we dare to ask in oh, right now, there are 2000000000 people who are overweight or obese. if possible, to sell food that he's fancy and sugary and faulty and addicted not at the individual level. it's not individual willpower. and if we go on believing that will never change as obesity epidemic, that industry has been influencing very deeply. the medical and scientific establishment, ah, what's driving the every city ever them it, it's corporate. me. ah,

you don't wake up. it's 2027. new 20 is every new, the new one. never in 2027. sarah takes care of everything for the pigeon, just because you will get that. daniel dunny, somebody when this was sarah is a virtual assistant. who knows exactly what's best for you was about to describe the image in the people that we had for children with just wanted to swap edition together. everywhere you go. artificial intelligence like sarah predicts your needs and does the work for you? ah,

i told you to do with all of these machines working for you, isn't life wonderful in 2027, but let's not get carried away before sarah changes your life forever. there's another story to tell one with less special effects i this story takes place behind the scenes of those businesses who are working to invent our future. 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, mover these digital giants are using a completely invisible workforce to keep their applications running with technology, you can actually find them, pay them the tiny amount of money, 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 to do $5.00 now. 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. they clean up social networks. you must have been told by recruiting team that you cannot mention that you are working for this project. we

went under cover is one of these web cleaners working as a content moderator for facebook. so there's a few things that i saw. those things are going to stay with me because i remember them as it was yesterday to meet the workers hiding behind your screen or taking you to the factory of the future. that digital economy's best kept secret. ah, you know, it's like a passage, a factory. they don't want people to come in to see how often did made. i mean, i think it's just that 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. hoover, netflix. in google, the we have a meeting, a 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, good night, you too. thank you very much for your time course. i know you have a busy schedule. no, 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 office space or, or backup and play cool and relaxed

probably or weren't stressed employee in place, maybe i think a pretty good i don't know very kind of our area is actually where i like to work my coffee got cold and in the reception area and impressive display. these are some of our, some of our customers and the different things that they did with our, our product. so 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, i feel especially proud of, you know, something like tesco right is able to,

to use us to improve their website, to show better searches or to people can find the items they're looking for. and i don't know, i don't know. what do you know, how like, why some of these get frankly, just stop in this is mr. brown had a p r ah, after our visit, the founder explains the in the magic knee. figure 8. ah, we color 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 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. ah, to get a better understanding of why i need humans to function. we stop joking around and get out the computer. ah. so here's 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 use something like this. so it's really important that they build reliable systems that can identify people. and the way that they learn to identify people is looking at lots of pictures of what the cars seeing from the camera. and then actually literally labeling where the people are in. here's a real example of how it works. to view what had teach his self driving car to

recognize a pedestrian, a human like you or i at 1st has to identify pedestrians from photos and then feed this information to the a i. 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 a gets involved using real people who are paid to do this work. so the task here is to look at this picture. and then label where the people are. and so you get paid for the, you get paid the draw boxes around the people. how much, you know, i'm not sure this task. but you know, maybe you would be like maybe $0.10 per person that you draw a box around. who do this job? employees doing these jobs and labeling people?

yes. with contractors on our, in our network, the log in and do 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 then want to, to work on these tasks. how many people work for? figure 8 in this capacity as, as laborers. 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 use 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? and they live all over the world actually. so they live all over america and then they live all over the world. so who are these millions of people who are being paid to train a technology in order to meet these

contractors as figure a cause them relieve silicon valley and had 500 miles north of san francisco in oregon. ah, there we are. here at 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 for this 1st one, it's showing examples of how to do it. the query is mac and cheese per rubies. and the 2 results are any home grown organic mac and cheese and n. he's really should or microwave will macaroni and she is,

which are neither of them are produce. so it's saying that want to be equally bad matches. what's the use of doing that? a lot of it, i think, is to train search, search algorithms. so like when someone says the computer and types a product, the algorithm will be able to determine with more accuracy what product is that that person is looking for. for every 10 answers curate earnest, 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 you earned $0.15 for whole half hour. which would be 30 cents t hour. yeah. which are pretty definitely not level

a livable wage. that's for sure. so they have the right 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 way 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 robots using only one rule supply and demand. it definitely feels like, 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 word for the whole. eventually jerrod is very philosophical about the idea. still he can afford to be to earn

a real living. he has another job selling 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, well, no, certainly no borders and a lot to nationalities as emerged. we don't have authority, we don't actually, the whole world needs to take action and be ready, not just people who judge, you know, crisis we can do better, we should be better. everyone is contributing each in their own way. but we also know that this crisis will not go on forever. the challenges to response has been

massive. so many good people are helping us. it makes us feel very proud that we are together in the, 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 tasks are proposed at 12, or 12 since 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 2 sets 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 at the recording features a man or a woman's voice. and if they are speaking english high in june, they're pleased. we worked for hours without ever earning more than $0.30 an hour i. it's difficult to imagine that there are people who work on these task on a full time basis for and main 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 loop. ah, her name is don carbone. she is 46 years old. oh, hello. thank you so much. you're welcome.

yes, we had a blizzard not that long ago, and it's also, i think negative 7 out there done is a single mother. she lives here with 3 of her children. 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 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 and both my like this would be the dashboard. you could see i'm done 6445 tasks since went 3 years. see these different badges. 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 bad. and then now when you get to level 3, you have access to virtually all the tasks that are put up. what is your level level right, right now 3, i've been level 3, have the level 3 for quite a while. don is considered a high performing worker figure 8, therefore offer sure more work than a beginner, but it isn't necessarily more interesting. ah,

i have to put boning locker room people. not really keen on this jones. the biggest problem is trying to find jobs that are viable right now. i don't have many. oh and it's definitely not better paid on a very good day. i could 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 this is a fair payment? was you know? 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 help fee as

a stay at home mom it, it helps with added income. yeah. don prefers to work from home because her youngest daughter jane has autism. what happened? don wants to be there to take care of her when she gets home from school at 3 pm. so i will go good day or bad day. really good there with her autism. i always have to be ready to jump my car and go get it 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 understanding, so i mean, i have to take the home and if i was working out of the home done receive $750.00 in government aid every month,

which isn't enough to cover all over 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, the all on figure 8, the pay is non negotiable. if you refuse the work, there will always be someone else to take it. oh, there is an unlimited supply of these ghost workers coming from all over the world . it's probably why lucas b wall is so happy. but he isn't the only one to take advantage of this phenomenon . who 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, and it's boss jeff bezos who invented the concept in 2005. think of it as micro work. micro working is a growing concern for the i l. o. the international labor organization, a us agency in charge of protecting worker's rights across the globe. hello jim, in jeanine berg because the resident expert on this subject at the low who speaks to us through skype. with globalization, you could see emerging that kind of a global labor force here. it's the next step. it's really the service industry that can break up work into kind of very short cap and then dive all due to, to workers all over the world to compete for the job. do the job. the price of the

wages are down because of this global labor supply and the technology has, has facilitated f t. that's the other the main advantage. jeanine berg wrote a report calculating that micro workers earned on average $3.31 an hour without any rights in 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 him down for 10 minutes and get them to work for you and then fire them out of 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. while 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 humour. do you have an idea of that? i will drive you 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 don't really make. there was a report on, i know saying that on average the people working on crowd sourcing were paid 3.351 dollars an hour. would that be consistent with what you pay? i'm not sure. is it possible for you to be less than the american minimum wage? is it can be possible. so this is legal

i'm not sure i want to go in this direction in case it's a different direction and i rather the folks are more than then. yeah. but this is the whole thing, i mean this is about crowdsourcing as well. so i have to ask questions on crowdsourcing because it's more i just, i have to move in a conversation than a counselor can conversation. no, i don't know. i think we just had, i don't really want to do. yeah. we can find someone else to talk about the stuff. okay. so it's not comfortable with with this question. now. you're right. it is an important part of the conversation, but it's not to be a conversation. we don't have time to pull up the video. lucas, be wild, makes a hasty exit without saying goodbye and leaves us alone with his head and p. r. one last chance to ask how the business treats these contractors as they call them here

. when i was working on this, i found many people complaining being disconnected. and i, and i actually have to go now to suits 11 o'clock. okay, so you don't want to to speak about human in the after that and i think we're the only artificial intelligence knew human. well, that's what we're prepared for. so sorry. ok, it's a bit to get some answers to our questions about lucas b, walt and his views on his workers. we thought we try a different tax on the day, the figure a founder made his statement on disposable workers. there were other entrepreneurs amongst him as well. as a researcher, really eroni just on the right, the

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 specialist subjects is the working culture of high tech business. we're lucky, she has a good memory number. so somebody reacted after this sentence, which is very brutal in a certain way, to be honest. the reaction was nothing. i remember that panel. everyone went up to him to talk to him. and 2 or 3 people came up 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 bad at an eyelash. how do you 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 ranch 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 or, and 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. the 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. the in my phone are 69 months.

jeff are under the dollar a former isis fighters and nel boating a philippine naval ship with $900.00. jeff, aren't abdulla still don't know what's waiting for them. can i get a hold of me

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