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  • They're everywhere.

  • Apparently algorithms are in the social media apps we use every day,

  • in search engines, even in dating apps.

  • But I'll be honest -

  • I've got absolutely no idea what they actually are

  • or how they work or who makes them.

  • Should we be worried about them?

  • Can they think for themselves?

  • Rather than be baffled by science, I'm going to go find out.

  • Where does every good piece of research start? A search engine.

  • So what is an algorithm?

  • Can I even spell it?

  • Oh, I think so. OK.

  • A process or set of rules to be followed in calculations

  • or other problem solving operations, especially by a computer.

  • Sounds like a riddle.

  • After an hour of searching about the internet

  • it all felt a little overwhelming.

  • So many different definitions without any clarity in what they actually do.

  • During my search I came across professor Victoria Nash

  • from the Oxford Internet Institute.

  • I called to pick her brains.

  • Speaking to Victoria has helped me understand what algorithms are

  • but how can the same thing that helps me bake a cake,

  • also give me the best results from a search engine?

  • No idea.

  • I'm taking a trip to Oxford

  • to visit one of Victoria's colleagues, Dr Bernie Hogan.

  • Bernie, great to see you.

  • Jon, nice to see you.

  • Where on earth are we?

  • So this is our university's data centre.

  • You know, it's pretty big. It's really noisy.

  • Really noisy.

  • There's a lot of computation happening here.

  • Each one of these belong to different departments.

  • They're doing different kinds of calculations.

  • So there's thousands of algorithms

  • going on in all these massive boxes like now?

  • Thousands? Try billions.

  • Billions?

  • Billions of algorithms.

  • Shall we go somewhere a little bit quieter

  • and talk in a little bit more detail

  • and try and get a better understanding

  • of how all of this works?

  • Sure. Let's do it.

  • It's weird to think how much of our lives

  • go on in nondescript server rooms all over the world.

  • But what exactly are these billions of algorithms doing?

  • So the reason that we use a list of instructions

  • is because we have a lot of data and we have to deal with that data.

  • Now data could be anything.

  • Data could be a list of towns in the UK

  • and how I get from one town to another,

  • or it could be a number of tweets.

  • Which tweet is going to show up at the top of the list?

  • Right.

  • Algorithms calculate based on a bunch of features,

  • the sort of things that will put something at the top of the list

  • and then something at the bottom of the list.

  • So if it's that simple, should we be scared of algorithms?

  • Well the trick with algorithms

  • that we perhaps should be a bit concerned about

  • is what happens in the black box.

  • So is that like, when you search for something

  • you don't know what their algorithm is doing because we can't see it.

  • Well a classic case of this

  • is people talk about searching for prices for flights,

  • and depending on which day you search on you might get a different flight,

  • where you search from.

  • And so this can mean difference of hundreds of pounds.

  • That's an example where an algorithm is not transparent

  • and perhaps should be.

  • Can algorithms think for themselves?

  • Well we wouldn't necessarily think of a computer as thinking,

  • but we know that algorithms can learn.

  • They can learn from other algorithms

  • and algorithms can create their own instructions now.

  • But the basis of it is still the same.

  • Data goes in, goes through instructions, result comes out.

  • I'm beginning to get it,

  • but I've still never actually seen an algorithm.

  • I don't even know what they look like.

  • So I'm heading to one of the UK's leading coding schools

  • to see for myself what goes into making one.

  • {\an2}- So this is code, right? - Yeah.

  • So what's the difference between an algorithm and code?

  • Coding is algorithms that a computer can run the instructions for you.

  • So we have to do it in a language

  • which the computer can actually understand.

  • So we've written this in Scratch

  • and it's really nice to use, really intuitive,

  • and you can just drag and drop these blocks

  • and we've got these instructions for the drone to follow.

  • It's going to do a flip?

  • It's going to do a flip. I hope it's going to do a flip.

  • It's time for a challenge - a drone race.

  • Izzy's algorithm versus me.

  • So the course is through the hoop, do a flip,

  • come back round, land and again.

  • So technically, because yours is programmed by an algorithm,

  • you should be able to do exactly the same thing

  • three times without a problem.

  • That's the plan. You ready? Challenge accepted.

  • {\an2}- Three, two, one. - I don't know what I'm doing.

  • {\an2}- Take off. Yes. - Okay.

  • Right.

  • So we're going set the speed.

  • Fly up. And then it's going fly left.

  • You're already ahead but I think mine's more reliable.

  • Hopefully it's going go forwards.

  • Go forwards, there we go.

  • {\an2}- Nice. - No, how did it do that?

  • {\an2}- Yes. - Full turn.

  • I'm going to make the time back in speed.

  • Speed.

  • {\an2}- And then forwards. - No!

  • Go, go, go, go, go, go, go, go, go.

  • {\an2}- Yes, oh, oh, oh! - Oh. Woah, woah.

  • Sorry cameraman!

  • I can just go and make a cup of tea. I'm just going to leave it.

  • No! [LAUGHS]

  • And down. Oh look how calm.

  • Have you done your three laps? I did do the three laps, yeah.

  • {\an2}- So you've won? - Yes.

  • So I think some of the big benefits of having algorithms versus humans

  • is that you don't have the human error

  • that, no offence, I think you had.

  • You don't have the human error in the same way.

  • The computer goes through the instructions

  • and that's all they know how to do.

  • The person writing the code could have written an error

  • and that's where problems can arise

  • but the computer doesn't make mistakes

  • it just does what it's supposed to do.

  • A computer might only do what it's supposed to do,

  • but what are the ethical considerations around algorithms

  • making so many decisions for us?

  • One of the public concerns is that computers are taking over the world,

  • robots are going to take over the world,

  • algorithms are going to take all of our jobs.

  • Is that going to be the case?

  • Taking our jobs, it's possible.

  • But also deskilling humans

  • if we become too dependent upon them and too trusting of them,

  • it can deskill us as well.

  • But on the flip side of it, they can be hugely beneficial and useful -

  • speeding up decision-making, making whole processes efficient,

  • maybe spotting things that we might not have spotted ourselves.

  • So we mustn't be frightened of them,

  • we just must use them in the correct manner.

  • What have we learnt then?

  • Algorithms are actually remarkably simple.

  • Just like Bernie said - data goes in,

  • follows a list of instructions and a result comes out.

  • In some parts of the world,

  • algorithms are now used in the criminal justice system,

  • in social care, in credit checks - they're prolific -

  • machines making decisions that directly affect our human lives,

  • not just the adverts that you see on the internet

  • or the people you match on dating apps.

  • The question for society isn't the algorithm,

  • it's who controls the algorithm

  • and where the data comes from that goes into them.

  • Thanks for watching. Don't forget to subscribe

  • and click the bell to receive notifications for new videos.

  • See you again soon.

They're everywhere.

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什麼是算法,它們是如何工作的?| 思想是什麼? (What is an algorithm and how do they work? | BBC Ideas)

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    Summer 發佈於 2021 年 01 月 14 日
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