10 Things You Need to Know About the Future Horizon


10 Things You Need to Know About the Future

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Transcript


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If you have ever wondered what's

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going to happen in the future,

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then this is the programme for you.

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Because we're going to be asking

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the kind of questions that we all have

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about our future.

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In this very special edition of Horizon we'll be

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revealing the ten things you definitely need to know that will,

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for better or worse, change our lives.

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We'll explore how artificial intelligence

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will change the way we work.

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Can I enquire, do you have pain in your mouth?

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-Yes, I do.

-I see.

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We'll look at the likely impact of our changing climate.

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It could well top 40 degrees in a few days' time.

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And discover how gene therapy will transform medicine.

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And he said, "There is no evidence of disease.

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"You are cancer-free."

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We'll introduce the people already turning themselves into cyborgs...

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This last year people just shout at me, Pokemon.

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And they try to catch me.

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..ask if renewable energy is here to stay...

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The place to be might not be down here,

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or even up on that hilltop up there.

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It's up there.

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..and reveal how we are mapping our brains...

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It's absolutely astonishing.

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..but jeopardising our very existence.

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What we are doing is removing the ability

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for us to live on this planet.

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We'll also celebrate, finally, the arrival of

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that science fiction cliche, the flying car.

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That's it, that's all it takes.

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So, if you want to know what's in store for you, then keep watching.

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Welcome to the future.

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Now, we are all going to experience the future

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and we all want to know how it will change our lives.

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What's going to be the future of our daily commute?

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What will we spend our money on?

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What's going to happen to our planet?

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Now, over the years, many people have made some pretty bold claims,

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including science fiction legend Arthur C Clarke,

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in an interview that he gave to Horizon in 1964.

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I'm perfectly serious when I suggest a world

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in which we can be in instant contact with each other,

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wherever we may be.

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Where we can contact our friends anywhere on Earth

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even if we don't know their actual physical location.

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It will be possible in that age,

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perhaps only 50 years from now,

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for a man to conduct his business from Tahiti or Bali,

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just as well as he could from London.

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Isn't that incredible? Arthur C Clarke, there, in 1964,

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accurately describing what is effectively the internet age.

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Something, of course, that we all take completely for granted now

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but a world that was totally alien to his audience.

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But, predicting the future is notoriously tricky.

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And while Arthur was bang on the money with that one,

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he didn't stop there. Because here he is with his follow-up prediction.

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The development of intelligent and useful servants

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among the other animals on this planet.

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We could certainly solve the servant problem

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with the help of the monkey kingdom.

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Sorry, come again?

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..solve the servant problem with the help of the monkey kingdom.

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Of course, eventually our super chimpanzees

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would start forming trade unions

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and we would be right back where we started.

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Well, I suppose one out of two ain't bad.

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But it does just go to show that predicting the future

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is usually a mug's game.

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Flying cars, salad-making robots and living in space colonies

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were the embarrassing staples of TV programmes like Tomorrow's World.

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Usually, their earnest predictions were way off.

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But this programme is different.

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And I'm as confident as I can be that these predictions

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aren't going to end up being laughed at by a TV audience in 2050.

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Because we are basing our predictions

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on real data from trusted sources,

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from today.

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And that is why we can confidently tell you that what you're

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about to watch really are the ten things

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that you need to know about the future.

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First up, Dr Kevin Fong on perhaps the biggest question of all.

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How can we cheat death and live longer?

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In the 1980s, if you wanted some constructive advice

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about how to achieve immortality,

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you went to see the film and musical Fame.

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The star of the piece was very clear about her advice,

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"I'm gonna live forever," she told us.

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And she was going to do that by becoming famous

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and living on forever in the memory of her adoring fans.

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And that kind of immortality is all that human beings

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have ever been able to aspire to.

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To be remembered by as many people as possible

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for as long as you possibly can.

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Woody Allen had a very different approach, of course.

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"I don't want to achieve immortality through my work," he said.

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"I want to achieve immortality by not dying."

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And if you want to live for longer, not dying is a great place to start.

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And the good news is that, on average,

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we're living longer today than we ever have in the past.

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But how far can we push that?

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How long can we expect to live in the future?

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Now, births and deaths are one thing that we have quite a lot of data on

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here in the UK. And here is some of that data.

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This shows you how our life expectancy has changed

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over the last 170 years or so.

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Now, Kevin Fong, welcome back to the studio.

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As a doctor, help me make some sense of these numbers.

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Well, I think this is all fascinating data.

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When you look at it, this is average life expectancy which, for almost

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the whole of human history,

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languishes around here, around 40-45 years.

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And then you hit the start of the 20th century.

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You get this massive kick.

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Why? Well, it's all prevention.

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It's all about stopping the things that kill you early on in life

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shortly after you've been born, like measles, mumps, rubella.

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It's all about stopping the diseases of infection.

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And that is achieved through vaccination and better sanitation.

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So that's what explains this big kick and these early gains here.

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So this bit really is all about sort of child mortality?

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Yep. Prevention is always better than cure, and that was vaccination.

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But it continues to go up past then. What about this bit over here?

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So this kick up the top here is us getting better at

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advanced modern medicine.

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So we have better lifestyles,

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but also we get better at treating diseases like heart disease and also

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cancer, so that gives us a bit of an extra gain here.

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So we still see increases all the way through.

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And then what about going forward to the future, then?

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Will this continue to increase?

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Is there a limit to how long we can live for?

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It would be lovely, wouldn't it,

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if this line kept going up and up and up to infinity?

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It doesn't look like it.

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It looks like this data plateaus.

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This graph shows that being born in 2011

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gives you a very high average life expectancy.

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But in terms of maximum possible age,

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you're no better off than your early Victorian ancestors.

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There's a fundamental limit, it would appear,

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at least at the moment, around 110, 120 years,

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to which we seem to be limited.

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If we want to improve things, and who doesn't,

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we could do a lot worse than to investigate the naked mole rat.

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It lives at least ten times longer than other rats.

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In human terms, that's a potential lifespan of upwards of 700 years.

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As it happens, we actually have a naked mole rat expert

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here in the studio with your mole rats.

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Welcome to the studio, Chris Faulkes.

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Tell me about these amazing creatures.

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Well, naked mole rats,

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just about everything about their biology

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is weird and wonderful and exceptional.

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And recently they've been generating a lot of interest

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because of their extreme longevity.

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Which can be... We don't know the upper limit, but more than 30 years.

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Gosh. Cos I guess a rat only lives, what, two or three years,

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-maybe at the most.

-Yeah, exactly.

-And these live to 30, did you say?

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Yeah. And counting.

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Wow. And do they get old in that time?

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Well, this is really the remarkable thing.

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Because not only do they have a long lifespan,

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but their health span is very long,

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which means that they go through a huge proportion of their life

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without showing any signs of ageing whatsoever,

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like an 80-year-old having the body of a 30-year-old.

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-Well, that would be nice, wouldn't it?

-It sure would.

-So, why is that?

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What is it about them that means that they have that feature?

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Well, it seems that it's not a single thing,

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but there's a whole mosaic of adaptations

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that have given them very low metabolic rate,

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a low body temperature, there's resistance to cancer,

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and a whole bunch of other things

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which all collectively give them

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this really long lifespan and health span.

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So, do they not get cancer?

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There's been virtually no recorded cases.

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As opposed to lab mice, for example, where 70% will die of cancer.

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Wow. Gosh, that's extraordinary.

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So what is it about them that means that they don't get cancer?

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There's a substance in the skin called hyaluronan that we all have.

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These guys have a very special version of that substance,

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which we think is what gives them their really elasticky skin,

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which is useful when you're living in tight tunnels.

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And this hyaluronan is implicated in one part of their cancer resistance.

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How stretchy is their skin?

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It's pretty stretchy.

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Do you want me to see if I can demonstrate?

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Yeah, go on, why not, let's have a look.

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They'll probably all go running off.

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And this sort of stretchy substance is one of

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the things that protects them against... Oh, my goodness.

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Yeah, so, there we go, they don't mind

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being picked up like this at all as you can see.

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The animal's quite relaxed. But see how really elasticky the skin is.

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Incredible. My goodness me.

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Let me just pop him back there. There we go.

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-And he's quite happy.

-Yeah, no problem.

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He has made a run for it, though.

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-Yes.

-Well, I guess the question is, really,

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how do we get that substance in ourselves?

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As labs around the world have been studying

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the genomes of naked mole rats,

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we're finding a whole bunch of

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candidate genes that are responsible,

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perhaps, for their longevity.

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And, you know, their health span, as well.

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And potentially apply them to ourselves.

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That could well be the case, I think.

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-It's not beyond the realms of possibility.

-Wow.

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So, what you need to know about the future of lifespan is this.

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The good news is that we are likely to live longer on average.

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But, until we crack the secrets of the mole rats' longevity,

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it does seem that our luck, on average,

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runs out just after the telegram from the Queen arrives.

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Right now, one in four of us is likely

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to be affected by mental health issues at some point in our lives.

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But when it comes to effective treatment,

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mental health really does lag behind other diseases.

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So, what does the future hold for our state of mind?

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Now, there is a very big incentive to answer this question.

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And it's because mental health issues

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are the number one cause of people being unable to work.

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So this graph here from 2010 shows

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the amount of money lost by people not being able to work

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with different diseases.

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And the results here are shown in trillions of dollars.

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But the exact numbers here aren't really the story.

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The story is that mental health illness

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really does top the pile here.

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Beating both cardiovascular disease

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and also cancer, just there.

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And if current trends continue,

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then the World Health Organization has made some predictions

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for what we can expect by 2030.

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And you can see things really are set to get a lot worse.

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And what's particularly bad about mental health illness

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is that it really is the disease

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that people end up living with for the longest.

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So this graph here shows you how long

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people live with different kinds of illness,

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so you can see unintentional injuries just there.

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There's cardiovascular diseases down there.

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And once again, mental health disorders and neurological disorders

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really are very much out in front.

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So what is being done to help understand the brain and to

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improve these things?

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Well, Michael Mosley has been to visit

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a research project in London to find out.

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The human brain is the most complex object in the known universe.

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And for a long time its workings were a complete mystery.

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Then, in the 19th century,

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scientists identified that some of our abilities,

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like being able to speak

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are linked to particular regions of the brain.

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But an awful lot of what goes on up here is not to do with regions.

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It's absolutely to do with connections.

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If your brain isn't properly wired up,

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then this puts you at greater risk of things like dementia,

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schizophrenia and, early in life, autism.

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Autism is the result of changes in the way

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that the brain processes information.

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By studying these physical changes,

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it's hoped new light will be shed on the workings of the whole brain.

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Here, at Evelina London Children's Hospital,

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a team from King's College London are looking at

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brain development in babies, using MRI scanners.

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Hello, my name is Anna, I'm one of the radiographers, OK?

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Even before they're born.

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I've never seen an MRI of a foetus.

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-That is amazing.

-It is amazing.

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It is absolutely astonishing.

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I mean, what's really amazing about it,

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it's relatively easy to get one quick flash through a scan

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but collecting all of the slices

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to make a three-dimensional reconstruction is the hard bit.

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This is a 3-D model made from one of the images of a baby who is about

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three months early. And as you can see, it's very small.

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It's very smooth, it's very underdeveloped.

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It has a lot more growing to do.

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And this is the baby who's about term,

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and the growth that has to happen

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between there and there is phenomenal.

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As the brain grows, more and more connections are made inside.

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And the team is able to identify that wiring

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using two kinds of MRI scanning.

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I have to say, I'm still blown away by those images.

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I don't know what I was expecting,

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but I wasn't expecting something as clear as that.

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I think, to be honest, we're blown away by the images.

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Once the MRI data is processed,

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it's translated into a basic map of connections,

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showing which parts of a baby's brain can talk to each other.

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These are much better than the images we used to get in the past.

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And the information content has gone up massively.

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At birth, the brain already has about 100 billion neurons.

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And each one is connected to thousands of others.

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So the brain's wiring diagram is enormously complex.

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Nonetheless, researchers have started to decipher it.

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The resulting map is called the connectome.

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And while everyone's individual connectome is unique,

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the hope is the average data will give us useful information

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about how all our brains work.

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So, one of the major uses for this is to define the connectome.

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Now, we obviously can't have all the connections in the brain because

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we're not looking at single nerve fibres.

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But we can get a pretty good idea of what that connection map would be.

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I think of it as being a bit like the Tube map of London.

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You can't find an individual road on the Tube map but you can find your

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way round London on it.

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Connectome studies around the world are gathering data

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in a bid to understand a whole range of mental health conditions

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and brain disorders.

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There's autism and ADHD at the beginning of life.

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Then psychoses like schizophrenia.

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Finally, as the level of connectivity deteriorates

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in the ageing brain, dementia.

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I do think that mapping the connectome

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could be the next big thing in our understanding of the brain.

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And that's important, not just because

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it will increase our knowledge of a normal brain,

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but it could also lead to better treatments when things go wrong.

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And now to our national obsession - the weather.

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We live, so we're told, in dangerous times.

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Planet Earth is getting hotter and that is going to change our climate,

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and there is a lot of data around this point.

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So here, for instance,

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is a map of what's happened around the world in the last 130 years,

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compared to an average in the middle of the 20th century.

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And as you're in the sort of '20s and '30s you can see a lot of blue

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and white on this map, the odd splodge of orange

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comes in every now and then.

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But, as time rolls on and we get closer to now,

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these orange splodges end up connecting to each other

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and we see some red coming in, in the north up there.

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Now, this effect actually is very extreme.

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2016, for instance,

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was the hottest year on record that the Earth has ever had.

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But what about if we go a bit further back in time?

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So this graph here shows you the global temperature

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for the last 11,000 years.

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Now it's certainly true that we have had

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changes in temperature before.

0:17:310:17:32

There's an ice age just here, a little hot patch just there,

0:17:320:17:36

about the same as we have now.

0:17:360:17:38

Another little mini ice age just there.

0:17:380:17:40

But what is important about this graph

0:17:400:17:43

is this section that we have just over here.

0:17:430:17:45

Because this here,

0:17:450:17:46

isn't a little flag pointing downwards to the data,

0:17:460:17:51

this line IS the data.

0:17:510:17:53

The changes that we've seen in global temperature recently

0:17:530:17:57

are so quick and so dramatic

0:17:570:17:58

that on this graph of 11,000 years,

0:17:580:18:00

it looks like a straight line going upwards.

0:18:000:18:03

And in fact, if this trend continues,

0:18:030:18:06

we expect to see the global temperature ending up looking

0:18:060:18:09

something like this as we move forward in time.

0:18:090:18:11

But the trouble is that we have heard a lot of this before.

0:18:110:18:15

And nothing really seems to change.

0:18:150:18:17

It doesn't feel like it's getting any warmer.

0:18:170:18:19

But there are some people out there who have already noticed the changes

0:18:190:18:23

that global warming is having, literally in their own backyard.

0:18:230:18:27

And weatherman Peter Gibbs is one of them.

0:18:270:18:30

Gardeners are ruled by the seasons, that annual cycle of sowing,

0:18:410:18:46

growing and harvesting.

0:18:460:18:47

But global warming has put a spanner in the works,

0:18:490:18:52

because spring now arrives

0:18:520:18:54

a few days earlier with every passing decade.

0:18:540:18:57

For a start, that means I need to start

0:19:010:19:03

mowing the lawn earlier in the year.

0:19:030:19:05

And while I used to retire the mower for the winter in, say,

0:19:050:19:09

late September, it's now not unusual to

0:19:090:19:12

cut the grass as late as November.

0:19:120:19:14

The growing season is the best part of six weeks longer

0:19:170:19:20

than it was before climate change kicked in.

0:19:200:19:22

Which is great if you want to grow grapes.

0:19:220:19:24

I'm getting a decent crop most years now.

0:19:240:19:26

Problem is, because it's all developing so much earlier

0:19:260:19:30

in the spring, that extends, surprisingly,

0:19:300:19:32

the season over which these little baby grapes

0:19:320:19:36

can actually be hit by a rogue frost.

0:19:360:19:39

The effects of climate change are frustratingly complicated.

0:19:420:19:45

It varies from one kind of plant to the next.

0:19:450:19:49

In winter, apple trees and blackcurrant bushes are dormant,

0:19:490:19:52

storing up energy reserves for the spring.

0:19:520:19:55

But as British winters get steadily warmer,

0:19:570:19:59

that chilling time will be cut short,

0:19:590:20:02

resulting in poor flowering and a lack of fruit.

0:20:020:20:06

The effects of climate change are already pretty apparent,

0:20:090:20:12

and that's with just a one-degree rise in temperature.

0:20:120:20:15

Trouble is, temperatures are expected to keep on rising.

0:20:150:20:19

If and when that happens, the impact will be even more dramatic.

0:20:190:20:24

Higher temperatures mean melting ice.

0:20:240:20:27

And here is what has been happening to Arctic sea ice since 1980.

0:20:270:20:31

It's been reducing at the rate of 13% per decade.

0:20:310:20:35

It's not just the sea ice, though.

0:20:350:20:37

Melting ice caps means rising sea levels, too.

0:20:370:20:41

And climate scientists have run some mathematical models to try and

0:20:410:20:44

predict what that will mean for us on land.

0:20:440:20:47

So, if all of Greenland melts, which admittedly would be quite dramatic,

0:20:470:20:51

but that would have a six metre change in the level of the sea.

0:20:510:20:55

And this is what Europe would look like as a result.

0:20:550:20:58

Holland - not looking great for Holland.

0:20:580:21:00

Norfolk also very badly hit.

0:21:000:21:02

And London too.

0:21:020:21:03

And over the other side of the Atlantic,

0:21:030:21:05

this is what would happen to Florida.

0:21:050:21:08

Quite a lot of it would end up being completely underwater,

0:21:080:21:12

including Cape Canaveral, just there.

0:21:120:21:14

You're going to need a new place to try and launch the rockets from.

0:21:140:21:17

But the big question is,

0:21:170:21:19

is our weather here in the UK going to be affected

0:21:190:21:21

by all of this in the future?

0:21:210:21:23

Now, I'm not a meteorologist, but happily Peter Gibbs, who is,

0:21:230:21:27

has rushed back from his garden to the BBC Weather Studio,

0:21:270:21:30

where he has prepared a weather forecast for 2050.

0:21:300:21:34

Hello, and welcome to Weather 2050.

0:21:340:21:37

Well, the usual floods and saturated ground that we saw during the winter

0:21:370:21:40

months are just a distant memory for most of us now,

0:21:400:21:43

as we see the familiar signs of

0:21:430:21:45

developing drought now that the summer heat has really kicked in.

0:21:450:21:49

And those temperatures are expected to build over the next few days,

0:21:490:21:52

so we'll all be cranking up the air-con, avoiding the daytime heat,

0:21:520:21:56

and struggling to sleep at night.

0:21:560:21:58

And that's certainly true in the south, where we'll hit 35 Celsius,

0:21:580:22:02

not unusual these days, of course.

0:22:020:22:03

We could well top 40 degrees in a few days' time.

0:22:030:22:07

A little bit more comfortable in the north,

0:22:070:22:09

thanks to patchy cloud and a breeze coming in from the sea.

0:22:090:22:12

But still, pretty humid.

0:22:120:22:14

Then eventually that heat will break down into scattered thunderstorms,

0:22:140:22:17

the warmer atmosphere of course able to hold more moisture these days,

0:22:170:22:20

so there will be some really intense downpours.

0:22:200:22:23

Probably won't too much for the droughts, though,

0:22:230:22:25

with the rain just running off the parched ground

0:22:250:22:28

and causing flash flooding.

0:22:280:22:30

So some disruption looks likely.

0:22:300:22:33

What you need to know about the weather of the future

0:22:330:22:35

is that we expect, on average,

0:22:350:22:37

the north to become warmer and wetter,

0:22:370:22:39

and in the south, hotter and drier.

0:22:390:22:42

But across the whole country,

0:22:420:22:43

weather patterns will become a lot more variable, with bigger extremes.

0:22:430:22:47

So whoever is doing the forecast then

0:22:470:22:49

will have a much more difficult job than I've had.

0:22:490:22:53

When it comes to the future of health care,

0:22:580:23:00

past triumphs give us good reason to be optimistic.

0:23:000:23:04

But what about the big C?

0:23:040:23:06

Now, a cure for cancer is something we'd all like to happen,

0:23:060:23:09

but how realistic a hope is that?

0:23:090:23:12

Well, in the year 2000,

0:23:120:23:13

Bill Clinton and Tony Blair announced a very big breakthrough.

0:23:130:23:18

We're here to celebrate the completion

0:23:190:23:22

of the first survey of the entire human genome.

0:23:220:23:25

Without a doubt, this is the most important,

0:23:250:23:27

most wondrous map ever produced by humankind.

0:23:270:23:32

Well, in just 50 years after the discovery of the structure of DNA,

0:23:320:23:37

teams from the US and the UK between them

0:23:370:23:39

had mapped all of the genes contained in us.

0:23:390:23:43

Now, the Human Genome Project, said Bill and Tony,

0:23:430:23:46

would cure all human suffering.

0:23:460:23:48

The blind would see, the lame would walk,

0:23:480:23:50

and cancers would be a thing of the past.

0:23:500:23:53

Well, Bill and Tony are now distant memories.

0:23:530:23:56

But what happened to the genome and its bid to end all suffering?

0:23:560:24:01

Geneticist Giles Yeo went to New York to find out.

0:24:010:24:04

Half of us will be diagnosed with cancer at some point in our lives.

0:24:130:24:18

The problem with cancer is that our body's defences

0:24:180:24:20

does not recognise it as a threat.

0:24:200:24:23

Our immune systems have evolved to distinguish between our

0:24:230:24:26

own bodies and those of foreign invaders,

0:24:260:24:29

such as bacteria and viruses.

0:24:290:24:31

But cancer is simply a mutated version of our own cells,

0:24:310:24:34

so it doesn't carry the typical characteristics

0:24:340:24:37

of an invading organism.

0:24:370:24:39

So our immune system doesn't recognise it, attack it and kill it.

0:24:390:24:43

In 2011, Karen was diagnosed with

0:24:460:24:49

a form of blood cancer called leukaemia.

0:24:490:24:51

It's caused by the uncontrolled production

0:24:530:24:55

of abnormal white blood cells.

0:24:550:24:57

Karen lived with the disease for three years.

0:24:590:25:02

But in 2014, she took a turn for the worse,

0:25:030:25:08

and was given two years to live.

0:25:080:25:10

That was brutal. Your brain is just going, "Oh, my God,

0:25:110:25:15

"now I have this nuclear bomb in my body.

0:25:150:25:18

"And it's going to kill me."

0:25:180:25:21

But Karen was offered a lifeline.

0:25:230:25:24

'In an experimental new treatment,

0:25:260:25:28

'Dr Michel Sadelain is able to hack the immune system

0:25:280:25:32

'and equip it with the ability to fight back.'

0:25:320:25:34

So in many cancers, as in Karen's cancer,

0:25:360:25:39

the immune system on its own is not capable of taking over the tumour.

0:25:390:25:44

It needs a little help.

0:25:440:25:46

Michel's target is a type of white blood cell called a T-cell.

0:25:470:25:50

These are the foot soldiers of the immune system,

0:25:510:25:54

whose purpose is to attack viruses and bacteria.

0:25:540:25:57

The first step was to collect some of Karen's T-cells.

0:25:580:26:01

And there a team of scientists and technicians

0:26:020:26:05

insert into those T-cells into a gene, a synthetic gene,

0:26:050:26:11

that provides this instruction to the T-cell which says,

0:26:110:26:14

"Recognise the cancer, seek it out and destroy it."

0:26:140:26:18

Michel used a virus to get the new gene into Karen's T-cells.

0:26:180:26:22

The T-cells were then infused back into Karen's bloodstream.

0:26:220:26:26

He's had some remarkable success with this technique.

0:26:260:26:29

The first clinical results showed a dramatic effect

0:26:290:26:33

in a majority of patients -

0:26:330:26:36

about 85% of these patients went into

0:26:360:26:39

what we call a complete remission.

0:26:390:26:43

Michel has treated about 100 patients using this technique.

0:26:440:26:47

Karen was one of the first.

0:26:480:26:50

Never did we expect what we were going to hear.

0:26:510:26:53

And he said, "There is no evidence of disease, you are cancer-free."

0:26:530:26:59

So what was it like to hear the doctor say, "You are cancer-free?"

0:26:590:27:02

It was unbelievable.

0:27:040:27:05

I still get... I obviously get emotional about it.

0:27:070:27:10

Because we didn't expect it.

0:27:110:27:13

For Karen, the results of the trial have been incredible.

0:27:130:27:16

I mean, they have saved her life.

0:27:160:27:18

But that's only half the story.

0:27:180:27:20

You know, because the technique doesn't always work,

0:27:200:27:23

and bespoke gene editing for every single patient,

0:27:230:27:25

it's just unrealistic.

0:27:250:27:27

It is expensive, it is complex, it is lengthy.

0:27:270:27:30

And patients have been known to die waiting

0:27:300:27:32

during the intervening period for their cells to be re-engineered.

0:27:320:27:36

The answer is a new technique called Crispr.

0:27:370:27:40

Crispr stands for Clustered Regularly Interspaced Short Palindromic Repeats,

0:27:400:27:46

which describes a property of bacterial DNA

0:27:460:27:49

that scientists have been able to exploit -

0:27:490:27:52

giving them, for the first time,

0:27:520:27:54

ultimate accuracy in gene editing.

0:27:540:27:56

What Crispr gives you is a pair of tweezers for you to be

0:27:560:28:00

able to place the DNA anywhere you want in any cell.

0:28:000:28:04

This new-found precision allows Michel to fix a fundamental problem.

0:28:040:28:10

The problem in taking someone else's T-cells is that those T-cells will

0:28:100:28:14

attack you. Because they will sense that, "It's not my body,

0:28:140:28:18

"it's not my molecules, I have to go on the attack."

0:28:180:28:22

So what Crispr Cas9 makes possible is the removal of those molecules

0:28:230:28:28

that initiate that attack.

0:28:280:28:30

It means that T-cells could be provided by a donor,

0:28:320:28:35

and can be genetically engineered to only attack the cancer.

0:28:350:28:38

From one donor,

0:28:390:28:41

you could make cells that could be administered to multiple recipients.

0:28:410:28:45

These cells would then be ready, and in pharmacies.

0:28:460:28:51

And now, we preserve them.

0:28:510:28:54

We may someday have pharmacies of T-cells, frozen vials of T-cells,

0:28:560:29:00

ready-made, ready for injection.

0:29:000:29:02

So there's the living drug.

0:29:020:29:05

Fast asleep in liquid nitrogen.

0:29:050:29:08

That's fantastic.

0:29:080:29:09

And this would make this form of therapy

0:29:090:29:11

accessible to many more individuals.

0:29:110:29:14

Donor T-cells have yet to be trialled in humans.

0:29:160:29:20

But the idea offers hope that in the future,

0:29:200:29:23

many more people could be treated.

0:29:230:29:24

We are now entering an unprecedented era of progress for gene therapy.

0:29:260:29:30

And we're not just talking about cancer,

0:29:300:29:31

because Crispr is now being used to treat muscular dystrophy,

0:29:310:29:34

and it's being talked about as an alternative to antibiotics.

0:29:340:29:38

What you need to know about the future is

0:29:380:29:40

that the Human Genome Project

0:29:400:29:42

may finally be delivering on its promise

0:29:420:29:44

to revolutionise the way we treat disease.

0:29:440:29:47

And now, work.

0:29:530:29:54

What will you be doing as a job in the future?

0:29:540:29:57

Well, 50 years ago, the world of work was pretty easy to understand.

0:29:570:30:00

You either did manual work,

0:30:000:30:02

which basically meant supervising machines.

0:30:020:30:05

Or you worked in an office,

0:30:050:30:07

which basically meant doing a lot of typing,

0:30:070:30:09

or getting somebody else to do a lot of typing for you.

0:30:090:30:11

Bottom line, people were integral to the workforce.

0:30:110:30:15

But no more.

0:30:150:30:17

Because, in the 1970s, machines got clever.

0:30:170:30:20

Car plants were filled with robots,

0:30:200:30:23

helplines were answered by computers,

0:30:230:30:25

and almost all bank clerks became extinct.

0:30:250:30:28

But I suspect that most of you are saying,

0:30:280:30:30

"Well, a robot couldn't possibly take my job."

0:30:300:30:33

But are you sure?

0:30:330:30:35

Have a look at this.

0:30:350:30:36

We sent Dr Zoe Williams to check out

0:30:380:30:40

a piece of software which is rumoured

0:30:400:30:42

to diagnose illnesses faster and more accurately

0:30:420:30:46

than human medical professionals.

0:30:460:30:49

So, should I be worried, as a GP?

0:30:490:30:52

The thought that a robot or artificial intelligence

0:30:520:30:55

could take my job just seems crazy.

0:30:550:30:58

I mean, I've spent six years at medical school,

0:30:580:31:01

ten years practising as a doctor.

0:31:010:31:03

Now, surely all of that can't be boiled down to a few lines of code?

0:31:030:31:06

Babylon Health are a medical tech company.

0:31:100:31:13

They've just received 60 million of funding

0:31:140:31:17

to develop an AI doctor.

0:31:170:31:19

The system works by asking questions.

0:31:210:31:24

But anyone can ask questions.

0:31:240:31:26

If it's going to replace me,

0:31:260:31:28

I really want to put it through its paces.

0:31:280:31:31

I'm going to pose as a patient and give myself an imaginary condition.

0:31:310:31:35

But I'm not going to tell anybody, I'm just going to write it down.

0:31:350:31:39

And then we can see just how accurate the machine really is.

0:31:410:31:44

May I ask, please, what's troubling you today?

0:31:460:31:49

I'm feeling tired all the time.

0:31:490:31:53

So, as well as feeling tired, I've been feeling kind of weak.

0:31:530:31:58

Let's tell the computer that.

0:31:580:32:00

And I've also been feeling...

0:32:010:32:03

..a bit of dizziness.

0:32:040:32:06

Is it OK to ask, "Do you have painful periods?"

0:32:080:32:12

There we go, that's better.

0:32:120:32:13

Painful periods as well.

0:32:130:32:15

Do you get breathless on exertion?

0:32:160:32:18

Yes, I do!

0:32:180:32:20

Thanks, I've noted this.

0:32:200:32:22

So, I've given the computer all of my symptoms now.

0:32:230:32:26

And it's come up with a diagnosis.

0:32:260:32:29

So, let's see if it's correct.

0:32:290:32:31

Here's my bit of paper from earlier.

0:32:310:32:33

And you can see that I have put down fibroids.

0:32:330:32:39

And the computer has said uterine leiomyoma,

0:32:390:32:43

which is actually the same thing.

0:32:430:32:44

That's impressive.

0:32:450:32:47

But how is it done?

0:32:470:32:49

Time to face down the evil genius

0:32:490:32:51

hell-bent on replacing me with my laptop.

0:32:510:32:55

So, you start off with a knowledge base.

0:32:550:32:58

And this is essentially a medical database which contains hundreds of

0:32:580:33:01

millions of medical concepts.

0:33:010:33:03

That's kind of like being at medical school and all the knowledge that is

0:33:030:33:06

inputted into the brain.

0:33:060:33:07

Exactly, so this might be all of the textbooks which you've read at

0:33:070:33:10

medical school, all of the papers which you've read at medical school,

0:33:100:33:14

and then applied to all of that information

0:33:140:33:16

we'll apply a set of methods known as machine-learning methods.

0:33:160:33:19

Machine learning is the ability of computers

0:33:210:33:24

to take vast amounts of data and make sense of it themselves.

0:33:240:33:28

Like this network of medical information,

0:33:300:33:32

which the computer uses to make a diagnosis.

0:33:320:33:35

What these circles represent are diseases,

0:33:360:33:39

-symptoms and risk factors.

-OK.

0:33:390:33:40

And what those lines represent are the relationships between those.

0:33:400:33:43

So, based on that,

0:33:430:33:45

the computer has taught itself actually how strongly related those

0:33:450:33:49

diseases, symptoms and risk factors are.

0:33:490:33:51

OK, so that's how it determines

0:33:510:33:52

the probability is from looking at past real-life cases?

0:33:520:33:56

Absolutely, and that's why this is machine learning.

0:33:560:33:59

As the network learns about more and more symptoms and diseases,

0:34:020:34:06

it's tested and refined by a team of doctors and programmers.

0:34:060:34:10

It's early days,

0:34:120:34:13

but the company sees a big future for their virtual medic.

0:34:130:34:16

We want to do with health care what, say, Google did with information.

0:34:170:34:20

It'll be in your phone, it'll be in the devices you carry with you.

0:34:200:34:25

Do you think that a machine could ever replace my role as a GP?

0:34:250:34:30

I don't think this is a competition between machines and humans.

0:34:300:34:34

This is machines being an aid to humans.

0:34:340:34:38

Half of the world's population has no access or very,

0:34:380:34:41

very little access to doctors.

0:34:410:34:43

Right? Imagine if you could see so many more because the machines do

0:34:430:34:47

the easier part, they save your time.

0:34:470:34:50

But can a machine put its hand on your shoulder and say, "Trust me,

0:34:500:34:54

"I'll look after you?" That's a different story.

0:34:540:34:56

It's not just in medicine that software's on the march.

0:34:580:35:02

In banking, AI is approving or not approving loan applications.

0:35:020:35:07

And even making investment decisions.

0:35:070:35:09

And, with autonomous vehicles on the horizon,

0:35:100:35:13

many who drive for a living will soon be superseded.

0:35:130:35:17

What you need to know about the future

0:35:190:35:21

is that no job is immune from the influence

0:35:210:35:23

of artificial intelligence.

0:35:230:35:24

If it doesn't take your job,

0:35:240:35:26

then it's likely to change the way in which you do it.

0:35:260:35:29

Now, whenever we think about the future,

0:35:350:35:37

however outlandish we imagine our housing,

0:35:370:35:40

our transport or our gadgets to be,

0:35:400:35:42

one thing that we never seem to question is that

0:35:420:35:44

there will always be a constant supply of electricity.

0:35:440:35:48

But if you look at the data, that's not necessarily a safe assumption.

0:35:480:35:51

So here is what's been happening in the UK

0:35:510:35:54

over the last 100 years or so.

0:35:540:35:55

And in the 20th century,

0:35:550:35:57

we've become very dependent on fossil fuels.

0:35:570:36:00

So you can see coal here in purple,

0:36:000:36:01

gas in blue coming in slightly later,

0:36:010:36:03

and then a bit of oil there throughout.

0:36:030:36:05

Now, there's a bit of nuclear there in red,

0:36:050:36:08

which has stayed pretty constant over time.

0:36:080:36:10

And some renewables coming in much later in green.

0:36:100:36:13

But the main story from this graph

0:36:130:36:15

is that we are very dependent on fossil fuels to heat our homes,

0:36:150:36:20

provide our transport and to generate our electricity.

0:36:200:36:23

Now, if you look at the picture globally,

0:36:230:36:26

the demand has been steadily increasing over time.

0:36:260:36:29

So you can see a little blip here for the 2008 financial crisis.

0:36:290:36:33

But generally speaking, the trend has been upwards.

0:36:330:36:35

And if this trend continues, then over the next 50 years,

0:36:350:36:39

we can expect the demand for energy consumption to increase by 48%.

0:36:390:36:44

But the trouble is, burning fossil fuels is pretty bad for the planet.

0:36:440:36:48

And in any case, we're going to run out of oil at some point anyway.

0:36:480:36:52

So the question is, how do we keep the lights on

0:36:520:36:55

while helping to save the planet?

0:36:550:36:57

So, we sent physicist Helen Czerski

0:36:570:36:59

to a place where they've already done it.

0:36:590:37:01

I'm in Norway, and this stunning country

0:37:150:37:17

is one of the world's biggest producers of renewable energy.

0:37:170:37:21

Almost all of their electricity comes from hydropower.

0:37:210:37:24

And government incentives mean that electric vehicles like this one are

0:37:240:37:27

becoming more and more common.

0:37:270:37:30

Relying on hydropower is fine if

0:37:300:37:32

you've got plenty of mountains and lakes.

0:37:320:37:35

But what about the rest of the world?

0:37:350:37:37

In the UK, just under half of our renewable energy

0:37:370:37:40

comes from wind turbines. But in spite of that,

0:37:400:37:43

wind energy only contributes 11% of our total electricity generation.

0:37:430:37:48

Part of the problem is finding enough places with strong winds.

0:37:530:37:57

But perhaps there are some other opportunities.

0:37:580:38:01

This is data from the University of Reading

0:38:010:38:03

showing typical wind speeds in this area.

0:38:030:38:05

And you can see that down here near the ground,

0:38:050:38:07

the wind speeds are almost always really low.

0:38:070:38:10

But as you go up, the wind speeds go right up.

0:38:100:38:13

And what that suggests is that if you are serious about wind energy,

0:38:130:38:17

the place to be might not be down here,

0:38:170:38:19

or even up on that hilltop up there.

0:38:190:38:21

It's up there.

0:38:210:38:23

That's exactly what engineer Dr Lode Carnel is doing

0:38:250:38:30

with this tiny plane he calls kitemill.

0:38:300:38:33

Kitemill is designed to fly in the high-altitude winds.

0:38:330:38:37

The force of the wind will cause it to pull on the tether,

0:38:390:38:43

and that generates electricity.

0:38:430:38:44

So, the tether's out, the kite's been assembled,

0:38:480:38:51

and it's ready to launch.

0:38:510:38:52

So the next step is to get it up into the air.

0:38:520:38:54

Here we go!

0:38:540:38:55

It's tiny in the sky.

0:39:070:39:09

It looks so, so small.

0:39:090:39:10

The idea that that could generate any energy at all

0:39:100:39:14

is really quite weird.

0:39:140:39:15

And it's fast, wow! Look at that!

0:39:160:39:19

So, the kite's up in the sky and it's doing two things.

0:39:190:39:22

It's either sitting flat, or it's going round and round in circles.

0:39:220:39:26

What are the circles about?

0:39:260:39:28

Yes, so when the system is located on the ground,

0:39:280:39:30

we need to take it up to a certain altitude,

0:39:300:39:33

and then it will fly in a circle, a pattern that we now see,

0:39:330:39:36

during which it can produce electricity.

0:39:360:39:38

Once the plane is high enough,

0:39:400:39:42

it glides upwards into a corkscrew pattern,

0:39:420:39:45

pulling on the tether.

0:39:450:39:47

So, here we have the ground station where we generate the energy.

0:39:480:39:51

You have the drum, where the tether is wound around.

0:39:510:39:55

But it is connected directly to a

0:39:550:39:57

motor or a generator, which is on the back.

0:39:570:39:59

So, when we wind off, the motor turns in one direction

0:39:590:40:02

and produces energy.

0:40:020:40:03

And so how much energy is this generating at the moment?

0:40:050:40:08

Two kilowatts roughly now,

0:40:090:40:11

which is roughly the consumption of one family in the UK.

0:40:110:40:14

Our next model has a capacity of 30 kilowatts.

0:40:140:40:17

That can power automatically 20 families in the UK.

0:40:170:40:20

However, this is not the end.

0:40:200:40:22

We need to scale up.

0:40:220:40:23

We want to produce energy with the lowest possible cost.

0:40:230:40:25

So then we are talking 500 kilowatts,

0:40:250:40:29

and that will be sufficient to power 300-400 families in the UK.

0:40:290:40:33

Once it reaches the end of its tether,

0:40:350:40:38

5% of the energy it's generated is used to reel it back in,

0:40:380:40:43

and the process starts again.

0:40:430:40:44

The plan is for the plane to stay up indefinitely, but this test is over,

0:40:460:40:51

so the plane is brought back in to land.

0:40:510:40:53

It's hard to imagine it working in the airspace

0:40:550:40:58

above our already crowded cities.

0:40:580:41:01

But it could have advantages in remote locations

0:41:010:41:04

and in developing countries.

0:41:040:41:06

And you can put it in places where you can't put a wind turbine.

0:41:070:41:10

That's important, isn't it?

0:41:100:41:12

This can extract energy from places

0:41:120:41:13

that are not accessible at the moment.

0:41:130:41:15

Correct, places where there is for example low wind speeds close to the

0:41:150:41:19

ground, but higher wind speeds at higher altitudes could use this

0:41:190:41:22

technology. Also, it's quite movable.

0:41:220:41:24

It's a flexible technology, so one truck can come,

0:41:240:41:27

and you can install everything.

0:41:270:41:28

Contrary to windmills,

0:41:280:41:29

where you need a lot of infrastructure and so on.

0:41:290:41:33

Kitemill alone isn't the answer to our energy crisis.

0:41:360:41:39

Power will have to come from a range of renewable sources.

0:41:430:41:46

I'm optimistic about the future

0:41:480:41:50

because I see lots of new technologies

0:41:500:41:51

like kitemill coming along,

0:41:510:41:53

each appropriate at a specific place or in a specific time.

0:41:530:41:57

And together, these are the building blocks

0:41:570:41:59

that will let us design a much more sophisticated energy future.

0:41:590:42:02

A lot of people look to science fiction

0:42:080:42:11

for a steer on what's going to happen in the future.

0:42:110:42:14

And if sci-fi tells us one thing,

0:42:140:42:16

it's that the future is littered with cyborgs.

0:42:160:42:19

Now, the idea of some kind of human-machine hybrid is certainly an

0:42:190:42:23

interesting one, and it's been explored in a number of different TV

0:42:230:42:27

programmes, from Six Million Dollar Man

0:42:270:42:29

all the way through to Star Trek.

0:42:290:42:31

But so far, the reality hasn't quite managed

0:42:310:42:34

to measure up for most of us.

0:42:340:42:36

Now, is that a relief, or an opportunity missed?

0:42:360:42:39

My name is James Young.

0:42:510:42:53

And I am a cyborg.

0:42:550:42:57

OK, and relax.

0:42:590:43:02

Terrible.

0:43:050:43:07

Taking a load off here.

0:43:080:43:10

Just over five years ago, I lost an arm and a leg in a train accident.

0:43:100:43:14

While I was coming to terms with the loss of my arm,

0:43:160:43:19

I won a competition to have something different made.

0:43:190:43:21

Yeah.

0:43:240:43:25

It's not great!

0:43:270:43:28

It was created to be more of an art piece,

0:43:330:43:36

so it was like a prototype from the day it was made.

0:43:360:43:38

It's got the lights that work and the hand...

0:43:400:43:43

four of the digits work on the hand, so it's kind of like...

0:43:430:43:45

..it's trying, it's trying its best,

0:43:470:43:49

but it's not in tiptop condition, basically.

0:43:490:43:52

My brief taste of being a cyborg has left me wanting more.

0:43:560:43:59

I'm now looking at prostheses that attach

0:44:000:44:03

directly to my skeleton and nervous system.

0:44:030:44:05

If I can replace my old abilities,

0:44:080:44:10

then can I go a step further and gain new ones?

0:44:100:44:13

The idea of expanding my abilities beyond

0:44:140:44:18

the human baseline is something that really, really intrigues me.

0:44:180:44:22

And because I almost studied cybernetics when I was considering

0:44:220:44:25

university, and it's a field that

0:44:250:44:26

everybody's kind of thinking about now,

0:44:260:44:28

because you get Elon Musk starting up initiatives to find, like,

0:44:280:44:32

a neural lace that would enhance human abilities

0:44:320:44:34

to kind of compete with AI and computing.

0:44:340:44:36

If you're really serious about becoming a cyborg,

0:44:380:44:41

tapping into the brain is the way you have to go.

0:44:410:44:43

There's been a lot of research into this.

0:44:450:44:47

Some brains have already been linked to a variety of devices in a bid to

0:44:470:44:51

help people with disabilities.

0:44:510:44:52

But I'm going to meet someone

0:44:540:44:55

who's hacked their brain in a different way.

0:44:550:44:58

At age 11, Neil Harbisson was diagnosed with

0:45:000:45:03

a condition called achromatopsia.

0:45:030:45:05

A form of total colour blindness,

0:45:050:45:08

meaning Neil has only ever seen in grayscale.

0:45:080:45:10

But in 2003, as part of an art project,

0:45:130:45:16

Neil found a new way to perceive colour.

0:45:160:45:18

By integrating technology into his skull.

0:45:190:45:21

He can now hear colour.

0:45:230:45:25

Could you explain how your antenna works front to back?

0:45:270:45:30

-What's it...

-Well, I thought that I should have a new body part,

0:45:300:45:33

a new sensory organ, specifically for colour perception.

0:45:330:45:37

So the light frequency goes inside the antenna,

0:45:370:45:40

and then it touches a chip inside my bone that vibrates,

0:45:400:45:43

so these vibrations in my head create inner sounds,

0:45:430:45:47

so I can hear different notes for different colours.

0:45:470:45:49

We created an app that tries to mimic

0:45:490:45:52

the sounds that I hear for each colour. So you'll notice...

0:45:520:45:56

HUMMING AND WHIRRING

0:45:560:46:00

This is the sound of yellow.

0:46:000:46:02

Cool.

0:46:020:46:04

HIGH-PITCH PULSE

0:46:050:46:09

-So it's kind of like...

-Pink is a higher frequency.

0:46:090:46:11

..a frequency shift.

0:46:110:46:12

FAST-PACED BEEPS

0:46:120:46:16

This is the sound of my jacket.

0:46:160:46:18

So I'm wearing electronic music!

0:46:180:46:19

So, with your antenna, is it kind of like when you have a new watch and

0:46:210:46:24

you have to become used to

0:46:240:46:25

the weight and feel of it when you're moving around?

0:46:250:46:28

I'm not using or wearing technology - I am technology.

0:46:280:46:33

So that's the difference.

0:46:330:46:34

I guess it's... I can't compare it with anything else,

0:46:340:46:38

because it's part of my skeleton.

0:46:380:46:41

Meeting Neil has given me an insight into what it might be like to have

0:46:430:46:46

genuine cyborg abilities.

0:46:460:46:47

What has it been like, you being in the public with your extra sense?

0:46:500:46:54

Some children ask me if it was some kind of extendable selfie stick!

0:46:540:46:58

And since last year, people just shout at me, Pokemon,

0:46:580:47:01

and they try to catch me!

0:47:010:47:02

So it changes, what people think it is.

0:47:020:47:04

Cyborgs are already amongst us, but it's not for everybody just yet.

0:47:050:47:10

So, for now, maybe it's kind of up to people like Neil and I,

0:47:100:47:14

who want to augment our bodies, to push the envelope.

0:47:140:47:18

Next up, nature.

0:47:240:47:26

Now, we all love nature,

0:47:260:47:28

and we know this because of the vast audiences that

0:47:280:47:30

BBC's Natural History Department gets, and also the fact that

0:47:300:47:33

David Attenborough is now Sir David Attenborough.

0:47:330:47:36

But, as much as we all claim to love the natural world,

0:47:360:47:41

apparently it is vanishing before our eyes.

0:47:410:47:44

If you have a little look at this graph here,

0:47:440:47:46

this is what has been happening to vertebrate populations from 1970 all

0:47:460:47:50

the way up to now. Now, this group,

0:47:500:47:52

they track the populations of almost 4,000 different species,

0:47:520:47:56

and come up with a score to say how well they are doing.

0:47:560:47:59

It turns out, not great.

0:47:590:48:01

Both the number of species

0:48:010:48:03

and the number of animals is in steady decline.

0:48:030:48:06

On land, there has been a 38% decrease in animal numbers.

0:48:060:48:10

In the sea, there has been a 36% decrease.

0:48:100:48:13

And worst of all, in freshwater,

0:48:130:48:15

there has been a huge 81% drop in population numbers.

0:48:150:48:20

And we can see from this graph that if this trend continues,

0:48:200:48:24

by 2020 we can expect to see a 67% drop based on what we had in 1970.

0:48:240:48:32

So, to find out if this really is as bad as it sounds,

0:48:320:48:34

evolutionary geneticist, writer and Renaissance man,

0:48:340:48:37

my very good friend Dr Adam Rutherford

0:48:370:48:39

is here to help us with the science.

0:48:390:48:41

Adam, we've been here before.

0:48:410:48:43

There have been extinctions before, right?

0:48:430:48:44

Yes, there have. In fact, over the last billion years or so,

0:48:440:48:47

the evolutionary trajectory of life on Earth,

0:48:470:48:49

extinction is completely the normal state of affairs.

0:48:490:48:52

I've got my own graph here.

0:48:520:48:53

If you look at the last 542 million years,

0:48:530:48:57

what this shows is extinction rates over that time period.

0:48:570:49:00

And there are five big peaks.

0:49:000:49:02

So there have been five great extinction events.

0:49:020:49:05

Everyone knows about the one that happened 66 million years ago,

0:49:050:49:08

it is called the K-Pg boundary,

0:49:080:49:09

and that was when a meteor dropped out of the sky.

0:49:090:49:11

-The dinosaurs.

-It did for the dinosaurs.

0:49:110:49:13

But also, 75% of all species on land and in the sea.

0:49:130:49:17

And that's not even the big one.

0:49:170:49:19

The big one is called the Great Dying, or the P-T boundary,

0:49:190:49:22

and that happens 252 million years ago.

0:49:220:49:25

95% of all species go extinct.

0:49:250:49:28

So, what's so different about this one?

0:49:280:49:30

The timescale is what's different.

0:49:300:49:32

So, the full extent of the Great Dying

0:49:320:49:34

really pans out over a million or two million years.

0:49:340:49:37

The dinosaur one, 66 million years.

0:49:370:49:39

We find dinosaurs 10,000 years after that happened.

0:49:390:49:43

What you just said was, 67% of species

0:49:430:49:47

will be lost since the 1970s.

0:49:470:49:49

If this is the start of another mass extinction,

0:49:510:49:54

its speed means that ecosystems and food chains will break down

0:49:540:49:58

catastrophically.

0:49:580:49:59

For some species, it is already too late.

0:50:010:50:04

Human activity means that coming generations

0:50:040:50:06

will never see a live white rhino or a Sumatran orangutan.

0:50:060:50:10

But what's worse is the potential impact

0:50:110:50:14

of losing less charismatic wildlife.

0:50:140:50:17

In the sea, rising temperatures have already disrupted

0:50:170:50:21

the food chain by killing coral.

0:50:210:50:23

And if the predicted further rises occur,

0:50:230:50:25

Asian seagrass could go extinct within 50 years,

0:50:250:50:29

causing the collapse of the entire

0:50:290:50:31

marine ecosystem in that part of the world.

0:50:310:50:34

In the future, our children will

0:50:350:50:38

almost certainly see less diversity of animals.

0:50:380:50:41

But unchecked, these changes also mean that

0:50:410:50:44

they themselves could be facing much more serious problems.

0:50:440:50:47

And as humans, are we immune to this?

0:50:490:50:52

No, absolutely not.

0:50:520:50:54

We are special, but we are living on this planet.

0:50:540:50:57

And what we are doing is removing the ability for us to live on this

0:50:570:51:00

planet whilst letting many, many species go extinct.

0:51:000:51:04

And I think the key thing is to recognise that we have created this

0:51:040:51:07

situation, and we also have the power to stop it.

0:51:070:51:10

Flying cars - there you go, I've said it.

0:51:150:51:17

Well, it wouldn't be a programme

0:51:170:51:19

about the future if someone didn't mention them.

0:51:190:51:21

But, let's be honest, they certainly would be pretty handy,

0:51:210:51:24

because our love of earthbound cars

0:51:240:51:27

has seen a steady increase in how many cars

0:51:270:51:29

there now are on the roads.

0:51:290:51:31

This graph here shows you how far we travel in motor vehicles since 1949.

0:51:310:51:36

And you can see here that car journeys, in red,

0:51:360:51:39

really have become all-conquering.

0:51:390:51:41

We're travelling a lot further, and we're doing it in cars.

0:51:410:51:44

And that makes the experience of actually driving them

0:51:440:51:48

a lot less appealing.

0:51:480:51:49

In fact, the average speed of traffic in central London

0:51:490:51:54

is now 7.3mph.

0:51:540:51:55

Basically, you'd be better off on a horse.

0:51:550:51:57

Now, we need to travel faster.

0:51:570:52:00

And dynamicist Teena Gade, who works

0:52:000:52:02

for Formula 1 team Sahara Force India,

0:52:020:52:04

she knows all about travelling quickly.

0:52:040:52:06

And she has been looking at, well,

0:52:060:52:08

there's no other way to put this, really - flying cars.

0:52:080:52:11

The worst thing about city driving is the traffic.

0:52:200:52:23

I think we're probably doing five, maybe 10mph, if that.

0:52:230:52:27

Right now, if my car could fly,

0:52:270:52:29

I'd take off and I'd jump this long queue of people in front of me

0:52:290:52:32

and be at my destination in no time.

0:52:320:52:33

History is littered with attempts at the fabled flying car.

0:52:360:52:40

Most of them hard to take seriously.

0:52:430:52:46

And moving it around is a job for a secretary

0:52:460:52:48

rather than a highly skilled and highly expensive helicopter pilot.

0:52:480:52:52

But prototypes for personal flying machines

0:52:590:53:02

have started to appear once again.

0:53:020:53:04

This time with serious financial backing.

0:53:050:53:08

I would absolutely love a personal flying car.

0:53:160:53:19

I think that would be absolutely fantastic.

0:53:190:53:21

Imagine going to work every day

0:53:210:53:22

and not having to sit in the traffic queues.

0:53:220:53:27

It might not be a good idea, though,

0:53:270:53:28

for everyone to have their own personal flying machine.

0:53:280:53:31

As I'm showing here, occasionally I can keep control of it,

0:53:310:53:34

but some of the time I'm not doing a very good job.

0:53:340:53:36

Right, that's it down. I'm just going to go and get it.

0:53:370:53:40

So, if we're all going to buzz around our cities in personal flying

0:53:430:53:46

machines, how do we keep from crashing into each other?

0:53:460:53:48

To find out, I've come to Zurich to meet robotics expert

0:53:530:53:57

Professor Raffaello D'Andrea.

0:53:570:53:59

He developed the Kiva robot system.

0:54:010:54:03

A network of thousands of bots

0:54:050:54:08

that work together to fulfil online orders.

0:54:080:54:11

This is basically a very large warehouse

0:54:120:54:14

where orders come in and they need to be fulfilled.

0:54:140:54:16

So, the system figures out which robots need to go to which pods,

0:54:160:54:22

pick it up and bring it to the perimeter of the warehouse,

0:54:220:54:25

where then people take things off of the pods

0:54:250:54:27

and put them into the orders which eventually go out.

0:54:270:54:30

There's a lot of robots in action here.

0:54:300:54:32

How come they don't collide?

0:54:320:54:33

The robots have to generate trajectories and plans.

0:54:330:54:37

And those plans are then shared to a coordinator,

0:54:370:54:40

which then figures out how they should go and execute their plan

0:54:400:54:43

so that they don't hit each other.

0:54:430:54:45

And with over 80,000 in operation,

0:54:460:54:50

the Kiva bots are the largest network of

0:54:500:54:52

autonomous vehicles in the world.

0:54:520:54:54

And so far, there haven't been any accidents.

0:54:540:54:56

If only something similar could be done with flying machines.

0:55:010:55:04

Oh, wow! That's incredible.

0:55:070:55:10

So what do we have here?

0:55:100:55:12

A swarm of 32 of these flying machines.

0:55:120:55:15

And they're going to do a little choreographed performance.

0:55:150:55:19

'This is more like it.'

0:55:190:55:21

What they are doing right now is a choreography

0:55:210:55:23

that is pre-programmed,

0:55:230:55:25

and ensures that they do not collide with each other.

0:55:250:55:28

So, what's in one of these?

0:55:310:55:33

-How are these made?

-They have four motors for propellers.

0:55:330:55:35

They have a cage to keep the propellers

0:55:350:55:37

away from other vehicles

0:55:370:55:39

and from people, and they have some custom electronics

0:55:390:55:42

that creates all the magic and intelligence.

0:55:420:55:44

And now, we just move out of the way.

0:55:450:55:48

Oh, they're coming in to land. If I put my hand out...

0:55:480:55:50

-I can catch one!

-Exactly.

0:55:500:55:52

So, if you could have this level of automation and planning in personal

0:55:560:56:00

flying machines, then perhaps they could become a reality.

0:56:000:56:04

How would that lead us to, for example, a transport system?

0:56:040:56:07

Well, so, what they would share with a transport system is the use of a

0:56:070:56:10

global positioning system.

0:56:100:56:11

We've developed an indoor global positioning system,

0:56:110:56:14

just like the one that exists outdoors.

0:56:140:56:16

And this is important, because then the vehicles

0:56:160:56:19

know where they are in space.

0:56:190:56:21

How it would differ is that the choreographies,

0:56:210:56:23

the trajectories wouldn't be preplanned.

0:56:230:56:25

The system is going to have to be much more reactive

0:56:250:56:27

when people want to fly from point A to point B.

0:56:270:56:30

Is this now setting us up for having our own personal flying machines?

0:56:340:56:38

I think we've certainly come a long way.

0:56:380:56:40

We can make flying machines that can do vertical take-off and landing,

0:56:400:56:43

fully electric, which has its own benefits.

0:56:430:56:46

I think that we will, in the near future.

0:56:460:56:48

Could this be the aerial highway of the future in miniature?

0:56:490:56:53

These drones were designed to perform at live events.

0:56:560:56:59

But they offer a glimpse into

0:56:590:57:01

what the cities of the future might look like.

0:57:010:57:03

Many of the big questions around safety

0:57:030:57:05

can be answered with current tech.

0:57:050:57:07

So what you need to know about the future of transport is

0:57:070:57:09

we may finally get our flying cars.

0:57:090:57:11

Making predictions about the future is a pretty risky business.

0:57:190:57:23

And many people have come unstuck in the past.

0:57:230:57:26

But I'm pretty confident that most

0:57:260:57:28

of what we've covered in this programme will actually happen.

0:57:280:57:32

But I'm also confident of something else.

0:57:320:57:34

The tenth thing that you need to know about the future

0:57:340:57:38

is that there will be many other developments

0:57:380:57:41

that none of us have even thought of.

0:57:410:57:43

Because, although Arthur C Clarke may have predicted

0:57:430:57:46

universal mobile communication,

0:57:460:57:47

even he would have been surprised that we now carry around

0:57:470:57:52

with us a little hand-held device that contains a typewriter,

0:57:520:57:57

a camera, a postbox, a television, a calculator, a calendar, a light,

0:57:570:58:02

a record player, a tape recorder, and not forgetting a telephone.

0:58:020:58:08

And that, for me at least,

0:58:080:58:10

is a lot cleverer and certainly a lot cleaner than a genetically

0:58:100:58:14

engineered monkey servant.

0:58:140:58:16

To find out more about the innovations that are changing

0:58:170:58:20

our health, our leisure and our work,

0:58:200:58:22

and will continue to shape our future,

0:58:220:58:24

go to bbc.co.uk/horizon and follow the Open University link.

0:58:240:58:29

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