La automatización del trabajo: ¿oportunidad o amenaza?
Cuando pensamos en el conductor del taxi que nos recoge en el aeropuerto o en el recepcionista encargado de hacer el check-in en el hotel, automáticamente atribuimos a estos profesionales determinadas características que consideramos indispensables para el desarrollo de su actividad laboral: amabilidad, eficiencia, servicio… Pero, ¿necesitan ser humanos? Con el actual proceso de automatización del trabajo, quizás ya no.
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00:00Machines are getting better and better.
00:06Today, machines can do things that we thought only humans could do.
00:12When we think about the complexity of the problems that artificial intelligence can solve, there are no limits.
00:20If you have a job that competes with activities that can be done by a machine, it will be very hard to make a living.
00:27Automation is inevitable. The workers will be replaced by machines. Who will benefit from that?
00:34Then there will be a lot of people who will lose their jobs. What do you do with them? How will they be compensated?
00:42Will there be a fairly gradual transition between old and new jobs, or will it be so abrupt that it will be difficult to recover from the impact?
00:58We are in Newburgh, New York, in the Washington Heights neighborhood, more specifically in the Hudson Valley, about an hour and a half from New York.
01:08It once had a thriving industrial city. Now there are a lot of empty buildings and a lot of poor and unemployed people.
01:16The population used to be bigger, the buildings were more full, the factories were full, and now you can see the state that everything is in.
01:26The state of deterioration in which it is.
01:36Throughout Newburgh there were buildings like this, which were boxes, bags, small factories that supplied the city of jobs that have now disappeared.
01:47People in this city had emigrated from the south to get jobs, but when they arrived, the jobs began to disappear.
02:00Some factories were moved to China or Mexico because they could produce cheaper. Also to other states in the United States, jobs disappeared overnight.
02:17Not so long ago, before globalization and externalization were established, there were thousands of people working in Newburgh.
02:27Today, most of those jobs have been volatile.
02:32And Newburgh is far from being an exception.
02:36Since the end of the last century, the same fate has fallen on all the small or large cities in the Western world.
02:43Millions of jobs in the industrial sector have emigrated to countries in Eastern Europe or Asia where wages are lower.
02:55However, on the other side of the Hudson River, not far from Newburgh, something even more devastating could be happening for the future of employment.
03:14This is Baxter, and he works in the factory.
03:17This particular robot has been working for about 8,000 hours without giving any problems.
03:24The trick is in the integration.
03:26Baxter has to communicate with another packaging robot, with the molding machine, the coloring machine and the conveyor belt.
03:33The team consists of several pieces that have to coordinate to carry out the work.
03:37Well, we used to have two employees, now we only have one per shift.
03:49It is the next step in an evolution that began a long time ago, but that seems to have entered a new, faster phase, automation.
04:00Some jobs are now automated, so they are much easier.
04:06Before we had to do them by hand, like in the other machine you've seen.
04:10Now Baxter packs the pieces.
04:14I just have to pack them.
04:20This is how the packaging of the medicine cups was done before.
04:25An employee takes them and makes a stack of 40 cups, and then he wraps them in a plastic bag.
04:33As you can see, it is an operation that requires a certain amount of work.
04:37We think that everyone will focus on what is important, because we know that our jobs may not be forever.
04:44Maintaining our level of demand, we can compete with the Chinese, the Mexicans or anyone else.
05:03The machines have escaped from their cages and are now among us.
05:12Yeah, El Camino Hospital is famous for its innovations and its use of technology.
05:16In the new building, we introduced the notion of transport robots.
05:28The robot should open the door automatically.
05:30Open the attack door, please.
05:32It is a pharmaceutical robot and it is trying to access the pharmacy, which is a restricted area.
05:38First, it warns the staff inside.
05:42The staff knows that the robot is here and they have to open the door.
05:49The cost of health care is so high that our duty as health professionals is to reduce it as low as possible.
05:56And one way to do it is with technology.
06:00Automation can bring great benefits.
06:02This is one of the most efficient way to store items in the world.
06:15What we have here is an automated system to obtain orders.
06:19We have divided the floor into squares so that the robots can move following a square pattern.
06:25What they are trying to do is find the items that we need in order to satisfy the orders of our clients.
06:33And what's happening is, as a client makes an order somewhere in the world,
06:38that or that item has to be located and transported.
06:45We have about 200 robots, probably equivalent to 600 or 800 people or even a thousand.
06:52It is a very efficient system.
06:54Our productivity has multiplied by 4 or 5 with respect to manual work.
07:06It is clear that today technology is able to perform more and more tasks in our place.
07:12Machines are getting better and better.
07:14If you have a job that competes with activities that can be carried out by a machine,
07:18it will cost you a lot to make a living.
07:21Nobody wants to compete with a robot.
07:25Automation means that what humans used to do,
07:30today machines, robots and codes do it.
07:38There is a great incentive to do it,
07:40but at the same time that means that there will be jobs that will no longer be available to people.
07:48The robot factory
07:55Next to these robotized factories,
07:57more and more people come to this type of place,
08:01the employment services, hoping to find a job.
08:05I only look for jobs full-time, with medical insurance.
08:09It all depends on the needs of each one.
08:19In the 90s, thousands and thousands of jobs were lost in the insurance industry.
08:23We were known as the country's archivist.
08:26And it is assumed that Hartford Post Office was the busiest in the United States,
08:31because the insurance industry was an activity based on paper.
08:39These jobs no longer exist, because now everything is done online, by computer.
08:45Hi, my name is Bob.
08:47Rochelle, nice to meet you.
08:49This way, please.
09:06Well, as I told you, my name is Bob.
09:10Let me clear this up.
09:12You are looking for professional advice, right?
09:16Yes.
09:17Good.
09:18I'm 26 years old.
09:20I studied at university, but I haven't graduated yet.
09:23I have a year and a half left.
09:24Now I prefer to focus on work.
09:26I can always resume my studies.
09:28How do you normally look for a job?
09:30The first thing I do is update my CV.
09:34Most jobs require a degree or any degree in a specific field,
09:39or in any other related to that job, so it will be more difficult to get.
09:43Currently, a degree is equivalent to a university degree.
09:46It all depends on the job you are looking for.
09:48I am open to all possibilities.
09:51Okay, we'll look for something for you.
10:06He loves Baxter, because Baxter is in charge of two of the machines,
10:09and he only has to operate one.
10:11One day, we'll have three Baxters, and Amador will be able to watch and not worry about anything.
10:15When the last generation of Baxters comes out,
10:17they will be able to learn more about the process,
10:19and will be able to correct any problem that comes up on the fly.
10:23He will be more in charge of planning the materials,
10:26and managing the machinery, than the manual tasks,
10:29to make sure that it works with the right parameters.
10:34Virtually all robotics companies say that they don't plan to replace the workers.
10:39No company wants to say something like that.
10:42Even if automation doesn't mean destroying jobs right now,
10:45it will probably mean destroying job creation in the future.
10:50We will see that fewer jobs will be created for people.
10:54So, you have to know how to separate, let's say, the reality from the marketing.
10:59In general, companies don't like to hear that their employees are going to lose their jobs.
11:06Instead, they prefer to emphasize the fact that they are retraining their staff.
11:14But that can be difficult,
11:17because in the machines of the past,
11:19they could be managed by under-qualified workers,
11:22while today's machines require more advanced training,
11:25and that transition will be difficult to carry out.
11:38It is also said that if, thanks to robots,
11:40factories become more competitive in the United States,
11:43and in the most developed countries,
11:45some factories could go back to China.
11:48Some factories could go back to China,
11:50but there wouldn't be many jobs,
11:52because they would be fully automated.
12:08There are economists who have begun to study the exact impact
12:11that automation can have on the labor market,
12:14and their answer is overwhelming.
12:18Here I have a study
12:20that has developed a list of all jobs
12:22that will be automated in 20 years.
12:26The conclusion is that 47% of the American labor market
12:32is ready to be automated.
12:36This does not mean that these jobs will necessarily disappear,
12:41only that technology allows them to be automated.
12:49Half of the jobs that exist today
12:52are likely to be automated in the next 20 years.
12:57Some have very low probabilities,
12:59while in other cases,
13:01the probability that they will be is almost 100%.
13:06The jobs that have to do with dirtiness,
13:09monotonous or dangerous,
13:11will disappear for sure.
13:14Amazon, for example,
13:16has been automating its warehouses for some time.
13:20The next step will be
13:22that there will also be robots packing the items.
13:25Hi Francisco, how's it going?
13:27Are you ready for the Amazon contest?
13:29Yes.
13:30In the Amazon distribution contest,
13:34some robots compete
13:37by taking objects from a shelf
13:42and placing them in boxes.
13:47In Amazon, they have held a distribution contest,
13:50but no robot reached the sole of the shoes
13:52of the human distributors,
13:54although, evidently, with time and technological advances,
13:57things will change.
14:01It will take between 5 and 10 years.
14:11Humans and machines
14:13have had a complicated love relationship
14:15from the beginning.
14:17People have always been concerned
14:19about technological unemployment.
14:21Almost 200 years ago, in England,
14:23the Luddites destroyed the mechanical warehouses,
14:26worried that they would take their jobs away.
14:30The craftsmen of the weaving industry were worried
14:33because their work could be done
14:35much faster with a machine.
14:38And that caused them a deep concern.
14:41They wondered what would become of their trades.
14:45The craftsmen were an important group,
14:48but not the majority of society.
14:50Now, when we talk about how machines
14:52are going to take their work away
14:54from the vast majority of adult workers,
14:57the degree of concern is very different
14:59than it could have been in 1800.
15:04One of the key things is that people always accept
15:07that the effect of technology
15:09is to eliminate jobs,
15:11when often that is not the case.
15:13For example, one of the key technologies
15:15of the Industrial Revolution
15:17was mechanical weaving,
15:19that is, the automation of weaving.
15:21So, over the course of the 19th century,
15:23the amount of time that a weaver
15:25used to produce a yard of fabric
15:27was divided by 50.
15:29In other words,
15:31technology automated 98% of the work.
15:34And yet, over that century,
15:36the number of jobs in the textile industry increased.
15:40Why?
15:41Because, thanks to increased productivity,
15:43the price of fabrics went down,
15:45became much more affordable,
15:47and demand grew so fast
15:49that the total number of jobs in the industry increased,
15:52although the time it took a weaver
15:54to produce a yard of fabric
15:56had drastically decreased.
16:00There has been debate after debate
16:02about the fact that automation
16:04was going to eliminate a lot of work
16:06and humans would have nothing to do.
16:09But the reality is that,
16:11in capitalist societies,
16:13we observe people
16:15and we always invent new industries
16:17based on those observations.
16:19For example, the service sector has grown.
16:21McDonald's employs hundreds of thousands of people.
16:24People didn't go out to dinner
16:26as much when McDonald's didn't exist.
16:28It's an example of new work
16:30that is based on something
16:32that was already being done at home,
16:34and now many workers get paid to do it.
16:39That fear that machines
16:41replace workers
16:43has existed for 200 years
16:45and it's always been a false alarm.
16:47But I really think that this time
16:49it's different.
16:51Of course, there are people
16:53who are skeptical of what I'm saying.
16:55The specific tasks
16:57that a warehouse weaver does,
16:59yes, that's a job that's going to disappear.
17:01But the entire logistical process
17:03and all the labor
17:05that involves transporting a product
17:07are not going to disappear
17:09because of technology,
17:11unless technology is able
17:13to perform all the tasks
17:15that a human worker does.
17:17As long as there are still
17:19substantial tasks to perform,
17:21we'll see an increase in demand
17:23that's going to offset
17:25job losses.
17:27We may get to that point,
17:29but for now, I don't see
17:31any job that can be signed
17:33without reservations.
17:35They're going to be automated.
17:39The reason why this time
17:41it could be different
17:43is that technology
17:45is becoming extremely powerful.
17:49When we consider
17:51the degree of complexity
17:53of the problems
17:55that artificial intelligence
17:57can solve,
17:59there doesn't seem
18:01to be any limit
18:03to what artificial intelligence
18:05can solve.
18:07According to IT experts,
18:09there's no reason to see
18:11that it stops somewhere.
18:13This is one of the signs
18:15that technological development
18:17has reached a level
18:19where more important changes
18:21can occur than many skeptics think.
18:23So, Mr. Bond,
18:25do you think you can get away
18:27with this automatic car?
18:29This is the emergency stop button
18:31that we use on the circuit
18:33when the car is driving
18:35without a driver.
18:45So, I've actually been working
18:47on the field of automated vehicles
18:49since 1992.
18:51And back at that time,
18:53if you wanted to control a car,
18:55you had to add your own motors
18:57to manipulate the accelerator cables,
18:59and forget about changing gears.
19:01But now, today's cars
19:03that come out of factories
19:05are basically platforms
19:07for automation.
19:09We've reached a point
19:11where it's possible
19:13that a car can drive
19:15on its own in a relatively simple environment.
19:17So, if you can reduce
19:19the speed when parking,
19:21problem solved.
19:23If we think about
19:25restricting the highways
19:27that could make an automatic car,
19:33our goal there is
19:35to develop a car
19:37that can drive
19:39even better than the best human being.
19:45Not long ago,
19:47it seemed impossible
19:49for a car to operate on its own
19:51in an environment as complex
19:53as a city.
19:55So, the question is not
19:57whether it's possible
19:59for the streets to be filled
20:01with self-driving cars one day,
20:03but when.
20:05Most people believe
20:07that driving a car
20:09is an extraordinary challenge,
20:11and we wouldn't see that
20:13in the near future.
20:15But the message here
20:17is that technology
20:19is evolving
20:21at an amazing rate.
20:23Many of the tasks
20:25that used to seem impossible to automate
20:27can be automated,
20:29or will be soon.
20:31Even things that we associate
20:33with pure mental effort,
20:35like writing a text.
20:37We're in the LA Times
20:39where hundreds of people
20:41work to publish a paper
20:43at a 24-hour website.
20:45There's also a team
20:47of reporters
20:49and computer programmers
20:51who put together data
20:53into stories.
20:57There are a couple of companies
20:59that are automating journalism.
21:01Every second, more or less,
21:03a news story is generated
21:05via an automated process,
21:07and in many cases,
21:09it can rival what a human being
21:11could write.
21:13Here's a post that was written
21:15entirely by a computer
21:17with a shallow magnitude 3.5
21:19at 18 km from Fort Bragg
21:21according to the US Geological Survey.
21:23This information comes from
21:25the US Geological Survey
21:27Earthquake Notifications Service.
21:29This text was created
21:31by an algorithm.
21:33What was the magnitude of the earthquake?
21:35When and where did it occur?
21:37That same sentence
21:39can be created in reference
21:41to any earthquake
21:43a few seconds after it occurs,
21:45which allows us to publish the news
21:47of the earthquake.
21:55The list of professions
21:57that can be automated
21:59includes increasingly
22:01large portions of the labor market.
22:03What surprises me the most
22:05is that a large part of the jobs
22:07in the service sector
22:09are already ready to be automated.
22:11Hi, Julie.
22:13Hi, Marie. You're right on time.
22:15Many of the so-called
22:17white-collar jobs can be automated.
22:19Jobs consisting of
22:21looking for information
22:23or doing the same repetitive task
22:25with a computer,
22:27any type of standardized analysis
22:29such as reports, etc.,
22:31or accounting,
22:33and also in the legal field.
22:35Before, lawyers had to study
22:37lots of documents to determine
22:39which ones were relevant
22:41for a judicial process.
22:43Now, lawyers have to finish
22:45a university degree
22:47and end up sitting in a desk
22:49in front of a computer.
22:51That's an idea that's been
22:53rooted in popular wisdom for a long time,
22:55but now many of those jobs
22:57can be in danger.
22:59Computers are becoming
23:01incredibly fast and intelligent,
23:03and that will eliminate
23:05all jobs that have to do
23:07with facts.
23:09The most important technology
23:11is the ability to learn from machines,
23:13to have good algorithms,
23:15to be able to process tons of data
23:17and learn from them.
23:21Today, machines are so fast
23:23and intelligent and learn so many things
23:25that we have to assume
23:27that they are able to do things
23:29that we only thought humans could do.
23:33There are computer programs
23:35capable of recognizing images
23:37at the level of human beings.
23:39They can translate languages in real time
23:41and do amazing things
23:43like science fiction.
23:47Before, a person would examine
23:49X-rays or magnetic resonances.
23:51Now, it's done by a machine.
23:53The machine learning algorithm
23:55is improving with time.
23:57It's capable of doing more and more tasks.
23:59The process is becoming more and more automatic.
24:03You can already see applications
24:05in many fields,
24:07like, for example,
24:09in the development of the stock market,
24:11in meteorological predictions.
24:15The ability to learn from machines
24:17could extend to the whole world
24:19and could have traumatic effects
24:21when it is adopted by large companies
24:23and the machines take on more and more work.
24:31In 20 years, I don't think so,
24:33but in 50, it's possible.
24:37I think the entire process
24:39of automation
24:41is something that's going to take a lot longer
24:43and, again,
24:45there's going to be a demand effect.
24:47Once you make it cheaper and easier,
24:49how the vehicles are driven,
24:51you're going to be doing a lot more of it.
24:57So, there is certainly a sector of people
24:59who are driving, nothing like a driver,
25:01who are doing jobs at risk.
25:03Lots of people who drive also do other things.
25:05Can a car pick up your luggage
25:07and put it in the trunk?
25:09Maybe not.
25:15So, it's correct.
25:17We're not seeing a big impact
25:19on the labor market right now,
25:21but as we look ahead,
25:23we have to ask ourselves
25:25about where the impact is going to be.
25:27Most of these technologies
25:29are still in diapers.
25:31An obvious example would be
25:33an emerging technology.
25:35If it does get to a point
25:37where it can catch drivers,
25:39and road delivery drivers,
25:41and so forth,
25:43it could happen very rapidly.
25:57It's very difficult for us
25:59to understand exponential function
26:01because we're not linear.
26:03This is how we work,
26:05and this is how technology works.
26:11Exponential function derives
26:13from Moore's law,
26:15which states that every 18 months
26:17technology doubles its capacity
26:19and decreases its price.
26:21Exponential functions grow very slowly,
26:23and people ask themselves,
26:25why doesn't everything advance faster?
26:27When the chips doubled their power,
26:29the difference wasn't that big.
26:31But then comes a point
26:33where exponential function really takes off.
26:39But now we're doubling the number
26:41of transactions.
26:43From 1,000 million we've gone to 2,000.
26:45It's a huge difference.
26:47And we're surprised
26:49at how rapidly it's happening.
26:51So at this rate, by 2025,
26:53a computer will have the same capacity
26:55as a human brain.
26:57It will have the same capacity
26:59as all the brains in the world.
27:01We can hardly imagine
27:03how powerful they will be.
27:07I would say among the experts
27:09it's likely to be gaining ground
27:11the idea that technology
27:13is going to create unemployment
27:15more than at any other time
27:17since the 1950s.
27:19I think there's more people
27:21who doubt technological unemployment
27:23than people who believe in it.
27:25It's a question
27:27that hasn't been discussed
27:29enough yet.
27:31But it seems to arouse
27:33a growing interest
27:35in part because of the acceleration
27:37of technology
27:39and in part
27:41because it seems
27:43to be going to affect
27:45the middle class.
27:47When the white-collar jobs
27:49well-paid
27:51are going to be
27:53remunerated
27:55that have to do with
27:57processing information
27:59being replaced
28:01by computer programs
28:03the situation will be more serious.
28:11There's no doubt
28:13that we're seeing all the time
28:15how jobs are being automated.
28:17The big question is
28:19will there be new jobs
28:21and will we see
28:23a gradual enough transition
28:25between old and new jobs
28:27so that people can
28:29go back to school
28:31and start a new career
28:33or will it be so abrupt
28:35that it will cost us
28:37to recover from the impact?
28:41New jobs will be created
28:43but we have to accept
28:45that we don't know how they're going to be.
28:47Today there are jobs
28:49that didn't exist 10 years ago.
28:51Social media experts
28:53are in positions
28:55that even their own bosses
28:57can't pronounce.
29:03The question is
29:05how long will it take
29:07to create new jobs
29:09to replace the old ones
29:11and the overall data
29:13suggests that the average salary
29:15is lower today than 20 years ago
29:17so when I look at the data
29:19I think it's not a good idea
29:21to create new jobs
29:23or to destroy them.
29:27The technological development
29:29has an inherent problem
29:31and that is that every new technological revolution
29:33implies a lesser need for workers.
29:37Today the companies
29:39that generate the most value
29:41employ a fraction of the workers
29:43that they used to employ
29:46There are certain types of technologies
29:48that allow a large volume of work
29:50without a lot of staff
29:52and that is one of the most fundamental
29:54aspects of computers
29:56because computer programs
29:58can be repeated over and over again.
30:01Google for example
30:03is a good example.
30:05With a relatively small number of workers
30:07it can offer its services
30:09in this case
30:11internet searches
30:13for a relatively small number of jobs.
30:18It's true that those highly valued
30:20technological companies
30:22don't have a lot of employees
30:24they have very small teams
30:26but they can create a large value
30:28in the market
30:30without the need to have thousands of employees
30:32producing things in a factory.
30:37As technological developments
30:39accelerate
30:41it becomes increasingly difficult
30:43to predict in which fields
30:45the jobs of the future will be created.
30:47I would say to young people
30:49that a safe career is the field of health
30:51especially nurses and doctors
30:53who deal directly with patients.
30:57They are safe professions
30:59as far as we can predict.
31:01The jobs of the future
31:03will reside in two areas
31:05first, science, technology, engineering
31:07and mathematics
31:09and second, humanity, education and creativity.
31:13We see that there are many professional categories
31:15that are being extinguished
31:17and others that are growing.
31:19It's what economists know as
31:21the elasticity of demand.
31:23The professions that are growing
31:25are the ones that require
31:27interpersonal competition
31:29such as coaching, creativity and entrepreneurship.
31:33One of the most fun things I do now
31:35is designing toys.
31:37I really enjoy it
31:39and everything comes in this little suitcase.
31:41It's very easy to transport.
31:43Good boy, bravo.
31:47I used to have a steady job
31:49in a marketing company.
31:51I liked it.
31:53It wasn't one of those jobs
31:55where you wake up in the morning
31:57and say,
31:59God, I have to go to work.
32:01It wasn't bad,
32:03but the recession came
32:05and it was quite adaptable.
32:07The truth is that I never had any problems
32:09until after two or three weeks
32:11I saw myself going to job interviews
32:13that offered half of my salary
32:15and there would be like 200 or 300 candidates.
32:17And so I knew
32:19that they were probably not going to pick me up
32:21because it was a scary six months.
32:25Are you going to stop whining?
32:27Are you sure?
32:29I think job seeking
32:31in the future
32:33is to think about what we're good at doing,
32:35what we like doing
32:37and how we can make a living doing it.
32:39I thought,
32:41well, if it stays like this,
32:43I'm going to end up having to ask for help from the state.
32:45I knew the longer I spent
32:47in unemployment,
32:49the harder it would be to find something,
32:51the harder it would be,
32:53the worse it would get.
32:55So I thought,
32:57what would I really want to do?
32:59And the answer was,
33:01one of the phone calls
33:03was to a TV shop
33:05and the next morning they called me
33:07to tell me,
33:09we think you have a lot of talent
33:11and you should create your own product line.
33:13Can you come and see us?
33:15What is happening
33:17more and more is a fusion
33:19between work and leisure.
33:21So some people, for example,
33:23do skateboarding
33:25and then find a way
33:27of earning a living out of it.
33:29Those are the key people.
33:35Most of my life I have been
33:37working for a company.
33:39In 2011 I got fired.
33:41And I actually was relieved
33:43because I was not getting along
33:45with my boss at all.
33:47So when he called me
33:49into his office
33:51to give me the finiquito,
33:53I was like, that's great.
33:55Thank you very much.
33:57Have a good day.
33:59And I saw my layoff
34:01as a new beginning.
34:09Some people don't see machines
34:11as a problem.
34:13In a world with less permanent jobs
34:15more and more people
34:17resort to self-employment
34:19and technology can be their ally.
34:23Early 2012 I started driving a taxi.
34:25I'd only been doing it for a short time
34:27when I saw an ad
34:29from a company called Sidecar.
34:31Sidecar is a mobile app
34:33that allows you to call a driver
34:35to come pick you up
34:37and take you wherever you want to go.
34:39I'm just waiting for a call.
34:41One may arrive while we're talking.
34:43I can turn on the Uber app.
34:47Uber is the spearhead
34:49of what some people call
34:51card economy.
34:53It has created a way
34:55for people to pay by foot
34:57to drive customers in their cars.
35:01It has created thousands
35:03of flexible part-time jobs
35:05which is positive
35:07but it has also created
35:09a whole category of workers
35:11who lack the basic social security
35:13that we're used to
35:15in most developed countries.
35:17I have to say, you know,
35:19those days when I don't feel
35:21like doing anything,
35:23I just remind myself
35:25that I don't have to really
35:27pay a boss who controls
35:29my future and my income.
35:31It's something that I like
35:33to remind myself and remind myself.
35:35I really like the independence.
35:37I love it.
35:39It's literally my dream job.
35:41I always liked to write,
35:43draw and make things
35:45but I never thought
35:47I could make a living like that.
35:49I never thought
35:51I'd end up doing
35:53what I love the most in the world.
35:55I think it's amazing
35:57that I can do that.
35:59Now I have employees
36:01and we have a great team
36:03so it's a dream come true.
36:07We used to work for a company
36:09for many years.
36:11We retired and we lived
36:13off our pensions.
36:15All that is changing.
36:17We are in a situation
36:19where a third of American workers
36:21work as freelancers
36:23and that's expected
36:25for the year 2020.
36:27The phenomenon changes 40%.
36:29It's a dramatic change
36:31in the paradigm of our country.
36:35Is it good or bad?
36:39Both.
36:43It depends on the situation
36:45but it's good
36:47if you have clients
36:49and you work on something
36:51by your own decision.
36:53But if you self-employ
36:55just to get to the end of the month
36:57it's much more stressful.
37:11One of the main challenges
37:13of the future
37:15will be to create
37:17viable conditions
37:19for those who are not
37:21made to be entrepreneurs.
37:25I used to earn
37:27more than $100,000 a year.
37:29I had a house and cars.
37:31My life was a success.
37:33When the economy fell
37:35I found myself
37:37without a job
37:39for the first time in many years.
37:43We have people who have
37:45two or three jobs.
37:47We have people who have
37:49a fixed salary
37:51and the reason they come
37:53is because they want
37:55to make money
37:57and they want to
37:59make money
38:01and they want to
38:03make money
38:05and they want to
38:07make money
38:09and they want to
38:11make money
38:13and the reason they come
38:15is because they don't make enough.
38:17If you make $7 or $8.50 per hour
38:19it's normal that you need
38:21two or three jobs
38:23to keep yourself afloat.
38:35I just bought a new Chevrolet
38:37from 2012 but I had an accident.
38:39It was a total disaster
38:41and I didn't have insurance
38:43so I lost about $13,000.
38:45Right now I'm trying
38:47to get my head up.
38:51Under-employment occurs when
38:53you don't work enough
38:55and you don't earn enough
38:57to survive.
38:59It's not a new concept
39:01in many parts of the world
39:03but in a country as rich
39:05as the United States
39:07and still not being able
39:09to support your family.
39:13In the United States
39:15they have accepted a situation
39:17where in general
39:19there are fewer people
39:21employed in the market
39:23and with worse salaries.
39:29Before when I was a consultant
39:31I didn't worry about money.
39:33If I wanted to take my family
39:35out to dinner I had to cut
39:37somewhere else.
39:39And although I do work here
39:41I'm also a client here
39:43and if it wasn't for this
39:45kind of place
39:47I wouldn't have anything
39:49to eat.
39:51Lunch break
39:53started as a soup kitchen.
39:55It's a phenomenon
39:57known as the poor workers
39:59a situation where people
40:01have work but still
40:03don't make ends meet.
40:05It's a situation that doesn't
40:07only happen in the United States
40:09but also more and more
40:11in developed countries in Europe.
40:13It also exists in Europe.
40:15In countries like
40:17Italy and France
40:19there are many of these
40:21poor workers
40:23especially in the subdued economy.
40:25Even in Germany
40:27very low salaries
40:29are appearing
40:31in the labor market.
40:35Every time there is
40:37a crisis
40:39whether it has to do
40:41with youth unemployment
40:43or the situation
40:45of immigrants
40:47low salaries
40:49are presented
40:51as a solution
40:53to the problem.
40:57In the United States
40:59the impact of this strategy
41:03people
41:05need two
41:07and sometimes even three jobs
41:09just to get
41:11to the end of the month.
41:13Hi, how are you?
41:15Good?
41:17It's a problem that has to be studied
41:19and analyzed with some compassion.
41:21What are we going to do with the people
41:23who have lost their jobs
41:25because of technology
41:27because the economy itself
41:29is unable to support them
41:31and companies have to fire them.
41:33Ultimately
41:35it is a situation in which the population
41:37is not able to satisfy
41:39their most basic needs.
41:41It is a vicious circle
41:43so that people can live
41:45from their work,
41:47salaries have to be higher
41:49but that is precisely the reason
41:51that employers resort to automation.
41:53In the United States
41:55since the salaries are lower
41:57there are fewer incentives
41:59for automation
42:01compared to Scandinavia.
42:03By raising the minimum wage
42:05we would be increasing
42:07the incentives for automation.
42:13What will happen
42:15when automation
42:17takes full effect?
42:21The alarmists foresee a dark future
42:23with massive unemployment rates
42:25and an increasing gap
42:27between those who have a job
42:29and those who don't.
42:33It is going to be a critical problem.
42:35We could find ourselves
42:37at the edge of an economic tsunami
42:39that could subject societies
42:41to terrible pressure.
42:43There will be mass protests,
42:45social unrest.
42:47We will be destroying the economy
42:49because who is going to buy
42:51a job when the population
42:53doesn't have a job?
42:55It is very important
42:57that people start thinking
42:59about what artificial intelligence
43:01and robotics can mean
43:03for our economy
43:05and start really having a debate
43:07about the possible solutions
43:09to the problems that will be created.
43:11A strategy would consist
43:13of regulating certain applications
43:15of technology in an effort
43:17to prevent the automation
43:19from becoming an alternative
43:21to generalized automation.
43:23It could be a policy
43:25that regulates automation
43:27so that we don't automate
43:29as much as we could
43:31or at least we automate
43:33following a series of guidelines,
43:35a certain calendar.
43:37The idea is that technology
43:39gives us the option
43:41to automate certain activities
43:43but it is not an obligatory option.
43:45Historically speaking,
43:47at all costs,
43:49employment against automation
43:51has never been a very viable cause.
43:55In modern trade unionism
43:57there is a desire
43:59to work with technology
44:01but at the same time
44:03there is a desire
44:05to protect jobs
44:07and sometimes they are
44:09contradictory things.
44:11A good example
44:13are the newspapers.
44:15It does not seem likely
44:17that individual companies
44:19or nations opt to limit automation
44:21through a series of rules
44:23and regulations as a strategy
44:25to save jobs.
44:27Yes, it is expected
44:29that any company,
44:31whether it is a corporation,
44:33an army or a government,
44:35uses technology to reduce costs,
44:37increase efficiency,
44:39perform better and have
44:41a better relationship
44:43That is precisely the problem
44:45that a country
44:47cannot stop automation
44:49in order to save jobs.
44:51The effect would be
44:53just the opposite.
44:55Competitiveness would be lost
44:57and jobs would disappear
44:59even faster.
45:01If we see ourselves
45:03in a situation
45:05where many jobs
45:07disappear,
45:09the only solution
45:11may be to accept
45:13that not everyone
45:15will be able to get a job.
45:17Right now
45:19the main source
45:21of income
45:23for the citizens
45:25is work.
45:27If the number of jobs
45:29is reduced,
45:31what do you do about that?
45:33How are they compensated?
45:35How do they survive?
45:37Sooner or later
45:39we will have to propose
45:41a guaranteed income system
45:43where everyone can
45:45access guaranteed income
45:47whether they can get a job or not.
45:49There are already
45:51several countries
45:53willing to explore different
45:55forms of citizen income
45:57with a guaranteed income
45:59for everyone.
46:01The most obvious question
46:03is what happens
46:05when people start
46:07to charge unconditionally?
46:13When you get a system
46:15that puts things on the table
46:17for its population,
46:19it can have a destructive effect.
46:21People are not happy
46:23staying at home
46:25and pulling the money
46:27out of the state.
46:29If they can, why not?
46:31It doesn't create
46:33any incentive
46:35for people to create things.
46:37It's not really an incentive
46:39for someone like me
46:41who is struggling to make money
46:43and not only to have a job
46:45and a salary to give people jobs.
46:47What incentive would we have
46:49to keep doing something like this
46:51if there are people
46:53In many countries
46:55there is strong support
46:57for a minimum wage
46:59but no support for a basic income.
47:01There is an assumption
47:03that everyone has to work
47:05to produce the things
47:07that we as a society need.
47:09And it's not like that.
47:11We can produce those things
47:13with less work
47:15or less hours.
47:23If machines can
47:25perform more and more tasks
47:27and increase productivity
47:29constantly,
47:31the question is
47:33whether it is really necessary
47:35for everyone to work so much.
47:37Automation
47:39is the greatest progress
47:41in the history
47:43of mankind.
47:53Productivity
47:55is the measure of what we produce
47:57in relation to the number of hours
47:59we work.
48:01It is a number that has multiplied
48:03many times throughout history
48:05which has allowed to improve
48:07working conditions and salaries.
48:11The working week
48:13has been reduced by stages
48:15up to 40 hours
48:17and paid holidays have gone from
48:19just 4 days to 5 weeks
48:21in many western countries.
48:25Throughout the last century
48:27productivity
48:29has multiplied
48:31by 20.
48:35One of the most important economists
48:37of the last century, John Maynard Keynes,
48:39predicted that by the year 2000
48:41technological advances
48:43would allow to reduce the working week
48:45to just 15 hours
48:47so that everyone could dedicate
48:49their free time to leisure.
48:51But as we all know,
48:53that did not happen.
48:55In the 80s something happened.
48:57Productivity
48:59doubled again,
49:01but salaries and working week
49:03did not change.
49:05The problem
49:07is that we have not benefited
49:09from this
49:11creating more freedom
49:13for people.
49:19Six years ago
49:21this land was a legal landfill
49:23until the local community
49:25invited some activists
49:27against climate change
49:29to occupy it.
49:35There are those who refuse
49:37to wait for the prophecy
49:39that Keynesian of a life
49:41with more free time.
49:43In the shadow of Heathrow airport
49:45in London, these people live
49:47as if the unemployed
49:49had already arrived.
49:51Yes, Heathrow airport is there,
49:53less than a kilometer away.
49:55Two years ago I graduated in art.
49:57I lived in the center of London.
49:59I worked full-time
50:01as a receptionist and hated it.
50:03I knew it was not
50:05the life I wanted to live.
50:07I wanted to feel that I was doing
50:09something more in the global struggle
50:11for the environment.
50:13Then I discovered this place.
50:15I started coming on weekends
50:17and some afternoons
50:19and I said to myself, it's over,
50:21I quit everything.
50:23This job makes me sick,
50:25I do not see the sunlight,
50:27I have to go outdoors
50:29and I left my job and I came here.
50:31It's very dark around here.
50:33I've been living here for a little over a year.
50:35I work one morning a week,
50:37not even a full day a week.
50:39And with that I spend
50:41everything I have decided I need.
50:43So I do not charge any social benefits,
50:45I do not ask the state for anything.
50:47My total living cost is
50:49about £ 70 a month.
50:53There are very divided opinions
50:55around basic income.
50:59Some say that people
51:01are going to stop working.
51:05And others, on the other hand,
51:07believe that people
51:09are going to become more creative.
51:13These are opinions based on speculation.
51:15I say, let's try it,
51:17let's see what happens.
51:21Wow, I see a guided tour is coming.
51:23This is one of the boards
51:25where we organize what we do together
51:27when we work together.
51:29Although most of the tasks
51:31have been wiped off,
51:33I guess either because they are already done
51:35or because there has been to postpone them
51:37for the bad weather.
51:39There is the idea that people on strike
51:41are going to be a burden,
51:43that kind of thing.
51:45Here we do not believe it.
51:47Our lifestyle allows us to live
51:49in contact with nature,
51:51in contact with the earth,
51:53get our hands dirty,
51:55which is something fantastic
51:57for the immune system.
51:59We pick up logs and wood chips.
52:01We work but we do not charge a salary.
52:05One thing is clear,
52:07we have to prepare for a future
52:09in which we are going to live with machines,
52:11whether we like it or not.
52:17And we may have to do it
52:19much earlier than we thought.
52:25Right now we are at a point
52:27where there are at least 20 technologies
52:29about to take off,
52:31from nanotechnology to cloud computing.
52:33Sooner or later,
52:35these technologies will develop
52:37all their potential
52:39and will begin to have an impact
52:41on all traditional industries
52:43and occupations that now employ
52:45millions of people.
52:47It will have a traumatic impact.
52:49There is not enough debate.
52:51Scientists have the responsibility
52:53to inform us
52:55of how powerful technology
52:57is becoming.
52:59In the long run,
53:01we could face
53:03a situation in which
53:05we would have to rethink
53:07our entire social organization.
53:09When jobs begin to disappear
53:11because of automation,
53:13we will have to find
53:15new solutions.
53:17Will income continue
53:19to be proportional to work in the future?
53:23Politicians have to think
53:25about what taxes
53:27companies will have to pay.
53:29If a robot
53:31performs a job,
53:35who will be taxed?
53:43If a company
53:45decides, for example,
53:49to replace 100 employees
53:51with robots,
53:53then
53:55there would be
53:57no viable basis.
54:05Ultimately,
54:07the solution to these challenges
54:09depends on the political
54:11concepts of each one
54:13and on the people's
54:15concept of what motivates their actions.
54:17Automation is an
54:19inevitable reality.
54:21Workers will be replaced
54:23by machines.
54:25This will increase
54:27the wealth of society
54:29because we will be able to do
54:31more things with less labor
54:33and less time.
54:35Who will benefit from this?
54:37We have to think about solutions
54:39like basic income
54:41or reducing the working week
54:43so that everyone
54:45works less for the same salary.
54:47Do we want to live
54:49in a society where factories
54:51are more expensive?
54:53Do we want to live in a world
54:55where abundance,
54:57which is possible thanks
54:59to technology,
55:01is shared among all
55:03and we can have more free time,
55:05be freer and live better?
55:07Technology itself
55:09is not a good or bad thing.
55:11It is a tool
55:13and today that tool
55:15is more powerful
55:17than it has ever been in history.
55:19I certainly expect
55:21that in about 20 years
55:23we will see a society
55:25very different from the current one.
55:27The aspect of the society of the future
55:29depends largely on the decisions
55:31we make now.
55:33That is why it is so important
55:35to debate these issues
55:37because we could choose
55:39to give in to automation
55:41without any control
55:43and cross our fingers
55:45and hope that everything
55:47will be as you say,
55:49maybe it will happen,
55:51maybe it won't.
55:53Are you easy to get to know?
55:55Easy to get to know,
55:57very easy to get to know.
55:59Technology is key
56:01in the labor market right now.
56:03At the moment,
56:05I'm not too worried.
56:07I think if I find a job now,
56:09I could keep it for many years
56:11before a robot or whatever
56:13comes to change the system.
56:15I'm not young,
56:17so I'm not going to be fired.
56:19No.
56:21I see myself retiring here.
56:25I love my job.
56:29I was making a lot of money
56:31helping companies to make even more money
56:33and I was miserable.
56:35It took me three hours to get to New York.
56:37I didn't have time for myself
56:39and I felt that my job
56:41was absorbing my soul.
56:43Now I feel better emotionally
56:45because I know that with my job
56:47I'm helping others.
56:53I think once we get rid of
56:55the slavery of full-time work
56:57and working part-time
56:59we could spend more time
57:01with our friends,
57:03our family,
57:05our neighbors,
57:07taking care of ourselves
57:09and taking care of others.
57:11You have to adapt
57:13because we're too far forward
57:15to sit around a bonfire
57:17and talk.
57:19So what else do we do?
57:21We have to keep progressing.
57:23That's the point of life, isn't it?
57:25To keep progressing.