Internet and Technology (4)
Well, I'm going to go for b) unmanned aerial vehicle.
Ok well, we'll see if you're right later on. Now let's talk more about drones,
which, apparently, seem to be everywhere now.
But are they safe and are they necessary? I've heard about them
being a hazard to aircraft because they've been flown close to airports.
Well, figures in 2016 showed that in the UK there were 70 near misses involving drones.
And that's more than double the year before. So that is a little worrying.
Yes. And there's the potential risk of people's privacy being
invaded when a drone is flown over their property with a camera attached to it.
Ah, but those cameras are also good at capturing some great
aerial footage – that's the film recording of the view from the above the ground. So
they're not all bad. And Dr Yoge Patel would agree. She is CEO of Blue Bear, which supplies
unmanned planes and drones. Here she is speaking about drones on the BBC's Woman's Hour programme…
They have the potential to be dangerous, agreed. They also have though, on the flip side,
the ability to be a game changer in both domestic use and in military use.
So, some of our drones are being used for aircraft inspections. We've put our drones into Fukushima.
So there you go Neil. There are many useful things drones can do,
and Dr Patel said they have the ability to be a game changer.
And by that you mean ‘something that completely
changes the way something is done or thought about'.
Yes. Her company has used drones to inspect the inside of the damaged
Fukushima nuclear power station in Japan. And another example of drones being a game
changer is UNICEF and the Malawian government testing drones for carrying medical supplies.
This could help save lives in remote places. And I have read that in Australia,
lifeguards are using drones to help rescue swimmers who get in trouble in the sea.
And have you heard about a Japanese firm that's planning to use a drone to force employees
out of their offices by playing music at them if they stay to work evening overtime.
I haven't, but you've convinced me – it seems like the sky's the limit for the uses of drones!
I mean there's no limit to what they can do. But I
am a little concerned about how they are regulated or controlled.
Well Dr Yoge Patel says because the technology is new,
regulations – or legal controls - are developing all the time…
As technology progresses, regulation and operational use needs to then be
harmonised with it. And we are, as a community, going through that whole process of saying
what is proportionate and appropriate regulation to go with different uses of drones.
So she talked about regulations being harmonised as technology progresses.
So I think she means ‘making regulations suitable and appropriate for what the drones
are being used for'. So they need some control, but not so they can't be useful and effective.
Like flying drones to stop you working late!
Now Rob, I'm dying to know what the other name for a drone is.
OK, let me tell you. So earlier I asked what does UAV stand for? Was it…
a) Unidentified aerial vehicle
b) Unmanned aerial vehicle c) Unaided aircraft vehicle
And I said b) – was that correct?
Yes Neil, you know your drones – that's correct. Well done. UAVs or drones have been around for
quite a while in different forms. It's thought they were first used
for providing practice targets for training military personnel. OK Neil,
let's quickly go over some of the vocabulary we have mentioned today, starting with surveillance.
"The police kept the jewellery shop under surveillance because they had
a tip-off about a robbery." So that means ‘carefully watching someone or something,
usually to try to stop something illegal'.
Then we mentioned aerial footage – that's film recording made from the sky.
"The aerial footage on TV of the dolphins swimming was spectacular."
Yes, drones have been a game changer for wildlife programmes on TV.
That means ‘something that completely changes the way something is done or thought about'.
We also mentioned the phrase 'the sky's the limit', meaning ‘there's no limit
to something'. "The sky is the limit to what professional footballers can earn these days."
Then we discussed harmonised – that describes two things being suitable for each other to
allow them to work properly. "The garden has been designed to harmonise with the natural landscape."
Very useful vocabulary, Neil. But let's stop droning on – and that means ‘talking
too much in a boring way' - and remind everyone to check out our You Tube,
Facebook, Twitter and Instagram pages – and of course, our website
at bbclearningenglish.com. See you next time. Goodbye.
Goodbye
Hello. This is 6 Minute English, I'm Neil.
And I'm Sam.
It's good to see you again, Sam.
Really?
Yes, of course, can't you tell by the way I'm smiling?
Ah well, I find it difficult to tell if someone is really smiling or if it's a fake smile.
Well, that's a coincidence because today's programme is all about how computers may
be able tell real smiles from fake smiles better than humans can. Before we get in to that though,
a question. The expressions we can make with our face are controlled by muscles.
How many muscles do we have in our face? Is it:
A: 26
B: 43 C: 62
What do you think, Sam?
No idea! But a lot, I'd guess, so I'm going with 62.
OK. Well, we'll see if you'll be smiling or crying later in the programme. Hassan Ugail is a
professor of visual computing at the University of Bradford. He's been working on getting computers
to be able to recognise human emotions from the expressions on our face. Here he is speaking on
the BBC Inside Science radio programme – how successful does he say they have been?
We've been working quite a lot on the human emotions, so the idea is
how the facial muscle movement, which is reflected on the face,
through obviously a computer through video frames and trying to understand how these
muscle movements actually relate to facial expressions and then from facial expressions
trying to understand the emotions or to infer the emotions. And they have been quite successful in
doing that. We have software that can actually look at somebody's face in real time and then
identify the series of emotions that person is expressing in real time as well.
So, have they been successful in getting computers to identify emotions?
Yes, he says they've been quite successful, and what's interesting is that he says that
the computers can do it in real time. This means that there's no delay. They don't have to stop and
analyse the data, or crunch the numbers, they can do it as the person is talking.
The system uses video to analyse a person's expressions and can then infer the emotions.
To infer something means to get an understanding of something without actually being told directly.
So, you look at available information and use your
understanding and knowledge to work out the meaning.
It's a bit like being a detective, isn't it? You look at the clues
and infer what happened even if you don't have all the details.
Yes, and in this case the computer looks at how the movement of muscles in the face
or facial muscles, show different emotions. Here's Professor Ugail again.
We've been working quite a lot on the human emotions so the idea is how the facial muscle
movement, which is reflected on the face, through obviously a computer through video
frames and trying to understand how these muscle movements actually relate to facial expressions
and then from facial expressions trying to understand the emotions or to infer the emotions.
And they have been quite successful in doing that. We have software that can actually
look at somebody's face in real time and then identify the series of emotions that person is
expressing in real time as well. So, how do the computers know
what is a real or a fake smile? The computers have to learn that first.
Here's Professor Ugail again talking about how they do that.
We have a data set of real smiles and we have a data set of fake smiles.
These real smiles are induced smiles in a lab. So, you put somebody on a chair and then show
some funny movies and we expect the smiles are genuine smiles.
And similarly we ask them to pretend to smile. So, these are what you'd call fake smiles. So,
what we do is we throw these into the machine and then the machine figures out what are the
characteristics of a real smile and what are the characteristics of a fake smile.
So, how do they get the data that the computers use to see if your
smile is fake or genuine – which is another word which means real?
They induce real smiles in the lab by showing people funny films. This means that they make
the smiles come naturally. They assume that the smiles while watching the funny films are genuine.
And then they ask the people to pretend to smile and the computer programme now has a
database of real and fake smiles and is able to figure out which is which.
Figure out means to calculate and come to an answer
Yes, and apparently the system gets it right 90% of the time,
which is much higher than we humans can. Right, well before we remind ourselves of our vocabulary,
let's get the answer to the question. How many muscles do we have in our face? Is it:
A: 26
B: 43 C: 62
Sam, are you going to be smiling? What did you say?
So I thought 62! Am I smiling, Neil?
Sadly you are not, you are using different muscles for that sort of sad look!
Actually the answer is 43. Congratulations to anyone who got that right. Now our vocabulary.
Yes – facial is the adjective relating to face.
Then we had infer. This verb means to understand something
even when you don't have all the information, and you come to this understanding based
on your experience and knowledge, or in the case of a computer, the programming.
And these computers work in real time, which means that there's no delay
and they can tell a fake smile from a genuine one, which means a real one, as the person is speaking.
They made people smile, or as the Professor said, they induced smiles by showing funny films.
And the computer is able to figure out or calculate whether the smile is fake or genuine.
OK, thank you, Sam. That's all from 6 Minute English today.
We look forward to your company next time and if you can't wait you can find
lots more from bbclearningenglish online, on social media and on our app. Goodbye!
Bye!
Welcome to 6 Minute English, where we bring you an intelligent topic and six
related items of vocabulary. I'm Neil.
And I'm Tim. And today we're talking about AI – or Artificial Intelligence.
Artificial Intelligence is the ability of machines to copy human intelligent
behaviour – for example, an intelligent machine can learn from its own mistakes,
and make decisions based on what's happened in the past.
There's a lot of talk about AI these days, Neil, but it's still just science fiction, isn't it?
That's not true – AI is everywhere. Machine thinking is in our homes,
offices, schools and hospitals. Computer algorithms are helping us drive our cars.
They're diagnosing what's wrong with us in hospitals.
They're marking student essays… They're telling us what to read on our smartphones…
Well, that really does sound like science fiction – but it's happening already, you say, Neil?
It's definitely happening, Tim. And an algorithm, by the way, is a set of steps a computer follows
in order to solve a problem. So can you tell me what was the name of the computer which
