BOX SET: 6 Minute English - 'Artificial intelligence' English mega-class! 30 minutes of new vocab!
BBC Learning English
https://www.youtube.com/watch?v=0EPYNMJv-oQ

Transkript (automatisch erstellt)

0:00 6 Minute English. From BBC Learning English.
0:05 Hello. This is 6 Minute English from BBC Learning English. I'm Neil. And I'm Rob.
0:11 Now, I'm sure most of us have interacted with a chatbot. These are bits of computer technology
0:18 that respond to text with text or respond to your voice. You ask it a question and usually it comes up with an answer.
0:26 Yes, it's almost like talking to another human, but of course it's not, it's just a clever piece of technology.
0:34 It is becoming more 'sophisticated' — more 'advanced and complex' — but could they replace real human interaction altogether?
0:41 We'll discuss that more in a moment and find out if chatbots really think for themselves.
0:47 But first I have a question for you, Rob. The first computer program that allowed some kind of plausible conversation
0:54 between humans and machines was invented in 1966, but what was it called? Was it a) Alexa? b) ELIZA? Or c) PARRY?
1:07 Ah, well, it's not Alexa, that's too new, so I'll guess c) PARRY. I'll reveal the answer at the end of the programme.
1:14 Now, the old chatbots of the 1960s and '70s were quite basic, but more recently, the technology is able to predict the next word
1:25 that is likely to be used in a sentence, and it learns words and sentence structures.
1:30 Mm, it's clever stuff. I've experienced using them when talking to my bank,
1:35 or when I have problems trying to book a ticket on a website. I no longer phone a human, I speak to a virtual assistant instead.
1:43 Probably the most well-known chatbot at the moment is ChatGPT.. It is. The claim is that it's able to answer anything you ask it.
1:52 This includes writing students' essays. Now, this is something that was discussed
1:57 on the BBC Radio 4 programme, Word of Mouth. Emily M Bender, Professor of Computational Linguistics
2:05 at the University of Washington, explained why it's dangerous to always trust what a chatbot is telling us.
2:11 We tend to react to grammatical, fluent, coherent-seeming text as authoritative and reliable and valuable and we need to be on guard against that,
2:23 because what's coming out of ChatGPT is none of that. So, Professor Bender says that well-written text that is 'coherent' —
2:30 that means it's 'clear, carefully considered and sensible' — makes us think what we are reading is reliable and 'authoritative'.
2:37 So it's 'respected, accurate and important sounding'. Yes, chatbots might appear to write in this way,
2:44 but really, they are just predicting one word after another, based on what they have learnt.
2:50 We should, therefore, be 'on guard' — be 'careful and alert' — about the accuracy of what we are being told.
2:57 One concern is that chatbots — a form of artificial intelligence — work a bit like a human brain in the way it can learn and process information.
3:06 They are able to learn from experience, something called deep learning. A cognitive psychologist and computer scientist called Geoffrey Hinton
3:15 recently said he feared that chatbots could soon overtake the level of information that a human brain holds.
3:22 That's a bit scary, isn't it? Mm, but for now, chatbots can be useful for practical information,
3:28 but sometimes we start to believe they are human and we interact with them in a human-like way.
3:34 This can make us believe them even more. Professor Emma Bender, speaking on the BBC's Word of Mouth programme,
3:40 explains why we might feel like that. I think what's going on there is the kinds of answers you get
3:47 depend on the questions you put in, because it's doing likely next word, likely next word,
3:52 and so if, as the human interacting with this machine, you start asking it questions about how do you feel, you know, Chatbot?
4:00 And "What do you think of this?" And, "What are your goals?" You can provoke it to say things
4:05 that sound like what a sentient entity would say. We are really primed to imagine a mind behind language
4:11 whenever we encounter language and so we really have to account for that when we're making decisions about these.
4:17 So, although a chatbot might sound human, we really just ask it things to get a reaction — we 'provoke' it —
4:24 and it answers only with words it's learned to use before, not because it has come up with a clever answer.
4:31 But it does sound like a sentient entity — 'sentient' describes 'a living thing that experiences feelings'.
4:38 As Professor Bender says, we imagine that when something speaks, there is a mind behind it.
4:44 But sorry, Neil, they are not your friend, they're just machines! Yes, it's strange then that we sometimes give chatbots names.
4:52 Alexa, Siri, and earlier I asked you what the name was for the first ever chatbot. And I guessed it was PARRY. Was I right?
5:01 You guessed wrong, I'm afraid. PARRY was an early form of chatbot from 1972, but the correct answer was ELIZA.
5:09 It was considered to be the first 'chatterbot' — as it was called then — and was developed by Joseph Weizenbaum at Massachusetts Institute of Technology.
5:19 Fascinating stuff. OK, now let's recap some of the vocabulary we highlighted in this programme.
5:25 Starting with 'sophisticated', which can describe technology that is 'advanced and complex'.
5:31 Something that is 'coherent' is 'clear, carefully considered and sensible'. 'Authoritative' means 'respected, accurate and important sounding'.
5:40 When you are 'on guard' you must be 'careful and alert' about something — it could be accuracy of what you see or hear,
5:47 or just being aware of the dangers around you. To 'provoke' means to 'do something that causes a reaction from someone'.
5:54 'Sentient' describes 'something that experiences feelings' — so it's 'something that is living'.
6:01 Once again, our six minutes are up. Goodbye. Bye for now.
6:05 6 Minute English. From BBC Learning English.
6:10 Hello. This is 6 Minute English from BBC Learning English. — I'm Sam. — And I'm Neil.
6:15 In the autumn of 2021, something strange happened at the Google headquarters in California's Silicon Valley.
6:22 A software engineer called Blake Lemoine was working on the artificial intelligence project
6:28 Language Models for Dialogue Applications, or LaMDA for short. LaMDA is a 'chatbot' — a 'computer programme
6:36 'designed to have conversations with humans over the internet'. After months talking with LaMDA
6:42 on topics ranging from movies to the meaning of life, Blake came to a surprising conclusion —
6:48 the chatbot was an intelligent person with wishes and rights that should be respected.
6:54 For Blake, LaMDA was a Google employee, not a machine. He also called it his friend.
7:00 Google quickly reassigned Blake from the project, announcing that his ideas were not supported by the evidence.
7:07 But what exactly was going on? In this programme, we'll be discussing whether artificial intelligence
7:14 is capable of consciousness. We'll hear from one expert
7:18 who thinks AI is not as intelligent as we sometimes think and, as usual, we'll be learning some new vocabulary as well.
7:25 But before that, I have a question for you, Neil. What happened to Blake Lemoine
7:29 is strangely similar to the 2013 Hollywood movie, Her, starring Joaquin Phoenix as a lonely writer who talks with his computer,
7:38 voiced by Scarlett Johansson. But what happens at the end of the movie?
7:42 Is it a) The computer comes to life? b) The computer dreams about the writer?
7:48 Or c) The writer falls in love with the computer? C) The writer falls in love with the computer.
7:54 OK, Neil, I'll reveal the answer at the end of the programme. Although Hollywood is full of movies about robots coming to life,
8:01 Emily Bender, Professor of Linguistics and Computing at the University of Washington, thinks AI isn't that smart.
8:10 She thinks the words we use to talk about technology — phrases like 'machine learning' —
8:15 give a false impression about what computers can and can't do. Here is Professor Bender discussing another misleading phrase —
8:23 'speech recognition' — with BBC World Service programme The Inquiry. If you talk about 'automatic speech recognition',
8:32 the term 'recognition' suggests that there's something cognitive going on, where I think a better term would be automatic transcription.
8:40 That just describes the input-output relation, and not any theory or wishful thinking
8:46 about what the computer is doing to be able to achieve that. Using words like 'recognition' in relation to computers
8:53 gives the idea that something 'cognitive' is happening — something 'related to the mental processes
8:59 'of thinking, knowing, learning and understanding'. But thinking and knowing are human, not machine, activities.
9:07 Professor Benders says that talking about them in connection with computers is 'wishful thinking' — 'something which is unlikely to happen'.
9:16 The problem with using words in this way is that it reinforces what Professor Bender calls 'technical bias' —
9:23 'the assumption that the computer is always right'. When we encounter language that sounds natural, but is coming from a computer,
9:30 humans can't help but imagine a mind behind the language, even when there isn't one.
9:36 In other words, we 'anthropomorphise' computers — we 'treat them as if they were human'.
9:42 Here's Professor Bender again, discussing this idea with Charmaine Cozier, the presenter of BBC World Service's The Inquiry.
9:50 So 'ism' means system, 'anthro' or 'anthropo' means human, and 'morph' means shape.
9:57 And so this is a system that puts the shape of a human on something, and, in this case, the something is a computer.
10:03 We anthropomorphise animals all the time, but we also anthropomorphise action figures, or dolls,
10:10 or companies when we talk about companies having intentions and so on. We very much are in the habit of seeing ourselves in the world around us.
10:19 And while we're busy seeing ourselves by assigning human traits to things that are not, we risk being blindsided.
10:26 The more fluent that text is, the more different topics it can converse on, the more chances there are to get taken in.
10:34 If we treat computers as if they could think, we might get 'blindsided', or 'unpleasantly surprised'.
10:41 Artificial intelligence works by finding patterns in massive amounts of data, so it can seem like we're talking with a human,
10:48 instead of a machine doing data analysis. As a result, we 'get taken in' — we're 'tricked or deceived'
10:55 into thinking we're dealing with a human, or with something intelligent. Powerful AI can make machines appear conscious,
11:03 but even tech giants like Google are years away from building computers that can dream or fall in love.
11:10 Speaking of which, Sam, what was the answer to your question? I asked what happened in the 2013 movie, Her.
11:17 Neil thought that the main character falls in love with his computer, — which was the correct answer! — OK.
11:23 Right, it's time to recap the vocabulary we've learned from this programme about AI, including 'chatbots' —
11:29 'computer programmes designed to interact with humans over the internet'. The adjective 'cognitive' describes anything connected
11:37 with 'the mental processes of knowing, learning and understanding'. 'Wishful thinking' means 'thinking that something which is very unlikely to happen
11:46 'might happen one day in the future'. To 'anthropomorphise' an object
11:49 means 'to treat it as if it were human, even though it's not'. When you're 'blindsided', you're 'surprised in a negative way'.
11:57 And finally, to 'get taken in' by someone means to be 'deceived or tricked' by them. My computer tells me that our six minutes are up!
12:05 Join us again soon, for now it's goodbye from us. Bye!
12:09 6 Minute English. From BBC Learning English.
12:14 Hello, I'm Rob. Welcome to 6 Minute English and with me in the studio is Neil. — Hello, Rob. — Hello.
12:21 Feeling clever today, Neil? I am feeling quite bright and clever, yes!
12:25 That's good to hear. Well, 'you'll need your wits about you' —
12:28 meaning 'you'll need to think very quickly' in this programme, because we're talking about intelligence,
12:33 or to be more accurate, artificial intelligence, and we'll learn some vocabulary related to the topic,
12:40 so that you can have your own discussion about it. Neil, now, you know who Professor Stephen Hawking is, right?
12:46 Well, of course! Yes. Many people say that he's a 'genius' —
12:49 in other words, he is 'very, very intelligent'. Professor Hawking is one of the most famous scientists in the world
12:56 and people remember him for his brilliance and also because he communicates using a synthetic voice generated by a computer —
13:04 'synthetic' means it's 'made from something non-natural'. 'Artificial' is similar in meaning —
13:09 we use it when something is 'man-made to look or behave like something natural'. Well, Professor Hawking has said recently
13:17 that efforts to create thinking machines are a threat to our existence. A 'threat' means 'something which can put us in danger'.
13:25 Now, can you imagine that, Neil?! Well, there's no denying that good things
13:28 can come from the creation of artificial intelligence. Computers which can think for themselves
13:33 might be able to find solutions to problems we haven't been able to solve. But technology is developing quickly and maybe we should consider the consequences.
13:42 Some of these very clever robots are already surpassing us, Rob. 'To surpass' means 'to have abilities superior to our own'.
13:51 Yes. Maybe you can remember the headlines when a supercomputer defeated the World Chess Champion, Gary Kasparov, to everyone's astonishment.
14:00 It was in 1997. What was the computer called though, Neil? Was it a) Red Menace? b) Deep Blue? Or c) Silver Surfer?
14:09 Erm, I don't know. I think c) is probably not right. Erm...
14:16 I think Deep Blue. That's b) Deep Blue. OK. Well, you'll know if you got the answer right at the end of the programme.
14:22 Well, our theme is artificial intelligence and when we talk about this, we have to mention the movies.
14:27 Mm, many science fiction movies have explored the idea of bad computers who want to harm us.
14:33 One example is 2001: A Space Odyssey. Yes, a good film.
14:38 And another is The Terminator, a movie in which actor Arnold Schwarzenegger played an android from the future.
14:44 An 'android' is 'a robot that looks like a human'. Have you watched that one, Neil? Yes, I have and that android is not very friendly.
14:51 No, it's not! In many movies and books about robots that think,
14:56 the robots end up rebelling against their creators. But some experts say the risk posed by artificial intelligence
15:02 is not that computers attack us because they hate us. Their problem is related to their efficiency.
15:09 What do you mean? Well, let's listen to what philosopher Nick Bostrom has to say.
15:14 He's the founder of the Future of Humanity Institute at Oxford University. He uses three words when describing what's inside the mind of a thinking computer.
15:25 This phrase means 'to meet their objectives'. What's the phrase he uses? The bulk of the risk is not in machines being evil or hating humans,
15:35 but rather that they are indifferent to humans and that, in pursuit of their own goals, we humans would suffer as a side effect.
15:42 Suppose you had a super intelligent AI whose only goal was to make as many paperclips as possible.
15:48 Human bodies consist of atoms and those atoms could be used to make a lot of really nice paperclips.
15:55 If you want paperclips, it turns out that in the pursuit of this, you would have instrumental reasons to do things that would be harmful to humanity.
16:02 A world in which humans become paperclips — wow, that's scary! But the phrase which means 'meet their objectives' is to 'pursue their goals'.
16:11 Yes, it is. So the academic explains that if you're a computer
16:16 responsible for producing paperclips, you will pursue your objective at any cost. And even use atoms from human bodies to turn them into paperclips!
16:26 — Now that's a horror story, Rob. — Mm. If Stephen Hawking is worried, I think I might be too!
16:32 How can we be sure that artificial intelligence — be either a device or software — will have a moral compass?
16:39 Ah, a good expression — a 'moral compass' — in other words, 'an understanding of what is right and what is wrong'.
16:45 Artificial intelligence is an interesting topic, Rob. I hope we can chat about it again in the future.
16:50 But now I'm looking at the clock and we're running out of time, I'm afraid, and I'd like to know if I got the answer to the quiz question right?
16:57 Well, my question was about a supercomputer which defeated the World Chess Champion, Gary Kasparov, in 1997.
17:04 What was the machine's name? Was it Red Menace, Deep Blue or Silver Surfer? And I think it's Deep Blue.
17:12 Well, it sounds like you are more intelligent than a computer, because you got the answer right.
17:17 Yes, it was Deep Blue. The 1997 match was actually the second one between Kasparov and Deep Blue,
17:23 a supercomputer designed by the company IBM and it was specialised in chess-playing.
17:29 Well, I think I might challenge Deep Blue to a game! Obviously, I'm a bit, I'm a bit of a genius myself.
17:35 Very good! Good to hear! Anyway, we've just got time to remember
17:38 some of the words and expressions that we've used today. Neil? They were...
17:42 you'll need your wits about you, artificial,
17:49 genius, synthetic,
17:54 threat, to surpass,
17:58 to pursue their goals, moral compass.
18:03 Thank you. Well, that's it for this programme. Do visit BBC Learning English dot com to find more 6 Minute English programmes.
18:10 — Until next time, goodbye! — Goodbye! 6 Minute English.
18:15 From BBC Learning English. Hello. This is 6 Minute English. I'm Rob. And joining me to do this is Sam.
18:23 Hello. In this programme, we're talking about robots.
18:27 Robots can perform many tasks, but they're now being introduced in social care to operate as carers,
18:34 to look after the sick and elderly. We'll be discussing the positive and negative issues around this,
18:40 but first, let's set you a question to answer, Sam. Are you ready for this? Fire away!
18:45 Do you know in which year was the first commercial robot built? Was it in a) 1944? b) 1954? Or c) 1964?
18:56 They're not a brand-new invention, so I'll go for 1954. OK, well, I'll tell you if you're right or wrong at the end of the programme.
19:07 So, let's talk more about robots, and specifically ones that are designed to care for people.
19:12 Traditionally, it's humans working as nurses or carers who take care of elderly people —
19:18 those people who are too old or too unwell to look after themselves. But finding enough carers to look after people is a problem —
19:27 there are more people needing care than there are people who can help. And recently in the UK, the government announced a £34 million fund
19:37 to help develop robots to look after us in our later years. Well, robot carers are being developed,
19:44 but can they really learn enough empathy to take care of the elderly and unwell? 'Empathy' is 'the ability to understand how someone feels
19:52 'by imagining what it would be like to be in that person's situation'. Well, let's hear about one of those new robots now, called Pepper.
20:01 Abbey Hearn-Nagaf is a research assistant at the University of Bedfordshire. She spoke to BBC Radio 4's You and Yours programme
20:11 and explained how Pepper is first introduced to someone in a care home. We just bring the robot to their room
20:18 and we talk about what Pepper can't do, which is important, so it can't provide physical assistance in any way.
20:23 It does have hands, it can wave. When you ask for privacy, it does turn around
20:28 and sort of cover its eyes with its hands, but that's the most it does. It doesn't grip anything, it doesn't move anything,
20:33 because we're more interested to see how it works as a companion, having something there to talk to, to converse with, to interact with.
20:41 So, Abbey described how the robot is introduced to someone. She was keen to point out that this robot has 'limitations' — 'things it can't do'.
20:52 It can wave or turn round when a person needs 'privacy' — 'to be private' — but it can't provide 'physical assistance'.
21:00 This means it can't help someone by 'touching or feeling' them. But that's OK, Abbey says.
21:06 This robot is designed to be a 'companion' — 'someone who is with you to keep you company' —
21:12 a friend, in other words, that you can converse or talk with. Well, having a companion is a good way to stop people getting lonely,
21:20 but surely a human is better for that? Surely they understand you better than a robot ever can?
21:27 Well, innovation means that robots are becoming cleverer all the time. And, as we've mentioned, in the UK alone there is a growing elderly population
21:37 and more than 100,000 care assistant vacancies. Who's going to do all the work?
21:42 I think we should hear from Dr Sarah Woodin, a health researcher in independent living from Leeds University,
21:49 who also spoke to the BBC's You and Yours programme. She seems more realistic about the introduction of robot carers.
21:59 I think there are problems if we consider robots as replacement for people. We know that money is tight — if robots become mass-produced,
22:08 there could be large institutions where people might be housed and abandoned to robots.
22:15 I do think questions of ethics need to come into the growth and jobs agenda as well,
22:21 because, sometimes, they're treated very separately. OK, so Sarah Woodin suggests that when money is 'tight' —
22:27 meaning there is 'only just enough' — making robots in large quantities — or mass-produced —
22:32 might be a cheaper option than using humans. And she says people might be abandoned to robots.
22:38 Yes, 'abandoned' means 'left alone in a place, usually forever'. So she says it might be possible that someone ends up being forgotten
22:49 and only having a robot to care for them. So is this right, ethically? Yes, well, she mentions 'ethics' — that's 'what is morally right' —
22:59 and that needs to be considered as part of the jobs agenda. So, we shouldn't just consider what job vacancies need filling,
23:05 but who and how it should be done. And earlier I asked you, Sam,
23:09 did you know in which year was the first commercial robot built? And you said? I said 1954.
23:16 Well, you didn't need a robot to help you there because you are right. — Ah, yay! — Well done!
23:21 Now let's do something a robot can't do yet, and that's recap the vocabulary we've highlighted today, starting with empathy.
23:29 'Empathy' is 'the ability to understand how someone feels by imagining what it would be like to be in that person's situation'.
23:37 'Physical assistance' describes 'helping someone by touching them'. We also mentioned a 'companion' —
23:43 that's 'someone who is with you and keeps you company'. Our next word was 'tight' — in the context of money,
23:49 when money is tight, it means there's 'not enough'. 'Abandoned' means 'left alone in a place, usually forever'.
23:56 And finally, we discussed the word 'ethics' — we hear a lot about business ethics or medical ethics —
24:03 and it means 'the study of what is morally right'. OK, thank you, Sam.
24:08 Well, we've managed to get through 6 Minute English without the aid of a robot. That's all for now, but please join us again soon. Goodbye!
24:15 Bye-bye, everyone! 6 Minute English.
24:19 From BBC Learning English. Hello. This is 6 Minute English from BBC Learning English. I'm Phil.
24:26 And I'm Georgie. Animal testing is when living animals are used in scientific research
24:32 to find out how effective a new medicine is, or how safe a product is for humans. Scientists in favour of it argue that animal testing
24:42 shows whether medicines are safe or dangerous for humans, and has saved many lives.
24:47 But animal rights campaigners say it's cruel, and also ineffective because animals and humans are so different.
24:55 Under British law, medicines must be tested on two different types of animals, usually starting with rats, mice or guinea pigs.
25:05 And in everyday English, the term 'human guinea pig' can be used to mean 'the first people to have something tested on them'.
25:14 But now, groups both for and against animal testing are thinking again, thanks to a recent development in the debate — AI.
25:23 In this programme, we'll be hearing how artificial intelligence could help reduce the need for scientific testing on animals.
25:30 But first, I have a question for you, Georgie. There's one commonly used medicine in particular
25:37 which is harmful for animals but safe for humans, but what? Is it a) Antibiotics?
25:46 b) Aspirin? Or c) Paracetamol?
25:51 Hmm, I guess it's aspirin. OK, Georgie, I'll reveal the answer at the end of the programme.
25:58 Christine Ro is a science journalist who's interested in the animal testing debate. Here, she explains to BBC World Service programme Tech Life
26:08 some of the limitations of testing medicines on animals. Of course, you can't necessarily predict from a mouse or a dog
26:15 what's going to happen in a human, and there have been a number of cases where substances that have proven to be toxic in animals
26:22 have been proven to be safe in humans, and vice versa. There are also, of course, animal welfare limitations to animal testing.
26:31 Most people, I think, if they had the choice, would want their substances to be used on as few animals or no animals as possible,
26:39 while still ensuring safety. Now, that's been a really difficult needle to thread,
26:43 but AI might help to make that more possible. Christine says that medicines which are safe for animals
26:49 might not be safe for humans. But the opposite is also true —
26:53 what's safe for humans might not be safe for animals. Christine uses the phrase 'vice versa'
27:00 to show that 'the opposite' of what she says is also true. Christine also uses the idiom to 'thread the needle'
27:08 to describe 'a task which requires a lot of skill and precision, 'especially one involving a conflict'.
27:16 Yes, medical animal testing may save human lives, but many people see it as cruel and distressing for the animal —
27:24 it's a difficult needle to thread. But now, the challenge of threading that needle has got a little easier
27:31 because of artificial intelligence. Predicting how likely a new medicine is to harm humans
27:37 involves analysing the results of thousands of experiments. And one thing AI is really good at is analysing mountains and mountains of data.
27:48 Here's Christine Ro again, speaking with BBC World Service's Tech Life. So, AI isn't the whole picture, of course,
27:54 but it's an increasingly important part of the picture and one reason for that is that there is a huge amount of toxicology data to wade through
28:02 when it comes to determining chemical safety, and, on top of that, there's the staggering number of chemicals being invented all of the time.
28:10 AI helps scientists wade through huge amounts of data. If you 'wade through' something,
28:17 you 'spend a lot of time and effort doing something boring or difficult, 'especially reading a lot of information'.
28:25 AI can process huge amounts of data, and what's more, that amount keeps growing as new chemicals are invented.
28:33 Christine uses the phrase 'on top of that', meaning 'in addition to something'. Often this extra thing is negative.
28:41 She means there's already so much data to understand and additionally, there's even more to be understood about these new chemicals.
28:49 Of course, the good news is that with AI, testing on animals could one day stop, although Christine warns that AI is not the 'whole picture',
29:00 it's not 'a complete description of something 'which includes all the relevant information'.
29:05 Nevertheless, the news is a step forward for both animal welfare and for modern medicine.
29:12 Speaking of which, what was the answer to your question, Phil? What is a commonly used medicine which is safe for humans, but harmful to animals?
29:21 I guessed it was aspirin. Which was the correct answer!
29:26 Right, let's recap the vocabulary we've discussed, starting with 'human guinea pigs'
29:33 meaning 'the first people to have something new tested on them'. The phrase 'vice versa' is used to indicate
29:39 that 'the opposite of what you have just said is also true'. To 'thread the needle'
29:45 describes 'a task which requires extreme skill and precision to do successfully'. The 'whole picture' means 'a complete description of something
29:55 'which includes all the relevant information and opinions about it'. If you 'wade through' something,
30:02 you 'spend a lot of time and effort doing something boring or difficult, 'especially reading a lot of information'.
30:09 And finally, the phrase 'on top of something' means 'in addition to something', and that extra thing is often negative.
30:18 That's all for this week. Goodbye for now! Bye!
30:21 6 Minute English. From BBC Learning English.