i'm not sure. i want to go in this direction in both millions of men and women are training artificial intelligence for next to nothing others are being hired and hidden out of sight to clean up social networks. you must have been told by rick listen, seeing that you cannot mention that you are working for this like okay, we went under cover as one of these web cleaners working as a content moderator for facebook and those a few things that i saw, those things organized there with me because i remember them as it was yesterday to meet the workers hiding behind your screen. we're taking you to the factory of the future. that digital economy's best kept secret. ah, you know, it's just like

a sausage factory. they don't want people to come in to see how this often does need. i mean, i think it's just that mm. to delve into the mysteries of artificial intelligence. we're heading to the west coast of the us here in san francisco and the silicon valley, the world of tomorrow is being developed. it's the high tech hub of giants, like apple, facebook, youtube, hubert, netflix, and google. we have a meeting of figure 8, a business, specializing in artificial intelligence that primarily works with google, the founder lucas

b wald. agreed to spend the morning with us. hello. hello guys. nice to meet you. thank you very much for your time, chris. i know you have a busy schedule. thank you. at 38 years old, this stanford graduate has already worked for the likes of microsoft and yahoo before founding his own company. once his microphone is on a quick tour of their startup style, california and office base does our, our best gust and play with cool and relaxed booth, probably or worse dressed in play with the play maybe isn't. i think i'm pretty good. i don't know. very kind of our area is actually where i like to work my coffee got cold with and in the reception area,

an impressive display. these are some of our some of our customers. oh and the, the different things that they did with our, our products. here's twitter. we help them remove a lot of people that were kind of bullying on their website. you know, american express is that in france. yeah. you know, i feel especially proud of, you know, something like tesco right is able to, to use us to improve their, um and website to show better search results. so people can find the items they're looking for. and i don't see google. oh no, i don't know what do you know how like, why some of these get up so we frankly need to stop a this is mr. brown had a p r o. after our visit, the founder explains the enigmatic name. figure 8. we call

a company figure it because we think of it as a loop. and the loop really has these, these 2 parts, right? there's the humans that do the labeling and then the machine learning that learns from the humans. and then it goes back to the humans for more labeling, right? so we think of this kind of like beautiful loop, right? where humans do the best things that humans can do. and the algorithms, the artificial intelligence does the best things that the algorithms can do. and we put that together, and that's what we call it re. ah huh . to get a better understanding of why a, i need humans to function. we stopped joking around and get out the computer. so here's an example. you know, a lot of people these days are trying to build cars that automatically drive. like, for example, tesla has a system where you can drive around in a car. but of course,

it's incredibly important that these cars don't run into pedestrians. so the car camera just see something like this. so it's really important that they build reliable systems that can identify people. and the way that they learned, identify people is looking at lots of pictures of what the cars seeing from the camera. and then an actually literally labeling where the people are. so here's a real example of how it works. if you wanted teach a self driving car to recognize a pedestrian, a human like you are i, it 1st has to identify pedestrians from photo and then feed this information to the ai. and this process has to be done over a 1000, even a 1000000 times over, which can be very time consuming. this is where figure 8 gets involved using real people who are paid to do this work

. so the task here is to look at this picture. and, and label where the people are. and so you get paid for this, you get paid to draw boxes around the people. how much. oh yeah, i'm not sure this task um, but you know, maybe would be like um maybe $0.10 per person that you draw box around. who do this job? i have employees doing this jobs and labeling people. yes. it's contractors on our in our network. that log in and did these jobs, what do you mean by contractors on, on your network? what kind of people? so it's like people that log in to this and then and, and want to work on these tasks. how many people work for figure 8. in this capacity is as labor's yeah. so again, it's, people can kind of come and go if they want to. so there's maybe around 100000 people that kind of consistently work every day for, you know,

for certain is cases that we have. but then there's also millions of people that log in from time to time and work on tasks. and where do those people live? they live all over the world actually. so they live all over america, and then they live all over the world. ah, so who are these millions of people who are being paid to train a i technology in order to meet these contractors as figure a caused them. we leave silicon valley and had 500 miles north of san francisco in oregon. there we are. ha success. jared mansfield signed up to figure 83 years ago. he now spent several hours

a week working for them. every day the company offers a list of tasks that he can complete for money. for example, training search engines long for this 1st one is showing examples of how to do it. the query is matt and cheese progress and the 2 results are any is homegrown organic mac and cheese and handy is really should or microwave will macaroni and cheese, which are neither of them approaches. so it's saying that won't be equally bad matches. what's the use of doing that? a lot of it, i think it is to train search, search algorithms. so like when someone said that a computer and types of products, the algorithm will be able to determine with more accuracy, what product it is that that person's looking for. for every 10 answers,

jared earns less than one cent. to get an idea of how much money he can make, we leave him to work for 30 minutes. he's answered 180 questions over the course of half an hour. how much in the earned $0.15 for how long a half hour. which would be 30 cents the hour. yeah. which are pretty definitely not level a livable wage. that's for sure. so they have are their i to do this. i mean, they have right to do whatever they want. i'm the one coming to them for a little tiny bits of, of coins on this website. and it's no we, there's no contract between me and them. no contract, no salary, no guaranteed minimum wage. these ghost workers are paid to train software and robot using only one rule supply and demand

with it definitely feels like i'm part of this invisible workforce. that is kind of made up of just random people throughout the world. and together, we're kind of training what's going to replace the workforce as a whole. eventually, here it is very philosophical about the idea. still he can afford to be to earn a real living. he has another job showing chicken in the supermarket for a little more than $1500.00 a month. figure 8 is just what he does on the side to earn a little extra cash. ah, ah

ah. bring you the very latest every out the day. this is all no fun, everyone had home with her. all those driven by dreamers shaped banks are those with theirs sinks. we dare to ask

in a, is this the beginning of the end or the end of the beginning? russian nato are at an impasse. both have presented their visions of pan european security. needless to say, there is no meeting of minds as diplomacy been exhausted. the mediterranean is the world's most over fish. see unsustainable exploitation of its fish, dogs. what's marine biodiversity undergoing threat? a lesson the getting a quote on sure, gustavo says he got our system. i'm not going to put any cookie, careful with tech and want to put our lives despite the promise is to end over fishing by 2020. the situation is changing too slow. well, i'm very disappointed with this is basically

not in public interest. they also do not in the mid interest of the fisheries. the only interest of the fishery lobby on the face of the only one is in danger. the fisherman also at risk of losing all plug in my thought of them before they get to them about that. i'm going to level more thought, i guess it might be real. she's been liberals on viewership lock on screen with after leaving oregon, we decided to take advantage of what we learned in america,

and sign ourselves up to figure 8 to train artificial intelligence. on the sites, welcome page small task or proposed at 12, or 12 sense. we chose this as our 1st task, drawing boxes around objects in images following the instructions. it took us several minutes to draw around 10 objects and earn $0.02 on the list of task. figure 8 also offers evaluations of search engine answers, jared's task of choice. we could also listen to conversations and confirm if the recording features a man or a woman's voice. and if they are speaking english. hi is june there please. we work for hours without ever earning more than $0.30 an hour. ah,

it's difficult to imagine that there are people who work on these tasks on a full time basis for in maine on the east coast of the united states, close to the canadian border. we've arranged to meet with one of the nets. ghost workers, the human side of the figure, 8 lou. her name is don carbone. she is 46 years old. oh, hello. oh, much. well, you're welcome. you. well, i yes i oh we had a blizzard. not that long now, and then we have is also a big negative seminar. dawn as a single mother. she lives here with 3 of her children. hey,

this is what subsidized housing looks like up here. i mean, it's not bad for public housing. she lives and works here, working on the figure 8 site all day i'll turn it on. like i said, right before 7 o'clock and get the initial stuff done. i'll, i'll turn it. i'll turn this off at 3 o'clock in the afternoon and then turn it back on at 9 o'clock at night. so i'll say 8 hours minimum. so i bust my like this would be the dashboard. and you can see i've done 6445 tasks since when 3 years see these different badges. now you start off, you have no batch and you have to do so many questions and get so many right. and

then you get your 1st level badge, and then when you get to level 3, you have access to virtually all the tasks that are put up. what is your level level right now? i'm on the 3 f in level 3. have been level 3 for quite a while. don is considered a high performing worker figure 8, therefore offers or more work than a beginner, but it isn't necessarily more interesting. i have to put bonding locks in the room. people not really keen on this town. the biggest problem is trying to find jobs that are viable right now. i don't have many years and it's definitely not better paid on

a very good day. i can do $5.00 now a really bad day. i could do $0.10 now. i mean, i mean i have had some really, really good days until february. yeah. do you think that this is a fair payment for sure. no, no, no, no, not at all. but i live in northern maine. we get a lot of snow it's. there's a very low job market and it helps b as a stay at home mom it, it helps with that. it income yeah. don prefers to work from home because her youngest daughter jane has autism. and don wants to be there to take care of her when she gets home from school at 3

pm. so how escal good their bad day really a good day with her autism. i always have to be ready to jump my car and go get her from school. i mean, it could happen one day or the week, or not at all or 3 days out of the week. and the school is very understandings. i mean, i have to take out the whole week if i was barking out at the home, don receive $750.00 in government aid every month, which isn't enough to cover all of her bills. this is why she signed up to figure 8 by working 8 hours a day and 5 days a week. she says she earns on average $250.00 a month on the site.

on figure 8, the pay is non negotiable. if you refuse the work, there will always be someone else to take it all. there is an unlimited supply of these ghost workers coming from all over the world. it's probably why lucas b walter is so happy. but he isn't the only one to take advantage of this phenomenon. various other businesses propose these sorts of repetitive and underpaid online tasks, the biggest amongst them being click worker and amazon mechanical turk, a platform provided by amazon at its boss, jeff bezos, who invented the concept in 2005. think of it is micro work. micro working is a growing concerned for the i l. o. lee international labor organization, a u. m. agency in charge of protecting worker's rights across the globe.

hello, john. this is john jeanine berg as the resident expert on this subject at the ilo, who speaks to us through skype. with globalization, you could see emerges and kind of a global labor force. here is the next step is really does the service industry backing break up work into kind of very short to 16 tasks oh dangled issue to workers all over the world to compete for the job. do the job and the price of the wages are very down because it is globally respite, and the technology has, has this to retain. se, better the other, the main advantage. jenny edburg wrote a report calculating that micro workers earn on average $3.31 an hour without any rights and return workers. extreme vulnerability is the key to lucas

b walls business model. after months of investigations, we found this video from 2010 that sums up his view of the labor force before the internet. it'll be really difficult to find someone sit down for 10 minutes and get them to work for you and then fire them after the 10 minutes. but when technology can actually find them, pay them the tiny amount of money, and then get rid of them when you don't need them anymore. well, we were interviewing him. we wanted to ask him if he still shared the same opinion . but when we start talking about work conditions, the figure 8 founder seemed to lose his sense of humor. do you have an idea that i will revenue per hour of your contributor? you know, i'm not sure it's totally dependent on the task that someone puts in. and it's hard

to track time on the internet because people can walk away from their computer and come back. so i don't know how much people doesn't really make. there was a report on i know seeing that on average the people working on crowdsourcing were bait 3.331 dollars an hour. would that be consistent with what you pay? i'm not sure. is it possible for you to pay less than the american minimum wage? it can be possible. so this is legal and i'm not sure i want to go in this direction. yeah. i think it's a different direction and i rather this little more hey i then yeah, but this is the whole thing. i mean this is about crowdsourcing as well. so i have to ask questions on crowdsourcing. oh, because it was more, i guess i have them for more than a i conversation than across the season. now i don't know. i didn't

i don't really wanna do. um. yeah, we can find someone else to other stuff. okay. so is not comfortable with with this part of the ah, noth gosh. now if you're a it is an important part of the conversation. things as it is not b a i can't say ah, we don't have time to pull up the video. lucas be wald. makes a hasty exit without saying goodbye and leaves us alone with his head a p. r. one last chance to ask how the business treats these contractors as they call them here i was when i was working on this, i found many people complaining being disconnected as an effort. i actually have to go now to suits 11 o'clock. okay. oh, so you don't want to to speak about human internet. that's that. i think we're

done so only artificial intelligence, no human. well that's what we're prepared for, so. sorry. okay, it's a pity to get some answers to our questions about lucas b. walt and his views on his workers. we thought we'd try a different tact. oh, a. on the day, the figure 8 founder made his statement on disposable workers. there were other entrepreneurs marked him as well as a researcher. the late iranian, just on the right, ah, 10 years after the conference, we find lily living south of los angeles, california. ah, really, you ronnie teaches at the university of san diego and one of her special subjects

is the working culture of high tech business. ah, we're lucky, she has a good memory to number. if somebody reacted after this sentence, which is very brutal in a certain way to be honest, i the reaction was nothing. i remember that panel. every one went up to him to talk to him, and 2 or 3 people came out to me to talk about the ethics of this form of labor. this is a room full of highly educated people in san francisco, and nobody batted an eyelash. how to extend that you know, the kinds of people who have access to these spaces are the kinds of people who never worked in a situation where they wondered if they could make rents or they never worked in a situation where, you know, somebody gets sick and they can't pay someone to go take care of them. so they have to kind of take a really bad job at home. and they,

they have no connection to the kinds of situations of the people that are willing to do this work is what happens when you go to schools like stanford and harvard and princeton. that tell you, you're the smartest person and you're going to be a future leader. and you've been chosen because you're special and that you have the power to change the world. ah, marks of software is not going to end. and the transformation of all industry is with us, whether people like it or not. the last industry in the world to be transformed by software was money and big coin rolled into town. and now money's been distance mediated or disrupted by this software. this protocol called bitcoin and of course, bankers hate at central bank or say it but less thought back. within 10 years,

all major central banks will be gone and we're going to be in a post central bank with a directly resell advertised as content to us. and decide who sees what content when and how much of it facebook claims that these algorithms are there to learn about our specific preferences. actually, this is untrue from their shaping preference. if tomorrow a person finds a fake point, it's the same, the flat, then this content ranks. huh. little. at least 20 percent or maybe even 40 percent or 30. that is true. but it's a very dangerous thing. a

with a 5 hour meeting between president futon and micron comes to a close with the 2 liters focusing on new ways to find stability in europe. a russian official brands, a u. s. claim that it is 70 percent ready to invade ukraine. as american propaganda stressing it is based on unnamed officials disco undisclosed sources and no evidence. it is the latest in a series of accusations, alleged russian aggression being hurled on a daily basis. and others, candidate capital declares a state of emergency, claiming it is under siege from protesters frustrated with coven vaccine mandates, auto police have.