Tails You Win: The Science of Chance


Tails You Win: The Science of Chance

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All our lives, we are pulled about and pushed around

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by the mysterious workings of chance.

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When chance seems cruel,

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some call it Fate.

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And when chance is kind,

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we might call it Luck.

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Scoring a big win...

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..being saved from disaster...

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..or meeting that special someone.

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But what actually is chance?

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Is it something fundamental in the fabric of the universe?

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Does chance have rules?

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And does it really exist at all?

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And if it does,

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could we one day even overcome it?

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This is the story of how we discovered how chance works...

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..learnt to tame it...

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..and even to work out the odds for the future.

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How we tried, but so often failed,

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to conquer it...

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and may finally be learning to love it.

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Chance plays its part in all our lives,

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though mine perhaps more than most.

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I'm a mathematician at Cambridge University

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and trying to make sense of chance is my job.

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I study how we can use the mathematics of chance

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to calculate probabilities,

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numbers that can give us a handle on what might happen in the future.

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SPLASHING SOUND EFFECT

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APPLAUSE SOUND EFFECT

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GASPING SOUND EFFECT

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Did you know that, on average,

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each person in Britain has a one-in-a-million daily chance

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of some kind of violent or accidental death?

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To put it in perspective, 1 in a million

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is roughly the chance of flipping heads 20 times.

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Imagine it like this.

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Flip a coin,

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20 heads, you're dead.

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Heads...

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Heads. Oh, dear!

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Heads...

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Tails! Oh, phew!

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It's easy to say that it's 50/50 for a coin to come up heads,

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but we can even put a probability on things

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that seem utterly chaotic and unpredictable.

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San Francisco.

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In October 1989,

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a huge, magnitude 7 earthquake struck totally without warning.

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Many people died.

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Today, San Francisco is its usual laid-back and beautiful self.

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But the people here know another disaster could hit at any moment.

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I know that my family members,

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we all have the earthquake kits and we try to have things ready,

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but, other than that, we're not very fazed by it, I don't think.

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Not until the big one comes.

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I believe in being prepared but I also believe that it is fate.

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I've been here for over 20 years

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and...it kind of puts you in a place

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where you live a bit more in the moment,

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where you know as much as you prepare,

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something could hit at any time.

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For millennia, we've met the uncertainties of life

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with just a fateful shrug of the shoulders.

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But mathematics can help us quantify fate,

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even if we can't banish it.

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What we now know from our studies is that

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the likelihood of a major earthquake hitting the Bay area

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is something like 63% over the next 30 years.

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But, associated with this 63% number,

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which sounds very precise,

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there's actually a huge range of uncertainty.

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It could be mid-40%

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or it could be 80%.

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Probabilities are often as much a matter of judgement as arithmetic.

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But they can still really help people decide what to do.

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After the 1989 earthquake,

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there were a lot of aftershocks

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and a woman called me and she said, "I'm so nervous to be here."

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"I think I want to drive to Los Angeles to visit my daughter."

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And I said, "I don't think that's a good idea," and she said, "Why?"

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I said, "Well, the likelihood that you'll be injured

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"in an automobile accident is much higher

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"than the likelihood that an aftershock will harm you."

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There's no escaping chance.

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But if we can understand how it works,

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then perhaps we can even turn it to our advantage.

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This was what the first mathematicians to investigate it

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hoped to do.

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To, as it were, tame chance.

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The scholars of the ancient world,

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the Egyptians, Babylonians, Greeks and others,

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laid down the foundations for geometry, algebra, number theory,

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and so much more.

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But extraordinarily,

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they never even got started on the maths of chance.

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It wasn't until the Renaissance that a few pioneering thinkers

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first got to grips with probability.

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But unlike the ancients,

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they weren't loftily pursuing knowledge for its own sake.

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They were trying to crack the secrets of gambling.

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The first was Gerolamo Cardano,

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from the Italian city of Milan.

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Cardano was a doctor.

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But he was also an obsessive life-long gambler.

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This was written in the 1570s,

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the earliest known work on probability.

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In it, Cardano set out a seasoned gambler's tips and insights,

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including how to cheat,

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and in one chapter,

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laid out the most fundamental principle of probability.

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Cardano realised a probability was also a fraction.

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So with the roll of a dice,

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the probability for each side coming up was one sixth.

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And it gets more interesting with two dice.

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With two dice, and 36 possible combinations,

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there's only one way to throw a 2.

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But you're much more likely to get a 7.

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Cardano's insight works with games like dice

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because we can assume that each of the faces is equally likely.

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Provided, as Cardano puts it in his book,

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"the dice are honest."

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This may seem simple to us now

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but it was the very first step in working out how to tame chance.

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Las Vegas.

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A place Cardano would have surely loved.

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The people who run this city have the measure of chance so well,

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they've built an entire glittering industry out of it.

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It's vital, even so, that anyone here CAN get lucky.

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You could even bet one dollar and win a million.

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Mike Shackleford is a professional gambler.

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His living depends on his command of casino maths.

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I analyse every casino game out there

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and my goal is to find out the probability

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of every possible event in every game.

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Almost always, the odds are going to be in the casino's favour.

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For example,

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in roulette, the house advantage is 5.26% under American rules.

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That means that for every dollar the player bets,

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on average he can expect to lose 5.26 cents.

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Not only do the casinos understand the probabilities perfectly,

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they also know that most of the punters don't.

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And these games can really mess with our minds.

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You'll see a series of outcomes from a slot machine

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and believe that there's a pattern to what you've just seen

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but that's really just the human brain playing a trick on you

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because what's happened in the past has no predictive value

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for what is going to happen next.

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Yes, the machine may have had this series of payouts in the past.

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It may have been hot or cold.

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But that has no bearing or no influence

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on what is going to happen on that next game.

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So you could hit the jackpot symbol

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two games in a row.

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We just hit the biggest jackpot we've ever hit here.

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8,600 dollars!

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We just went to this machine about half an hour ago,

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so...we got lucky!

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Jackpots don't worry the casinos.

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They know the slots are programmed

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to deliver high house edges in the long run.

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Smart players, like Mike, rarely touch them.

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A professional gambler plays games where the odds are in their favour.

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Probably the most well known is card-counting in Blackjack.

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In Blackjack, every time a card is dealt,

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the odds change for all the cards that are left.

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Mike tracks the cards that are dealt,

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to work out how those odds are changing.

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So, if the player notices that in the first 25% of the shoe

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a lot of small cards came out, more than expected,

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he knows that the remaining cards are going to have a surplus of big cards.

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So he will adjust his bet size

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and he will change how he plays

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and by doing that, he can get the odds in his favour.

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On a good day, Mike can get a 1% advantage over the house.

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It doesn't sound much

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but it could mean a lot of money.

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The casinos, of course,

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don't like card counters

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and Mike's been banned from almost every joint in town.

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In the world of games,

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if you know the rules, you can figure out the probabilities.

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But what about the chances of life and death itself?

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EVIL LAUGHTER

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BELL TOLLS, SPOOKY MUSIC

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To be able to put probabilities on our own lives

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needed another great mathematical leap.

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And this time, the rewards would be even bigger.

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For most of history, it was almost a given

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that we had not the slightest inkling

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of when our time on earth was up.

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Death visited when he wanted

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and the results were never pretty.

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Thank goodness for the consolation of eternal life in the hereafter!

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The sculptors who carved this terrifying monument

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were capturing the brutal truth of our mortality

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as a warning to everyone here, quaking in the pews.

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But around the time this was carved, about 300 years ago,

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scientists began trying to work out

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the mathematical chances, for each individual,

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that Death would soon be paying them a call.

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The revelation was that you could study one group of people,

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the residents of this parish, for instance,

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and see how old they were when they died.

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From this, you could estimate the chances of death

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at each age for everybody else too.

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This was a radical idea.

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Count the dead

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and Death would become less of a divine punishment

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and more of a predictable force of nature.

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The man who really cracked

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how to apply the maths of chance to human lives

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was Edmund Halley, the famous astronomer.

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Edmund Halley had no interest in what went on in there.

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What fascinated him was what had happened out here.

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Most people now remember him for his famous comet,

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but I salute him as one of history's greatest nerds!

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Halley realised that he could calculate

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the probabilities of life and death.

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All he needed was some good data.

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83...

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52...

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27...

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In faraway Breslau, now a city in Poland,

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locals were spooked by an ancient superstition

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that being aged 49 or 63

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was particularly risky.

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To prove the superstition wrong,

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a Breslau clergyman collected details of all the town's deaths

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and circulated these to the leading scientists of the day.

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Halley got hold of the data

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and realised the results would have an impact far beyond Breslau.

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Halley constructed a table

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that was made up of, essentially, two columns.

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The first column was age

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and the second column was how many people were alive at that age.

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The first column started at birth with 1,000 people,

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and as the ages increased,

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what we saw is that the number of people alive decreased

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and this wasn't uniformly.

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Halley found nothing special about 49 or 63.

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But his data showed that the older you got,

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the greater the chance of you dying.

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It seems obvious to us now.

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But before Halley,

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people thought the chances much the same for everyone,

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young and old alike.

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And Halley's table had an immediate practical benefit.

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Halley's tables were also ground-breaking

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because not only did he publish

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the probability of death at a certain age,

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he took that one step further

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and applied that to the price of a pension

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or the price of life assurance.

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He included formulae as to how you could actually come up

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with a price for a pension.

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People in the 17th century wanted to buy pensions

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and life insurance, just like they do today.

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But before Halley, anybody who provided them

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was in danger of going bankrupt.

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So Halley's breakthrough would form the foundation

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for the entire pensions and life insurance industry.

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And death would never seem as capricious and mysterious again.

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And what of Edmund Halley?

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He lived all the way to 86,

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off his own table!

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Costly if you were his pension provider!

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Today, the insurance and pensions industry is huge,

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and has collected so much data

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they can correlate your life and death chances

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to your gender, your address,

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your job and your lifestyle.

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And knowledge of the odds could help us all.

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So what do we know about what affects our chances,

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for better or for worse?

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Imagine this 100 metres is 100 years of possible life.

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How many of those years are we actually going to see?

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How far along this track are we going to get?

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When I was born, the average British male

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expected a much shorter life than if born today.

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I was born in the 1950s and back then,

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my expected lifespan was just 67 years.

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But thanks to medical advances

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and changes to the way we live and work,

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our chances are continually getting better.

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The average lifespan is actually rising by three months a year.

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If I were born today, I could expect to live to 78.

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Even better, the longer you live,

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the longer you can expect to live,

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because you've been lucky enough not to die young.

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So at my age now,

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I can expect to live not to 67...

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..or 78...

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..but...

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..82.

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But what's not so cheerful

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is the effect of all those things I might do throughout my life

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that could stop me getting this far, or even further.

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Research tells us that

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for every day you're five kilos overweight, like I am,

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you can expect to lose half an hour off your life.

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Aah!

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Sad to say,

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if you're a man sinking three pints a day

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then that's also half an hour.

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But what about exercise? Won't that make things better?

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Yes, it will. But there's a catch.

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A regular run of half an hour

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and you can expect to live longer.

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Half an hour longer.

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So I hope you actually like running.

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Cos that's how you just spent your extra half hour.

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Surprise, surprise, the worst news is for all you smokers.

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Two cigarettes costs half an hour.

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But the average smoker's on nearly 20 a day.

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And it all adds up.

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Doing something that costs half an hour a day...

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Well, that's more than a week off each year

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and, in the long run, that's a whole year off your life.

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For that 20-a-day smoker,

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that's a staggering 10 years you should expect to lose.

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All these figures tell us a lot.

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But as for chance itself,

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that's certainly not disappeared.

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When I say I can expect to live to 82,

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I'm not actually making a prediction.

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It may be shorter or, with luck, it may be longer.

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82 is the average.

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Imagine 100 possible future me's, each equally likely.

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I'm 58 now and as the years roll by,

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in more and more of these possible futures, I die,

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until by the age of 82

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about half of my future selves will be dead

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and about half still alive.

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Which is going to be me? That's just chance.

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Beyond 82, more and more drop dead.

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And there's a very small chance I could live to be very old indeed.

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If I were a smoker, it's just possible I'd beat the odds.

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But overall, my chances wouldn't look nearly so good.

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Of course, many people would say going on about risks

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is being a big killjoy.

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The writer Kingsley Amis famously said,

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"No pleasure is worth giving up

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"for the sake of two more years

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"in a geriatric home at Weston-super-Mare."

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But I believe understanding the risks

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might actually help us to have more fun, not less.

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OK. Just put one arm through there for me...

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the other through there and turn around. Thank you.

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What we'll do is we'll start strapping you in.

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Many of my favourite experiences would be impossible

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without taking some risk,

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but I'm about to do something I've never done before

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which really does involve risk.

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The best way to compare risky activities

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is to use the micromort,

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a cheery little unit which represents

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a one-in-a-million chance of death.

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Skydiving is actually safer than you might think.

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There's only about a seven-in-a-million chance of dying.

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That's seven micromorts.

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That's about the same risk as 40 miles on a motorbike.

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But there's still a risk.

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And you may think I should be old enough to know better.

0:21:460:21:48

But I think it could be rational to take more risks when you get older.

0:21:480:21:52

An average 18-year-old has a chance of dying in the next 12 months

0:21:550:21:59

of about 500 micromorts.

0:21:590:22:01

But at my age, the equivalent is 7,000 micromorts.

0:22:030:22:07

7,000 micromorts doesn't sound great, does it?

0:22:110:22:13

But my extra risk of skydiving is only seven micromorts more.

0:22:130:22:17

That's not much difference.

0:22:170:22:18

So the risk is actually pretty low.

0:22:210:22:23

But the funny thing is,

0:22:250:22:26

now I'm actually in the plane and there's no backing out,

0:22:260:22:29

it suddenly seems a lot worse.

0:22:290:22:31

Will my parachute fail? I don't know.

0:22:330:22:37

Will we be blown into a tree? I don't know.

0:22:370:22:40

Will I be sick with fright over my jumpsuit?

0:22:420:22:45

The probability of that is getting close to 100%!

0:22:450:22:48

It's the moment of truth.

0:22:530:22:55

Here we go!

0:22:580:22:59

Yes, I'm a Professor of Risk

0:23:040:23:06

and I've made a sound decision rooted in the numbers,

0:23:060:23:10

but as I fall, I can't help thinking

0:23:100:23:12

there's a chance I'll die very soon indeed.

0:23:120:23:14

I could buy myself a pair of silver hairbrushes.

0:23:190:23:22

Oh, hello!

0:23:220:23:24

I'm having a go at these premium bonds.

0:23:240:23:25

They're wonderful things - you can't lose.

0:23:250:23:28

Look, there are staggering prizes each month,

0:23:280:23:31

you can get your money back any time you like,

0:23:310:23:33

and, what's more, all your tickets go back into each draw

0:23:330:23:36

whether you've been lucky before or not!

0:23:360:23:38

I might win a thousand quid!

0:23:380:23:40

I love a bit of a flutter.

0:23:400:23:42

Not a word to Bessie about that!

0:23:420:23:43

In 1956,

0:23:450:23:46

Britain introduced a brand new kind of savings scheme,

0:23:460:23:49

Premium Bonds,

0:23:490:23:51

that instead of paying you interest

0:23:510:23:54

gave you the chance to win big prizes.

0:23:540:23:57

At its heart was something created by mathematicians,

0:23:570:24:00

a world of pure chance, randomness.

0:24:000:24:04

This is a world where every element

0:24:060:24:08

is disconnected from every other,

0:24:080:24:10

that operates beyond our influence or control.

0:24:100:24:13

The Premium Bonds monthly prize draw

0:24:140:24:17

needed complete randomness

0:24:170:24:20

to make sure it was scrupulously fair.

0:24:200:24:22

There was quite a lot of human interest in randomness

0:24:380:24:40

for the first time,

0:24:400:24:42

where people began to think about,

0:24:420:24:44

"what are the chances of my winning?"

0:24:440:24:46

But what it required was

0:24:460:24:49

a source of random numbers

0:24:490:24:52

and a special purpose computer was built for this

0:24:520:24:55

and it was one of the very first special purpose computers.

0:24:550:24:58

We're going to an electronic machine, if you understand what that is,

0:24:580:25:01

but thank goodness its complicated name is ERNIE for short.

0:25:010:25:05

ERNIE stood for Electronic Random Number Indicating Equipment.

0:25:050:25:11

Truly random numbers are hard to produce,

0:25:110:25:13

and ERNIE got them by sampling the electrical noise

0:25:130:25:16

from a series of vacuum tubes.

0:25:160:25:18

It was state-of-the-art engineering.

0:25:180:25:20

Randomness really, in a certain extent, means unpredictable,

0:25:220:25:26

but also, for the purposes of ERNIE,

0:25:260:25:28

it needed to be unpredictable and unbiased

0:25:280:25:31

and my job as a young mathematician

0:25:310:25:34

was to show that it really was unbiased

0:25:340:25:36

to any particular Premium Bond number.

0:25:360:25:39

This was quite a skilled and lengthy task

0:25:390:25:42

to say those weasel words that mathematicians use,

0:25:420:25:45

"We have no reason to suppose that ERNIE is not random."

0:25:450:25:50

For me, as a mathematician, complete randomness is fascinating.

0:25:580:26:02

It's full of curiosities.

0:26:020:26:05

And unexpectedly, it turns out to have its own rules,

0:26:050:26:08

patterns and structure.

0:26:080:26:10

This is officially the most boring book in the world. Ever.

0:26:130:26:19

It's called One Million Random Digits

0:26:190:26:22

and that's literally what it is.

0:26:220:26:24

Page after page of random numbers.

0:26:240:26:27

Say what you like about this book, though,

0:26:290:26:32

at least the plot is unpredictable.

0:26:320:26:34

Printed in 1955,

0:26:360:26:37

these numbers were produced by an early computer rather like ERNIE.

0:26:370:26:43

And people have used them since

0:26:430:26:45

for everything from randomised clinical trials

0:26:450:26:48

to encrypting communications.

0:26:480:26:50

I might not read this book cover to cover,

0:26:510:26:54

but I promise you there are some really interesting parts.

0:26:540:26:57

I mean, look at this. 00000.

0:26:570:27:01

And here's another great bit.

0:27:010:27:03

12345.

0:27:060:27:08

It seems really strange to see these.

0:27:080:27:11

I mean, how can these be random?

0:27:110:27:12

But, of course, they're as random as the numbers next to them.

0:27:120:27:16

Not only can you expect to find patterns like these,

0:27:160:27:20

you can even calculate how often you expect to find them.

0:27:200:27:23

A perfect sequence of five numbers.

0:27:230:27:25

There should be 50 of these in the book.

0:27:250:27:28

And the same number five times in a row,

0:27:280:27:31

there should be about 100 of these.

0:27:310:27:33

You can even expect,

0:27:330:27:34

somewhere in these one million random numbers,

0:27:340:27:37

the same number to occur seven times in a row.

0:27:370:27:40

And I've found it.

0:27:400:27:42

6666666.

0:27:430:27:47

What makes randomness so useful

0:27:530:27:55

is that it is completely unpredictable...

0:27:550:27:58

but in a predictable way.

0:27:580:27:59

So predictable that it has its own shape.

0:28:020:28:04

A lottery is a great example.

0:28:070:28:09

Each National Lottery draw is...

0:28:110:28:13

well, random.

0:28:130:28:15

There seems no pattern at all.

0:28:150:28:18

But there are also seemingly strange results.

0:28:180:28:21

Today, after something approaching 2,000 National Lottery draws

0:28:220:28:27

over 20 years, there are huge differences

0:28:270:28:30

in how often different numbers have come up.

0:28:300:28:32

Number 38 has been picked 241 times...

0:28:330:28:37

..while number 20 has come up just 171.

0:28:370:28:41

It might look like something's wrong,

0:28:430:28:45

but taking all the results together,

0:28:450:28:47

the totals match the shape of randomness remarkably well.

0:28:470:28:51

And even the outlying results

0:28:530:28:55

are just where the shape shows they should be.

0:28:550:28:58

Here we go. Let's pick some numbers.

0:29:040:29:06

It's not a great bet, I admit.

0:29:080:29:11

There's only a 1-in-14-million chance of me winning the jackpot.

0:29:110:29:15

In fact, I'm very unlikely to win anything at all.

0:29:150:29:17

There's only a 1-in-56 chance

0:29:170:29:19

of me getting the smallest prize of £10.

0:29:190:29:23

Overall, the lottery only pays back

0:29:230:29:25

45% of the money it takes in.

0:29:250:29:27

Far, far worse than any casino game.

0:29:270:29:30

If you must play,

0:29:300:29:33

though you can't change your chances of winning,

0:29:330:29:35

you can improve your chances of not sharing the jackpot.

0:29:350:29:39

Many people pick birthdays or other significant dates,

0:29:390:29:42

so avoid the numbers up to 31.

0:29:420:29:44

You may even want to steer clear

0:29:440:29:46

of that supposedly lucky number, 38.

0:29:460:29:48

In the end, it doesn't matter what numbers you choose,

0:29:500:29:53

every combination, say 1, 2, 3, 4, 5, 6,

0:29:530:29:56

is as likely as any other.

0:29:560:29:58

That's because it's completely random.

0:29:580:30:01

But randomness can confuse us.

0:30:060:30:10

For example, use the shuffle feature on the original iPod

0:30:100:30:14

to play its tracks in random order and before too long

0:30:140:30:17

you're very likely to land on the same album again.

0:30:170:30:20

People found it so off-putting

0:30:220:30:24

that the shuffle on later-generation iPods was supposedly tweaked.

0:30:240:30:27

Apple famously explained,

0:30:300:30:31

"We're making it less random so it feels more random."

0:30:310:30:35

Patterns and connections like this are what we call coincidences.

0:30:420:30:47

And no matter how much we should expect them,

0:30:470:30:49

they nonetheless still make our heads spin.

0:30:490:30:51

I love coincidences so much

0:30:530:30:57

I decided to try to collect them.

0:30:570:30:59

Luckily, it's an interest the nation shares.

0:30:590:31:02

Let's talk about coincidences now, at 7:24, why do they happen?

0:31:020:31:06

-Professor David Spiegelhalter, good morning.

-Good morning.

0:31:060:31:08

You are an expert in risk and chance, is what I'm reading,

0:31:080:31:11

at Cambridge University,

0:31:110:31:13

but why are you interested in chance and coincidence?

0:31:130:31:15

Well, it's part of my job.

0:31:150:31:16

I'm Professor of the Public Understanding of Risk,

0:31:160:31:19

so everything to do with chance, uncertainty and coincidences

0:31:190:31:22

is what I'm interested in.

0:31:220:31:23

And we've set up this website where we're collecting coincidence stories

0:31:230:31:27

which people are sending in,

0:31:270:31:29

and the sort of things where people, when they happen to them, say,

0:31:290:31:32

"Ooh, what are the chances of that?"

0:31:320:31:34

And we're trying to work out what the chances of that really are.

0:31:340:31:37

It's like a family having three children all with the same birthday,

0:31:370:31:41

born in different years, but all three children being born

0:31:410:31:44

on the same birthday. You'd think, "Wow, what are the chances of that?"

0:31:440:31:47

Well, we can work those out.

0:31:470:31:49

Since there's a million families in this country with three children,

0:31:490:31:52

we'd expect there's about 8 families like that.

0:31:520:31:54

Now, we've found three of them.

0:31:540:31:56

People read great significance into these things, though.

0:31:560:31:59

Are they misguided in doing that?

0:31:590:32:01

Well, it's Friday 13th, exactly the day that shows people do believe

0:32:010:32:04

in luck and fortune and things like that...

0:32:040:32:06

But I suppose I'm being a bit scientific about them,

0:32:060:32:08

so some of them we try to take apart and do the maths,

0:32:080:32:11

but other ones are just amazing.

0:32:110:32:13

There's a lovely example last year where a French family,

0:32:130:32:16

their house was hit by a meteorite.

0:32:160:32:17

Well, that's pretty surprising itself,

0:32:170:32:20

but their name was Comette. Isn't that just beautiful?

0:32:200:32:23

"What are the chances of never experiencing a coincidence?"

0:32:230:32:25

says Steve in Cheshire.

0:32:250:32:26

Oh, very low indeed. That would be really, really bizarre.

0:32:260:32:30

Good one, Steve.

0:32:300:32:32

7:29. What are the chances of any decent weather over the weekend?

0:32:320:32:35

'Pretty good, actually, Rachel.

0:32:350:32:37

'We've got some clear skies out there at the moment,

0:32:370:32:40

'but because of those clear skies

0:32:400:32:42

'temperatures are hovering at or just below freezing...'

0:32:420:32:45

The radio show was a huge success.

0:32:450:32:48

The stories flooded in. Over 3,000 of them.

0:32:480:32:51

We got lots of coincidences with numbers, names and words.

0:32:510:32:57

And loads of calendar ones,

0:32:570:32:59

including one more of those rare triple birthdays.

0:32:590:33:03

Some of these stories are really amazing.

0:33:030:33:06

Lots of them are about running into friends and acquaintances

0:33:060:33:09

in the most unlikely places. And I love this one.

0:33:090:33:12

Mick Preston was on a cycling holiday in the Pyrenees

0:33:130:33:16

and during one stop-over, he wrote his friend, Alan, a postcard.

0:33:160:33:19

But, incredibly, on the way to post it, he bumped into Alan,

0:33:190:33:23

who just by chance was on holiday in the same place,

0:33:230:33:26

so Mick gave him the postcard in person.

0:33:260:33:29

As Mick himself said,

0:33:290:33:31

that was a waste of a good stamp!

0:33:310:33:33

What's striking is that although these and other coincidences

0:33:380:33:42

happened a long time ago, people were so jolted by them

0:33:420:33:46

they still remember them years later.

0:33:460:33:48

I think our brains are hard-wired to look for cause and effect,

0:33:490:33:53

to try to come up with reasons why things happen.

0:33:530:33:57

So when things happen for no apparent reason at all,

0:33:570:34:00

we find it really spooky.

0:34:000:34:02

We just don't seem to easily accept

0:34:020:34:05

that we might not be able to understand or control

0:34:050:34:08

what happens in our lives.

0:34:080:34:09

Random events that have no explanation beyond chance

0:34:140:34:18

saturate our lives...

0:34:180:34:20

..but some people think they can eliminate the random -

0:34:220:34:24

control everything - and that chance has nothing to do with them at all.

0:34:240:34:29

Ed Smith was once said to be the golden boy of English cricket.

0:34:300:34:35

For years he held an idea about chance -

0:34:350:34:37

or, as he called it, "luck" -

0:34:370:34:39

that he shared with many of his fellow sporting professionals.

0:34:390:34:43

When I turned full-time professional in 1999,

0:34:550:34:58

we had all these meetings

0:34:580:34:59

about how we were going to approach the season

0:34:590:35:02

and someone put his hand up and said,

0:35:020:35:04

"I don't think we should say, 'bad luck,' to each other.

0:35:040:35:06

"That's an excuse. It's not bad luck.

0:35:060:35:08

"If someone gets out, it's their fault."

0:35:080:35:10

I think as sportsmen we're conditioned to think that,

0:35:100:35:13

that you are in total control.

0:35:130:35:16

I mean, if you, if you walk out to bat in professional cricket

0:35:160:35:18

and you say, "Well, maybe I'll be lucky and maybe I won't,

0:35:180:35:21

"and maybe someone will bowl a good ball I'll be out, and I can't do anything about it,"

0:35:210:35:24

then you're stacking the deck against yourself before you even begin.

0:35:240:35:27

Ed played for England and became captain of Middlesex.

0:35:300:35:34

Everything went well for him,

0:35:350:35:37

until one day during a county cricket match at Lord's.

0:35:370:35:43

So, we're in the middle of this match, it's going well,

0:35:430:35:45

we're pretty much cantering to victory.

0:35:450:35:47

We're on a bit of a streak of five, six wins in a row, everything's going well

0:35:470:35:50

and I'm doing the most routine thing in cricket, I'm running a two.

0:35:500:35:54

It happens all the time, you know...

0:35:540:35:56

it's not particularly demanding, athletically,

0:35:560:35:58

to run 20 yards and then come back again.

0:35:580:36:00

And I ran the first one and then you just rub the bat in,

0:36:000:36:04

and I just, sort of, collapsed.

0:36:040:36:06

And I'm lying in this, and have this shooting pain in my ankle,

0:36:060:36:09

and it was only quite a few weeks later that there was an X-ray,

0:36:090:36:14

and it turned out that I'd broken my ankle,

0:36:140:36:17

and I wasn't going to play any time soon!

0:36:170:36:20

I missed the rest of that season and then I retired, effectively,

0:36:200:36:23

at the end of that season and didn't play professional cricket again.

0:36:230:36:27

In a single moment, Ed's entire career vanished.

0:36:270:36:31

He had been touched by chance.

0:36:310:36:34

No-one and nothing was to blame.

0:36:340:36:37

I think I found it hard to accept. You know, my own willpower,

0:36:370:36:41

my determination to control, to shape my own life, was so great

0:36:410:36:46

but the reality is that I wasn't in control.

0:36:460:36:49

The fact that I had a broken ankle was just a fact.

0:36:490:36:52

It was a circumstance that had happened to me.

0:36:520:36:55

So, it was like a clash between, er, my own desire to control everything

0:36:550:36:59

and the fact of luck, and, you know, luck won.

0:36:590:37:03

The moral of Ed's story is clear -

0:37:050:37:07

don't beat yourself up about every failure.

0:37:070:37:10

But the opposite is also true -

0:37:100:37:12

don't be too chuffed with yourself about every success.

0:37:120:37:16

Remember this?

0:37:190:37:21

I know you can't get rid of luck, but right now I wish you could!

0:37:210:37:25

The parachute hasn't failed at least!

0:37:280:37:31

I don't seem to be being blown into a forest!

0:37:330:37:36

And I haven't even been sick!

0:37:360:37:38

That was so cool! Can we do it again?

0:37:410:37:44

You know, the really interesting thing is that whilst I was confident

0:37:470:37:51

I would land safely, I couldn't be absolutely certain.

0:37:510:37:56

The question is, "Why not? Why does chance exist?"

0:37:560:38:00

The story of science, for centuries, has been a triumph -

0:38:100:38:14

unlocking the mathematical laws behind everything,

0:38:140:38:18

from the atom to the universe.

0:38:180:38:20

So why is there still room for the random? For unpredictability?

0:38:240:38:30

Why, instead, can't everything in nature be determined?

0:38:300:38:33

In which case, we could get rid of chance altogether

0:38:340:38:38

and I would be out of a job.

0:38:380:38:41

In the 1680s Isaac Newton revolutionised science

0:38:460:38:51

with a set of universal laws.

0:38:510:38:54

He calculated the orbits of moons and planets...

0:38:540:38:57

even predicted the timings of eclipses

0:38:570:39:01

and, of course, explained the fall of an earthbound apple.

0:39:010:39:05

Oh!

0:39:050:39:06

Newton's friend, Edmund Halley, predicted the returns of comets...

0:39:080:39:12

..and other scientists eagerly worked to discover new laws

0:39:150:39:19

and make more predictions.

0:39:190:39:21

"The Enlightenment", it came to be called.

0:39:210:39:24

In 1779, the French scientist Pierre-Simon Laplace

0:39:270:39:31

had a bold vision.

0:39:310:39:32

If some vast intellect

0:39:330:39:36

could not only comprehend all the laws of nature,

0:39:360:39:38

but could also measure everything, even down to the tiniest atom,

0:39:380:39:42

then he might predict the future precisely.

0:39:420:39:45

And uncertainty would simply disappear.

0:39:450:39:48

Hmm.

0:39:500:39:51

In theory, with the right mathematics,

0:39:520:39:55

everything in the physical universe could be measured and predicted,

0:39:550:39:58

just like the movement of the stars and the planets.

0:39:580:40:01

So, for example, if I threw a dice

0:40:010:40:04

I could predict exactly how it would land.

0:40:040:40:07

This theory is what we call "scientific determinism".

0:40:100:40:14

In theory, if we gather the data and do the calculations,

0:40:140:40:18

we should be able to get rid of chance altogether,

0:40:180:40:21

but, in practice, prediction has proved frustratingly hard.

0:40:210:40:25

It's as if there is something about our physical world

0:40:250:40:28

that makes prediction all but impossible.

0:40:280:40:31

Despite the promise of the laws of Newton

0:40:330:40:35

and all the scientists who followed him, we remain in the dark.

0:40:350:40:39

But why?

0:40:390:40:40

In the 20th century, scientists - like meteorologist Ed Lorenz -

0:40:410:40:46

discovered that even tiny influences could have immense

0:40:460:40:49

and unpredictable consequences.

0:40:490:40:51

As Lorenz put it, "The flap of a butterfly's wings in Brazil

0:40:540:40:58

"could cause a tornado in Texas."

0:40:580:41:00

The theory of determinism had to acknowledge complexity and chaos.

0:41:020:41:07

The laws of physics weren't wrong,

0:41:070:41:09

but the real world was just too complicated

0:41:090:41:12

to ever fully comprehend.

0:41:120:41:14

Also in the 20th century, physicists, like Werner Heisenberg,

0:41:150:41:20

delving ever deeper into the nature of matter,

0:41:200:41:22

realised there was an absolute limit to what they could ever know.

0:41:220:41:27

In his work on quantum mechanics,

0:41:270:41:30

Heisenberg set out the uncertainty principle -

0:41:300:41:33

essential parts of the subatomic world

0:41:330:41:36

could at best only ever be described as a probability.

0:41:360:41:40

The dreams scientists once had of conquering chance

0:41:430:41:47

have been shattered.

0:41:470:41:48

Quantum mechanics has shown us a subatomic world

0:41:480:41:51

that is fundamentally uncertain.

0:41:510:41:53

Beyond the subatomic, we are still governed by mechanical

0:41:530:41:57

and therefore deterministic laws,

0:41:570:41:59

but, paradoxically, the mathematics of chaos and complexity

0:41:590:42:03

means that things are still ultimately unpredictable.

0:42:030:42:06

So what is chance?

0:42:070:42:09

Is it real? Is it something out there in the fabric of the universe?

0:42:090:42:13

Or is chance in here? Just an excuse?

0:42:130:42:17

What Laplace called, "Merely the measure of our ignorance?"

0:42:170:42:21

Or is it a bit of both?

0:42:210:42:22

After centuries of discovery,

0:42:220:42:24

we are still not much closer to knowing what chance really is.

0:42:240:42:28

One thing is certain - chance is here to stay.

0:42:310:42:35

What's more, it has actually been put to work.

0:42:350:42:39

Faced with complex and unpredictable problems,

0:42:390:42:42

scientists have found ways to use chance itself

0:42:420:42:45

to convert blind uncertainty into computable probability.

0:42:450:42:49

In the early years of the Cold War,

0:42:520:42:54

nuclear physicists at Los Alamos

0:42:540:42:57

were working to design a new atomic bomb.

0:42:570:43:00

They wanted to predict when an atomic chain reaction

0:43:000:43:03

might go critical,

0:43:030:43:05

but the physics was so complex that at each step in the chain

0:43:050:43:09

they were uncertain about what would happen next.

0:43:090:43:12

So they turned to the mathematics of chance.

0:43:120:43:15

For each step, they chose an outcome at random

0:43:170:43:20

and then calculated what the resulting chain reaction would do.

0:43:200:43:25

Then they randomly chose a new set of outcomes

0:43:250:43:28

and calculated a new result.

0:43:280:43:30

They did this repeatedly until they had hundreds of different,

0:43:320:43:35

but equally likely, possible results.

0:43:350:43:39

And combining them all gave the Los Alamos scientists

0:43:390:43:42

an extremely accurate probability

0:43:420:43:44

for what the chain reaction would do for real.

0:43:440:43:46

They called it the Monte Carlo method,

0:43:480:43:51

like rolling a dice over and over again.

0:43:510:43:55

And the bomb worked.

0:43:570:43:59

Today, that very same Monte Carlo method,

0:44:090:44:12

creating arrays of possible futures to compute probabilities,

0:44:120:44:16

is being used to try to solve problems in many different fields.

0:44:160:44:20

And what's most exciting for me and my fellow Brits

0:44:200:44:23

is that this might help to answer

0:44:230:44:25

that all-important question: When I go out, do I take an umbrella?

0:44:250:44:30

In the 1920s, the economist John Maynard Keynes

0:44:380:44:43

wrote a famous book about chance.

0:44:430:44:46

And for the ultimate metaphor of impenetrable uncertainty

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he chose the British weather.

0:44:500:44:52

He wrote, "Is our expectation of rain, when we start out for a walk,

0:44:560:45:01

"always MORE likely than not,

0:45:010:45:03

"or LESS likely than not, or AS likely as not?

0:45:030:45:06

"I am prepared to argue that on some occasions none of these alternatives hold,

0:45:060:45:12

"and that it will be an arbitrary matter

0:45:120:45:15

"to decide for or against the umbrella."

0:45:150:45:17

But we want certainty.

0:45:200:45:22

And so we demand it from our weather forecasters.

0:45:220:45:26

And then after wet weekends and washed-out holidays

0:45:260:45:29

we blame the poor old forecasters for getting it wrong.

0:45:290:45:33

Hello, it was a disappointing day in many places

0:45:330:45:37

and I'm optimistic it's going to be a better day for most of us tomorrow.

0:45:370:45:41

Britain's most famously wrong weather forecast

0:45:410:45:45

was on 15th October, 1987.

0:45:450:45:47

Good afternoon. Earlier on today,

0:45:470:45:49

a woman rang the BBC and said she heard a hurricane was on the way.

0:45:490:45:53

Well, don't worry, there isn't.

0:45:530:45:55

But there was!

0:45:550:45:57

That night England was lashed by the strongest winds

0:45:570:46:01

for almost 300 years.

0:46:010:46:03

NEWS: Southern England suffered the full fury of the freak hurricane force winds,

0:46:030:46:07

in their wake, a trail of devastation,

0:46:070:46:09

the worst damage to property since the Second World War.

0:46:090:46:12

Nowhere escaped unscathed.

0:46:120:46:14

Today the most advanced meteorologists don't try making predictions

0:46:180:46:22

like Michael Fish did.

0:46:220:46:24

In Reading at the European Centre for Medium-Range Weather Forecasts,

0:46:240:46:28

they use a form of Monte Carlo method

0:46:280:46:32

to make forecasts using probabilities instead.

0:46:320:46:36

To show why they do this,

0:46:360:46:38

they've revisited the same weather data Michael Fish had in 1987.

0:46:380:46:43

What this shows us is that October '87 was an exceptionally

0:46:540:46:58

unpredictable and exceptionally chaotic situation

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and so it was always going to be impossible to make a precise, deterministic forecast.

0:47:030:47:08

Weather forecasts go wrong because even small errors

0:47:090:47:14

at the beginning can grow into huge differences after just a few days.

0:47:140:47:18

And that's as true for everyday weather as it is for hurricanes.

0:47:180:47:22

To tackle the problem, Tim Palmer and his colleagues

0:47:250:47:28

routinely compute 50 different forecasts,

0:47:280:47:30

each with slightly varying starting points to reflect the uncertainty.

0:47:300:47:35

Before returning to the hurricane, Tim shows us an everyday example.

0:47:350:47:40

So we're looking at today's weather forecast

0:47:400:47:44

right at the beginning of the forecast period.

0:47:440:47:47

These are all basically giving the same type of weather.

0:47:470:47:50

A weather forecaster would look at these pressure maps and say,

0:47:500:47:53

"There's a northwesterly airstream coming down over the UK,

0:47:530:47:57

it's giving us slightly cool temperatures,

0:47:570:48:00

but fundamentally it's exactly the same no matter which of these 50 forecasts you're looking at.

0:48:000:48:05

Taking the same set of forecasts to three days in the future,

0:48:050:48:09

it's a different story.

0:48:090:48:12

Now there are discernible differences.

0:48:120:48:14

For example, member 14 has a stronger wind, there are tighter gradients

0:48:140:48:18

in the pressure than member 15 and that's telling us that

0:48:180:48:22

although we can be certain of the general direction of the wind, it's coming from the northwest,

0:48:220:48:27

the strength of the wind we cannot be so certain about.

0:48:270:48:30

So we have to make a prediction in probabilistic terms.

0:48:300:48:33

To work out the probabilities, Tim counts how many

0:48:330:48:37

of the three-day forecasts show a particular kind of weather.

0:48:370:48:40

It turns out that in about 30% of the forecasts

0:48:420:48:45

there are gale force winds over much of England.

0:48:450:48:48

Similarly rainfall, we find across much of England about 30%.

0:48:480:48:52

What this DOESN'T mean is that it's raining for 30% of the day.

0:48:520:48:57

What it means is that over the 50 possible futures,

0:48:570:49:01

in 30% of them it is raining.

0:49:010:49:04

So what can Tim see using the new method with the 1987 hurricane data?

0:49:040:49:10

There's around a 20 to 30% probability

0:49:100:49:13

over parts of southern England of hurricane force winds.

0:49:130:49:17

Now, the probability normally of hurricane force winds

0:49:170:49:20

in southern England is negligibly small,

0:49:200:49:23

so even though there's a divergence of solutions, there's real information here.

0:49:230:49:28

Adapting the Monte Carlo method and embracing chance

0:49:280:49:32

gives much better results.

0:49:320:49:34

But in Britain the forecasts most of us see don't give us

0:49:340:49:37

this kind of information yet.

0:49:370:49:39

We should now be trying to get this type of information out on the daily weather forecast.

0:49:400:49:45

And indeed I think it will enhance

0:49:450:49:47

the credibility of meteorologists themselves to be able to say

0:49:470:49:51

not only is weather forecasting an uncertain science,

0:49:510:49:56

but we can actually quantify the uncertainty in a very precise way.

0:49:560:50:00

If you were a cynic, you might think that weather forecasters

0:50:110:50:15

who give you probabilities and not predictions are just

0:50:150:50:19

hedging their bets, ducking out of doing the one thing they're supposed to

0:50:190:50:23

so they can never be accused of being wrong again.

0:50:230:50:27

But I don't agree.

0:50:270:50:28

Better a reliable probability than a wrong prediction.

0:50:280:50:32

And knowing the probabilities we can all make our own decisions.

0:50:320:50:36

THUNDER CLAPS

0:50:360:50:38

Like to bring that umbrella.

0:50:400:50:42

Remember that San Francisco probability?

0:50:530:50:56

A 40 to 80% chance of an earthquake?

0:50:560:51:00

In 1906, the city's worst-ever earthquake

0:51:000:51:03

killed 3,000 people

0:51:030:51:06

and destroyed almost 30,000 buildings.

0:51:060:51:09

Even if a similar catastrophe in the future can't be predicted,

0:51:120:51:16

it certainly can't be ignored.

0:51:160:51:18

So today scientists are applying new mathematical methods to the problem.

0:51:190:51:24

They're computing probabilities literally building by building,

0:51:250:51:29

so bold decisions can be taken about what to do.

0:51:290:51:32

In Berkeley, across the bay from San Francisco,

0:51:390:51:42

one major fault runs right across the pitch

0:51:420:51:46

of the California Memorial Stadium,

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home of the Golden Bears Football Team.

0:51:490:51:52

They're rebuilding the stadium at a cost of over 200 million dollars.

0:51:520:51:57

The fault starts

0:51:570:51:58

just to the west of the south scoreboard,

0:51:580:52:01

and you can see in the bowl

0:52:010:52:04

there are those double stair-step curves at two points,

0:52:040:52:08

-that's where our joints are for that piece of the stadium.

-Right.

0:52:080:52:12

It allows this part of the building to move independently

0:52:120:52:16

in an earthquake from the two sides of the stadium on either side of it.

0:52:160:52:20

-Right.

-The base of the entire part of that building is on layers of sand

0:52:200:52:25

-and high density polyethylene plastic.

-That's amazing.

0:52:250:52:28

It allows that part of the building to move a little easier than it would otherwise,

0:52:280:52:33

so when the ground moves six feet horizontal and two feet vertical,

0:52:330:52:37

it can just go along for the ride and the rest of the stadium is protected.

0:52:370:52:41

The stadium is just one part of a massive building

0:52:420:52:46

and strengthening programme all round San Francisco Bay.

0:52:460:52:49

A colossal 30 billion has been committed in total.

0:52:500:52:54

Will it be enough? They can only hope so.

0:52:540:52:57

Even if we knew exactly what earthquake is going to occur,

0:53:000:53:03

we may not know exactly how strong the shaking will be

0:53:030:53:06

and how it will vary across the city because of different soil types.

0:53:060:53:10

So you set a standard, you agree the buildings will be built to that

0:53:100:53:15

and then you hope that that's good enough.

0:53:150:53:17

You can't actually engineer chance out of the system altogether.

0:53:170:53:21

At least in San Francisco they've a good idea of what to expect,

0:53:240:53:29

even if they can't know exactly.

0:53:290:53:31

But there's one last sting in the tail.

0:53:310:53:33

Chance can sometimes come up with something you never even thought of.

0:53:330:53:38

As we know, there are known knowns,

0:53:390:53:42

there are things we know we know.

0:53:420:53:44

We also know there are known unknowns.

0:53:440:53:47

That is to say we know there are some things we do not know.

0:53:470:53:50

But there are also unknown unknowns,

0:53:500:53:53

the ones we don't know we don't know.

0:53:530:53:55

And if one looks throughout the history of our country and other free countries,

0:53:550:53:59

it is the latter category that tend to be the difficult ones.

0:53:590:54:03

Donald Rumsfeld may have just been trying to excuse an unfolding disaster in Iraq.

0:54:030:54:09

But "unknown unknowns" are a real and profound challenge for us all.

0:54:090:54:13

And don't we just know it.

0:54:140:54:16

The Bank of England is the rock-solid institution

0:54:210:54:26

to which we all turn in these turbulent times.

0:54:260:54:29

Surely I can find some certainty here?

0:54:300:54:33

I'm meeting Spencer Dale.

0:54:370:54:40

The Bank of England is the main financial institution in the country.

0:54:510:54:55

People want it to tell them what's going on in the economy, but can you predict what's going to happen?

0:54:550:55:00

Unfortunately not. Forecasting the economy is very difficult to do,

0:55:000:55:04

in part because the economy is very large and complex

0:55:040:55:08

and it's made even more difficult because it depends on people

0:55:080:55:13

and their decisions and that makes trying to model behaviour

0:55:130:55:17

and how the economy is going to change over time even more difficult.

0:55:170:55:21

Every quarter, the Bank makes a forecast for the nation

0:55:230:55:26

in the form of what it calls a "fan chart".

0:55:260:55:29

And it deliberately builds in uncertainty.

0:55:290:55:31

The chart shows that Britain's future economic growth

0:55:330:55:36

might have a 5% chance of lying in each one of the shaded bands.

0:55:360:55:41

This was the Bank's chart from 2007,

0:55:420:55:46

just before the big crash.

0:55:460:55:48

At the time we made this forecast,

0:55:480:55:50

we thought in three years' time

0:55:500:55:52

the annual growth of the economy may be anywhere

0:55:520:55:55

between 5% or close to zero.

0:55:550:55:58

But the Bank is even less certain than that.

0:55:580:56:02

It also leaves room for the unknown unknowns.

0:56:020:56:05

This only shows 90% of probability.

0:56:050:56:08

So it's shows you 90 times out of 100 we think the economy will go somewhere in this range.

0:56:080:56:13

So there's a one-in-ten chance it could just do anything?

0:56:130:56:16

There's a one-in-ten chance it will fall outside of this fan chart.

0:56:160:56:20

We don't try and put precise probabilities on those very extreme outcomes.

0:56:200:56:25

With these charts, the Bank is making one thing clear -

0:56:270:56:31

we must expect the unexpected.

0:56:310:56:33

And soon after the Bank made this chart, chance struck.

0:56:340:56:38

It was a genuinely surprising event, the economy to behave in a way

0:56:400:56:43

which we hadn't seen for almost an entire generation.

0:56:430:56:47

The environment which we operate in is inherently uncertain,

0:56:470:56:50

the future is uncertain

0:56:500:56:53

and the impact of our decisions are often very uncertain.

0:56:530:56:56

Some people might want to hammer the Bank of England

0:56:580:57:02

for not knowing what's around the corner.

0:57:020:57:04

But you can't blame them for the nature of chance.

0:57:040:57:07

And though the Bank can't give us the information we want,

0:57:070:57:11

I think they show the way to the wisdom we need.

0:57:110:57:14

There's just no use in looking for absolute certainty.

0:57:200:57:24

We can never rely on predictions.

0:57:240:57:27

We can tame chance, but only up to a point.

0:57:290:57:33

Putting numbers on chance is a powerful way

0:57:340:57:37

to get a handle on the future.

0:57:370:57:40

But these numbers can only ever be as good

0:57:400:57:43

as the information we have to hand.

0:57:430:57:46

Though we try to measure reality with precision,

0:57:460:57:49

sometimes they're little more than guesses.

0:57:490:57:52

What all this means is that uncertainty

0:57:520:57:55

is an essential part of being alive.

0:57:550:57:58

And whether our uncertainty

0:57:580:58:00

ultimately comes from out there or in here

0:58:000:58:03

won't, in the end, matter,

0:58:030:58:05

because either way surprises will most certainly happen.

0:58:050:58:10

For instance, in this year of the Diamond Jubilee,

0:58:100:58:12

I found a chicken nugget in the shape of Her Majesty the Queen!

0:58:120:58:17

What's the chances of that?

0:58:170:58:19

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