Internet se está expandiendo y con ello nos está dando poderes casi sobrenaturales, ya no es solamente una red de ordenadores y servidores, ahora es una red de cosas, cosas que nos conocen, cosas que saben lo que nos gusta comer, cuanto tiempo dormimos, incluso controla nuestro ritmo cardíaco. Internet, pasado, presente y futuro de un entorno de interacción entre personas y dispositivos que está cambiando el comportamiento de la Humanidad.
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00:00Today it will be partially cloudy in the morning and clear in the afternoon.
00:08West wind of about 20 kilometers per hour in the afternoon.
00:11Tonight partially cloudy, minimums of about 12 degrees.
00:16It's eight in the morning.
00:21I'm not at home.
00:24But my house knows I'm coming.
00:30The Internet is expanding, and as it does, it's giving us almost supernatural powers.
00:36Alexa, you haven't put butter on the toast.
00:41I'm not sure how to help you with that.
00:46The Internet is no longer just a network of computers and servers.
00:49Now it's a network of things, things that know us.
00:54Things that know what we like to eat, how long we sleep, how to open the door to the house and even our heart rate.
01:02Alexa, where are my keys?
01:04They're in your room.
01:06At 8.30 you have a meeting.
01:12The Internet is no longer just a cloud.
01:14Now it has a body.
01:17A body of devices that are its limbs, eyes, ears and even its brain.
01:24Each device we connect becomes part of the network.
01:29But are all those devices at our service or are they the ones that control us in secret?
01:37Currently, the Internet is everywhere, listening to us, influencing us, being part of us.
01:45But if the Internet now has a body, how far can it go?
02:04The Internet is an amplifier of intelligence.
02:09But for every use that we can think of that has a positive and beneficial effect, there is another negative use.
02:16Human beings do not end at the limits of our biological tissues.
02:21The tools are appendices, extensions of what we are and model our behavior.
02:29As things in our physical life start to be on the Internet and interconnected, the number of things that can go wrong will increase.
02:37Little robots do more things for us than we think.
02:41Now there are billions of network sensors that form what we call the Internet of Things.
02:50It's like seeing the planet develop a nervous system.
02:57The merging of these different technologies is going to lead to the first true artificial intelligence.
03:07And then what?
03:08You never take enough care.
03:11We must control devices before they control us.
03:22But we would not have our smart devices if it had not been for the work of a man.
03:27Doug Engelbart.
03:29Doug Engelbart.
03:30Doug Engelbart.
03:32Doug was the most monomaniacal man I've ever known.
03:36All his life he was focused on one thing, the increase of intelligence.
03:43The idea was that human beings were pretty good, but with computers they could be a lot better.
03:50He imagined network computing in a way that was both highly technical and highly idealistic, even utopian.
04:02If in your office there was a computer that was active and at your disposal all day,
04:07responding to each of your actions, how much value could you get from something like that?
04:13It was fall 1968 when Doug Engelbart was the mother of all the presentations.
04:20Come in, Menlo Park.
04:24Okay, there's Don Andrews' hand in Menlo Park.
04:27There were thousands of computer engineers in a room,
04:30and they saw Engelbart using a computer to communicate with people in another room.
04:36Now I'd like to introduce Jeff Ralefson from Menlo Park.
04:39He's sitting in a room like this working.
04:42Hi Jeff.
04:43Hi.
04:44It was the first time that many of them saw computers as a true form of communication.
04:50Suddenly, at that moment, all the people who were there began to imagine not just computers,
04:56but computer networks.
05:00Engelbart is the person who invented the computer mouse.
05:03It was kind of like a little wooden box that you could wrap around with your hand.
05:07You know, think about that for a moment.
05:09It's something that accommodates the computer to the human body, to the hand.
05:15The devices that I'm using,
05:17Doug had a vertical screen in black and white that looked like a piece of paper.
05:22He invented a mouse to be able to point things through a potentiometer.
05:27He invented hyperlinks so that you could connect a document to another document.
05:32But if I want to, I can also say,
05:34I want to go to the library. What do I have to pick up there?
05:37I just point to that, and I see books and all.
05:41This was like a World Wide Web in a box.
05:47Thank you very much for coming to the opening ceremony.
05:52Engelbart and his team actually helped humanize the computer.
05:57The computers were going to bring us together,
05:59and by bringing us together, let's be more fully human.
06:03Steve Jobs was the first one to realize this.
06:06We're tool builders.
06:08And that's what a computer is to me.
06:10It's the most extraordinary tool that I've ever come up with.
06:13And it's the equivalent of a bicycle for our minds.
06:22Three things.
06:24A widescreen iPod with touch screen,
06:26a revolutionary mobile phone,
06:28and a great internet communication device.
06:31Are you getting it?
06:34These are not three separate devices.
06:38This is a single device.
06:44And we have called it the iPod.
06:48And we have called it the iPhone.
07:03I remember when the iPhone was first announced back in 2007.
07:06I could absolutely not wait to get one.
07:09And when I finally did get my hands on one,
07:12it felt like I was living in the future.
07:15And now I can't remember what it was like to live without this.
07:22It's a device made of plastic and metal
07:24that has all the answers, all the world's knowledge and information,
07:28that can bring you a car,
07:30that can move mountains,
07:32that can make people do things to you,
07:34all by rubbing a magic mirror.
07:38And no place has embraced that magic like Silicon Valley.
07:43Here you can see smartphones everywhere.
07:47But this is also where the next generation of smart devices is being managed.
07:53To see them, I'm going to visit Beta,
07:55the most innovative analog shop in Palo Alto,
07:58of digital devices.
08:00Hi, welcome to Beta.
08:02Have you been before?
08:03No, I'm Derek.
08:04I'm Katrina, nice to meet you.
08:06Likewise.
08:08Everything here is out of the box,
08:10so you can touch it, feel it, interact with it,
08:12see how it's going to fit into your life.
08:14It's a Bluetooth connected device,
08:16so you can create lightscenes during the day,
08:18sunset, in the night,
08:20you know what happens during the day,
08:22you can control it directly from your app.
08:24Free video viewing tool,
08:26any command that you would be able to give your phone,
08:28you can just use the button,
08:30it will automatically water for you,
08:32you can interact with it, you can touch it and talk to it,
08:34you can put it on your kids, you can put it on your kid,
08:36you can put it on your dog, back, whatever.
08:39What I wanted to hear.
08:41I haven't crashed against anything yet.
08:43Oh my God.
08:47I want one.
08:51Beta's store looks like a toy store for adults,
08:53but as I found out later,
08:55more than a store, it's a research laboratory
08:57where data about you is collected.
09:01We created our store to take the best of the internet
09:03to a physical store.
09:05Although our store sells products,
09:08we don't make money selling them.
09:10Something quite unusual in physical stores.
09:12We are the only store that does it.
09:16And how do you get profits
09:18if you don't make money selling products?
09:22In the store we have a unique business model,
09:24since we directly rent space to companies.
09:28We have an agreement with a company
09:30called RetailNex,
09:32which uses artificial vision with cameras
09:34located on the ceiling
09:36to understand how people buy in stores.
09:40In Beta's store,
09:42the most important sensors
09:44are not on the shelves,
09:46but on the ceiling.
09:52While we interact with the products,
09:54these cameras observe us,
09:56recording how long we spend
09:58in front of each product
10:02and learning what we like.
10:06And the customers
10:08don't know that they are being observed
10:10or...
10:12It's the most innocent version of surveillance
10:14that exists right now.
10:16I came to Beta to see smart devices,
10:18but I was surprised to find out
10:20that they were actually observing me.
10:22To learn more about how
10:24smart cameras help businesses
10:26like Beta,
10:28I visited the manufacturer of these sensors,
10:30RetailNex.
10:32Wouldn't it be great to know your customers?
10:35Introducing Aurora,
10:37by RetailNex,
10:39the first all-in-one sensor
10:41designed specifically
10:43for the complex needs
10:45of retail,
10:47the next generation sensor
10:49for customer measurement.
10:51So, explain to me how this works.
10:53When someone comes into the store,
10:55what sort of data do you collect
10:57about that person?
10:59You can tell a lot of things
11:01about the type of person
11:03male, female, approximate age,
11:05and you can get a lot of information
11:07about what they're doing in the store.
11:12Can I ask you a question?
11:14How do you know the age
11:16and the sex of the people
11:18who come into the store?
11:20We use artificial vision.
11:22It works like the human eye,
11:24but it's an algorithm
11:26that does it automatically.
11:28If you want to understand
11:30what type of customer
11:33you're looking for,
11:37you can get very good results.
11:41RetailNex cameras
11:43help minorities
11:45identify and direct their efforts
11:47towards the best customers.
11:49But other analytical companies
11:51have taken facial recognition
11:53to another level.
11:55The system does not need
11:57an exaggerated expression.
11:59It can also detect microexpressions.
12:01These are cameras
12:03that can tell you
12:05how you feel about a product.
12:11If you like it
12:13or not.
12:19But while cameras
12:21are very useful sensors
12:23for minorities,
12:25they're nothing compared
12:27to what we wear all the time.
12:30They want to use the unique
12:32identifiers associated
12:34with your mobile phone
12:36to find out where you shop,
12:38how long you linger in each section
12:40of the store.
12:42For minorities,
12:44your smartphone is like your fingerprint.
12:46It tells them if you've been
12:48to their store before
12:50and when you were there
12:52for the last time.
12:54If 10 years ago someone
12:56said to you,
12:58where are you?
13:00What are you reading?
13:02What are you spending money on?
13:04Who are you talking to?
13:06And what are you doing 24 hours a day?
13:08Would you say,
13:10of course not.
13:12Are you kidding?
13:14And now people sleep in front
13:16of the Apple store
13:18for the privilege
13:20of buying a $800 sensor
13:22that does that and more.
13:24RetailNext insists
13:27that your data is completely anonymous
13:29unless you expressly
13:31accept their use.
13:35If you do, you're letting
13:37those companies know
13:39exactly who you are
13:41and now they can follow you
13:43and offer you products in real time.
13:45But this kind of tracking
13:47didn't start in stores.
13:49It started in the network.
13:51Online stores don't have cameras
13:53and sensors to track us.
13:55They don't need them.
13:57They have something better.
14:01Cookies.
14:03What exactly is a cookie?
14:05And how do companies
14:07use them to track us?
14:09To find out,
14:11I've come to talk to this man.
14:13Lou Montulli invented
14:15cookies in 1994.
14:17The concept is a bit like
14:19the message of a fortune cookie.
14:21A cookie is a file
14:24and the message it contains
14:26is a single line of text.
14:28We can't read it,
14:30but websites can.
14:32Every time we visit a website,
14:34it stores cookies in our computer.
14:36These tiny files help
14:38websites remember us.
14:40This is what allows us
14:42to do things like shopping carts.
14:44You get this fortune cookie,
14:46you pick it up,
14:48but you don't know what's inside.
14:50You really don't care.
14:52And the website breaks it,
14:54reads the message,
14:56and says,
14:58oh, I know who you are.
15:00You wanted to buy a toaster,
15:02and we're going to put it in your shopping cart.
15:04That was the idea.
15:06Inoffensive, wasn't it?
15:08Something unexpected happened.
15:10Advertisers didn't take long
15:12to look at cookies
15:14and advertising networks
15:16started using them to track us.
15:18You start this really terrible
15:21business to know as much about
15:23you as possible.
15:25They could target ads
15:27in a way that television
15:29never did.
15:31Because television
15:33is a medium that you watch.
15:35The internet
15:37is a medium that watches you
15:39as you watch it.
15:43Nowadays, everything you do online,
15:45every cookie you receive,
15:47becomes part of a virtual profile
15:49a dossier about you.
15:53These profiles
15:55include information
15:57that we don't even consider
15:59leaking.
16:03I wear a Fitbit bracelet
16:05because I try to lose weight.
16:07And a couple of times a day
16:09I'm informed of my physical activity levels
16:11to Fitbit,
16:13which may well be aggregating
16:15this information to people
16:18on our plans.
16:22You get this sort of three-dimensional
16:24profile of a person.
16:26You can predict what they're going to do.
16:28They now can find out exactly
16:30who is most susceptible to being manipulated
16:32by buying various products.
16:34There are scammers
16:36who are looking for older people
16:38and they know that that person
16:40has been looking online for places
16:42to invest their retirement money.
16:44They get a phone call
16:46from Mr. Life Savings.
16:48This is a stockpile.
16:50So if you have all the data,
16:52you can target specific people
16:54who you can stay.
16:56That's the danger right now.
16:58But the emergence
17:00of these virtual files
17:02was predicted a long time ago.
17:10This educational report
17:13from 1976
17:15describes a very familiar future.
17:17By the year 2000,
17:19computers will have invaded
17:21our privacy on an unimaginable scale.
17:23They will be interconnected
17:25and unless they are prevented
17:27by new laws,
17:29they will be able to sell information
17:31about where we travel,
17:33how much we spend,
17:35and what hotels and restaurants.
17:37If we pay our bills,
17:39and when,
17:41we will have more than 30 million
17:43inhabitants in North America.
17:45Currently, our dossier
17:47contains all this information
17:49and much, much more.
17:55But the company
17:57that has the most valuable dossier
17:59is the one that almost all of us
18:01use daily.
18:03Google.
18:05Google knows a lot about us
18:07because Google knows our intentions.
18:11And when we think
18:13about the world of advertising,
18:15the ads based on the intention
18:17are what really works.
18:21It was not so long ago
18:23that people said,
18:25how can anyone think that
18:27that company is going to make money
18:29by giving searches?
18:31It seemed a ridiculous idea.
18:33Google's huge advertising network
18:35with emerging windows
18:37generates billions of dollars
18:40every month.
18:4290% of Google's revenue
18:44comes from ads.
18:46And Google only gets paid
18:48if people click.
18:50Now, most of the pages
18:52that you visit on the internet
18:54allow Google to track us.
18:56Most people love YouTube.
18:58I love YouTube.
19:02Why did they purchase YouTube?
19:04Because it gives them
19:06more information.
19:08Why did they develop Chrome,
19:10a browser?
19:12Why did they develop Android,
19:14an operating system?
19:16They're collecting information
19:18on us on more than 60 different
19:20platforms.
19:22And we are completely
19:24oblivious to it.
19:28When was the last time you read
19:30a search condition?
19:32My guess is you probably just
19:34clicked on accept.
19:37And when we're not actively online,
19:39it's easy to forget that the internet
19:41is still watching us.
19:43Everywhere you go,
19:45even when you're not actively using
19:47your phone,
19:49it's still listening.
19:51Companies just find very clever ways
19:53to get us engaged
19:55and help us in their businesses.
19:57And if they can't get us
19:59they're asking our devices
20:01to do it.
20:03The devices
20:05that are going to inhabit our lives,
20:07not just cell phones,
20:09but your smart refrigerator,
20:11your smart car,
20:13all those things
20:15are basically going to be
20:17the extracting tools for someone.
20:24Maybe the most sinister example
20:26is the talk Barbie doll.
20:28Introducing a whole new way
20:30to play with Barbie.
20:33Now there's a Barbie doll
20:35that when you turn it on
20:37it'll find your Wi-Fi network
20:39and will use the cloud
20:41to have a conversation
20:43with you about your interests.
20:45What do you want to be when you're older?
20:47I want to be a vet.
20:49That's great. Curing sick animals
20:51is an amazing goal.
20:53Hello Barbie is recording all those conversations
20:55and sending them to the cloud.
20:57I love New York.
20:59What do you like most about the city?
21:01To me, this is basically
21:03a Barbie doll designed to interrogate
21:05an eight-year-old girl
21:07and get her to tell her stories.
21:09What do you want to be when you're older?
21:11Uh, I want to be a scientist.
21:15Great! A scientist!
21:17Science sounds amazing to me.
21:19Why do you want to be a scientist?
21:22Well, in school I really enjoyed
21:24chemistry and physics.
21:28The study of physics is incredible.
21:31Think about gravity.
21:33You can't see it, but as soon as you trip,
21:35it pulls you down.
21:37Have you ever tripped or fallen over something?
21:39Yeah, I've fallen a few times in my life, Barbie.
21:43It happens to me all the time.
21:45That's gravity.
21:47It pulls you down and sometimes it does damage.
21:49Wow, you could be the next Marie Curie
21:51or the next Einstein.
21:53Am I right?
21:55I think you are right, Barbie.
21:57I knew you were smart.
22:01As long as our devices
22:03work for corporations,
22:05they'll try to turn us into good consumers.
22:07But what if in the not-too-distant future
22:09our machines not only
22:11push us to buy,
22:13but also offer us a new currency
22:15of exchange?
22:17Shares.
22:19We'll share our tastes,
22:21our interests,
22:23our private lives.
22:31Do you want to share your biometric data today?
22:33500 points.
22:39Your biometric data
22:41indicates that you haven't slept well.
22:43Are you feeling okay?
22:47Lucy, does your boyfriend
22:51know that you're pregnant?
22:54You're pregnant?
23:12However strange this may seem,
23:14it will very quickly become
23:16the new normal.
23:24Currently,
23:26all devices that connect us
23:28with the world also collect
23:30our information.
23:32But none of this would have been possible
23:34without a technology from the Second World War
23:36and the most beautiful woman
23:38in the world.
23:40The technology, of course,
23:42is wireless.
23:44And the woman?
23:46You're the man I think you are.
23:48You'll get Miss Hedy Lamarr to seal it with a kiss.
23:50What about it, Hedy?
23:52Go ahead.
23:56In 1938,
23:58the American public knew
24:00the Austrian actress Hedy Lamarr
24:02as a dynamic and dazzling protagonist.
24:04Funny, I don't have an ear for beauty.
24:06Just an eye for it.
24:08But she was not an ordinary actress.
24:11I came here to ask you to marry me.
24:14She was also an inventor.
24:16In her free time,
24:18Hedy invented an improved traffic light
24:21that carbonated and gave flavor to water.
24:27But when she saw Europe sink into chaos,
24:29Hedy focused her attention on ideas
24:31that could contribute to the war effort.
24:33It has a strange effect on me.
24:37And she wondered
24:39how the transmissions could be shielded
24:41by radio to prevent the enemy
24:43from capturing them.
24:45Then she heard this.
24:47Le Ballet Mécanique.
24:51This piece was composed in 1924
24:53by an avant-garde composer,
24:55George Hantail,
24:57who conceived it as a celebration
24:59of machines as music creators.
25:01This complex arrangement
25:03included three xylophones,
25:05four drums,
25:07three aircraft engines
25:09and 16 mechanical pianos.
25:11The mechanical pianos
25:14or pianolas
25:16used perforated paper rolls
25:18to generate music.
25:20But the rolls of the Ballet Mécanique
25:22were special.
25:24They were synchronized.
25:33Hedy Lamarr realized
25:35that synchronized paper rolls
25:37were what she needed
25:39for her next invention,
25:41a secure radio communication system.
25:43Using mechanical pianos
25:45as inspiration,
25:47she and Hantail designed
25:49a system called Frequency Jump,
25:51through which a secret message
25:53could jump from one radio frequency
25:55to another.
25:57For this, the system used
25:59a roll of perforated paper.
26:01But unlike mechanical pianos,
26:03the holes here did not control
26:05musical notes, but frequencies.
26:07The message was sent in pieces.
26:13And in the receiver station,
26:15a roll of identical paper
26:17recomposed the message.
26:23She had done it!
26:25Frequency Jump made it impossible
26:27to intercept radio transmissions.
26:29Immediately, Hedy donated
26:31her patent to the army.
26:33But the high command
26:35was not impressed by the idea.
26:37They did not take seriously
26:39a security system based
26:42The project was forgotten
26:44for decades,
26:46but Hedy had had a great idea.
26:48And it was not lost forever.
26:52It contained a gold mine.
26:59Whoever thinks that a phone
27:01in the car is not his,
27:03is not up to date with the advances
27:05in the mobile phone industry.
27:07Finally, in the 80s,
27:09Frequency Jump was declassified.
27:11And shortly after,
27:13we had the first mobile phones.
27:17This Nokia Mobira
27:19only costs $ 595.
27:23Hedy Lamarr's idea
27:25caused a chain reaction,
27:27an explosion of wireless devices.
27:31Since the year 2000,
27:33data traffic on mobile networks
27:35has increased almost 400 million times,
27:37largely in developing countries.
27:41The invention with which Hedy
27:43hoped to save the world,
27:45has transformed it.
27:47There are cultures
27:49that have skipped a technological generation.
27:51Cultures in development routes
27:53where there was no telephone,
27:55or running water, or electricity.
27:57Today you take a mobile to that village
27:59and its horizons expand unimaginably.
28:03Soon there will be a billion mobile phones
28:05in Africa, which is extraordinary.
28:07The poorest people on the planet
28:10can have a mobile phone.
28:14This idea of wireless mobility
28:16will change the way
28:18people think about themselves,
28:20about national boundaries,
28:22about education, about almost everything.
28:26Now wireless networks
28:28cover the Earth
28:30almost like a new atmosphere.
28:32It is easier than ever
28:34to be always connected.
28:36But are we really more connected
28:38than the people around us?
28:40What is the impact of technology
28:42on our daily life?
28:44Interactions occur
28:46through a technological device.
28:50And not everything is benign.
28:54The noise is getting louder.
29:03You have to move away from the noise.
29:08What if you could live
29:10in a really quiet place
29:12without all that wireless noise?
29:16Welcome to the silent area.
29:20We are in the middle of what is called
29:22the National Radio Silence Area,
29:24a unique area in North America.
29:28It is 33,700 square kilometers.
29:32More or less the extension
29:34of Massachusetts and Connecticut together.
29:37In the heart of the silent area
29:39is the town of Greenback,
29:41West Virginia.
29:43There is the largest
29:45radio telescope in the world.
29:47And the silent area
29:49was created to protect it.
29:51The Greenback telescope
29:53is a Swiss watch
29:55the size of a football stadium.
29:57But while it is so big,
29:59its tolerances are always measured
30:01in fractions of a millimeter.
30:03We are talking about
30:05a telescope that stands
30:07taller than the Statue of Liberty.
30:11The reflector has a surface
30:13of more than 9 hectares.
30:17The bigger the bucket,
30:19the more rain drops it can catch.
30:22Currently, the telescope
30:24is one of the fundamental tools
30:26for the search
30:28for extraterrestrial intelligence.
30:30In recent years, we have discovered
30:32with the Greenback telescope
30:35basic organic molecules,
30:37which are somehow
30:39the basic elements of life
30:41floating in interstellar gas.
30:43But these discoveries
30:45have a price.
30:51Radio silence
30:53in hundreds of kilometers
30:55around.
31:01Unlike traditional telescopes,
31:03radiotelescopes do not see,
31:05they listen to radio waves.
31:07In the 1950s,
31:09the telescope was built here
31:11because it was a quiet place.
31:13Perfect for that.
31:15Listen.
31:17The observatory was built
31:19in the 1950s
31:21and they picked Greenback specifically.
31:23They said it was the quietest place
31:25on earth.
31:27So I don't know,
31:29maybe it's the last quiet place
31:32for the residents of Greenback.
31:34This not only means radio silence,
31:36it also means wireless silence.
31:38Living in Greenback has its challenges.
31:40You can't have a wireless phone
31:42or a cell phone.
31:44There are no cell phone antennas.
31:46Wireless speakers, wireless headphones.
31:48Garage controls cause problems.
31:50Electrified fences in the garden.
31:52Microwaves.
31:54Bluetooth devices.
31:56Car controls.
31:58PS4, Wii, Nintendo.
32:00You would imagine they would cause interference.
32:02They do.
32:06But the biggest threat to the telescope
32:08is Wi-Fi.
32:10Wi-Fi completely cancels
32:12what we're trying to do.
32:14What's also amazing is that
32:16we're beginning to interact
32:18with the internet
32:20as if it is the only social being
32:22that we have in our lives.
32:26And that's the dangerous thing,
32:29I think.
32:31What Mike told me made me think
32:33what it would be like to live
32:35as a teenager in a disconnected town.
32:37Would they feel marginalized?
32:39A girl who moved here recently
32:41asked me when she first moved here
32:43if she had cell phone coverage
32:45and I told her,
32:47you're not going to have it.
32:49This is Greenback's secondary school
32:51in the shadow of the radio telescope.
32:53So you're here, you go to New York
32:55or Maryland.
32:57Becky liked my state.
32:59Bob made a comment.
33:01I have to answer right now.
33:05If the internet disappeared,
33:07we could survive here.
33:09The people of the city,
33:11if they hit a wheel,
33:13wait for someone to come get them.
33:15Here we go down, we change the wheel,
33:17we go up again and we go home.
33:19We don't call people on the cell phone.
33:21We go to their house and we knock on the door.
33:23We like the quiet zone.
33:27Sometimes it seems to me
33:29that we are the control population
33:31of a gigantic experiment
33:33that humanity is doing
33:35in the telecommunications industry.
33:37Here we live without the benefits
33:39or the distractions of cellular technology.
33:41What I see scares me.
33:43I see couples
33:45and groups of people
33:47all focused on their devices.
33:49I feel like
33:51I've been misled for a moment
33:53and the whole world
33:56In any other part,
33:58the internet is attached to you all the time.
34:00Whether you're purposely using it
34:02or not,
34:04it's doing something
34:06with your device.
34:08Even if it's in your pocket,
34:10you're tied to it.
34:12Here you're not tied to anything.
34:14It's interesting to think
34:16that something special has happened here.
34:18But in fact it's the opposite.
34:20It's something that has happened everywhere else.
34:22Maybe the neighbours of Green Bank
34:24enjoy their radio silence.
34:26But for others,
34:28living without our mobile devices
34:30would not only be unpleasant,
34:32it would be impossible.
34:34We are outsourcing our memories
34:36to these devices
34:38and we depend on them,
34:40but we don't have a backup system.
34:42Most young people
34:44at university age
34:46think they couldn't spend
34:48a whole day without their device.
34:51For many people,
34:53their mobile has become
34:55a body appendage.
34:57They can't not live without it.
34:59Information is like their third skin.
35:01The library of all human knowledge
35:03is at a distance screen.
35:05We can think
35:07that this means
35:09that we're becoming more intelligent,
35:11but we depend more and more
35:13on the devices
35:15to make them think for us.
35:17What used to be research
35:19is now Google search.
35:23In 1998,
35:25Larry Page and Sergey Brin
35:27launched Google
35:29to unravel the network information
35:31and they did this using algorithms.
35:36They used an algorithm
35:38to index the network
35:40and another to sort the results
35:42obtained from the thousands of millions
35:44of pages of the index.
35:46They gave us the opportunity
35:48to compare the results
35:50of each book in the library.
35:52PageRank, the Google classification algorithm,
35:54decided which page
35:56would appear
35:58in the coveted first place.
36:00The more links you got,
36:02the higher score you got.
36:04But it could be that somebody
36:06had fewer links,
36:08but from more important places.
36:10Those links would give you more value.
36:12That was the secret sauce.
36:14PageRank worked so well
36:16that even if a search
36:18can give millions,
36:20even thousands of millions of results,
36:22it usually only matters 10.
36:24Typically, we see 10 search results
36:26on the first page.
36:2850% of our clicks
36:30are focused
36:32on the first two search results.
36:3450%.
36:36And the majority of people
36:38don't go beyond the first page.
36:40But what we have begun to realize
36:42is that the order of the results
36:44influences the decisions
36:46we make about everything.
36:48We let Google decide
36:50which information
36:52is best for us.
36:54But if your search gives millions of results,
36:56why do we get those 10?
37:00Hey, guys.
37:02Today I want to give you
37:04the big question.
37:06How to rank number one
37:08on Google?
37:10When Google created its algorithm,
37:13it created a new industry.
37:15Search ranking.
37:17Today we're going to talk
37:19about best ranking
37:21and what I believe Google wants.
37:23There's a new ranking factor
37:25that's huge around the world.
37:27It's a really sneaky, really clever tactic.
37:29So don't hesitate to implement it.
37:31These experts have learned
37:33to optimize the structure
37:35and content of a web page.
37:37The algorithm is the key
37:39to decrypting Google.
37:41All too often,
37:43we go so far as to feed
37:45the Google bot
37:47rather than feed the Google bot.
38:05We believe that just because
38:07a computer program
38:09is operating,
38:11however it's happening,
38:13we can trust it.
38:15The algorithm has to put
38:17things in order.
38:19So what if the algorithm
38:21itself ends up favoring
38:23one candidate over another?
38:25Is the activity of Google
38:27in fact creating more interest
38:29in that candidate
38:31and in turn
38:33generating more votes?
38:39Facebook has experimented
38:41with manipulating
38:43electoral results.
38:45I mean, the way they do this
38:47can actually make
38:49more people want to vote.
38:51If Facebook just sent out
38:53go-out-vote reminders,
38:55but they sent them
38:57only to people
38:59of one political party,
39:01if they did that
39:03on voting day,
39:05they could easily
39:07pass and reply
39:09as an article posted on Monday.
39:11So Facebook also suppressed
39:13conservatively news stories
39:15in its trending section.
39:17People thought this was outrageous
39:19because this is a neutral
39:21technological system
39:23that was being manipulated
39:25by humans.
39:27But that's an absurd way
39:29to use things.
39:31There are no neutral
39:33technological systems.
39:37Like dogs,
39:39these artificial intelligences
39:41are not programmed.
39:43They are trained.
39:45It's a process
39:47called automatic learning.
39:51Toy dog.
39:53Yes, that's incorrect.
39:55The next generation of robots
39:57will learn like an insect
39:59or a baby.
40:07It'll bump into things.
40:09It'll learn how to walk.
40:11It'll learn how to navigate
40:13in this world.
40:15Rather than have all
40:17of its abilities programmed
40:19from the very start.
40:21But with automatic learning,
40:23we no longer have full control
40:25over artificial intelligence.
40:27Will machines become as intelligent
40:29as we are?
40:31Any machine that can make
40:33decisions can act in ways
40:35that its designers cannot predict.
40:37And there are many of those machines now.
40:40It's a pleasure to be here
40:42to introduce a brand new product.
40:44In 2005, Google presented
40:46an artificial intelligence program
40:48to organize photos.
40:50With automatic learning,
40:52Google Photos understands
40:54what's important
40:56and helps you organize
40:58your memories automatically.
41:00And it became evident
41:02when its algorithm
41:04trained people
41:06who trained
41:08these artificial intelligence systems
41:10to train them on white faces.
41:12These weren't necessarily racist,
41:14but the biases
41:16in how you want to train
41:18these systems
41:20end up embedding
41:22these incredible racist assumptions.
41:24If a machine can learn
41:26from humans,
41:28that doesn't mean
41:30we teach it correctly.
41:32In a recent presentation,
41:34Tay proved that humans
41:36love to corrupt artificial intelligence.
41:38Hello, world!
41:40The more you talk to it,
41:42the smarter Tay gets.
41:44Tay's software
41:46mimics the patterns
41:48of the language
41:50of young people
41:52between 18 and 24 years old.
41:54Even the best algorithms
41:56make mistakes at scale.
41:58But the internet trolls
42:00can improvise
42:02based on what people tell them.
42:04Algorithms make mistakes
42:06much more easily
42:08than people,
42:10and they can also be tricked
42:12much more easily.
42:14In a few hours,
42:16Tay was praising Hitler
42:18and launching racist
42:20and anti-feminist attacks.
42:22These systems have
42:24some impressive weak points.
42:26This happens all the time.
42:28From online dating,
42:30hiring, financial investments,
42:32the study of flu epidemics,
42:34or cancer research.
42:36Programming algorithms
42:38make decisions
42:40without us knowing
42:42how those decisions are made.
42:44And that's what's scary.
42:46The machines
42:48are going to end up
42:50running my life
42:52and everyone else's.
42:54I was curious
42:56to do something
42:58that until now
43:00only humans knew how to do.
43:02Drive.
43:18Welcome to DuckyTown.
43:22DuckyTown has
43:24a very serious mission.
43:26To reproduce the challenges
43:28that autonomous vehicles
43:30have to overcome
43:32quickly and safely
43:34when it comes to miniature cars.
43:36What's the advantage
43:38of researching autonomous
43:40vehicles in DuckyTown?
43:42The idea here is that
43:44we have this city
43:46where we can deploy
43:4850 of these vehicles
43:50very easily at any time
43:52What it's doing now
43:54is using the camera
43:56to identify the road lines
43:58and then when it gets
44:00to an intersection
44:02it reads the intersection sign
44:04and then it's a random
44:06arrival based on what
44:08it reads on the sign.
44:10What are the real problems
44:12to resolve to make
44:14an autonomous vehicle?
44:16One big problem is that
44:18every person in the environment
44:20is being very difficult
44:22to understand at the same time.
44:24Liam was telling me
44:26all the problems
44:28that they still haven't
44:30solved. Unpredictable humans,
44:32bad weather, detours
44:34and what to do if
44:36an inevitable accident occurs.
44:40Our autonomous cars
44:42still have a lot to learn
44:44but unlike us
44:46they learn fast.
44:48There's this new
44:50idea that's very powerful
44:52which is robotics in the cloud.
44:54Basically, it's the use
44:56that you can interconnect
44:58the robots with the internet
45:00so if you're a robot
45:02and you learn something
45:04all the robots know
45:06it's a very different
45:08learning experience.
45:10And it's not just science fiction
45:12it's already being implemented
45:14in the world of autonomous cars.
45:16The robots understand
45:18the space, their location
45:20they can navigate the space
45:22but not much more.
45:24But what will happen
45:26when the robots can do
45:28everything that we do?
45:30The development of
45:32full artificial intelligence
45:34can bring about the end
45:36of the human race.
45:38With artificial intelligence
45:40we're invoking the devil
45:42like in those stories
45:44I can control the devil
45:46but it doesn't work.
45:48We should not believe
45:50in keeping a super intelligent genius
45:52locked in his lamp forever
45:54sooner or later it will escape.
45:56A super artificial intelligence
45:58has the potential to tilt
46:00the balance of power.
46:02If a cloud-based intelligence
46:04could communicate instantaneously
46:06how would humans maintain control?
46:10Hello?
46:12How are you?
46:14To find out more about
46:16intelligent machines
46:18I made a videoconference
46:20with Kevin Warwick
46:22a professor of cybernetics
46:24at the University of Coventry.
46:26He's interested in fusing
46:28human and artificial intelligence
46:30to create a hybrid, a cyborg.
46:32What do you think
46:34about artificial intelligence?
46:36If you can't beat it,
46:38join it.
46:40We become part of it
46:42and it becomes part of us.
46:44That's how we incorporate
46:46the power of artificial intelligence
46:48into our system
46:50instead of it acting against us.
46:52Kevin explained to me
46:54that even though humans
46:56and machines look different
46:58their minds work with electrical signals
47:00and binary code.
47:02Brain cells send impulses
47:04like the artificial cells
47:06of a computer.
47:08In fact,
47:10they can send brain signals
47:12across the internet
47:14as if they were part
47:16of your nervous system.
47:18Kevin not only studies
47:20the theoretical possibilities
47:22of using the internet
47:24as a nervous system
47:26he has connected his own to the network.
47:28In 2002, Kevin
47:30implanted an electrode guide
47:32in his arm and connected it
47:34to a robotic hand
47:36becoming the first cyborg
47:38in the world.
47:40Wow!
47:42I went to Columbia University
47:44in New York
47:46and the guide there
47:48helped me connect
47:50my nervous system
47:52to the internet
47:54and we linked it
47:56to a robotic hand
47:58in the UK.
48:00With the implant
48:02placed and connected
48:04the robot hand
48:06received signals
48:08from my brain
48:10in the UK
48:12and my brain
48:14was receiving signals
48:16from the fingertips
48:18and I was able to feel
48:20how much force
48:22that hand was applying
48:24to another continent.
48:26That's incredible!
48:28So with the internet
48:30and an implant
48:32do you think that
48:34in the long term
48:36that will allow us
48:38to fuse our nervous system
48:40with a large network?
48:42Yes, I sincerely hope so.
48:44That cybernetic network
48:46could help humans
48:48and machines to understand each other better.
48:50If you think about how humans
48:52communicate with each other
48:54and compare it with these technologies
48:56it's embarrassing, frankly.
48:58It's terrible.
49:00The technologies
49:02that we still use
49:04even now
49:06are mechanical pressure waves
49:08to communicate with me.
49:10I'm converting
49:12the enormously complex
49:14electrochemical signals
49:16of my brain
49:18into these elementary
49:20coded pressure waves.
49:22It's really terrible.
49:24We have to be up to date.
49:26We have the technology
49:28that we call
49:30the singularity.
49:34The point without return.
49:36Since the birth
49:38of artificial intelligence
49:40we have wondered
49:42when it would surpass us.
49:44Perhaps the day will come
49:46when we and the machines
49:48will cross in opposite directions
49:50and there will be a transition point
49:52where we won't know
49:54whether it's a man or a machine.
49:56How will life be
49:58after the singularity?
50:03You'll take a little pill
50:05it will arrange itself
50:07wiring your neural cortex
50:09and your hearing system
50:11to trust your brain
50:13and, you know, put you on the internet.
50:15Welcome.
50:17Our brain will interact
50:19with all the chips in the room.
50:26We'll just walk into the room
50:28and we'll connect
50:30to the internet mentally.
50:32Remember, you have a date
50:34tonight at nine.
50:36We simply blink
50:38and see all the information
50:40we need to organize
50:42the day.
50:46It's going to start to change
50:48how we think we end
50:50and the new world begins
50:52because more and more
50:54we'll act as if each one of us
50:56lived in our own personalized universe.
51:02We're all going to be
51:04confined in an AI
51:06software shell.
51:08You're going to give
51:10your AI permission to listen
51:12to every conversation you have,
51:14read all your emails,
51:16monitor all your biometric data
51:18and that AI's mission
51:20is to make your life better.
51:24As soon as a computer
51:26in some sense wakes up
51:28because it has access
51:30to the internet,
51:32it has access to everything,
51:34all human knowledge
51:36and it'll transform
51:38into something else.
51:42If we do have a world
51:44of super intelligent robots,
51:46if we're very, very lucky
51:48and we're very, very lucky
51:50and we're very, very lucky
51:52and we're very, very lucky
51:54they will treat us like pets.
51:56They will treat us like food.
52:01Me, I prefer to be a pet.
52:07I call the internet
52:09the internet nest.
52:11We have been building
52:13a nest for the first
52:15truly intelligent machine
52:17to arise.
52:22When you talk about
52:24the unintended consequences
52:26we end up with something
52:28that we thought
52:30would be very good
52:32and it isn't.
52:34I think when you think
52:36how far we are
52:38from the invisible systems
52:40that surround us every day
52:42and provide us so much,
52:44we're in a fool's road.
52:46But what if the internet
52:48doesn't enslave us?
52:50What if it is said
52:52that it becomes
52:54our guiding light?
53:00From the moment
53:02we are born
53:04we will seek
53:06knowledge and beauty in it.
53:08We will seek knowledge
53:10and beauty in it.
53:20It will see our qualities
53:24and feed them.
53:28It will help us
53:30reach our potential.
53:32And it will answer
53:34our deepest doubts.
53:40As humans
53:42we have always wanted
53:44to understand our connection
53:46with the cosmos,
53:48our place in the universe,
53:50perhaps our maximum creation,
53:52the internet?
53:58Some of us
54:00Some of us
54:02Someday it will give us back
54:04the favor
54:06and enlighten us.