Episode 4 Bang Goes the Theory


Episode 4

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Transcript


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Good evening and welcome to the show.

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Have you just arrived home?

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Have you fought your way through queues and off crowded trains

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and did you do the British thing of queuing very politely,

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but actually inwardly seething?

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With this country's population growing to 70 million people,

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-we're going to have to learn how to cope in crowded places, aren't we?

-We are.

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So, in tonight's show,

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Jem experiences the crush of a crowded gig

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and finds out where's the worst place to stand...

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It's a bit of a squeeze to say the least!

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Number-crunching Legend Johnny Ball hits the streets of London and counts cabs

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to show how maths can help you guess the size of a crowd.

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Whether we'll get this right, I can't be sure.

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And later, I'll be seeing if a random group of people

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can cooperate with each other without even knowing it.

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Not only have they figured it out, they're actually playing a game.

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So if you haven't guessed it yet...

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Tonight's show is all about the science of crowds,

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-the hows...

-The whats...

-..the whens

-..and the whys.

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Where better to start than outside a football stadium on match day?

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-Who do we love?

-ALL: Arsenal.

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THEY LAUGH

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We're all used to, aren't we, phrases like group mentality

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or following the crowd?

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But is there any actual basis to that

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and can being part of a large group

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actually make you do things that you wouldn't normally do?

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I've never seen Arsenal play live,

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but I can already feel the camaraderie here rubbing off on me.

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It's almost kind of like you belong to something.

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You're reclaiming it for yourselves,

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all the things you wouldn't normally do, like walk in the middle of the road,

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it's suddenly OK. People talking to each other and everyone bonding.

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It feels nice.

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Being in this crowd doesn't make me want to go on the rampage

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and from what I've seen, no one else here is about to riot either.

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But is there some kind of Jekyll and Hyde switch

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that can bring out our worst or our best when we're in a big group?

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I've joined world expert on crowd psychology,

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Steve Reicher to find out. And he's a Spurs fan.

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Yes, people do behave differently in groups.

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They are transformed in groups.

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That sense of empowerment,

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you making history and controlling the world on your own terms,

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that's exhilarating, that's exciting,

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that's one of the things people get out of crowd behaviour.

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Behind that empowerment is a shared sense of identity.

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This crowd are united just by the colours of red and white,

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wherever they come from.

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These Arsenal fans down here are going to be thrilled

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if somebody, often from another country, kicks a ball into the goal.

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Not because they've done anything,

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not because they've achieved anything,

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because the group has done well.

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And in groups and in crowds

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it's the fate of the group that you care about.

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If they do well, you've done well. If they are valued, you are valued.

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That doesn't mean that they just do anything and get carried away.

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But there are instances perhaps within a group,

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there was a chap, I remember in the student loan protest

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who threw a fire extinguisher...

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Potentially he's not going to do that when he's not in a group?

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People just don't behave in that way generally.

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The interesting thing in that incident

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was there had been confrontation with the police.

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There had been a certain level of conflict, but at that moment,

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when somebody did something which threatened life and limb,

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which so clearly violated people's sense of what was acceptable,

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actually, that de-escalated the conflict.

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OK, so being in a crowd can change your behaviour,

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but it doesn't automatically make us all rioters.

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In fact, you're usually reined in by the crowd if you get out of control.

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Quite how being part of crowd could have such a profound effect on us

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has always been a mystery.

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But here at the University of Nijmegen,

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Dr Vasily Klucharev thinks he may have found an answer.

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And in order to show me, he needs me inside his functional MRI scanner.

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While I'm in here, he wants me to perform a test.

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On a screen above me, 100 faces are displayed, one after the other.

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I have to score them for beauty out of eight.

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Here's the weird part - after each score I give,

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the screen shows me how other people rated that face.

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20 minutes later, Vasily shows me the inside of my head

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and explains his testing had nothing to do with beauty

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and everything to do with those red bits in my brain.

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So in fact, this experiment

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was about social conformity.

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We are interested in how much

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actually you change your opinion in line with others.

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I thought there was something fishy going on,

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because I was trying to figure out,

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why were you showing me what other people were thinking?

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Basically, we hypothesise

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that whenever your opinion deviates from the group opinion,

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your brain will emit certain error signals,

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that you did something wrong when you judged faces differently.

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-So, you've done something wrong?

-Exactly.

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Is this an unconscious thing we do because we want to follow the crowd?

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It's very automatic response.

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During the scanning, we saw when you experienced a conflict with others,

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your brain emitted this kind of signal.

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If I chose one thing and the group chose something different

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I actually felt, blimey, did I miss something here?

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Have I done something wrong?

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It's that hard-wired alarm signal in the brain

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that Vasily has been looking at over the last few years.

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And by looking at the size of that response,

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he can now categorise people as conformists, or rebels.

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I just wanted to show you, that here in the medial pre-frontal cortex,

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this area is very important for learning

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and it drives behavioural adjustments.

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In conformists, we see that area lights up.

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In nonconformist, this area doesn't respond.

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So all these terms, peer pressure, following the crowd,

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these are things we're all familiar with,

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they're actually backed up really, by real, solid data?

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Exactly, so we've perhaps for the first time,

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suggested real neurobiological mechanisms for this.

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So looking at the picture of my brain,

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am I a conformist, or am I a rebel?

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-Am I a free thinker?

-Let's have a look.

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You have a smaller, but still some activity here,

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so I would say that your brain activity is somewhere in between.

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What does he mean "somewhere in between"?

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My rebel legend dreams shattered.

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Vasily reckons he can prove his diagnosis

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in the final stage of the test.

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He reckons I can never override

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my annoyingly slightly conformist tendencies,

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so when faced with those same 100 pictures,

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I'll subconsciously adjust my scores closer to the groups' scores.

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Although now I can't remember any of the scores from before,

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I'm determined not to be influenced and 10 minutes later...

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OK, I'm good.

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..I'm ready for the results.

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-This is an index of extreme conformist.

-Yes.

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The person changed a lot in the second session

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and this is your change.

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You can see you changed a bit your opinion,

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on average, slightly in line with the group.

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It's a defeat.

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Despite my best efforts to score the faces exactly as before,

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I have been swayed by the group opinion, just as Vasily predicted.

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Tell me, why does this happen?

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Why is there perhaps a tendency for human beings to want to conform?

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Is there a selective reason?

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Because I'm a biologist, I'm very much biased by biology

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and I think there is an evolutionary reason for this.

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Simply the group is smart.

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The average group opinion is better than individual opinion.

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So, hang on, I think I'm a nonconformist.

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What we'll do is hook you up to Vasily's MRI scan and have a closer look.

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Looking forward to that.

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As we all know, last year was a census year.

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70 million people now living in the UK, which got us to thinking,

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how do you figure out the size of the population

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if you don't actually have a census form?

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Had you count the number of fish in the sea, for example?

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Very simple. You use maths.

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Not my forte, I'll be honest, but made bearable when I was a kid

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by this week's special guest, none other than Johnny Ball himself.

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We asked him to think of a number.

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He'd never heard that joke before.

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Hello. As it happens,

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I know a very good mathematical way of estimating an unknown population.

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Using, ping-pong balls.

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What a lot of ping-pong balls. But how many?

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Well, I don't know so I'm going to try to estimate the number.

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I could count them one by one, but that would take ages,

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so this is a little more tricky.

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What I do is take a good sample,

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quite a few balls and I mark them with a felt tip pen. Here we go.

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One, two...

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This technique is called capture, recapture.

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Biologists use it to find out animal populations.

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..98, 99, 100.

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Now what do I do? I pour all these back in again.

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With real animals you might clip or tag them

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and then set them free and hope that they mix back randomly.

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I think that might be pretty random

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but I'm going to choose another 100, but this time,

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we're going to use a blindfold.

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Four, five, six...

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'I've put the blindfold on so I can't see whether I'm choosing the ones

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'that are marked or not.' 100.

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The question is how many of those hundred are marked? So here we go.

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'Knowing how many are marked by my original mark....'

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One mark. Two mark.

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'..will help me to work out how many there are overall.'

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17.

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Nope. No.

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No.

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This is the theory.

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If you divide the 17 balls into the second sample of 100 balls,

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the proportion should be the same as dividing the first

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sample of 100 balls into the total number of balls.

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'So, second sample divided by 17...'

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Equals 5.88.

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'Now the first sample multiplied up - and that gives...'

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588 balls.

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That's our estimate.

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It is time to reveal the actual number of balls.

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There are...

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600.

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Not bad at all.

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'It's all very well finding out how many ping-pong balls are in a tank...'

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Taxi! 'But things get much more difficult in the real world.'

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So here is another capture recapture experiment.

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How many black cabs are there in London?

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By using the same maths as I did with the ping-pong balls, I'll try to estimate that number.

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'I genuinely have no idea how many they are out there,

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'there must be thousands. So I will need some help.'

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-Off you go!

-OK.

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'The bigger the sample, the more accurate our estimate will be.

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'So we spent two hours counting cabs in five places across London.'

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This counting taxis is not as easy as it looks.

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Whether we will get this right, I can't be sure.

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'We are noting the unique licence numbers as our way of tagging the taxis.

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'We then come back the same time the next day to count taxis for another two hours,

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'to see what proportion of them we've tagged the day before.

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'Now into the warm for some maths.'

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So there we are, we have counted taxis on two separate days for two hours each session.

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We've fed all the figures into the computer

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so now it is the moment of truth.

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How many taxis did we count?

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The number of taxis we spotted on both days, having run them

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through the computer, is 321.

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So we now do the same maths that we did with the ping-pong balls,

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and it should give us our estimate.

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So the second day's numbers divided by the number of repeats.

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Equals 6.64 or roughly a sixth of the cabs we saw on day two had been

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marked the day before as well.

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So all we need to do is take 6.64

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and multiply it by the number of cabs we saw on day one to

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get our estimate of the number of cabs on London's streets.

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The total estimate is 12,140. With some decimal places.

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'So how accurate is that? I know just the person to ask.

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'Bob Oddy is a long-time taxi driver

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'and now General Secretary of the Cabbies' Union.

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'So what did he think of our number?'

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Well, the total number of taxis licensed in London would be about 23,000 -

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-give or take a dozen or so.

-We were miles out! Wow!

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-But you're talking about the number of cabs working at any one time.

-Yes.

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Well, allowing for day shift, night shift, overlaps,

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11-12,000.

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We were spot on!

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Bob, thanks ever so much.

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Taxi!

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So this capture recapture system worked very well for us

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and it does work in quite a lot of places.

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As for me, I will be happy to catch a London cab any time.

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But as far as counting was concerned, never again.

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It's a good job taxis work in shifts. Imagine the chaos

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if they all crowded onto the roads at once.

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But there are times when PEOPLE simply can't avoid

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crowding together - at rush-hour, sports events and big rock concerts.

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One-two, one-two.

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When you get a large crowd, you can have hundreds of tons

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of people sloshing around like a liquid.

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When that happens you get the human version of flows,

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waves and pressures building up.

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I've come to Bucks New University to find out how that is measured

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and what it's like to be in the thick of it.

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This is Professor Chris Kemp, an expert in crowd safety.

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He has designed a pressure suit capable of monitoring impact

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and temperature readings from anywhere in the crowd.

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One, two, three, four - let's go, guys!

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I'm going to put the suit into action at this specially staged concert.

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Like most of us, I've headed straight for the front.

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Just run in.

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Chris directs wave after wave of sweaty students

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to pile on the pressure.

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It's a bit of a squeeze to say the least!

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With about 100 of them charging into me, this was a pretty realistic simulation.

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Chris, I've not felt crowd pressures like that

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since Friday nights out in Telford in the late '80s.

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I remember bars where you could be up there

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and lift your feet off the floor and you don't fall.

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What do the numbers say from your read-outs?

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This is where the first row of people hit you, OK?

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I remember.

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Then it goes down because the pressure isn't sustained.

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Is that a significant difference?

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It is, because it is one pound per square inch.

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This is where the second row hits you, then the third row,

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then the fourth row, etc.

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The pressure on the barrier was 2.67 kilonewtons per metre.

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To translate, that is over a quarter of a ton of crowd pressure.

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That's like a small horse falling on you. It is!

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Is that typical of an intense gig or does it get bigger than that?

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It does. The biggest recorded crowd pressure that

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we know about is 8.6 kilonewtons at a gig.

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But that has just been for a second. It is when it is sustained that it's dangerous.

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If you take Hillsborough, that was sustained pressure in one small area with a lot of people.

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That's why the fences were taken down because there was no way out.

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Research has shown that a sustained 1.2 kilonewtons

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for 15 minutes is enough to be fatal.

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Are there times when it really drops off or times when it really peaks?

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What does happen is that if you are on a barrier, a wall,

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or a fence, you have the ability to push backwards,

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but then if people are coming forwards, one metre to one-and-a-half metres,

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the people there have the double pressure coming into them.

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That's where you have got to watch a little bit.

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So the message is don't stand a couple of rows

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back from the front if you want to avoid the highest pressures.

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But pressure isn't the only thing to watch out for in a crowd. There's also heat.

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When you first came into the pit the temperature around you was 24 degrees.

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As you gradually go through there's a curve upwards to 32 degrees

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over a half an hour period.

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That's an eight degree increase in the temperature around you.

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-That's quite high.

-And it felt high.

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Would you say that heat is almost more of a danger in big crowds than pressure?

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It can be, and it's interesting when we record this

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because last summer at a very hot festival we recorded

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a 14 degree increase in temperature on two of the girls who were in the pit.

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That's because they were very small and the lads around them

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were very tall and it traps the air inside that so it can't get out.

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But if you do get into trouble what's the best time to get out?

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Pressure drops significantly when people put their hands in the air to clap at the end.

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-Right.

-The actual body mass of the arms is taken out of the equation. It's in the air.

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If you want to move when you're in a crowd like that,

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wait until the end of the song and then sneak through.

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What we want is for everybody to be as safe as possible

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so anything we can do to support that we will do.

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What an amazing crowd you are. You're so amazing.

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It's time for this week's brain teaser with the great

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brain teaser himself Dr Yan. Yan? Yan?

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This week I'm going to try and guess how many buses there are in the whole of London,

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but unlike Johnny Ball I'm not going to do any counting whatsoever.

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Can you guess how I'm going to do it? I'll give you a clue.

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The answer is hopefully all around me.

0:18:420:18:46

As always, you can find Yan's answer on our website,

0:18:460:18:50

and whilst you're there follow the links to the Open University

0:18:500:18:53

for more crowd science.

0:18:530:18:55

Don't forget to check for details of the Bang live roadshows.

0:18:570:19:00

You can get hands on with us in Edinburgh in a couple of weeks.

0:19:000:19:04

Then we are off to Sheffield and Poole.

0:19:040:19:06

Tickets are free from our website.

0:19:060:19:08

OK. So far we've been looking at the problems with crowds, but we've all seen schools of fish

0:19:090:19:15

or flocks of birds moving beautifully as a single unit.

0:19:150:19:19

Almost as if they have a collective consciousness

0:19:190:19:21

and this is one of science's greatest mysteries.

0:19:210:19:24

It got me thinking, could human beings behave the same way?

0:19:240:19:28

In about 20 minutes or so, this cinema is going to fill up

0:19:280:19:32

with a few hundred people, fingers crossed.

0:19:320:19:35

They will be taking part in an experiment

0:19:350:19:37

and the thing is they have no idea about what this experiment is about.

0:19:370:19:42

And I'm not going to tell them anything,

0:19:420:19:44

but it all comes down

0:19:440:19:45

to this plastic paddle with a red and a green side.

0:19:450:19:50

The question is, will they be able to figure out for themselves what it's all about?

0:19:500:19:53

Our guinea pigs in this social experiment are visitors to Birmingham's Giant Screen.

0:19:530:20:00

Each one of them has been given one of the reflective paddles on their way in.

0:20:000:20:05

And watching them all from beneath the giant screen are cameras which

0:20:050:20:09

record which side of the reflective paddles they are holding up.

0:20:090:20:12

Our crowd don't know it yet but the experiment starts as soon as they sit down.

0:20:120:20:16

People are looking at their paddles, everyone is looking at it and wondering what on earth

0:20:160:20:21

it's for, like "What is this for?" Look, here's something interesting, look. Here we go.

0:20:210:20:27

Suddenly everybody's holding their paddle up to the screen...

0:20:270:20:31

..and they're making the connection now almost instantaneously.

0:20:330:20:36

Just a couple of people did it and suddenly everyone did it.

0:20:360:20:39

You can see them pointing with their fingers. "There's me. There's me."

0:20:390:20:43

Another thing the audience don't realise is that we've actually divided them into two teams.

0:20:430:20:48

We're going to introduce something else - the classic video game Pong.

0:20:480:20:52

Obviously we've updated the graphics a bit, but the aim is still

0:20:520:20:56

to bounce the shark across the screen past the opposing team's bat.

0:20:560:21:00

The teams have to work together to control their bat.

0:21:000:21:05

It'll only move right to the top if they all showed green at once

0:21:050:21:08

and the more red that they show, the further down it moves.

0:21:080:21:11

That's amazing because it's all about cooperation.

0:21:110:21:17

Between them they have realised that some people have to be red

0:21:170:21:19

and some people have to be green.

0:21:190:21:22

It's difficult to keep it moving because you've got to get the right

0:21:240:21:27

amount of people showing red and the right amount of people showing green

0:21:270:21:31

depending on where you want it.

0:21:310:21:33

Obviously these guys are just sensing each other,

0:21:330:21:35

feeling it, and working it out amongst themselves.

0:21:350:21:39

FROM CROWD: Right, go red.

0:21:390:21:40

Oh, they just got it in time.

0:21:400:21:44

In hardly any time at all each team is suddenly working as one.

0:21:440:21:49

CHEERING

0:21:490:21:52

Here's the incredible thing. This has happened with no instruction whatsoever.

0:21:520:21:57

CHEERING

0:21:570:22:00

Pong was always my favourite videogame.

0:22:000:22:02

CHEERING

0:22:020:22:04

APPLAUSE

0:22:060:22:08

What made you decide, "I will do a bit of green, no, I will do a bit of red"?

0:22:120:22:15

I know most people are going to go red because everyone was

0:22:150:22:18

shouting red, we'll go green.

0:22:180:22:19

I can't believe the way it works.

0:22:190:22:21

How that's coordinated I've no idea.

0:22:210:22:26

I didn't think they would get that so quickly.

0:22:260:22:29

You see what we can do when we work together?

0:22:290:22:32

If that kind of cooperation is possible,

0:22:320:22:34

even at a subconscious level,

0:22:340:22:37

you wouldn't know it in the chaos of morning rush-hour.

0:22:370:22:40

Up and down the country, as the trains are pulling in, it's every man for himself.

0:22:400:22:45

Britain's population recently passed 70 million and the majority of these people live in our cities.

0:22:480:22:55

Huge numbers like these can create real challenges for urban planners

0:22:570:23:02

because they have to make sure that crowds that big

0:23:020:23:05

can move around quickly and safely.

0:23:050:23:08

Delays and queues aren't the only worries.

0:23:080:23:12

Tragedies can and do happen,

0:23:120:23:13

especially during emergency evacuations.

0:23:130:23:16

I've come to a very windy vantage point

0:23:160:23:19

high above the streets of London to find out how

0:23:190:23:22

scientists are tackling the problem.

0:23:220:23:25

Andrew, from here when you look at that massive crowd it does look

0:23:250:23:30

fairly organised and calm despite the number of people.

0:23:300:23:32

That's right.

0:23:320:23:33

Especially at large densities, you start to see collective behaviour emerging.

0:23:330:23:38

The crowd doesn't just act as individuals on their own.

0:23:380:23:40

It starts to exhibit good behaviour.

0:23:400:23:43

Andrew uses computer models to analyse the way crowds move

0:23:430:23:47

through a cityscape.

0:23:470:23:48

This can help him predict bottlenecks

0:23:480:23:50

and ultimately to make cities safer for us all.

0:23:500:23:55

Aside from razing everything to the ground and starting again,

0:23:550:23:58

what can we do to deal with the growing number of people

0:23:580:24:01

moving into our cities?

0:24:010:24:02

It would be lovely to demolish everything

0:24:020:24:04

and start again, wouldn't it?

0:24:040:24:06

We have to work with the cities we have. The only way that is good to happen is

0:24:060:24:10

if we use the new technologies that are emerging to understand

0:24:100:24:14

the crowd and even to start to influence the crowd in subtle ways.

0:24:140:24:17

'With his colleague Anders Johansson from the University of Bristol,

0:24:200:24:22

'Andrew has been studying how crowd flow is affected by the most common

0:24:220:24:28

'bottleneck - the doorway.

0:24:280:24:29

'They've asked me to round up some friends to help carry out an experiment.'

0:24:290:24:34

As an added extra incentive we've got some cupcakes at the other

0:24:340:24:38

end of the doorway.

0:24:380:24:39

There are not enough cupcakes for all of you.

0:24:390:24:43

The challenge is to get to that cupcake without actually killing

0:24:430:24:47

the person next to you.

0:24:470:24:48

-Are you guys ready? ALL:

-Yes.

0:24:480:24:51

OK, three, two, one, go!

0:24:510:24:54

SHOUTING

0:24:540:24:57

Whoa!

0:24:570:24:59

Filter through, filter through.

0:24:590:25:01

SHOUTING AND LAUGHTER

0:25:010:25:04

-They are really packing through.

-20.75 seconds.

0:25:040:25:10

There was a lot of jamming and then flowing again, jamming and then flowing again. Is that normal?

0:25:100:25:16

What we are see during evacuation conditions,

0:25:160:25:18

we have periods of total blockage

0:25:180:25:20

and then sudden outbursts of small groups, intermittent outflows.

0:25:200:25:23

OK. Really that's a classic example of how what can go wrong

0:25:230:25:26

when too many people are trying to rush through a tiny narrow

0:25:260:25:29

-entrance like that.

-Exactly. This is the faster-is-slower effect.

0:25:290:25:34

The more that people push, it lowers the outflow of people through the doorway.

0:25:340:25:40

OK, fair enough.

0:25:400:25:41

The team's research has produced some surprising solutions to the problem.

0:25:410:25:46

We really want to prevent people from clogging in the doorway.

0:25:460:25:51

One way to achieve that is to put an obstacle in front of the door which

0:25:510:25:54

will prevent people from clogging, it will split up the crowd.

0:25:540:25:58

OK that sounds counterintuitive,

0:25:580:25:59

to put an obstacle in that narrow doorway while all of you are

0:25:590:26:03

trying to squeeze past. It sounds like it's going to slow everything down.

0:26:030:26:06

-But let's see what happens.

-Yes.

-What are we using as an obstacle? A chair?

0:26:060:26:10

Let's use you, Liz! We'll put you in front of this!

0:26:100:26:13

After what I have just seen I don't think that's a good idea!

0:26:130:26:15

Oh, Lord! OK, are you guys ready?

0:26:150:26:18

-ALL:

-Yes!

0:26:180:26:19

Please don't hurt me! Three, two, one, go!

0:26:190:26:25

Whoa! Barging through!

0:26:260:26:29

Easy does it, guys. Nice. Keep going, keep going.

0:26:320:26:37

16.37. Result.

0:26:370:26:41

APPLAUSE

0:26:410:26:42

Who knew?

0:26:420:26:44

'It's that 20 percent speed increase that excites Andrew and Anders.

0:26:440:26:49

'But their discovery is still too radical for many architects.'

0:26:490:26:52

It's so counterintuitive that putting an obstacle in front of a doorway

0:26:520:26:58

would actually improve the flow,

0:26:580:26:59

that quite often building designers don't want to do that in case

0:26:590:27:04

it makes people feel less safe.

0:27:040:27:05

Until such measures are widely adopted

0:27:070:27:10

Andrew can offer us a few techniques to help speed you through doors.

0:27:100:27:15

One of the classic tricks is, if there is a single doorway that

0:27:150:27:18

a crowd is trying to move through, generally moving around the edge of the crowd

0:27:180:27:22

and walking along the surface of the obstacle

0:27:220:27:25

will get you there quicker.

0:27:250:27:26

Good science if you want to design, say, the Olympic Stadium

0:27:290:27:33

and you need to get everyone in and out really quickly.

0:27:330:27:36

Exactly. If you visit the Olympic Village you'll find that

0:27:360:27:38

every doorway has been designed with science in mind.

0:27:380:27:41

If you see a random bollard, it's there for a reason.

0:27:410:27:44

-Brilliant thinking.

-That's all for now.

0:27:440:27:46

We'll see you in two weeks when we will be looking at phone

0:27:460:27:49

and Wi-Fi signals, the effect they have on our health,

0:27:490:27:53

and how they could be used to beam free electricity from space.

0:27:530:27:56

-Goodbye from us from Oxford Circus. See you soon.

-Bye.

0:27:560:28:00

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