En la era de la automatización, surge una pregunta fundamental: ¿realmente necesitamos humanos en el servicio al cliente, como en el caso de los taxistas o recepcionistas de hoteles? Este tema ha ganado relevancia a medida que la tecnología avanza y las máquinas se vuelven capaces de realizar tareas que tradicionalmente requerían un toque humano. La automatización en el sector de transporte y hospitalidad ha permitido la implementación de sistemas eficientes y económicos, desde aplicaciones de taxi hasta kioscos de check-in automatizados.
Sin embargo, aunque estas tecnologías ofrecen rapidez y conveniencia, la interacción humana sigue siendo invaluable. La amabilidad, empatía y capacidad de adaptación son habilidades que los humanos aportan y que las máquinas aún no pueden replicar por completo. Por ejemplo, un conductor de taxi no solo transporta pasajeros; también proporciona una experiencia, una conversación, y puede manejar situaciones imprevistas con flexibilidad.
En este contexto, es crucial considerar el equilibrio entre automatización y la intervención humana. Mientras que la eficiencia es importante, el toque humano en el servicio al cliente crea conexiones y lealtad. En última instancia, la pregunta no es si los humanos son necesarios, sino cómo podemos integrar la tecnología de manera que potencie la experiencia del cliente sin sacrificar la calidez del servicio humano.
A medida que avanzamos hacia un futuro más automatizado, es fundamental evaluar qué aspectos del servicio al cliente pueden beneficiarse de la tecnología y cuáles aún requieren el invaluable toque humano.
**Hashtags:** #Automatización, #ServicioAlCliente, #TecnologíaYHumanos
**Keywords:** automatización, servicio al cliente, taxis, recepcionistas, experiencia del cliente, interacción humana, tecnología, amabilidad, eficiencia, futuro del trabajo.
Sin embargo, aunque estas tecnologías ofrecen rapidez y conveniencia, la interacción humana sigue siendo invaluable. La amabilidad, empatía y capacidad de adaptación son habilidades que los humanos aportan y que las máquinas aún no pueden replicar por completo. Por ejemplo, un conductor de taxi no solo transporta pasajeros; también proporciona una experiencia, una conversación, y puede manejar situaciones imprevistas con flexibilidad.
En este contexto, es crucial considerar el equilibrio entre automatización y la intervención humana. Mientras que la eficiencia es importante, el toque humano en el servicio al cliente crea conexiones y lealtad. En última instancia, la pregunta no es si los humanos son necesarios, sino cómo podemos integrar la tecnología de manera que potencie la experiencia del cliente sin sacrificar la calidez del servicio humano.
A medida que avanzamos hacia un futuro más automatizado, es fundamental evaluar qué aspectos del servicio al cliente pueden beneficiarse de la tecnología y cuáles aún requieren el invaluable toque humano.
**Hashtags:** #Automatización, #ServicioAlCliente, #TecnologíaYHumanos
**Keywords:** automatización, servicio al cliente, taxis, recepcionistas, experiencia del cliente, interacción humana, tecnología, amabilidad, eficiencia, futuro del trabajo.
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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.