1 00:00:00,240 --> 00:00:03,880 Speaker 1: So could you show me like a chord that's major 2 00:00:04,000 --> 00:00:06,200 Speaker 1: and then a chord that's minor, just so we can 3 00:00:06,200 --> 00:00:09,960 Speaker 1: hear the difference. Yep, So here's a C major chord 4 00:00:14,480 --> 00:00:22,319 Speaker 1: C minor to meet. Anyone who prefers C major is 5 00:00:22,320 --> 00:00:25,759 Speaker 1: out of their mind, Like I wish them well, but 6 00:00:25,840 --> 00:00:29,120 Speaker 1: we can't ever fully understand one another or be close 7 00:00:29,160 --> 00:00:33,920 Speaker 1: friends because C minor is true and C major that's 8 00:00:33,920 --> 00:00:37,040 Speaker 1: for selling soap. Wow, I never knew. I mean, I 9 00:00:37,040 --> 00:00:39,320 Speaker 1: know you felt strong. I didn't know you felt this strongly. 10 00:00:42,680 --> 00:00:46,040 Speaker 1: That's me and Andy Thompson talking shop. He's a composer 11 00:00:46,080 --> 00:00:48,400 Speaker 1: and a producer who works out of a basement studio 12 00:00:48,440 --> 00:00:52,000 Speaker 1: called Instrument Landing. And I'm Dessa, host of the show 13 00:00:52,200 --> 00:00:55,840 Speaker 1: Deeply Human. I'm wearing my podcast had today. But I 14 00:00:55,920 --> 00:00:58,120 Speaker 1: make my living as a hip hop artist, and Andy 15 00:00:58,160 --> 00:01:01,360 Speaker 1: and I are frequent collaborators. Most of the music that 16 00:01:01,400 --> 00:01:03,760 Speaker 1: I write is pretty dark, so much so that my 17 00:01:03,800 --> 00:01:06,560 Speaker 1: bandmates tease me about it. Even my fans tease me 18 00:01:06,600 --> 00:01:09,160 Speaker 1: about it. Years ago, when I sent an early mix 19 00:01:09,160 --> 00:01:11,720 Speaker 1: of an album to my mom, she said she liked it, 20 00:01:11,959 --> 00:01:14,560 Speaker 1: but then asked, why do you always make music to 21 00:01:14,640 --> 00:01:19,120 Speaker 1: bleed out? To I've loved sad songs since I was 22 00:01:19,120 --> 00:01:24,120 Speaker 1: a teenager. My favorite genre was arguably total devastation. Tracy 23 00:01:24,200 --> 00:01:27,280 Speaker 1: Chapman's Fast Car That was a big one, some of 24 00:01:27,360 --> 00:01:29,680 Speaker 1: my mom's Bonnie ray Its slow Jams messed me up 25 00:01:29,680 --> 00:01:37,600 Speaker 1: pretty good, and of course Jeff Buckley's rendition of Hallelujah. 26 00:01:38,640 --> 00:01:42,240 Speaker 1: I played them over and over again because they reliably 27 00:01:42,280 --> 00:01:49,920 Speaker 1: made me feel exquisitely awful. Listening to sad songs is 28 00:01:49,920 --> 00:01:53,760 Speaker 1: a weird, counterintuitive thing to do. Why would anyone willfully 29 00:01:53,800 --> 00:01:57,240 Speaker 1: gravitate towards something that hurts to hear? To find out, 30 00:01:57,320 --> 00:02:01,800 Speaker 1: I'm asking a music critic, a philosopher, an experimental researcher, 31 00:02:01,920 --> 00:02:07,880 Speaker 1: and a songwriter, why do we listen to sad music? First, 32 00:02:08,000 --> 00:02:11,200 Speaker 1: let's holler at our critic, someone who listens to music professionally. 33 00:02:11,720 --> 00:02:15,080 Speaker 1: Stephen Thompson is a writer, an editor, and a broadcast 34 00:02:15,120 --> 00:02:17,600 Speaker 1: guy with National public radio in the US, and he's 35 00:02:17,639 --> 00:02:23,040 Speaker 1: a serious sad song enthusiast. I know that you made 36 00:02:23,040 --> 00:02:27,480 Speaker 1: a playlist called Weeping at the Wheels right, right right, 37 00:02:28,720 --> 00:02:30,880 Speaker 1: and the cover image was just a box of tissues 38 00:02:30,880 --> 00:02:33,840 Speaker 1: on a dashboard, and man, the car is definitely one 39 00:02:33,880 --> 00:02:36,720 Speaker 1: of the best spots to be totally disemboweled by a song. 40 00:02:37,000 --> 00:02:40,919 Speaker 1: There's a couple of songs that that I'm not allowed 41 00:02:40,960 --> 00:02:46,600 Speaker 1: to drive to because because I become an irresponsible pilot 42 00:02:46,720 --> 00:02:49,600 Speaker 1: of a motor vehicle in the throes of that much emotion, 43 00:02:49,800 --> 00:02:52,360 Speaker 1: you know, you know, when you cry, it can sometimes 44 00:02:52,360 --> 00:02:55,800 Speaker 1: like help you, like irrigate your emotions a little bit. 45 00:02:56,160 --> 00:02:58,000 Speaker 1: And I think, I think sad songs kind of have 46 00:02:58,120 --> 00:03:01,120 Speaker 1: that same that same function. I have a depressive streak, 47 00:03:01,160 --> 00:03:03,680 Speaker 1: and I have an anxious streak. And when I was 48 00:03:03,720 --> 00:03:07,520 Speaker 1: in high school, I remember my anxiety had gotten to 49 00:03:07,520 --> 00:03:09,560 Speaker 1: the point where I wasn't able to sleep at night, 50 00:03:09,720 --> 00:03:12,680 Speaker 1: and I started making lists of all the things that 51 00:03:12,720 --> 00:03:14,720 Speaker 1: I had to do. And then when I was done 52 00:03:14,760 --> 00:03:17,280 Speaker 1: writing down everything I had to do, and I was 53 00:03:17,360 --> 00:03:20,600 Speaker 1: able to process and handle it. And I think in 54 00:03:20,639 --> 00:03:24,600 Speaker 1: a way, sad songs for me are like those lists, 55 00:03:24,639 --> 00:03:27,919 Speaker 1: those anxiety lists, you know, so I can my brain 56 00:03:28,000 --> 00:03:32,920 Speaker 1: can just be this haunted circus of terrible emotions, and 57 00:03:33,400 --> 00:03:37,760 Speaker 1: a song that has a way of processing those emotions 58 00:03:38,320 --> 00:03:40,760 Speaker 1: can sometimes like serve as like almost like a sorting 59 00:03:40,800 --> 00:03:45,000 Speaker 1: mechanism for that web of feelings in my head. And 60 00:03:45,040 --> 00:03:47,880 Speaker 1: so I think sad music is really therapeutic for me 61 00:03:47,920 --> 00:03:52,480 Speaker 1: in that way, clarifying a painful feeling, pinning it to 62 00:03:52,520 --> 00:03:55,960 Speaker 1: a board, the clean, neat description provides some degree of relief, 63 00:03:56,120 --> 00:03:58,880 Speaker 1: even if the feeling itself persists. I know that in 64 00:03:58,960 --> 00:04:01,680 Speaker 1: my life being able to call demons by their proper 65 00:04:01,760 --> 00:04:05,400 Speaker 1: names just helps somehow. It's a relief to know exactly 66 00:04:05,440 --> 00:04:07,800 Speaker 1: what I'm up against, you know how, like your kid 67 00:04:07,840 --> 00:04:10,000 Speaker 1: and you come crying to your parents you've had a nightmare, 68 00:04:10,000 --> 00:04:13,600 Speaker 1: and your parents explain, like, nightmares are your brain's way 69 00:04:13,640 --> 00:04:15,960 Speaker 1: of taking out the garbage. And I always thought that 70 00:04:16,000 --> 00:04:18,320 Speaker 1: was a great way of thinking about nightmares. It's your 71 00:04:18,400 --> 00:04:21,280 Speaker 1: your brain's way of processing difficult and dark things and 72 00:04:21,520 --> 00:04:24,280 Speaker 1: so that you can handle them going forward. I think 73 00:04:24,320 --> 00:04:27,080 Speaker 1: in a way, sad songs ping a little bit of 74 00:04:27,120 --> 00:04:29,559 Speaker 1: that same thing. I wonder though, if there's like an 75 00:04:29,640 --> 00:04:33,920 Speaker 1: undercurrent of intimacy that runs through sad music that isn't 76 00:04:33,960 --> 00:04:37,279 Speaker 1: necessarily there and like dance music and that it's okay 77 00:04:37,279 --> 00:04:40,520 Speaker 1: to tell anyone, hey, I want to dance, but the 78 00:04:40,560 --> 00:04:42,359 Speaker 1: idea that like, hey, I think I'm getting a divorce, 79 00:04:43,480 --> 00:04:46,000 Speaker 1: that's a secret, that's an intimacy, and that like there 80 00:04:46,000 --> 00:04:48,680 Speaker 1: are fewer people in places that you can share that information, 81 00:04:49,040 --> 00:04:51,839 Speaker 1: and so maybe, like we understand ourselves to be in 82 00:04:51,839 --> 00:04:55,880 Speaker 1: a more intimate and trusting relationship with a musician who's 83 00:04:55,920 --> 00:04:58,680 Speaker 1: telling us a sad story than one who's telling us 84 00:04:58,680 --> 00:05:02,120 Speaker 1: is celebrating the song, can feel like you're communing with 85 00:05:02,160 --> 00:05:05,160 Speaker 1: an artist who understands and has been through what you've 86 00:05:05,200 --> 00:05:09,240 Speaker 1: gone through. And so it's not necessarily hopeless because here's 87 00:05:09,279 --> 00:05:11,440 Speaker 1: somebody who clearly went through some of the same things 88 00:05:11,440 --> 00:05:13,359 Speaker 1: that I did and came out on the other side 89 00:05:13,360 --> 00:05:15,680 Speaker 1: and wrote a song about it. I mean, I think 90 00:05:15,720 --> 00:05:20,360 Speaker 1: empathy is just one of the most powerful and important 91 00:05:20,520 --> 00:05:24,719 Speaker 1: experiences we can have as human beings. This is the 92 00:05:24,720 --> 00:05:28,080 Speaker 1: whole misery loves Company thing, but the way that Steven 93 00:05:28,120 --> 00:05:31,640 Speaker 1: tells it, maybe it's also like proof of life, evidence 94 00:05:31,640 --> 00:05:34,400 Speaker 1: that a fellow sufferer with a misery much like yours 95 00:05:34,800 --> 00:05:36,520 Speaker 1: was able to get back on our feet and get 96 00:05:36,600 --> 00:05:39,279 Speaker 1: stable enough to hire a band and a publicist and 97 00:05:39,360 --> 00:05:45,800 Speaker 1: release some music into the world. All right, for Steven's 98 00:05:45,839 --> 00:05:48,240 Speaker 1: walk off music, let's tee up a cut from his 99 00:05:48,279 --> 00:06:12,679 Speaker 1: Weeping at the Wheel playlist, and now back to Andy's 100 00:06:12,720 --> 00:06:16,159 Speaker 1: basement studio for a second to talk fundamentals. What is 101 00:06:16,240 --> 00:06:19,920 Speaker 1: sad music exactly? My lad jewel vary and there are 102 00:06:20,000 --> 00:06:22,960 Speaker 1: exceptions to every rule, but Andy ticked off a few 103 00:06:23,000 --> 00:06:25,880 Speaker 1: of the features that makes sad songs sound sad. A 104 00:06:25,920 --> 00:06:27,359 Speaker 1: lot of times when you feel sad, you kind of 105 00:06:27,480 --> 00:06:30,120 Speaker 1: pull inward and you're quiet, and you don't necessarily want 106 00:06:30,120 --> 00:06:32,320 Speaker 1: to speak to other people. And so I think one 107 00:06:32,360 --> 00:06:36,640 Speaker 1: thing a composer can do is to bring the dynamic down. 108 00:06:42,520 --> 00:06:46,240 Speaker 1: Another thing a composer can do is use just sparseness 109 00:06:46,520 --> 00:06:48,400 Speaker 1: and not have a lot going on, have the notes 110 00:06:48,400 --> 00:06:57,679 Speaker 1: to be very alone with themselves. But there are other things, 111 00:06:58,160 --> 00:07:03,000 Speaker 1: like major and minor keys that are a little bit 112 00:07:03,000 --> 00:07:06,280 Speaker 1: more of a mystery. Keep in mind, this conversation is 113 00:07:06,320 --> 00:07:08,960 Speaker 1: being had by two Western musicians, and the world is 114 00:07:08,960 --> 00:07:12,760 Speaker 1: a very wide musical place, but in very broad strokes. 115 00:07:13,080 --> 00:07:16,600 Speaker 1: Major chords are usually considered happy and minor chords sad. 116 00:07:17,080 --> 00:07:19,800 Speaker 1: So let's break down the chords to see what they're 117 00:07:19,840 --> 00:07:24,280 Speaker 1: made of. C major chord has a C in the 118 00:07:24,360 --> 00:07:28,560 Speaker 1: major third and five. To make it a minor chord, 119 00:07:28,600 --> 00:07:30,679 Speaker 1: you take that second note and you move it down 120 00:07:31,360 --> 00:07:35,240 Speaker 1: a half step, which is the shortest distance you can 121 00:07:35,280 --> 00:07:50,280 Speaker 1: move an interval in music. Usually they're C minor. Dissecting 122 00:07:50,280 --> 00:07:53,200 Speaker 1: a chord doesn't explain the feeling it foakes much better 123 00:07:53,200 --> 00:07:56,720 Speaker 1: than cutting open a candle explains romance. You're basically talking 124 00:07:56,760 --> 00:08:01,120 Speaker 1: about two frequencies interacting, and when they interact one way, 125 00:08:01,440 --> 00:08:04,600 Speaker 1: it generally makes people feel happy, and when they interact 126 00:08:04,640 --> 00:08:06,680 Speaker 1: a different way, it makes him feel sad. And that 127 00:08:06,760 --> 00:08:08,960 Speaker 1: to me is it's kind of like a black hole. 128 00:08:09,000 --> 00:08:13,120 Speaker 1: I don't know. It goes like this, the F five, 129 00:08:13,640 --> 00:08:19,760 Speaker 1: the minor fall and the major lived, the baffle king composing. 130 00:08:26,360 --> 00:08:30,040 Speaker 1: Have we just learned that some chords are associated with sadness? 131 00:08:30,160 --> 00:08:32,880 Speaker 1: Or is there a mathematical relationship between the notes that 132 00:08:32,960 --> 00:08:35,480 Speaker 1: makes us feel that way? People who have spent a 133 00:08:35,520 --> 00:08:39,040 Speaker 1: lifetime trying to master the how of music still don't 134 00:08:39,040 --> 00:08:44,160 Speaker 1: know the why. Myself very much included segue to our philosopher. 135 00:08:44,559 --> 00:08:48,280 Speaker 1: Andrew Huddleston, teaches at Birkbeck College in London. Is an undergrad. 136 00:08:48,320 --> 00:08:50,680 Speaker 1: He wrote a thesis on why we're drawn to sad music, 137 00:08:51,160 --> 00:08:54,600 Speaker 1: and I asked him how sad music evolks emotion. One 138 00:08:54,720 --> 00:08:59,240 Speaker 1: theory is that the musical expressions resemble the expressions of 139 00:08:59,280 --> 00:09:02,959 Speaker 1: sad people think of the face of a Saint Bernard dog, 140 00:09:03,600 --> 00:09:06,200 Speaker 1: we say that the face is sad, even though we 141 00:09:06,240 --> 00:09:08,760 Speaker 1: think the dog is not sad. Now why do we 142 00:09:08,840 --> 00:09:11,520 Speaker 1: think that, Well, it resembles in a certain way the 143 00:09:11,600 --> 00:09:15,520 Speaker 1: expression of sad people, maybe in a kind of caricatured way, 144 00:09:15,760 --> 00:09:18,720 Speaker 1: the kind of drooping quality of the Saint Bernard dog's face. 145 00:09:19,000 --> 00:09:21,800 Speaker 1: And you think something similar might be the case in 146 00:09:21,960 --> 00:09:25,160 Speaker 1: the contours of music, that they might have these kinds 147 00:09:25,200 --> 00:09:31,120 Speaker 1: of qualities that put us in mind of sadness. Some 148 00:09:31,240 --> 00:09:34,120 Speaker 1: sad music might actually resemble the sounds that come out 149 00:09:34,120 --> 00:09:37,320 Speaker 1: of sad humans, that sound like wailing or like laments. 150 00:09:37,360 --> 00:09:39,959 Speaker 1: And I think that that's a very common thing in 151 00:09:40,240 --> 00:09:43,160 Speaker 1: vocal music and in some purely instrumental music too, where 152 00:09:43,160 --> 00:09:45,640 Speaker 1: that quality is mirrored. And I think that that really 153 00:09:45,679 --> 00:09:49,839 Speaker 1: puts us in mind of expressions of sadness, that kind 154 00:09:49,840 --> 00:09:53,600 Speaker 1: of rising and falling suddenly falling vocal line, or the 155 00:09:53,640 --> 00:10:01,559 Speaker 1: sense of a sigh in the music. My mom used 156 00:10:01,600 --> 00:10:03,480 Speaker 1: to sing a lullaby to me and my kid brother 157 00:10:03,559 --> 00:10:07,120 Speaker 1: Maxie called No Nando, and I think it has the 158 00:10:07,160 --> 00:10:09,480 Speaker 1: kind of melody lines that Andrew's talking about. It has 159 00:10:09,520 --> 00:10:14,400 Speaker 1: these like super epic swells and cascades My mom is 160 00:10:14,400 --> 00:10:16,800 Speaker 1: Puerto Rican and most of the words are in Spanish, 161 00:10:16,960 --> 00:10:19,839 Speaker 1: but I've always suspected that maybe, like the trills in 162 00:10:19,880 --> 00:10:23,160 Speaker 1: the vocal line were forged by Sephardic Jewish singers with 163 00:10:23,240 --> 00:10:26,240 Speaker 1: roots in Spain. It's one of those songs where a 164 00:10:26,400 --> 00:10:28,760 Speaker 1: mom like puts her kid's name into it, and I 165 00:10:28,800 --> 00:10:31,600 Speaker 1: do not have kids, so I'm gonna use Max's name. 166 00:10:31,880 --> 00:10:39,480 Speaker 1: But it goes like this an no na do no 167 00:10:39,679 --> 00:10:51,040 Speaker 1: no go me baby Maxie it done, and no na 168 00:10:51,600 --> 00:11:00,120 Speaker 1: gole no na go ani no na and the nina no. 169 00:11:05,200 --> 00:11:08,480 Speaker 1: It is an insanely dramatic way to put a kid 170 00:11:08,559 --> 00:11:11,240 Speaker 1: to bed. I used to hate it when you go high, 171 00:11:11,280 --> 00:11:13,319 Speaker 1: because I knew and he was almost done and I 172 00:11:13,360 --> 00:11:16,679 Speaker 1: had to go to sleep. I still sing on nonando 173 00:11:16,840 --> 00:11:20,000 Speaker 1: sometimes around my apartment, and my voice right now sounds 174 00:11:20,000 --> 00:11:24,120 Speaker 1: a lot like my mom's did then. But why I 175 00:11:24,160 --> 00:11:26,520 Speaker 1: am a grown adult who could listen to dance music 176 00:11:26,600 --> 00:11:29,160 Speaker 1: or just eat Peanut M and M's or right a 177 00:11:29,240 --> 00:11:32,679 Speaker 1: Shetland pony through a field of daisies. I asked Andrew 178 00:11:32,760 --> 00:11:35,120 Speaker 1: for the philosopher's take on why we listen to sad 179 00:11:35,240 --> 00:11:41,000 Speaker 1: music at all. We're interested in knowing about what the 180 00:11:41,040 --> 00:11:45,040 Speaker 1: world is like, even about extreme kinds of suffering and horror, 181 00:11:45,440 --> 00:11:48,560 Speaker 1: even if that's not particularly pleasant. You know, why are 182 00:11:48,600 --> 00:11:51,360 Speaker 1: people drawn to tragedy? Why are people drawn to films 183 00:11:51,360 --> 00:11:53,760 Speaker 1: that are about really horrible things? Why do they read 184 00:11:53,800 --> 00:11:55,600 Speaker 1: novels that are about really horrible things? And I think 185 00:11:55,640 --> 00:11:58,480 Speaker 1: one of the explanations is we care about knowledge. We 186 00:11:58,520 --> 00:12:00,880 Speaker 1: care about knowing what the world is, even if what 187 00:12:00,960 --> 00:12:04,679 Speaker 1: we find out is something that's depressing. There might also 188 00:12:04,760 --> 00:12:08,480 Speaker 1: be something important about packaging sadness in music. So I 189 00:12:08,559 --> 00:12:12,240 Speaker 1: think the beauty plays a really considerable role here. One 190 00:12:12,240 --> 00:12:14,760 Speaker 1: thing that it can provide is in itself a certain 191 00:12:14,840 --> 00:12:18,640 Speaker 1: kind of consolation. Perhaps the presence of the beauty in 192 00:12:18,720 --> 00:12:23,520 Speaker 1: this expression of something that's sad or depressing, it might 193 00:12:23,600 --> 00:12:27,560 Speaker 1: also intimate a certain kind of hope as well. Maybe 194 00:12:27,600 --> 00:12:30,280 Speaker 1: the music here becomes the mixer and a stiff drink, 195 00:12:30,880 --> 00:12:32,960 Speaker 1: or the sticker the doctor gives to a little kid 196 00:12:33,000 --> 00:12:35,960 Speaker 1: after her shot. It's still going to burn, but the 197 00:12:36,000 --> 00:12:38,040 Speaker 1: beauty of the music gives you something for the pain. 198 00:12:39,400 --> 00:12:44,120 Speaker 1: Andrew himself is a Wagner guy, So DJ drop something 199 00:12:44,120 --> 00:13:03,240 Speaker 1: from the ring cycle. Yeah, my name is Boskowski. I 200 00:13:03,280 --> 00:13:07,280 Speaker 1: work at the University of Oslo as an Associate professor 201 00:13:07,360 --> 00:13:10,720 Speaker 1: in music cognition. Yana was part of a team that 202 00:13:10,800 --> 00:13:14,520 Speaker 1: conducted an experiment to study fans of sad music. They 203 00:13:14,559 --> 00:13:18,839 Speaker 1: wanted to find out what kinds of personality traits are 204 00:13:18,880 --> 00:13:23,079 Speaker 1: related to people's enjoyment of sad music. Jana's team recruits 205 00:13:23,080 --> 00:13:26,080 Speaker 1: a bunch of research participants, put some in fancy headphones 206 00:13:26,320 --> 00:13:34,280 Speaker 1: and presses play on eight minutes of sad instrumental music. Next, 207 00:13:34,400 --> 00:13:37,160 Speaker 1: you wanna hit some with a questionnaire to record their feelings. 208 00:13:37,679 --> 00:13:42,080 Speaker 1: It's got different emotional adjectives like moved, melancholic, sad, peaceful, 209 00:13:42,280 --> 00:13:45,600 Speaker 1: and intensity scales from one to seven. Also, they filled 210 00:13:45,600 --> 00:13:50,880 Speaker 1: in a whole battery of different kinds of personality tests 211 00:13:50,920 --> 00:13:55,880 Speaker 1: and questions about their current mood and also their experienced 212 00:13:56,200 --> 00:13:59,720 Speaker 1: quality of life and kind of general health related questions. 213 00:14:00,320 --> 00:14:02,720 Speaker 1: Some of the participants were hooked up with electrodes to 214 00:14:02,760 --> 00:14:07,520 Speaker 1: measure bodily responses to evidence of intense emotional reactions. With 215 00:14:07,559 --> 00:14:10,000 Speaker 1: all the data collected, Yonah and her team crunch the 216 00:14:10,080 --> 00:14:13,959 Speaker 1: numbers looking for patterns, and they find one one thing 217 00:14:14,040 --> 00:14:19,720 Speaker 1: that really consistently seemed to predict people's enjoyment of sad music. 218 00:14:20,320 --> 00:14:25,680 Speaker 1: Was empathy. Those who score the highest in empathic concern 219 00:14:25,920 --> 00:14:28,720 Speaker 1: or sympathy for others, they seem to be enjoying sad 220 00:14:28,800 --> 00:14:32,880 Speaker 1: music the most. So perhaps they are connecting to something 221 00:14:33,040 --> 00:14:36,400 Speaker 1: human in the music. They're reacting to sad music, gus 222 00:14:36,440 --> 00:14:40,480 Speaker 1: they would to a sad person. Got admit as emo. 223 00:14:40,600 --> 00:14:44,480 Speaker 1: Kids are coming off pretty good right now, kind compassionate. 224 00:14:45,720 --> 00:14:47,920 Speaker 1: Sure you could date somebody from the varsity team will 225 00:14:47,920 --> 00:14:50,280 Speaker 1: only listens to metal, but they might let your cat 226 00:14:50,320 --> 00:14:52,880 Speaker 1: on fire something. And if they do, we will have 227 00:14:52,920 --> 00:14:54,600 Speaker 1: a hot cup of tea ready if you want to 228 00:14:54,600 --> 00:14:58,400 Speaker 1: talk about it all right. For Yonah's walk off music, 229 00:14:58,920 --> 00:15:02,160 Speaker 1: I persuaded her to say the melancholic finish lullaby that 230 00:15:02,240 --> 00:15:07,520 Speaker 1: her mother used to sing, You want me to sing? Okay, 231 00:15:07,800 --> 00:15:13,720 Speaker 1: here goes bier Nicki, Sulin boy Gan and Holy yon 232 00:15:14,040 --> 00:15:20,400 Speaker 1: None ohmak Covery, be a nil, Lucky Soli, loly Bion, 233 00:15:21,720 --> 00:15:32,600 Speaker 1: Bion and Bienny. And we listened to sad music for clarity, 234 00:15:32,800 --> 00:15:35,600 Speaker 1: for comfort. But what about the people who write the songs? 235 00:15:35,680 --> 00:15:39,240 Speaker 1: Why do we wallow and suffering? I invited a fellow songwriter, 236 00:15:39,440 --> 00:15:42,320 Speaker 1: Mayotta to talk it out. She's found herself in tears 237 00:15:42,360 --> 00:15:46,200 Speaker 1: over her keyboard while crafting a particularly sad joint. Why 238 00:15:46,240 --> 00:15:48,000 Speaker 1: do you do that? Why do we do that? That 239 00:15:48,000 --> 00:15:53,200 Speaker 1: doesn't make any sense that um my general thought that 240 00:15:53,280 --> 00:15:56,040 Speaker 1: why we do that? I think it's for catharsis, and 241 00:15:56,120 --> 00:15:59,360 Speaker 1: for me specifically, it's definitely for catharsis without sweating the 242 00:15:59,400 --> 00:16:01,680 Speaker 1: dictionary different and like, what does that mean when you 243 00:16:01,760 --> 00:16:05,560 Speaker 1: use that word says release? I think, like that's the 244 00:16:05,560 --> 00:16:10,160 Speaker 1: main thing I'm thinking of, is release. I really see 245 00:16:10,440 --> 00:16:16,440 Speaker 1: trauma as like stagnant energy that got stuck and wasn't 246 00:16:16,480 --> 00:16:19,000 Speaker 1: allowed to like move through you. Like I literally just 247 00:16:19,000 --> 00:16:20,600 Speaker 1: heard this from my therapist a couple of days ago, 248 00:16:20,680 --> 00:16:23,000 Speaker 1: and she dragged me and was like, well, you have 249 00:16:23,120 --> 00:16:25,720 Speaker 1: to feel to heal. If you don't let yourself feel 250 00:16:25,760 --> 00:16:28,040 Speaker 1: your lows, you don't get to feel the highs either, 251 00:16:28,280 --> 00:16:36,400 Speaker 1: Like everything numbs out. I know from personal experience that 252 00:16:36,480 --> 00:16:38,840 Speaker 1: it can be a serious challenge to perform while your 253 00:16:38,840 --> 00:16:41,760 Speaker 1: body isn't the throes of a big feeling. Your hands, 254 00:16:41,800 --> 00:16:45,760 Speaker 1: shake your voice titans, your diaphragm might want to do 255 00:16:45,920 --> 00:16:49,720 Speaker 1: that spasm thing. Sadness affects all the muscles that are 256 00:16:49,760 --> 00:16:52,800 Speaker 1: supposed to be playing the damn song. But Mayada built 257 00:16:52,840 --> 00:16:55,960 Speaker 1: room for these feelings into the architecture of her arrangements. 258 00:16:56,520 --> 00:17:02,640 Speaker 1: Oh man, oh wow, Wolf, I'm just like I'm like 259 00:17:02,760 --> 00:17:06,639 Speaker 1: viscerally coming back to a couple of times. I wrote 260 00:17:06,640 --> 00:17:10,919 Speaker 1: a lot of like really belty swelling, like kind of 261 00:17:10,960 --> 00:17:15,840 Speaker 1: squalling type of moments into these songs, and so it 262 00:17:15,880 --> 00:17:19,879 Speaker 1: was like a yell just dropped jaw on an awe, 263 00:17:20,160 --> 00:17:24,080 Speaker 1: but like really loud, and I think that was the 264 00:17:24,160 --> 00:17:28,720 Speaker 1: release instead of like straight up crying like something needs 265 00:17:28,760 --> 00:17:31,000 Speaker 1: to get out of me. But I'm gonna do it 266 00:17:31,040 --> 00:17:33,320 Speaker 1: in a kind of pretty way because my choir teacher 267 00:17:33,359 --> 00:17:36,440 Speaker 1: taught me, like in high school, when you have to scream, 268 00:17:36,840 --> 00:17:40,560 Speaker 1: do it musically right, like breathe like you would be singing. 269 00:17:40,920 --> 00:17:43,600 Speaker 1: And while my body was like on some very like 270 00:17:43,760 --> 00:17:47,639 Speaker 1: shaky type of thing, I knew that if I just 271 00:17:47,920 --> 00:17:51,199 Speaker 1: made it to the chorus, I could basically scream, And 272 00:17:51,240 --> 00:17:54,720 Speaker 1: I think that was kind of what shorted up. Does 273 00:17:54,760 --> 00:17:57,440 Speaker 1: it feel like you're sometimes writing sad songs for political, 274 00:17:57,840 --> 00:18:03,679 Speaker 1: you know, reasons, like specifically absolutely? Actually, I would venture 275 00:18:03,720 --> 00:18:05,760 Speaker 1: to say that those are the ones that are the hardest, 276 00:18:06,480 --> 00:18:10,760 Speaker 1: like ones that came out of some very specifically rough 277 00:18:10,880 --> 00:18:13,960 Speaker 1: stuff about just like my my black experience. For example, 278 00:18:14,680 --> 00:18:16,920 Speaker 1: it's like, in the most technical of senses, I am 279 00:18:16,960 --> 00:18:20,160 Speaker 1: literally performing my pain right now. But like, I'm doing 280 00:18:20,200 --> 00:18:22,560 Speaker 1: this thing and I know that I'm incurring damage from it, 281 00:18:22,600 --> 00:18:25,800 Speaker 1: and I know that it's like stress. It's like stressing 282 00:18:25,840 --> 00:18:28,480 Speaker 1: my body to have to explain this over and over again. 283 00:18:28,680 --> 00:18:31,720 Speaker 1: But also like, I still believe in the power of 284 00:18:31,880 --> 00:18:37,400 Speaker 1: sharing my experience, but I need you to hear me. 285 00:18:38,320 --> 00:18:40,800 Speaker 1: Some sad music might be used as a call to action, 286 00:18:41,040 --> 00:18:43,439 Speaker 1: a request, or a challenge for listeners to come to 287 00:18:43,480 --> 00:18:47,080 Speaker 1: one another's aid. I think that a lot of Western 288 00:18:47,119 --> 00:18:53,800 Speaker 1: experience of music, particularly of art, is for entertainment, and 289 00:18:54,640 --> 00:18:57,160 Speaker 1: I don't really see my job as one as as 290 00:18:57,160 --> 00:19:00,320 Speaker 1: an entertainer. If you had a business card, like would 291 00:19:00,320 --> 00:19:03,040 Speaker 1: it say, Wow, what was the first thing that came 292 00:19:03,080 --> 00:19:07,000 Speaker 1: to my musical healer? Yeah? I think musical healer. That 293 00:19:07,119 --> 00:19:09,760 Speaker 1: song with the belty yell instead of cry chorus that 294 00:19:09,800 --> 00:19:13,400 Speaker 1: Mayatta was talking about is called Cracked Chest. She hasn't 295 00:19:13,440 --> 00:19:15,600 Speaker 1: recorded a studio version yet, but we're lucky enough to 296 00:19:15,640 --> 00:19:24,880 Speaker 1: premiere the Devil here. It's oh mind, oh my, oh mind, 297 00:19:24,920 --> 00:19:38,359 Speaker 1: oh my, oh my, oh my. Was somebody my hen 298 00:19:49,160 --> 00:19:51,280 Speaker 1: for a while? My dad made his living as a 299 00:19:51,359 --> 00:19:53,800 Speaker 1: loot player. If you can't picture it, a loot is 300 00:19:53,800 --> 00:19:56,080 Speaker 1: a precursor of the guitar, the kind of instrument you 301 00:19:56,119 --> 00:19:58,679 Speaker 1: might see on a tapestry. It's not the line of 302 00:19:58,680 --> 00:20:01,119 Speaker 1: work you pursue hoping to get rich. And by the 303 00:20:01,200 --> 00:20:03,920 Speaker 1: nineteen eighties my dad had missed the loot craze by 304 00:20:03,960 --> 00:20:09,240 Speaker 1: like so years. Still he sat alone for many hours 305 00:20:09,440 --> 00:20:13,440 Speaker 1: playing these delicate, melancholy songs written by other sensitive men. 306 00:20:13,760 --> 00:20:17,879 Speaker 1: Now long did When I asked what drove his musical obsession, 307 00:20:18,160 --> 00:20:21,480 Speaker 1: I met the hard limit of his sentimentalism. He said 308 00:20:21,480 --> 00:20:23,880 Speaker 1: he was deeply moved by the music. He found great 309 00:20:23,920 --> 00:20:26,960 Speaker 1: beauty in it, but he just didn't see any evidence 310 00:20:27,000 --> 00:20:29,600 Speaker 1: that it had some higher meaning. He used the phrase 311 00:20:29,760 --> 00:20:32,920 Speaker 1: mental masturbation, like that might be what all this loop 312 00:20:32,960 --> 00:20:36,239 Speaker 1: playing amounted to. And some people have suggested that our 313 00:20:36,280 --> 00:20:39,960 Speaker 1: affinity to music is just a byproduct of evolution, that 314 00:20:40,000 --> 00:20:43,399 Speaker 1: our pattern sensitive brains built for language might just geek 315 00:20:43,440 --> 00:20:45,359 Speaker 1: out our music like a house cat does on a 316 00:20:45,440 --> 00:20:50,840 Speaker 1: laser pointer. Stephen Pinker, a famous cognitive psychologist, characterized music 317 00:20:51,160 --> 00:21:04,600 Speaker 1: as auditory cheesecake. H I don't understand music in theory, 318 00:21:06,080 --> 00:21:09,560 Speaker 1: but I understand it in practice, and I see how 319 00:21:09,560 --> 00:21:12,119 Speaker 1: the faces in the crowd change when the big ballad 320 00:21:12,200 --> 00:21:14,840 Speaker 1: begins and the strings lift like a tidal wave, and 321 00:21:14,880 --> 00:21:17,359 Speaker 1: we are all briefly relieved of the obligation to be 322 00:21:17,400 --> 00:21:21,320 Speaker 1: our professional, presentable selves, and instead the full truth of 323 00:21:21,320 --> 00:21:23,959 Speaker 1: our lives is welcomed into the room, the fears and 324 00:21:24,000 --> 00:21:27,480 Speaker 1: the fractures, and until the final notes ring, we are 325 00:21:27,520 --> 00:21:31,359 Speaker 1: suspended in communion with one another, like rafts and rough water, 326 00:21:31,560 --> 00:21:38,280 Speaker 1: somehow fortified by the storm. The music sensitizes us to 327 00:21:38,320 --> 00:21:41,200 Speaker 1: the world and to the other people in it. There's 328 00:21:41,240 --> 00:21:44,480 Speaker 1: this line often attributed to the Persian poet Roomy, that 329 00:21:44,560 --> 00:21:47,720 Speaker 1: about sums it up for me. You have to keep 330 00:21:47,760 --> 00:21:53,520 Speaker 1: breaking your heart until it opens as I let myself out. 331 00:21:53,800 --> 00:21:56,240 Speaker 1: Here's a clip of a song I sometimes play on tour. 332 00:21:56,920 --> 00:22:10,639 Speaker 1: It's called good Grief. How can it's head bad? Maybe 333 00:22:13,440 --> 00:22:24,320 Speaker 1: good grieves one's good? How can it at our next meeting? 334 00:22:24,480 --> 00:22:27,840 Speaker 1: Deeply Human is examining the teenage brain to find out 335 00:22:27,840 --> 00:22:31,360 Speaker 1: why there's such an intensity of feeling during adolescents. Why 336 00:22:31,359 --> 00:22:36,280 Speaker 1: does the world burn brighter in your teens? Deeply Human 337 00:22:36,400 --> 00:22:39,080 Speaker 1: is a co production of the BBC World Service and 338 00:22:39,119 --> 00:22:42,600 Speaker 1: American public media with I heart Media and as you 339 00:22:42,640 --> 00:22:45,080 Speaker 1: know by now, I'm a musician and a songwriter too, 340 00:22:45,480 --> 00:22:47,280 Speaker 1: so if you'd like to share your thoughts on songs, 341 00:22:47,480 --> 00:22:50,320 Speaker 1: sad or happy ones, you can find me at Duessa 342 00:22:50,520 --> 00:22:53,040 Speaker 1: Darling on Twitter. Thanks for listening.