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Human or robot? The AI revolution comes to podcasts · The Front

• 0:08
  Speaker 1: From The Australian. This is the weekend edition of The Front.
• 0:10
  Speaker 1: I'm Claire Harvey.
• 0:15
  Speaker 2: These people aren't real the creative underclass. That's a powerful phrase,
• 0:21
  Speaker 2: but doesn't that risk romanticizing things a bit.
• 0:24
  Speaker 3: That's a really crucial point and your rate to push
• 0:26
  Speaker 3: back on it.
• 0:27
  Speaker 1: But they're coming to a podcast near you very soon.
• 0:31
  Speaker 1: And so, just as in art and music, the most
• 0:34
  Speaker 1: human of art forms is being replicated by artificial intelligence
• 0:39
  Speaker 1: models that aren't satisfied with just helping humans. They want
• 0:42
  Speaker 1: to imitate us too. Here at The Australian, we will
• 0:46
  Speaker 1: always make handmade human journalism, but some of our peers
• 0:50
  Speaker 1: in the podcast world aren't so sure. So what happens
• 0:54
  Speaker 1: when AI steps out from behind the curtain and tries
• 0:58
  Speaker 1: to claim the spotlight. The Australian's audio lead, Jasper League,
• 1:02
  Speaker 1: joins me today and we look at podcasts that can
• 1:05
  Speaker 1: be created with the click of a button. Jas But
• 1:14
  Speaker 1: you are a very chilled out dude. I don't often
• 1:16
  Speaker 1: see you lose it, but one moment in the past
• 1:20
  Speaker 1: year when I have seen you rattled is when we
• 1:23
  Speaker 1: were doing a great AI boot camp here at work.
• 1:26
  Speaker 1: We were learning all about the AI tools that can
• 1:28
  Speaker 1: help us do our journalism. One of them is called
• 1:31
  Speaker 1: Notebook LM, Google's Large Language Model, and the way we
• 1:36
  Speaker 1: use it here at News is that we might upload
• 1:39
  Speaker 1: a very long research report or ten council meeting minutes
• 1:44
  Speaker 1: and ask it to analyze that text for us, give
• 1:46
  Speaker 1: us some dot points that might help us in researching
• 1:48
  Speaker 1: a story. We never actually publish anything that Notebook LM
• 1:51
  Speaker 1: spits out for us, but it's useful in helping us
• 1:54
  Speaker 1: get our heads around a concept so that we can
• 1:56
  Speaker 1: then do the journalism to check out what it's telling us.
• 2:00
  Speaker 1: Thing that got you riled up was Notebook LM has
• 2:03
  Speaker 1: an audio summary feature. What is that and why did
• 2:07
  Speaker 1: it annoy you?
• 2:08
  Speaker 4: Well?
• 2:08
  Speaker 5: Notebook LM has an audio overview feature that is essentially
• 2:13
  Speaker 5: the text to voice component of Notebook LM, where the
• 2:17
  Speaker 5: Australian use text to audio technology in our articles sometimes,
• 2:23
  Speaker 5: which is a feature I like, you know, it's something
• 2:24
  Speaker 5: handy for you know, if you're driving somewhere and you
• 2:27
  Speaker 5: really want to read that feature, but you don't have
• 2:30
  Speaker 5: the twenty minutes to set aside to actually sit there
• 2:32
  Speaker 5: and read it, you can hit play and you can
• 2:34
  Speaker 5: listen to it on the go.
• 2:35
  Speaker 1: And this is what it sounds like.
• 2:37
  Speaker 4: This article is read by an automated voice. Real wage
• 2:41
  Speaker 4: growth is going backwards for the first time since September
• 2:44
  Speaker 4: twenty twenty three, after inflation outpaced the latest annual nominal
• 2:48
  Speaker 4: wage growth figures published on Wednesday.
• 2:52
  Speaker 1: So it's an audio reading out of this newspaper story.
• 2:56
  Speaker 1: And while your hands are full, or you're cooking, or
• 2:59
  Speaker 1: you're driving, you can read the paper.
• 3:01
  Speaker 2: That's right.
• 3:01
  Speaker 5: That's a great use of that particular technology. But what
• 3:05
  Speaker 5: notebook LM does is it creates what's called an audio overview,
• 3:09
  Speaker 5: which is a simulation of a podcast. You can upload
• 3:14
  Speaker 5: a huge amount of information to notebook LM, and instead
• 3:17
  Speaker 5: of sitting there and sifting through it all yourself, you
• 3:19
  Speaker 5: can say, Hey, create me a ten minute podcast on
• 3:22
  Speaker 5: everything that I've just uploaded, and the end result is
• 3:26
  Speaker 5: an engaging to host podcast on the theme of your choice.
• 3:31
  Speaker 5: And this technology we're seeing an outside of notebook LM
• 3:34
  Speaker 5: now and they all sort of get advertised in the
• 3:36
  Speaker 5: same way, which is essentially a podcast created with the
• 3:39
  Speaker 5: click of a button.
• 3:40
  Speaker 1: There's two aspects to the way we pull our podcast together. First,
• 3:43
  Speaker 1: we do the journalism, which is reporting, writing, fact checking,
• 3:48
  Speaker 1: getting things legal through our lawyers. And then it comes
• 3:51
  Speaker 1: to the audio production and polishing. That means putting all
• 3:55
  Speaker 1: the audio together and then making it sound good. What
• 3:59
  Speaker 1: are the tasks involved in making it sound good?
• 4:02
  Speaker 5: A huge chunk of my time every day is spent
• 4:04
  Speaker 5: just cleaning audio, removing all the gross mouth sounds that
• 4:09
  Speaker 5: nobody really wants to listen to. It's like photoshopping or
• 4:14
  Speaker 5: retouching audio. These tasks add up because I mean, in
• 4:18
  Speaker 5: fifteen minutes of audio, there's a lot of clicks, and
• 4:20
  Speaker 5: there's a lot of plosives and a lot of loud breaths,
• 4:22
  Speaker 5: and there's a lot of false starts, and there's a
• 4:24
  Speaker 5: lot of semi complete thoughts that need to be edited
• 4:29
  Speaker 5: down into a way that they can be better understood
• 4:31
  Speaker 5: by an audience. And then there's also balancing and then
• 4:35
  Speaker 5: pairing journalism with music or sound design. There are a
• 4:38
  Speaker 5: lot of moving parts and it's not an easy job.
• 4:41
  Speaker 5: But I have a lot of pride in doing these
• 4:43
  Speaker 5: things in the way that I think they should be done.
• 4:45
  Speaker 1: One of your rules of FULMB which our whole team
• 4:47
  Speaker 1: abides by, is that five minutes of published audio will
• 4:52
  Speaker 1: take roughly an hour in terms of cleaning and polishing
• 4:56
  Speaker 1: to make it sound as good as we wanted to
• 4:58
  Speaker 1: hear at the Australian.
• 4:59
  Speaker 5: And the idea of course, is that the audience would
• 5:01
  Speaker 5: never even notice. And there is a bit of a
• 5:02
  Speaker 5: sleight of hand going on sometimes when you see a
• 5:05
  Speaker 5: show that looks very casual and informal, but it's not
• 5:10
  Speaker 5: like it just so happens to sound really clean and
• 5:13
  Speaker 5: balanced and there are no gross mouth sounds. It's like
• 5:17
  Speaker 5: the illusion is that it's just this easy thing that's
• 5:19
  Speaker 5: been thrown together. There is always a lot of work
• 5:22
  Speaker 5: that then happens on the back end to create that illusion.
• 5:25
  Speaker 1: So Jesper, you did a bit of an experiment with
• 5:27
  Speaker 1: Notebook LM and it involved being on the treadmill at
• 5:30
  Speaker 1: the gym.
• 5:31
  Speaker 5: Yes, yes, what happened. So I was at the gym
• 5:34
  Speaker 5: recently and I was sick of the music in my
• 5:36
  Speaker 5: playlist and I couldn't find a podcast that I wanted
• 5:39
  Speaker 5: to listen to. What I was wanting to listen to
• 5:41
  Speaker 5: doesn't really exist. I wanted to listen to a short
• 5:45
  Speaker 5: ten to fifteen minute episode on the town where I live,
• 5:48
  Speaker 5: So I thought, well, this could be a perfect opportunity
• 5:51
  Speaker 5: to take Notebook LM for a spin. As you said before,
• 5:55
  Speaker 5: Notebook LM doesn't scan the Internet for its information. It
• 5:59
  Speaker 5: only responds to information that you give it. So understanding
• 6:03
  Speaker 5: that Notebook ELM is a walled garden, I went to
• 6:05
  Speaker 5: Google's generative AI tour called Gemini to create a script
• 6:10
  Speaker 5: for me. And the prompt I gave it was pretty
• 6:12
  Speaker 5: embarrassing in hindsight, but it was something like, I want
• 6:15
  Speaker 5: a short podcast on Northkatoomba. Any facts that you can
• 6:18
  Speaker 5: share with me? Is it low income? Go? And it
• 6:22
  Speaker 5: only took Gemini a matter of seconds really to whip
• 6:25
  Speaker 5: up a script, and then I copied and pasted that
• 6:27
  Speaker 5: script into Notebook LM, hit the audio of a view
• 6:30
  Speaker 5: feature and within a couple of minutes I had my podcast.
• 6:34
  Speaker 1: Let's have a listen.
• 6:36
  Speaker 2: Welcome back to the deep Dive. If you've ever been
• 6:39
  Speaker 2: to the Blue Mountains, you know that feeling, the damp,
• 6:43
  Speaker 2: cool air, the smell of eucalyptus, and just the sheer
• 6:47
  Speaker 2: scale of it all. It's breastaking, it really is. We're
• 6:50
  Speaker 2: up here a thousand years above sea level in Katoomba,
• 6:53
  Speaker 2: which most people know for the postcard view.
• 6:56
  Speaker 3: The three sisters, the cliff.
• 6:57
  Speaker 2: Walks exactly, the Carrington Hotel, but that whole picture, that
• 7:02
  Speaker 2: entire tourist world, it's pretty much all on one side
• 7:05
  Speaker 2: of the train tracks South Katuma.
• 7:07
  Speaker 3: And that's why today we're actually turning our backs on
• 7:10
  Speaker 3: those cliffs. Okay, we are, you know, physically crossing the
• 7:13
  Speaker 3: railway line to dive into the story of North Katuma.
• 7:17
  Speaker 2: The other side of the tracks. Literally.
• 7:19
  Speaker 3: Literally, our whole mission here is to look at the
• 7:22
  Speaker 3: sources that tell this, this tale of two cities that
• 7:25
  Speaker 3: really defines the community.
• 7:27
  Speaker 5: I'm going to stop it there because I find that
• 7:29
  Speaker 5: bit really interesting where you hear the female voice pause
• 7:34
  Speaker 5: and she says um, and then it's almost like she's
• 7:37
  Speaker 5: checking her notes or something. Yeah, but it's like, of
• 7:39
  Speaker 5: course there are no notes. This whole thing is a simulation.
• 7:43
  Speaker 1: It's quite eerie, it is.
• 7:44
  Speaker 5: I also I hate it too. To me, it's a
• 7:49
  Speaker 5: gimmick that doesn't really have much value, nested in a
• 7:53
  Speaker 5: product that has immense value.
• 7:56
  Speaker 1: So there's a huge convenience opportunity here. You wanted something
• 8:01
  Speaker 1: very niche and very bespoke about North Katomba to listen
• 8:05
  Speaker 1: to while you're on the treadmill, in Northkatomber. Yes, you
• 8:07
  Speaker 1: got these two robots to talk about it for you,
• 8:10
  Speaker 1: and then they pretended to be humans.
• 8:12
  Speaker 5: That's right. If I'm going to go to a sort
• 8:15
  Speaker 5: of an artificial product like this, my preference would be
• 8:18
  Speaker 5: to have the AI version of.
• 8:20
  Speaker 1: That, to have it sound artificial, to have it sound artificial.
• 8:24
  Speaker 1: I did my own experiment with Notebook LM. I had
• 8:27
  Speaker 1: to do some pre reading for a meeting. I uploaded
• 8:30
  Speaker 1: the documents into notebook LM. I got it to give
• 8:32
  Speaker 1: me an audio summary a little podcast episode, so I
• 8:35
  Speaker 1: didn't have to do the reading for this meeting. I
• 8:37
  Speaker 1: then thought, Wow, that was sort of alarmingly warm and chatty.
• 8:41
  Speaker 1: But I wonder what it's like with some confronting material.
• 8:44
  Speaker 1: So I went and downloaded the Charter of Hamas, which
• 8:48
  Speaker 1: is out there on the internet. And I was hoping
• 8:50
  Speaker 1: that the robots would take that same kind of chummy tone,
• 8:55
  Speaker 1: but actually it disappointed me by taking quite an appropriate tone.
• 9:00
  Speaker 1: Let's listen.
• 9:02
  Speaker 2: It's really a foundational text, isn't. It gives you a
• 9:04
  Speaker 2: snapshot of their stated principles, their goals right back when
• 9:07
  Speaker 2: it was written exactly.
• 9:09
  Speaker 3: And our mission here, as always is just to understand
• 9:11
  Speaker 3: what the source material says, especially with something this politically charged.
• 9:15
  Speaker 4: Yeah.
• 9:16
  Speaker 2: Absolutely, we're just extracting the key ideas from this specific document.
• 9:21
  Speaker 2: Impartially just helping you get informed about what's actually in it.
• 9:24
  Speaker 2: We're reporting, not endorsing anything here.
• 9:27
  Speaker 3: So let's just bring in how does the charter define itself?
• 9:30
  Speaker 3: What's the fund?
• 9:31
  Speaker 1: Again? With the arms and the h's and the hesitations
• 9:34
  Speaker 1: and the checking of the notes. Yes, it's pretending to
• 9:37
  Speaker 1: be considering this information. So while it's able to recognize
• 9:41
  Speaker 1: that this is confronting material, or it's at least very serious,
• 9:45
  Speaker 1: it's not appropriate to joke. I find the fake humanity
• 9:50
  Speaker 1: really depressing.
• 9:52
  Speaker 5: Yeah, I do too. The big difference with your podcast
• 9:55
  Speaker 5: in mind was that I uploaded a script copied and
• 10:00
  Speaker 5: pasted from Google's Gemini that had been compiled using various
• 10:05
  Speaker 5: bits of information from the web. Bearing in mind, I
• 10:09
  Speaker 5: asked it for a podcast on the tower where I live,
• 10:11
  Speaker 5: which is North Katoomba. The first thing that the host
• 10:14
  Speaker 5: started to talk about was a brief history of the gully.
• 10:18
  Speaker 5: It was an indigenous settlement home to quite a proud
• 10:21
  Speaker 5: Indigenous community that were ultimately moved off their land when
• 10:27
  Speaker 5: a decision was made to build a racetrack in the
• 10:31
  Speaker 5: middle of the gully. The racetrack was ultimately a bust,
• 10:34
  Speaker 5: and the whole thing really just amounts to a sad
• 10:37
  Speaker 5: chapter in Katomba's history.
• 10:39
  Speaker 1: This must have made the robots sad.
• 10:41
  Speaker 5: They were very empathetic.
• 10:44
  Speaker 1: Do you hear a bit of it? Yeah? Sure, hear
• 10:46
  Speaker 1: a bit of the robots speak sad.
• 10:47
  Speaker 5: Yeah.
• 10:49
  Speaker 2: What happened?
• 10:49
  Speaker 3: A group of local businessmen decided Katoomba needed a big,
• 10:53
  Speaker 3: modern attraction, not just lookouts. They wanted something loud, They wanted.
• 10:56
  Speaker 2: A racing circuit and they chose the gully.
• 10:58
  Speaker 3: They chose the gully irony. The cruelty of that decision
• 11:02
  Speaker 3: is just it's hard to process.
• 11:04
  Speaker 2: So what did that look like for the families living there?
• 11:06
  Speaker 3: The documents from the time are heartbreaking. They were given
• 11:09
  Speaker 3: almost no notice and then they were forced to watch
• 11:13
  Speaker 3: watch the bulldozers roll in systematically destroying their homes, their churches,
• 11:18
  Speaker 3: everything they had built to clear the ground for the
• 11:21
  Speaker 3: Catalina racetrack.
• 11:22
  Speaker 5: Wow, Claire, huge issue with this part of the podcast.
• 11:28
  Speaker 5: What is it the gullies in South Katoomba. That's a
• 11:36
  Speaker 5: real problem and that's not notebook LM's fault. That's Google
• 11:40
  Speaker 5: Gemini's fault. But I just thought, I can't trust this.
• 11:44
  Speaker 1: The people who have trained these artificial intelligence models think
• 11:49
  Speaker 1: that what audiences want is to hear computer generated voices
• 11:55
  Speaker 1: having feelings. I don't think they do.
• 11:58
  Speaker 5: It does make me wonder about the bubble that these
• 12:01
  Speaker 5: people work in Silicon Valley's obviously in California. The sound
• 12:06
  Speaker 5: of this AI podcast is quite clearly modeled on the
• 12:11
  Speaker 5: Southern Californian sound of NPR, but by sort of foisting
• 12:15
  Speaker 5: that on the rest of us, there's an arrogance to that.
• 12:18
  Speaker 1: I think podcasting is a relatively new medium. This was
• 12:23
  Speaker 1: the great disruption to radio, and what we learned about
• 12:27
  Speaker 1: audiences is actually they wanted to hear natural voices, candid conversations.
• 12:32
  Speaker 1: They didn't need news readers to sound like this anymore. Yes, sure,
• 12:36
  Speaker 1: and now AI models are aping that to create products
• 12:44
  Speaker 1: in audio that have no humans involved at all.
• 12:46
  Speaker 2: It's very black mirror.
• 12:48
  Speaker 5: Another thing I noticed was that there's almost an artificial
• 12:52
  Speaker 5: instinct to please very much.
• 12:54
  Speaker 1: So they call that hallucination in tools like Google's AI
• 12:58
  Speaker 1: summary or Gemini, where it gives you the answer it
• 13:01
  Speaker 1: thinks you want. I had an example of this when
• 13:04
  Speaker 1: there are lots of shark attacks happening in Sydney. We
• 13:06
  Speaker 1: were down on the south coast of New South Wales.
• 13:09
  Speaker 1: I googled the local estuary where we swim. Have there
• 13:12
  Speaker 1: been any bull sharks in this estuary? And it said, yes,
• 13:15
  Speaker 1: there have been bull sharks in this estuary. And when
• 13:19
  Speaker 1: I looked at the links that it was using to
• 13:21
  Speaker 1: give me that answer, they were all related to Queensland,
• 13:24
  Speaker 1: or South Africa or somewhere else. So it thought I
• 13:27
  Speaker 1: wanted it to say yes. In fact, I really did
• 13:30
  Speaker 1: not want it to say yes. Sure, so it gave
• 13:32
  Speaker 1: me the answer it thought I wanted, and it hallucinated
• 13:36
  Speaker 1: that into being.
• 13:37
  Speaker 5: The truth is, there's not a huge amount to talk
• 13:39
  Speaker 5: about in North Katuma. There's not a lot going on.
• 13:41
  Speaker 5: You know, it's you know, it's quiet, it's residential. There
• 13:45
  Speaker 5: are some industrial pockets and there's a beautiful waterfall on
• 13:48
  Speaker 5: one side of town. There's one cafe, and there's a
• 13:50
  Speaker 5: gin distillery and there's an op shop. Instead of just
• 13:53
  Speaker 5: saying look no, I can't do that, or you've asked
• 13:58
  Speaker 5: for fifteen minutes, I can give you the fact that
• 14:01
  Speaker 5: it just patted out the podcast with a lot of
• 14:06
  Speaker 5: information that wasn't really connected to North Katoomba at all.
• 14:10
  Speaker 5: Made me feel good about the work that we do here.
• 14:12
  Speaker 1: One of the interesting things about audio as a medium,
• 14:15
  Speaker 1: especially in this new, very warm, kind of candid era
• 14:18
  Speaker 1: of podcasting, is that it's very emotional. You want to
• 14:21
  Speaker 1: laugh along with the podcast hosts, you want to be
• 14:23
  Speaker 1: outraged by, for example, when Heavenly Thomas tells you that
• 14:27
  Speaker 1: a woman's been murdered and the cops didn't care in
• 14:30
  Speaker 1: one of his long form investigations like for example, the
• 14:32
  Speaker 1: Teacher's Pet. So for a fake podcast to be trying
• 14:35
  Speaker 1: to push those same emotional buttons feels ultra manipulative and.
• 14:40
  Speaker 5: It doesn't work.
• 14:42
  Speaker 2: The ability to.
• 14:44
  Speaker 5: Write in a way that elicit's real buy and from
• 14:48
  Speaker 5: a listener is a distinctly human attribute. AI can mimic formulas,
• 14:53
  Speaker 5: and that can mimic the way that people talk, but
• 14:56
  Speaker 5: I think coming up with stories that elicit real human
• 15:00
  Speaker 5: emotion is best left to us humans.
• 15:03
  Speaker 1: This is relevant now because this is not just a
• 15:05
  Speaker 1: tool that we're using in our living rooms or on
• 15:08
  Speaker 1: the treadmill to inform us about something. AI podcasts are
• 15:12
  Speaker 1: being published by real publishers who are making money from them,
• 15:17
  Speaker 1: and that seems to be their main goal. The Hollywood Reporter,
• 15:20
  Speaker 1: which is a venerable news source employing lots of real
• 15:23
  Speaker 1: journals in America, did an article about this. Let's hear
• 15:26
  Speaker 1: a bit of it and this is read by their
• 15:28
  Speaker 1: text to speech function.
• 15:30
  Speaker 6: I met the high costs for producing narrative podcasts and
• 15:33
  Speaker 6: pricy short term contracts for popular hosts. The idea here
• 15:37
  Speaker 6: is being able to own scale and control the talent
• 15:40
  Speaker 6: unlike those off the cuff humans, and produce shows at
• 15:43
  Speaker 6: a minimal cost. The company builds a stable of AI
• 15:46
  Speaker 6: talent to host podcasts.
• 15:48
  Speaker 1: It referenced the company there. That's Inception point AI. That's
• 15:52
  Speaker 1: a company run by a woman named Jeanine Wright. She
• 15:55
  Speaker 1: was previously a senior executive at a very established podcasting
• 15:59
  Speaker 1: company called One Wonder. Is actually famous for making beautiful
• 16:02
  Speaker 1: handmade human podcast.
• 16:04
  Speaker 5: Isn't it Teaming up with the La Times They made
• 16:06
  Speaker 5: Dirty John. They are the team behind Doctor Death, widely
• 16:10
  Speaker 5: seen as one of the best podcast distributors. Inception point
• 16:14
  Speaker 5: AI's way of creating podcasts isn't actually too different to
• 16:18
  Speaker 5: how I created my podcast on Off Katoomba. They go
• 16:20
  Speaker 5: to AI for script generation. They dump the script into
• 16:24
  Speaker 5: a voice to text tool, they hit a button and bang,
• 16:27
  Speaker 5: you've got your podcast. The company say that takes them
• 16:30
  Speaker 5: about an hour to produce a podcast with very little
• 16:34
  Speaker 5: human involvement.
• 16:36
  Speaker 1: And they say in that Hollywood Reporter article that they
• 16:38
  Speaker 1: choose generic topics that people might be googling, like, for example, wales.
• 16:43
  Speaker 1: So they churn out an episode about blue whales. Twenty
• 16:46
  Speaker 1: people listen, they hear some ads, and inception point Ali
• 16:50
  Speaker 1: makes money for them.
• 16:51
  Speaker 5: That's a win.
• 16:52
  Speaker 1: So one way that we could respond to this, being
• 16:55
  Speaker 1: emotional human beings, just go cool, no worries, you guys
• 16:57
  Speaker 1: do that. We'll do what we do, real journalism, handmade
• 17:01
  Speaker 1: audio productions, and we'll have faith that our audience wants this. Yes,
• 17:05
  Speaker 1: what's the other way to think about it?
• 17:08
  Speaker 5: Cry in the shower. To be totally frank, this company
• 17:12
  Speaker 5: clearly isn't looking at their audience as people. They're looking
• 17:15
  Speaker 5: at them as numbers in a spreadsheet, and they think, well,
• 17:18
  Speaker 5: if we can get twenty people to listen to one
• 17:20
  Speaker 5: of these podcasts, then we've done our job and we've
• 17:22
  Speaker 5: made our company money.
• 17:24
  Speaker 1: It really reminded me of when you get into a
• 17:26
  Speaker 1: lyft in a shopping center, or you're shopping on a
• 17:29
  Speaker 1: quiet Wednesday, we can actually hear the music that the
• 17:31
  Speaker 1: shopping center is playing. It's often musak analyzed or stripped
• 17:36
  Speaker 1: back versions of real songs, so you might hear Nirvana's
• 17:40
  Speaker 1: smells like teen Spirit played on something that sounds like
• 17:43
  Speaker 1: the Glockonshbiel. Yes, it's a joke. Now. Music it's a
• 17:52
  Speaker 1: byword for something kind of cheap and tacky and cynical.
• 17:56
  Speaker 1: It's kind of like that, isn't it.
• 17:58
  Speaker 5: Music itself is a corruption of a lovely idea that
• 18:02
  Speaker 5: music can be wallpaper, but it can be beautiful wallpaper.
• 18:07
  Speaker 5: One of the pioneers of warpaper music was French composer
• 18:10
  Speaker 5: Eric Sarti, who was active in France at the turn
• 18:13
  Speaker 5: of the last century, who very intentionally wrote music to
• 18:19
  Speaker 5: create a mood. Sati was famously an eccentric man. There
• 18:23
  Speaker 5: are stories that he would attend soirees in Paris where
• 18:29
  Speaker 5: his music was being played. It wasn't being performed, it
• 18:32
  Speaker 5: was just being played in the background to set a
• 18:34
  Speaker 5: mood for the event, and he would walk through the
• 18:37
  Speaker 5: crowd and if you noticed people listening to his music
• 18:40
  Speaker 5: to stop and appreciate it because it was very beautiful music.
• 18:43
  Speaker 5: He would hit them with his umbrella and say, don't
• 18:45
  Speaker 5: listen to the music. You just meant to be enjoying yourself.
• 18:47
  Speaker 5: Just let the music have sort of washed over you
• 18:50
  Speaker 5: don't listen to it. So it's sort of this idea
• 18:52
  Speaker 5: of like subliminal music, which is actually as an artistic statement,
• 18:56
  Speaker 5: it's a really interesting thing to do. But then, like
• 19:00
  Speaker 5: you said, that quite pure and interesting idea was eventually
• 19:03
  Speaker 5: hijacked and turned into a big business idea that we
• 19:07
  Speaker 5: all need to have the golf mpperanina playing in every
• 19:09
  Speaker 5: elevator around the world.
• 19:11
  Speaker 1: Let's hear a little bit of Jim Nipiti number one
• 19:14
  Speaker 1: by Eric Satti. It's funny that he thought that this
• 19:25
  Speaker 1: was just to be heard in the background, because it's
• 19:29
  Speaker 1: very arresting. It's very different.
• 19:35
  Speaker 5: I think if it was just the cause, you could
• 19:38
  Speaker 5: ignore that. I think a melody like that comes in,
• 19:41
  Speaker 5: how you're not going to.
• 19:41
  Speaker 7: Listen to that.
• 19:42
  Speaker 1: It's a beautiful work of art. Yeah, it's amazing, just
• 19:44
  Speaker 1: like our podcasts.
• 19:46
  Speaker 7: Thanks Jeffer, thank you.
• 20:01
  Speaker 1: Jasperlik is the Australian's audio lead. You can read his
• 20:04
  Speaker 1: article about AI podcasts at the Australian dot com dot au.
• 20:08
  Speaker 1: This episode of the Front was hosted by me Claire
• 20:10
  Speaker 1: Harvey and produced by Jasperlik, who edited the episode and
• 20:13
  Speaker 1: also wrote our theme. Thanks for joining us on the
• 20:16
  Speaker 1: Front this week. Our team also includes Kristin Amiot, Leat Sammaglu,
• 20:20
  Speaker 1: Tiffany Dimack and Joshua Burton.