00:00:00
6 Minute English.
00:00:02
From BBC Learning English.
00:00:05
Hello. This is 6 Minute English
from BBC Learning English. I'm Neil.
00:00:09
And I'm Rob.
00:00:11
Now, I'm sure most of us
have interacted with a chatbot.
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These are bits of computer technology
00:00:18
that respond to text with text
or respond to your voice.
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You ask it a question
and usually it comes up with an answer.
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Yes, it's almost like talking to
another human, but of course it's not,
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it's just a clever piece of technology.
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It is becoming more 'sophisticated' —
more 'advanced and complex' —
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but could they replace
real human interaction altogether?
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We'll discuss that more in a moment
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and find out if chatbots
really think for themselves.
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But first I have a question for you, Rob.
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The first computer program that allowed
some kind of plausible conversation
00:00:54
between humans and machines was invented
in 1966, but what was it called?
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Was it a) Alexa? b) ELIZA? Or c) PARRY?
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Ah, well, it's not Alexa, that's too new,
so I'll guess c) PARRY.
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I'll reveal the answer
at the end of the programme.
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Now, the old chatbots of the 1960s
and '70s were quite basic,
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but more recently, the technology
is able to predict the next word
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that is likely to be used in a sentence,
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and it learns words
and sentence structures.
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Mm, it's clever stuff.
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I've experienced using them
when talking to my bank,
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or when I have problems
trying to book a ticket on a website.
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I no longer phone a human,
I speak to a virtual assistant instead.
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Probably the most well-known chatbot
at the moment is ChatGPT..
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It is. The claim is that it's able
to answer anything you ask it.
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This includes writing students' essays.
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Now, this is something that was discussed
00:01:57
on the BBC Radio 4 programme,
Word of Mouth.
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Emily M Bender,
Professor of Computational Linguistics
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at the University of Washington,
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explained why it's dangerous to always
trust what a chatbot is telling us.
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We tend to react to grammatical,
fluent, coherent-seeming text
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as authoritative and reliable and valuable
and we need to be on guard against that,
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because what's coming out of ChatGPT
is none of that.
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So, Professor Bender says that
well-written text that is 'coherent' —
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that means it's 'clear,
carefully considered and sensible' —
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makes us think what we are reading
is reliable and 'authoritative'.
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So it's 'respected, accurate
and important sounding'.
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Yes, chatbots might appear
to write in this way,
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but really, they are just predicting
one word after another,
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based on what they have learnt.
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We should, therefore, be 'on guard' —
be 'careful and alert' —
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about the accuracy
of what we are being told.
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One concern is that chatbots —
a form of artificial intelligence —
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work a bit like a human brain in the way
it can learn and process information.
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They are able to learn from experience,
something called deep learning.
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A cognitive psychologist and computer
scientist called Geoffrey Hinton
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recently said he feared that chatbots
could soon overtake
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the level of information
that a human brain holds.
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That's a bit scary, isn't it?
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Mm, but for now, chatbots can be useful
for practical information,
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but sometimes we start to believe
they are human
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and we interact with them
in a human-like way.
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This can make us believe them even more.
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Professor Emma Bender, speaking on
the BBC's Word of Mouth programme,
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explains why we might feel like that.
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I think what's going on there is the kinds
of answers you get
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depend on the questions you put in,
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because it's doing likely next word,
likely next word,
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and so if, as the human
interacting with this machine,
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you start asking it questions about
how do you feel, you know, Chatbot?
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And "What do you think of this?"
And, "What are your goals?"
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You can provoke it to say things
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that sound like
what a sentient entity would say.
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We are really primed
to imagine a mind behind language
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whenever we encounter language
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and so we really have to account for that
when we're making decisions about these.
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So, although a chatbot might sound human,
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we really just ask it things
to get a reaction — we 'provoke' it —
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and it answers only with words
it's learned to use before,
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not because it has come up
with a clever answer.
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But it does sound like a sentient entity —
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'sentient' describes 'a living thing
that experiences feelings'.
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As Professor Bender says,
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we imagine that when something speaks,
there is a mind behind it.
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But sorry, Neil, they are not your friend,
they're just machines!
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Yes, it's strange then
that we sometimes give chatbots names.
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Alexa, Siri, and earlier I asked you what
the name was for the first ever chatbot.
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And I guessed it was PARRY. Was I right?
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You guessed wrong, I'm afraid.
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PARRY was an early form of chatbot from
1972, but the correct answer was ELIZA.
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It was considered to be the first
'chatterbot' — as it was called then —
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and was developed by Joseph Weizenbaum
at Massachusetts Institute of Technology.
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Fascinating stuff.
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OK, now let's recap some of the vocabulary
we highlighted in this programme.
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Starting with 'sophisticated',
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which can describe technology
that is 'advanced and complex'.
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Something that is 'coherent' is 'clear,
carefully considered and sensible'.
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'Authoritative' means 'respected,
accurate and important sounding'.
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When you are 'on guard' you must be
'careful and alert' about something —
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it could be accuracy
of what you see or hear,
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or just being aware
of the dangers around you.
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To 'provoke' means to 'do something
that causes a reaction from someone'.
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'Sentient' describes 'something
that experiences feelings' —
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so it's 'something that is living'.
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Once again, our six minutes are up.
Goodbye.
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Bye for now.
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6 Minute English.
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From BBC Learning English.
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Hello. This is 6 Minute English
from BBC Learning English.
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— I'm Sam.
— And I'm Neil.
00:06:15
In the autumn of 2021,
something strange happened
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at the Google headquarters
in California's Silicon Valley.
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A software engineer called Blake Lemoine
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was working on
the artificial intelligence project
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Language Models for Dialogue Applications,
or LaMDA for short.
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LaMDA is a 'chatbot' —
a 'computer programme
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'designed to have conversations
with humans over the internet'.
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After months talking with LaMDA
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on topics ranging from movies
to the meaning of life,
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Blake came to
a surprising conclusion —
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the chatbot was an intelligent person
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with wishes and rights
that should be respected.
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For Blake, LaMDA was a Google employee,
not a machine.
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He also called it his friend.
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Google quickly reassigned Blake
from the project,
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announcing that his ideas
were not supported by the evidence.
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But what exactly was going on?
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In this programme, we'll be discussing
whether artificial intelligence
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is capable of consciousness.
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We'll hear from one expert
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who thinks AI is not as intelligent
as we sometimes think
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and, as usual, we'll be learning
some new vocabulary as well.
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But before that,
I have a question for you, Neil.
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What happened to Blake Lemoine
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is strangely similar
to the 2013 Hollywood movie, Her,
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starring Joaquin Phoenix as a lonely
writer who talks with his computer,
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voiced by Scarlett Johansson.
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But what happens at the end of the movie?
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Is it a) The computer comes to life?
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b) The computer dreams about the writer?
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Or c) The writer falls in love
with the computer?
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C) The writer falls in love
with the computer.
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OK, Neil, I'll reveal the answer
at the end of the programme.
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Although Hollywood is full of movies
about robots coming to life,
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Emily Bender, Professor of Linguistics and
Computing at the University of Washington,
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thinks AI isn't that smart.
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She thinks the words we use
to talk about technology —
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phrases like 'machine learning' —
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give a false impression
about what computers can and can't do.
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Here is Professor Bender discussing
another misleading phrase —
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'speech recognition' — with
BBC World Service programme The Inquiry.
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If you talk about
'automatic speech recognition',
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the term 'recognition' suggests that
there's something cognitive going on,
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where I think a better term
would be automatic transcription.
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That just describes
the input-output relation,
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and not any theory or wishful thinking
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about what the computer is doing
to be able to achieve that.
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Using words like 'recognition'
in relation to computers
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gives the idea that something 'cognitive'
is happening —
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something 'related to the mental processes
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'of thinking, knowing, learning
and understanding'.
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But thinking and knowing are human,
not machine, activities.
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Professor Benders says that talking about
them in connection with computers
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is 'wishful thinking' —
'something which is unlikely to happen'.
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The problem with using words in this way
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is that it reinforces what
Professor Bender calls 'technical bias' —
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'the assumption
that the computer is always right'.
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When we encounter language that sounds
natural, but is coming from a computer,
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humans can't help but imagine
a mind behind the language,
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even when there isn't one.
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In other words,
we 'anthropomorphise' computers —
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we 'treat them as if they were human'.
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Here's Professor Bender again, discussing
this idea with Charmaine Cozier,
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the presenter
of BBC World Service's The Inquiry.
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So 'ism' means system,
'anthro' or 'anthropo' means human,
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and 'morph' means shape.
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And so this is a system that puts
the shape of a human on something,
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and, in this case,
the something is a computer.
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We anthropomorphise animals all the time,
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but we also anthropomorphise action
figures, or dolls,
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or companies when we talk about
companies having intentions and so on.
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We very much are in the habit of
seeing ourselves in the world around us.
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And while we're busy seeing ourselves
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by assigning human traits to things
that are not, we risk being blindsided.
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The more fluent that text is, the more
different topics it can converse on,
00:10:30
the more chances there are
to get taken in.
00:10:34
If we treat computers
as if they could think,
00:10:36
we might get 'blindsided',
or 'unpleasantly surprised'.
00:10:41
Artificial intelligence works by finding
patterns in massive amounts of data,
00:10:45
so it can seem like
we're talking with a human,
00:10:48
instead of a machine doing data analysis.
00:10:51
As a result, we 'get taken in' —
we're 'tricked or deceived'
00:10:55
into thinking we're dealing with a human,
or with something intelligent.
00:10:59
Powerful AI can make machines
appear conscious,
00:11:03
but even tech giants like Google
00:11:05
are years away from building computers
that can dream or fall in love.
00:11:10
Speaking of which, Sam,
what was the answer to your question?
00:11:13
I asked what happened in the 2013 movie,
Her.
00:11:17
Neil thought that the main character
falls in love with his computer,
00:11:20
— which was the correct answer!
— OK.
00:11:23
Right, it's time to recap the vocabulary
we've learned from this programme
00:11:27
about AI, including 'chatbots' —
00:11:29
'computer programmes designed to interact
with humans over the internet'.
00:11:34
The adjective 'cognitive'
describes anything connected
00:11:37
with 'the mental processes of knowing,
learning and understanding'.
00:11:41
'Wishful thinking' means 'thinking that
something which is very unlikely to happen
00:11:46
'might happen one day in the future'.
00:11:48
To 'anthropomorphise' an object
00:11:49
means 'to treat it as if it were human,
even though it's not'.
00:11:53
When you're 'blindsided',
you're 'surprised in a negative way'.
00:11:57
And finally, to 'get taken in' by someone
means to be 'deceived or tricked' by them.
00:12:02
My computer tells me
that our six minutes are up!
00:12:05
Join us again soon,
for now it's goodbye from us.
00:12:08
Bye!
00:12:09
6 Minute English.
00:12:11
From BBC Learning English.
00:12:14
Hello, I'm Rob. Welcome to 6 Minute
English and with me in the studio is Neil.
00:12:19
— Hello, Rob.
— Hello.
00:12:21
Feeling clever today, Neil?
00:12:22
I am feeling quite bright and clever, yes!
00:12:25
That's good to hear.
00:12:26
Well, 'you'll need your wits about you' —
00:12:28
meaning 'you'll need to think very
quickly' in this programme,
00:12:30
because we're talking about intelligence,
00:12:33
or to be more accurate,
artificial intelligence,
00:12:36
and we'll learn some vocabulary
related to the topic,
00:12:40
so that you can have
your own discussion about it.
00:12:42
Neil, now, you know
who Professor Stephen Hawking is, right?
00:12:46
Well, of course! Yes.
00:12:47
Many people say that he's a 'genius' —
00:12:49
in other words,
he is 'very, very intelligent'.
00:12:53
Professor Hawking is one of
the most famous scientists in the world
00:12:56
and people remember him for his brilliance
00:12:58
and also because he communicates using a
synthetic voice generated by a computer —
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'synthetic' means it's 'made from
something non-natural'.
00:13:07
'Artificial' is similar in meaning —
00:13:09
we use it when something is 'man-made
to look or behave like something natural'.
00:13:14
Well, Professor Hawking has said recently
00:13:17
that efforts to create thinking machines
are a threat to our existence.
00:13:21
A 'threat' means
'something which can put us in danger'.
00:13:25
Now, can you imagine that, Neil?!
00:13:26
Well, there's no denying that good things
00:13:28
can come from the creation
of artificial intelligence.
00:13:31
Computers which can think for themselves
00:13:33
might be able to find solutions
to problems we haven't been able to solve.
00:13:38
But technology is developing quickly and
maybe we should consider the consequences.
00:13:42
Some of these very clever robots
are already surpassing us, Rob.
00:13:47
'To surpass' means
'to have abilities superior to our own'.
00:13:51
Yes. Maybe you can remember the headlines
when a supercomputer
00:13:54
defeated the World Chess Champion, Gary
Kasparov, to everyone's astonishment.
00:14:00
It was in 1997.
What was the computer called though, Neil?
00:14:03
Was it a) Red Menace? b) Deep Blue?
Or c) Silver Surfer?
00:14:09
Erm, I don't know.
00:14:12
I think c) is probably not right. Erm...
00:14:16
I think Deep Blue. That's b) Deep Blue.
00:14:18
OK. Well, you'll know if you got the
answer right at the end of the programme.
00:14:22
Well, our theme is artificial intelligence
00:14:24
and when we talk about this,
we have to mention the movies.
00:14:27
Mm, many science fiction movies
have explored the idea
00:14:30
of bad computers who want to harm us.
00:14:33
One example is 2001: A Space Odyssey.
00:14:36
Yes, a good film.
00:14:38
And another is The Terminator, a movie
in which actor Arnold Schwarzenegger
00:14:42
played an android from the future.
00:14:44
An 'android' is 'a robot that looks like
a human'. Have you watched that one, Neil?
00:14:48
Yes, I have and that android
is not very friendly.
00:14:51
No, it's not!
00:14:52
In many movies and books
about robots that think,
00:14:56
the robots end up
rebelling against their creators.
00:14:59
But some experts say the risk
posed by artificial intelligence
00:15:02
is not that computers attack us
because they hate us.
00:15:06
Their problem
is related to their efficiency.
00:15:09
What do you mean?
00:15:10
Well, let's listen to what philosopher
Nick Bostrom has to say.
00:15:14
He's the founder of the Future of
Humanity Institute at Oxford University.
00:15:19
He uses three words when describing what's
inside the mind of a thinking computer.
00:15:25
This phrase means 'to meet their
objectives'. What's the phrase he uses?
00:15:30
The bulk of the risk is not in machines
being evil or hating humans,
00:15:35
but rather that they are indifferent
to humans
00:15:38
and that, in pursuit of their own goals,
we humans would suffer as a side effect.
00:15:42
Suppose you had a super intelligent AI
00:15:44
whose only goal was to make
as many paperclips as possible.
00:15:48
Human bodies consist of atoms
00:15:50
and those atoms could be used
to make a lot of really nice paperclips.
00:15:55
If you want paperclips,
it turns out that in the pursuit of this,
00:15:58
you would have instrumental reasons to do
things that would be harmful to humanity.
00:16:02
A world in which humans
become paperclips — wow, that's scary!
00:16:07
But the phrase which means 'meet their
objectives' is to 'pursue their goals'.
00:16:11
Yes, it is.
00:16:12
So the academic explains
that if you're a computer
00:16:16
responsible for producing paperclips, you
will pursue your objective at any cost.
00:16:22
And even use atoms from human bodies
to turn them into paperclips!
00:16:26
— Now that's a horror story, Rob.
— Mm.
00:16:28
If Stephen Hawking is worried,
I think I might be too!
00:16:32
How can we be sure
that artificial intelligence —
00:16:35
be either a device or software —
will have a moral compass?
00:16:39
Ah, a good expression —
a 'moral compass' —
00:16:41
in other words, 'an understanding
of what is right and what is wrong'.
00:16:45
Artificial intelligence
is an interesting topic, Rob.
00:16:48
I hope we can chat about it again
in the future.
00:16:50
But now I'm looking at the clock
and we're running out of time, I'm afraid,
00:16:53
and I'd like to know if I got
the answer to the quiz question right?
00:16:57
Well, my question
was about a supercomputer
00:17:00
which defeated the World Chess Champion,
Gary Kasparov, in 1997.
00:17:04
What was the machine's name? Was it
Red Menace, Deep Blue or Silver Surfer?
00:17:09
And I think it's Deep Blue.
00:17:12
Well, it sounds like you are
more intelligent than a computer,
00:17:15
because you got the answer right.
00:17:17
Yes, it was Deep Blue.
00:17:19
The 1997 match was actually the second one
between Kasparov and Deep Blue,
00:17:23
a supercomputer
designed by the company IBM
00:17:26
and it was specialised in chess-playing.
00:17:29
Well, I think I might challenge Deep Blue
to a game!
00:17:32
Obviously, I'm a bit,
I'm a bit of a genius myself.
00:17:35
Very good! Good to hear!
00:17:36
Anyway, we've just got time to remember
00:17:38
some of the words and expressions
that we've used today. Neil?
00:17:41
They were...
00:17:42
you'll need your wits about you,
00:17:46
artificial,
00:17:49
genius,
00:17:52
synthetic,
00:17:54
threat,
00:17:56
to surpass,
00:17:58
to pursue their goals,
00:18:02
moral compass.
00:18:03
Thank you.
Well, that's it for this programme.
00:18:05
Do visit BBC Learning English dot com
to find more 6 Minute English programmes.
00:18:10
— Until next time, goodbye!
— Goodbye!
00:18:13
6 Minute English.
00:18:15
From BBC Learning English.
00:18:18
Hello. This is 6 Minute English. I'm Rob.
And joining me to do this is Sam.
00:18:23
Hello.
00:18:24
In this programme,
we're talking about robots.
00:18:27
Robots can perform many tasks,
00:18:29
but they're now being introduced
in social care to operate as carers,
00:18:34
to look after the sick and elderly.
00:18:36
We'll be discussing the positive
and negative issues around this,
00:18:40
but first, let's set you a question
to answer, Sam. Are you ready for this?
00:18:44
Fire away!
00:18:45
Do you know in which year
was the first commercial robot built?
00:18:49
Was it in a) 1944? b) 1954? Or c) 1964?
00:18:56
They're not a brand-new invention,
so I'll go for 1954.
00:19:02
OK, well, I'll tell you if you're right
or wrong at the end of the programme.
00:19:07
So, let's talk more about robots,
00:19:09
and specifically ones that are designed
to care for people.
00:19:12
Traditionally, it's humans
working as nurses or carers
00:19:16
who take care of elderly people —
00:19:18
those people who are too old
or too unwell to look after themselves.
00:19:22
But finding enough carers
to look after people is a problem —
00:19:27
there are more people needing care
than there are people who can help.
00:19:31
And recently in the UK, the government
announced a £34 million fund
00:19:37
to help develop robots to look after us
in our later years.
00:19:41
Well, robot carers are being developed,
00:19:44
but can they really learn enough empathy
to take care of the elderly and unwell?
00:19:49
'Empathy' is 'the ability to understand
how someone feels
00:19:52
'by imagining what it would be like
to be in that person's situation'.
00:19:57
Well, let's hear about one of those
new robots now, called Pepper.
00:20:01
Abbey Hearn-Nagaf is a research assistant
at the University of Bedfordshire.
00:20:07
She spoke to BBC Radio 4's
You and Yours programme
00:20:11
and explained how Pepper is first
introduced to someone in a care home.
00:20:15
We just bring the robot to their room
00:20:18
and we talk about what Pepper can't do,
which is important,
00:20:20
so it can't provide physical assistance
in any way.
00:20:23
It does have hands, it can wave.
00:20:26
When you ask for privacy,
it does turn around
00:20:28
and sort of cover its eyes with its hands,
but that's the most it does.
00:20:31
It doesn't grip anything,
it doesn't move anything,
00:20:33
because we're more interested to see
how it works as a companion,
00:20:37
having something there to talk to,
to converse with, to interact with.
00:20:41
So, Abbey described how the robot
is introduced to someone.
00:20:45
She was keen to point out that this robot
has 'limitations' — 'things it can't do'.
00:20:52
It can wave or turn round when a person
needs 'privacy' — 'to be private' —
00:20:57
but it can't provide
'physical assistance'.
00:21:00
This means it can't help someone
by 'touching or feeling' them.
00:21:05
But that's OK, Abbey says.
00:21:06
This robot is designed
to be a 'companion' —
00:21:10
'someone who is with you
to keep you company' —
00:21:12
a friend, in other words,
that you can converse or talk with.
00:21:16
Well, having a companion is a good way
to stop people getting lonely,
00:21:20
but surely a human is better for that?
00:21:23
Surely they understand you
better than a robot ever can?
00:21:27
Well, innovation means that robots
are becoming cleverer all the time.
00:21:32
And, as we've mentioned, in the UK alone
there is a growing elderly population
00:21:37
and more than 100,000
care assistant vacancies.
00:21:40
Who's going to do all the work?
00:21:42
I think we should hear from
Dr Sarah Woodin,
00:21:45
a health researcher in
independent living from Leeds University,
00:21:49
who also spoke to the BBC's
You and Yours programme.
00:21:53
She seems more realistic
about the introduction of robot carers.
00:21:59
I think there are problems if we consider
robots as replacement for people.
00:22:03
We know that money is tight —
if robots become mass-produced,
00:22:08
there could be large institutions where
people might be housed
00:22:13
and abandoned to robots.
00:22:15
I do think questions of ethics
00:22:17
need to come into the growth and jobs
agenda as well,
00:22:21
because, sometimes,
they're treated very separately.
00:22:23
OK, so Sarah Woodin suggests
that when money is 'tight' —
00:22:27
meaning there is 'only just enough' —
00:22:29
making robots in large quantities —
or mass-produced —
00:22:32
might be a cheaper option
than using humans.
00:22:35
And she says people
might be abandoned to robots.
00:22:38
Yes, 'abandoned' means
'left alone in a place, usually forever'.
00:22:44
So she says it might be possible
that someone ends up being forgotten
00:22:49
and only having a robot to care for them.
So is this right, ethically?
00:22:54
Yes, well, she mentions 'ethics' —
that's 'what is morally right' —
00:22:59
and that needs to be considered
as part of the jobs agenda.
00:23:02
So, we shouldn't just consider
what job vacancies need filling,
00:23:05
but who and how it should be done.
00:23:08
And earlier I asked you, Sam,
00:23:09
did you know in which year was the first
commercial robot built? And you said?
00:23:14
I said 1954.
00:23:16
Well, you didn't need a robot to help you
there because you are right.
00:23:19
— Ah, yay!
— Well done!
00:23:21
Now let's do something
a robot can't do yet,
00:23:24
and that's recap the vocabulary we've
highlighted today, starting with empathy.
00:23:29
'Empathy' is 'the ability
to understand how someone feels
00:23:33
by imagining what it would be like
to be in that person's situation'.
00:23:37
'Physical assistance' describes
'helping someone by touching them'.
00:23:41
We also mentioned a 'companion' —
00:23:43
that's 'someone who is with you
and keeps you company'.
00:23:46
Our next word was 'tight' —
in the context of money,
00:23:49
when money is tight,
it means there's 'not enough'.
00:23:53
'Abandoned' means
'left alone in a place, usually forever'.
00:23:56
And finally,
we discussed the word 'ethics' —
00:23:59
we hear a lot about business ethics
or medical ethics —
00:24:03
and it means
'the study of what is morally right'.
00:24:06
OK, thank you, Sam.
00:24:08
Well, we've managed to get through 6
Minute English without the aid of a robot.
00:24:12
That's all for now,
but please join us again soon. Goodbye!
00:24:15
Bye-bye, everyone!
00:24:17
6 Minute English.
00:24:19
From BBC Learning English.
00:24:22
Hello. This is 6 Minute English
from BBC Learning English. I'm Phil.
00:24:26
And I'm Georgie.
00:24:28
Animal testing is when living animals
are used in scientific research
00:24:32
to find out how effective a new medicine
is, or how safe a product is for humans.
00:24:38
Scientists in favour of it
argue that animal testing
00:24:42
shows whether medicines
are safe or dangerous for humans,
00:24:46
and has saved many lives.
00:24:47
But animal rights campaigners
say it's cruel,
00:24:50
and also ineffective because animals
and humans are so different.
00:24:55
Under British law, medicines must be
tested on two different types of animals,
00:25:01
usually starting with rats, mice
or guinea pigs.
00:25:05
And in everyday English,
the term 'human guinea pig'
00:25:09
can be used to mean 'the first people
to have something tested on them'.
00:25:14
But now, groups both for and against
animal testing are thinking again,
00:25:19
thanks to a recent development
in the debate — AI.
00:25:23
In this programme, we'll be hearing
how artificial intelligence
00:25:26
could help reduce the need
for scientific testing on animals.
00:25:30
But first, I have a question for you,
Georgie.
00:25:34
There's one commonly used medicine
in particular
00:25:37
which is harmful for animals
but safe for humans, but what?
00:25:43
Is it a) Antibiotics?
00:25:46
b) Aspirin?
00:25:48
Or c) Paracetamol?
00:25:51
Hmm, I guess it's aspirin.
00:25:54
OK, Georgie, I'll reveal the answer
at the end of the programme.
00:25:58
Christine Ro is a science journalist who's
interested in the animal testing debate.
00:26:04
Here, she explains to BBC World Service
programme Tech Life
00:26:08
some of the limitations
of testing medicines on animals.
00:26:12
Of course, you can't necessarily predict
from a mouse or a dog
00:26:15
what's going to happen in a human,
and there have been a number of cases
00:26:19
where substances that have
proven to be toxic in animals
00:26:22
have been proven to be safe
in humans, and vice versa.
00:26:27
There are also, of course, animal welfare
limitations to animal testing.
00:26:31
Most people, I think,
if they had the choice,
00:26:33
would want their substances to be used on
as few animals or no animals as possible,
00:26:39
while still ensuring safety.
00:26:41
Now, that's been a really difficult needle
to thread,
00:26:43
but AI might help
to make that more possible.
00:26:45
Christine says that medicines
which are safe for animals
00:26:49
might not be safe for humans.
00:26:51
But the opposite is also true —
00:26:53
what's safe for humans
might not be safe for animals.
00:26:57
Christine uses the phrase 'vice versa'
00:27:00
to show that 'the opposite'
of what she says is also true.
00:27:05
Christine also uses the idiom
to 'thread the needle'
00:27:08
to describe 'a task which requires
a lot of skill and precision,
00:27:12
'especially one involving a conflict'.
00:27:16
Yes, medical animal testing
may save human lives,
00:27:20
but many people see it as cruel
and distressing for the animal —
00:27:24
it's a difficult needle to thread.
00:27:27
But now, the challenge of threading
that needle has got a little easier
00:27:31
because of artificial intelligence.
00:27:33
Predicting how likely
a new medicine is to harm humans
00:27:37
involves analysing the results
of thousands of experiments.
00:27:41
And one thing AI is really good at is
analysing mountains and mountains of data.
00:27:48
Here's Christine Ro again, speaking
with BBC World Service's Tech Life.
00:27:52
So, AI isn't the whole picture, of course,
00:27:54
but it's an increasingly important part
of the picture and one reason for that
00:27:58
is that there is a huge amount
of toxicology data to wade through
00:28:02
when it comes to determining
chemical safety, and, on top of that,
00:28:06
there's the staggering number of chemicals
being invented all of the time.
00:28:10
AI helps scientists wade through
huge amounts of data.
00:28:14
If you 'wade through' something,
00:28:17
you 'spend a lot of time and effort
doing something boring or difficult,
00:28:22
'especially reading a lot of information'.
00:28:25
AI can process huge amounts of data,
00:28:28
and what's more, that amount keeps growing
as new chemicals are invented.
00:28:33
Christine uses the phrase 'on top of
that', meaning 'in addition to something'.
00:28:38
Often this extra thing is negative.
00:28:41
She means there's already so much data
to understand
00:28:44
and additionally, there's even more to be
understood about these new chemicals.
00:28:49
Of course, the good news is that with AI,
testing on animals could one day stop,
00:28:56
although Christine warns that AI
is not the 'whole picture',
00:29:00
it's not 'a complete description
of something
00:29:02
'which includes
all the relevant information'.
00:29:05
Nevertheless, the news is a step forward
00:29:08
for both animal welfare
and for modern medicine.
00:29:12
Speaking of which, what was the answer
to your question, Phil?
00:29:16
What is a commonly used medicine which is
safe for humans, but harmful to animals?
00:29:21
I guessed it was aspirin.
00:29:23
Which was the correct answer!
00:29:26
Right, let's recap the vocabulary
we've discussed,
00:29:30
starting with 'human guinea pigs'
00:29:33
meaning 'the first people to have
something new tested on them'.
00:29:37
The phrase 'vice versa'
is used to indicate
00:29:39
that 'the opposite of what
you have just said is also true'.
00:29:44
To 'thread the needle'
00:29:45
describes 'a task which requires extreme
skill and precision to do successfully'.
00:29:51
The 'whole picture' means 'a complete
description of something
00:29:55
'which includes all the relevant
information and opinions about it'.
00:29:59
If you 'wade through' something,
00:30:02
you 'spend a lot of time and effort
doing something boring or difficult,
00:30:06
'especially reading a lot of information'.
00:30:09
And finally, the phrase
'on top of something'
00:30:12
means 'in addition to something',
and that extra thing is often negative.
00:30:18
That's all for this week. Goodbye for now!
00:30:20
Bye!
00:30:21
6 Minute English.
00:30:23
From BBC Learning English.
