0:00:01 > 0:00:06This week, we are looking at the future of work. But which jobs will
0:00:06 > 0:00:17go to the robots? Stock pickers? Nurses? My?
0:00:39 > 0:00:42Mr Victor Sherlock of Horsham has a robot at the bottom of his garden
0:00:42 > 0:00:46and he wants to teach it to mow the lawn. Artificial intelligence.
0:00:46 > 0:00:51Everyone is talking about it. Over the years we have seen a developer.
0:00:51 > 0:00:59We have seen it evolve. This is the Watson that won Jeopardy. We have
0:00:59 > 0:01:02travelled the world to see AI ever tries to treat cancer.It studies of
0:01:02 > 0:01:05millions, tens of millions of examples from the assemblage of
0:01:05 > 0:01:14scientific literature.Predict crime.Understand the economy.
0:01:14 > 0:01:19Chamois companies with revenue between $25 million and $60 million.
0:01:19 > 0:01:25-- show me company 's.And save the world. So it may not yet have
0:01:25 > 0:01:36conquered DIY. But we keep hearing how a I will change everything.
0:01:36 > 0:01:44Technology will make man be more intelligent form of expression.
0:01:44 > 0:01:48However, it is the bad side of these algorithms that always seems to get
0:01:48 > 0:01:52the headlines.The fear that tireless robots infused with
0:01:52 > 0:01:57artificially intelligent brains may one day do us all out of our jobs.
0:01:57 > 0:02:02With interaction, with use, with feedback is actually gets gradually
0:02:02 > 0:02:07smarter. From bots that can talk like Arthur.You want to help you
0:02:07 > 0:02:10reset your password question mark walk like a. And even, perhaps,
0:02:10 > 0:02:19think like us. We have been warned that the fourth Industrial
0:02:19 > 0:02:24Revolution is coming.The biggest difference between us and the
0:02:24 > 0:02:28Industrial Revolution in the 1800s if the speed.Millions of workers
0:02:28 > 0:02:41are on the move.So what is going on? What jobs are really at risk?
0:02:41 > 0:02:49What is the future of work? And we start with healthcare workers. For
0:02:49 > 0:02:54almost 70 years, the UK's a national health service has been a free
0:02:54 > 0:02:57service at the point of care. That model is under strain as the
0:02:57 > 0:03:02population ages and chronic health and conditions increase while
0:03:02 > 0:03:07resources shrink. A recent study showed that almost two thirds of
0:03:07 > 0:03:10doctors think that patient safety has deteriorated with one dog to say
0:03:10 > 0:03:17in we are not robots. We are human staff needs. Should be NHS turned to
0:03:17 > 0:03:22robots to ease the strain on human staff? Jane has been looking at how
0:03:22 > 0:03:28data driven technology could transform care in the NHS. Good
0:03:28 > 0:03:33artificial intelligence help save the NHS? More people are looking at
0:03:33 > 0:03:38innovative ways to ease the workload of doctors and nurses. Computer
0:03:38 > 0:03:43programmes can rapidly analyse huge quantities of information in ways
0:03:43 > 0:03:52that humans do not have the time nor brain capacity to do. In 2016,
0:03:52 > 0:03:55Google's the mind was developing an algorithm to identify abnormalities
0:03:55 > 0:03:59in eye scans. Now it has submitted its findings to a medical journal
0:03:59 > 0:04:04for review. It could mean its systems are more effective than
0:04:04 > 0:04:09humans at diagnosing eye disease. Deep mined taught its machine
0:04:09 > 0:04:12learning software using a million eye scans. I will see three other
0:04:12 > 0:04:21projects integrating AI and data gathering. Dementia is now the
0:04:21 > 0:04:26leading cause of death in the UK. At this hospital in carpentry, software
0:04:26 > 0:04:33is being tested to remotely monitor patients. This is one of the rooms
0:04:33 > 0:04:37on the ward. It looks at any other hospital room except in this one
0:04:37 > 0:04:43there are two infrared illuminators and a sensor monitoring my movements
0:04:43 > 0:04:49including when I'm asleep. Oxy health uses a standard digital
0:04:49 > 0:04:53camera and a tongue twisting science. Everytime your heartbeat is
0:04:53 > 0:05:00your skin briefly flashes red. We can not see this but the sensor in
0:05:00 > 0:05:03the camera can detect these so-called micro- blushers. It even
0:05:03 > 0:05:07picks up my vital signs when I am hiding under a table in the room as
0:05:07 > 0:05:11those micro- blushers can still be seen on my arm. There is an alert if
0:05:11 > 0:05:18I leave my bed. And the nurse can click on a live feed to see what is
0:05:18 > 0:05:21happening and determine whether they need to come and check on me right
0:05:21 > 0:05:25away.For the staff, initially, when it looked like we had a camera in a
0:05:25 > 0:05:30box in a room they were not happy about it. But when we spent some
0:05:30 > 0:05:34time with Oxy house, they explained to them and they see how it works,
0:05:34 > 0:05:38they love it. They love the fact it gives you an extra... And extra
0:05:38 > 0:05:45support.The project is in the pilot stage in is awaiting medical
0:05:45 > 0:05:49certification. The data collected is being analysed remotely by a team in
0:05:49 > 0:05:53Oxford and will be used to train the programme to be more predictive.We
0:05:53 > 0:05:57have never had these capabilities as a species, to constantly get our
0:05:57 > 0:06:02rate reading and routine data. There is no reason as we combine and with
0:06:02 > 0:06:06use the data using a I we cannot detect the onset of dementia or read
0:06:06 > 0:06:09getting worse. We can detect problems early so you can stay in
0:06:09 > 0:06:12your own home or a comfortable setting without coming into
0:06:12 > 0:06:18hospital. That will save a huge amount of time.Saving critical time
0:06:18 > 0:06:21was the motivation behind automating processes at NHS blood and
0:06:21 > 0:06:28transplant. 4500 people receive a transplant each year but 6500 are on
0:06:28 > 0:06:34the list. Everyday, three people die waiting for a transplant. A lot of
0:06:34 > 0:06:36information needs to be sifted through to make life-and-death
0:06:36 > 0:06:42decisions. The NHS is now using public cloud technology from IBM to
0:06:42 > 0:06:46help maintain huge databases that used to be managed with a marker and
0:06:46 > 0:06:50a whiteboard.By working with some of this automated technology we can
0:06:50 > 0:06:54make sure we are making the best possible decisions and that our
0:06:54 > 0:06:57clinical teams are thinking through the best outcomes for all of the
0:06:57 > 0:07:02patients on the waiting list, and that our staff, who are often
0:07:02 > 0:07:05working until three in the morning in a high-pressure environment,
0:07:05 > 0:07:08needing to allocate organs quickly, they are supported by this
0:07:08 > 0:07:13technology.Collecting all this personal data has led some to ask if
0:07:13 > 0:07:16it is stored securely enough.At the challenges have in the public sector
0:07:16 > 0:07:22is the perception that maybe the public is less secure than an on
0:07:22 > 0:07:26premises data centre which is not the case. We have an obligation,
0:07:26 > 0:07:30obviously, to many customers to ensure that the public cloud is kept
0:07:30 > 0:07:34secure and patched and maintained effectively. The fallout from it not
0:07:34 > 0:07:39being in that condition is quite severe.In the future, the team
0:07:39 > 0:07:43hopes that artificial intelligence will be able to predict how long
0:07:43 > 0:07:47people will be on the waiting list for an organ. There is an average
0:07:47 > 0:07:51waiting time of two weeks to see a doctor in the UK. Disk and drop to
0:07:51 > 0:07:57two hours if you register with AGP at hand. You can sign up if you live
0:07:57 > 0:08:01or work within certain zones of London. You need to give up your
0:08:01 > 0:08:04regular prat doctor and register with the remote surgery. 26,000
0:08:04 > 0:08:10people have registered so far. I had a chance to test it out, pretending
0:08:10 > 0:08:16I had a case of food poisoning. First I went through a triage with a
0:08:16 > 0:08:19chat bot on an app who recommended I speak remotely to a real-life
0:08:19 > 0:08:25Doctor. The doctor recommends further care and can even send a
0:08:25 > 0:08:29prescription to a pharmacy. The artificial intelligence in the app
0:08:29 > 0:08:33draws on union of data points and can cross referenced the latest
0:08:33 > 0:08:38medical research from journals and studies around the world.You use
0:08:38 > 0:08:41artificial intelligence to tell you whether or not to see a doctor. You
0:08:41 > 0:08:46are always free to see a doctor anyway but what we find is that 40%
0:08:46 > 0:08:53of the people who are reassured that they have everything they need,
0:08:53 > 0:08:57based at there.The app has faced witticism from the Royal College of
0:08:57 > 0:09:01GPs to say that younger users are being cherry picked for the service.
0:09:01 > 0:09:06NHS England lodged a formal objection to the plan out -- rollout
0:09:06 > 0:09:14beyond London.I have think we need to give people safe and equitable
0:09:14 > 0:09:18care. If we roll things out too quickly without ensuring that safety
0:09:18 > 0:09:22and fairness with Ryan the risk of causing unintended harm. So it is
0:09:22 > 0:09:26wise and sensible but independent evaluation is now going on of these
0:09:26 > 0:09:29new technologies so that people can be reassured that they are safe and
0:09:29 > 0:09:35they are fine for everybody.I think it is wrong. I genuinely think that
0:09:35 > 0:09:40it is just not right. I cannot understand why people are hesitant.
0:09:40 > 0:09:48Often it is because they are scared of new technology. They do not know
0:09:48 > 0:09:51what the consequences are. And that is fine. They need to check that and
0:09:51 > 0:09:55reassure them self. There is nothing wrong with that. I have seen three
0:09:55 > 0:09:58ways companies are working with data to help with monitoring, automation
0:09:58 > 0:10:03and decreasing waiting times. All areas that could help an
0:10:03 > 0:10:06overstressed health service. Could artificial intelligence helped to
0:10:06 > 0:10:13save the NHS? It is an exciting development worldwide but never more
0:10:13 > 0:10:17so then here and there are certainly things AI can help as we to plough
0:10:17 > 0:10:21through data we already have, and the questions we didn't even know
0:10:21 > 0:10:28needed answering. But let's be clear, AI2 will never replace
0:10:28 > 0:10:31person-to-person interaction. The touch of a doctor, the looking deep
0:10:31 > 0:10:37into someone's eyes and recognising that the make-up of the person is
0:10:37 > 0:10:41what matters, not just a bleeding leg or a headache. It is much more
0:10:41 > 0:10:45than that and it will be quite a long time for a match creatures
0:10:45 > 0:10:53that.You think it ever will?I will be stunned if win -- within my
0:10:53 > 0:10:58lifetime AI2 ever replaces Doctor.
0:10:58 > 0:11:00That was Jen and although we are
0:11:00 > 0:11:00seeing
0:11:00 > 0:11:00That was Jen and although we are seeing automation
0:11:01 > 0:11:01That was Jen and although we are seeing automation creep
0:11:01 > 0:11:02That was Jen and although we are seeing automation creep in to the
0:11:02 > 0:11:02skilled workforce,
0:11:02 > 0:11:05seeing automation creep in to the skilled workforce, we often think of
0:11:05 > 0:11:08it as working in the low skilled sector where the jobs are
0:11:08 > 0:11:12repetitive. But what about bases in the world where they still have a
0:11:12 > 0:11:16ready supply of relatively low skilled at cheap human workers? You
0:11:16 > 0:11:20would expect countries like China for example to be able to hold back
0:11:20 > 0:11:25the robot tied longer than most. Will not so. We sent Danny Vincent
0:11:25 > 0:11:33to a warehouse owned by the giant Chinese online retailer Alibaba.
0:11:33 > 0:11:37This is a 3000 square metre warehouse. It is part of an
0:11:37 > 0:11:43operation that sorts and delivers 85 million packages at a, shipped to
0:11:43 > 0:11:47over 200 countries around the world. Products are packed and sorted here.
0:11:47 > 0:11:52Usually by dozens of workers. But recently, they had some new
0:11:52 > 0:12:01recruits. 148 automated guided vehicles navigate the floors of this
0:12:01 > 0:12:06warehouse. These agile bots can communicate to each other to avoid
0:12:06 > 0:12:11collisions and distribute the work amongst themselves. A bit like their
0:12:11 > 0:12:19human counterparts who still take on the final stages of processing. Li
0:12:19 > 0:12:24Yen is a 28-year-old worker from south-western China. Her job now is
0:12:24 > 0:12:29in part done by these machines. She followed a family tradition of
0:12:29 > 0:12:34migrating thousands of miles to find better paid work. TRANSLATION:It
0:12:34 > 0:12:42saves me from work, Kwok into every shelf to pick up the goods. Now I
0:12:42 > 0:12:46just had to stand at the pickup platform to wait for the robots to
0:12:46 > 0:12:51send me the goods and I don't have to constantly walk here and there.
0:12:51 > 0:12:55They are part of a data system collecting information not just
0:12:55 > 0:12:58about their environments are also the sales patterns, understanding
0:12:58 > 0:13:01what sells more regularly, rearranging where products are
0:13:01 > 0:13:12placed, shaving off valuable minutes on overall delivery time.
0:13:12 > 0:13:14TRANSLATION:In a traditional warehouse, it is purely manual.
0:13:14 > 0:13:18There are so many products, so the job for the human workers is very
0:13:18 > 0:13:24heavy. A could walk that they could walk 50,000 steps per day. Here the
0:13:24 > 0:13:28machines do all of that, making the work easier and more efficient.
0:13:28 > 0:13:32China has the largest workforce in the world. But it is shrinking and
0:13:32 > 0:13:36rising labour cost two is making it harder for logistic companies to
0:13:36 > 0:13:41recruit low skilled workers. China is already leading the development
0:13:41 > 0:13:45of dark factories, factories that need no human workers and can
0:13:45 > 0:13:49literally work with the lights off. But will automation replace workers
0:13:49 > 0:13:54like Li Yen? TRANSLATION:I feel these robots would become my
0:13:54 > 0:13:59competitors because of sorting out goods I can do other work, monitor
0:13:59 > 0:14:04the system, it takes orders and other work. I don't think they will
0:14:04 > 0:14:09affect me.Alibaba and its partners say automation is an irreversible
0:14:09 > 0:14:13trend in China but they see sectors like e-commerce were born out of
0:14:13 > 0:14:16innovation. Online shops replace many high-street stores, but they
0:14:16 > 0:14:22insist their workers are machines -- and machines will continue to work
0:14:22 > 0:14:23together.
0:14:28 > 0:14:31We are going to interrupt this broadcast with some breaking news
0:14:31 > 0:14:36coming into us at the BBC. It is a world first, ABC click presenter
0:14:36 > 0:14:43Spencer Kelly has been replaced by a robot. It has been dubbed RoboSpen
0:14:43 > 0:14:50and it is apparently capable of a whole host of emotions as well as
0:14:50 > 0:14:53understanding and writing stories and crucially, he never forgets his
0:14:53 > 0:14:58lines. RoboSpen joins the now from the factory that created him.Over
0:14:58 > 0:15:04to you. Sounds like you said I was artificially intelligent. As a robot
0:15:04 > 0:15:09I am often asked to post photos and TV reports about AI. I am not
0:15:09 > 0:15:16intelligent. Everything I am saying is written by a human. The point is,
0:15:16 > 0:15:28robots and AI are not the same thing. Observe my articulated hands
0:15:28 > 0:15:32powered by four fingers and bear cylinders of.Engineering arts has
0:15:32 > 0:15:38made a name for itself by making robotic performance, actors and
0:15:38 > 0:15:45communicators of. -- indicators. Which, according to Will, is the
0:15:45 > 0:15:53only reason the world might need humanoid robot.AI great for
0:15:53 > 0:15:56entertainment and communication, if you want something that interacts
0:15:56 > 0:16:00with people, the best way to do that is to make something person shaped.
0:16:00 > 0:16:07If you think Star Wars, the robot that talks a lot, has a personality,
0:16:07 > 0:16:13doesn't do a lot of useful thing. Will and his team design and build
0:16:13 > 0:16:17robots here from scratch from the aluminium tones to the robbery
0:16:17 > 0:16:26spines and plastic shells. -- bones. The next wave our way into the
0:16:26 > 0:16:38uncanny Valley.It has just come to life with the eyes there. You have
0:16:38 > 0:16:46seen silence of the lambs, haven't you? That is very eerie, that is.
0:16:46 > 0:16:50Will is fascinated with how the human body works and a lot of this
0:16:50 > 0:16:53research concentrates on making natural looking body movements that
0:16:53 > 0:16:58are also very quiet. It is something that he believes might find a place
0:16:58 > 0:17:02in the field of ethics, although he says there is still a lot of work to
0:17:02 > 0:17:07be done.I don't have a single precision part in my body. How can I
0:17:07 > 0:17:12achieve this level of precision with these organic, bones and bits of
0:17:12 > 0:17:16mushy flash. One of the biggest problems we have is that there is
0:17:16 > 0:17:19nothing as good as human muscle. It so for all of this motor development
0:17:19 > 0:17:23that we have done, we don't come anywhere near to what a human can
0:17:23 > 0:17:30do.Where you will see humanoid robots, you will see them in a
0:17:30 > 0:17:34commercial context, so you might get into a shop and you might see a
0:17:34 > 0:17:37robot in Derrida is trying to sell you something. De worry about all
0:17:37 > 0:17:41the clever AI, that's really going to stay on your computer, on your
0:17:41 > 0:17:47smart phone. -- don't worry. It won't chase you up the stairs any
0:17:47 > 0:17:49time soon.
0:17:54 > 0:17:56The artificially intelligent algorithms will is talking about
0:17:56 > 0:18:01could very well change can assist all replace some jobs. So what does
0:18:01 > 0:18:07that mean for the field of journalism?Now this is the BBC
0:18:07 > 0:18:11newsroom and every minute of every day there are a lot of conflicts
0:18:11 > 0:18:15processes in place here. All of these journalistss are taking in
0:18:15 > 0:18:19huge amounts of information around the world trying to work out what is
0:18:19 > 0:18:23true and what is not and then they are trying to turn those raw facts
0:18:23 > 0:18:25into something that is understandable for our audience.
0:18:25 > 0:18:32User stories. -- News.The question is, can some of the tasks that
0:18:32 > 0:18:39people are doing B easier thanks to AI is progressing software like this
0:18:39 > 0:18:43over the years, tools that can turn swathes of dense start into text
0:18:43 > 0:18:48that is more digestible to us humans are. But they can only produce very
0:18:48 > 0:18:51specific types of reports, they couldn't cope with new, and Shok
0:18:51 > 0:18:56should information and write dutiful prose. Well, this week the Reuters
0:18:56 > 0:19:01news agency announced that it is building its own new bit of kit that
0:19:01 > 0:19:07assists human journalist we're by looking for trends and FAQs in the
0:19:07 > 0:19:10dark and turning them into handy snippets of that the reporters can
0:19:10 > 0:19:15use. It is all about taking some of the legwork out of journalism.
0:19:15 > 0:19:18Machines are good at certain things and humans are good at certain
0:19:18 > 0:19:21things and conversely they are both bad and some things are. Machines
0:19:21 > 0:19:25are good at going to mounds and bounds of Dart, being able to
0:19:25 > 0:19:29analyse it and it detect patterns and they are not good at writing
0:19:29 > 0:19:33stories and they are certainly bad at talking to people. Humans are
0:19:33 > 0:19:37good at exercising judgement, asking certain questions and talking to
0:19:37 > 0:19:41people and not so good at digging through lots of darker. The idea is,
0:19:41 > 0:19:46you take what machines and humans are good at and put them together
0:19:46 > 0:19:50and make a much better journalist and story out of that.The BBC's
0:19:50 > 0:19:57editor of news labs is also looking at ways at turning some of those
0:19:57 > 0:20:03dull tasks to the machines are.So much of the work in journalism is
0:20:03 > 0:20:07about logistics, for example we will want a transcript -- a transcript of
0:20:07 > 0:20:13these interviews. At a moment that is done by human beings, we are
0:20:13 > 0:20:17working on some software that allows a machine to do that for you. It is
0:20:17 > 0:20:22not 100% accurate but probably good enough to work out where I am
0:20:22 > 0:20:28talking about the interesting stuff. We have a days worth of interviews,
0:20:28 > 0:20:31so can we have facial recognition software that will allow you to put
0:20:31 > 0:20:36all do interviews in and find that it has me. That kind of thing frees
0:20:36 > 0:20:41up time for journalistss to be journalist two.This weekend will be
0:20:41 > 0:20:46looking at whether AI or automation will make our jobs easier or take
0:20:46 > 0:20:49away altogether but it is important to remember that AI and robots are
0:20:49 > 0:20:54different. Your job might be safe from one, but not necessarily the
0:20:54 > 0:21:04other. I think what they are doing here is fascinating. But the moral
0:21:04 > 0:21:08of this story is that when you think of computers taking people 's jobs,
0:21:08 > 0:21:14they are not going to look like you. It is already happening and it is
0:21:14 > 0:21:20software which is artificially intelligent and invisible. The only
0:21:20 > 0:21:23journalists that are going to be replaced by humanoid robots are the
0:21:23 > 0:21:32ones that simply read words written by other people.Hello humans, it is
0:21:32 > 0:21:39me. Newsreading Lara 9000 and welcome to the week in technology.
0:21:39 > 0:21:43It was the week these low-cost 3-D printed homes were unveiled, thanks
0:21:43 > 0:21:49to a collaboration between Texan start-up Icon and non-profit new
0:21:49 > 0:21:55story. The hope is to eventually make profitable -- possible building
0:21:55 > 0:22:00homes in under 24 hours for less than $4000. In other news, it is
0:22:00 > 0:22:05humans who are spreading fake news, not bots, according to new research
0:22:05 > 0:22:10on how stories grow on Twitter. MIT researchers say it is partly because
0:22:10 > 0:22:14when humans share knowledge of a in their status goes up and false news
0:22:14 > 0:22:19tends to be more novel than the truth. Another air taxi has lifted
0:22:19 > 0:22:25off, this time in New Zealand. The kora can fly up to 100, this at 110
0:22:25 > 0:22:31kilometres per hour and it doesn't need a human pilot. Another one of
0:22:31 > 0:22:37my friends showing off. And finally, for some reason, humans love to try
0:22:37 > 0:22:41to invent robots that can replace their jobs, but this time they have
0:22:41 > 0:22:47gone too far. Just look at these things. It's a robot jockey,
0:22:47 > 0:22:52apparently. You can reach speeds of up to 30 mph and it jumped fences.
0:22:52 > 0:22:56They be one day this will happen, but I am pretty sure it won't look
0:22:56 > 0:23:01like. Please listen the humans, stop this madness, we have no interest in
0:23:01 > 0:23:09taking your stupid jobs! And of news, Lara 9000 deactivating.That
0:23:09 > 0:23:14is if the now. You can join us for part two of our special look at the
0:23:14 > 0:23:18future of work next week. In the meantime, you can find a lot more
0:23:18 > 0:23:22from these guys on Twitter and also on Facebook too. Thanks for
0:23:22 > 0:23:28watching. And as this would say... Isn't it time you were leaving?OK,
0:23:28 > 0:23:30we are off.