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.
- 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.
- Three, two, one. - I don't know what I'm doing.
- 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.
- Nice. - No, how did it do that?
- Yes. - Full turn.
I'm going to make the time back in speed.
Speed.
- And then forwards. - No!
Go, go, go, go, go, go, go, go, go.
- 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.
- 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.
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