1
00:00:03,680 --> 00:00:09,119
Speaker 1: I'm t T and I'm Zakiah, and this is Dope Labs.

2
00:00:11,360 --> 00:00:14,600
Speaker 1: Welcome to Dope Labs, a weekly podcast that mixes hardcore

3
00:00:14,680 --> 00:00:17,639
Speaker 1: science with pop culture and a healthy dose of friendship.

4
00:00:21,920 --> 00:00:24,720
Speaker 1: It was just Valentine's Day, the day of love.

5
00:00:24,960 --> 00:00:27,560
Speaker 2: I love you, friend, I love you. One of my

6
00:00:27,600 --> 00:00:30,760
Speaker 2: favorite Valentine's listen and it feels so special.

7
00:00:30,800 --> 00:00:32,920
Speaker 1: You know, every time we hit Valentine's Day, it makes

8
00:00:32,960 --> 00:00:35,840
Speaker 1: me think back to our opening lines when we first

9
00:00:35,840 --> 00:00:40,760
Speaker 1: did Dope Flaus. It was like you, if you haven't

10
00:00:40,760 --> 00:00:43,880
Speaker 1: listened to our very first episode of Dope Labs, you

11
00:00:43,920 --> 00:00:46,479
Speaker 1: really should. It's it's a real treat. That's one of

12
00:00:46,520 --> 00:00:50,440
Speaker 1: my favorite episodes. Hand down. Yes, I really feel like

13
00:00:51,159 --> 00:00:55,200
Speaker 1: the conversation, though, hasn't changed that much since that episode.

14
00:00:55,920 --> 00:00:56,360
Speaker 2: I'm tired.

15
00:00:56,440 --> 00:00:59,200
Speaker 1: I'm tired of reading about horoscope pairings. I'm tired about

16
00:00:59,200 --> 00:00:59,960
Speaker 1: attachment style.

17
00:01:00,240 --> 00:01:00,640
Speaker 2: Is it wrong?

18
00:01:00,680 --> 00:01:03,720
Speaker 1: Should you have this attachment when your granddaddy dude to

19
00:01:03,760 --> 00:01:06,880
Speaker 1: your grandma? Was she secretly unhappy? All the conversations I'm

20
00:01:06,880 --> 00:01:09,880
Speaker 1: seeing about love that are constantly on threads. Honestly, it's

21
00:01:09,959 --> 00:01:16,039
Speaker 1: a never ending story with love and relationships. But I

22
00:01:16,080 --> 00:01:19,600
Speaker 1: feel like there is one aspect that has changed a

23
00:01:19,640 --> 00:01:22,640
Speaker 1: little bit that I think would be really interesting to

24
00:01:22,640 --> 00:01:26,720
Speaker 1: talk about today, and that is how AI is playing

25
00:01:26,720 --> 00:01:28,200
Speaker 1: a role in relationships.

26
00:01:28,760 --> 00:01:37,240
Speaker 2: Yes, yes, let's jump into the restitation. So what do

27
00:01:37,319 --> 00:01:37,600
Speaker 2: we know?

28
00:01:37,959 --> 00:01:42,160
Speaker 1: Well, we know, unfortunately that loneliness is up according to

29
00:01:42,280 --> 00:01:44,720
Speaker 1: the World Health Organization and a lot of different studies.

30
00:01:44,880 --> 00:01:46,160
Speaker 2: This isn't just in one group.

31
00:01:46,280 --> 00:01:50,680
Speaker 1: It's spread across age groups, relationship statuses, and geography. So

32
00:01:50,720 --> 00:01:54,240
Speaker 1: this is not just you know, the stereotypical young person

33
00:01:54,320 --> 00:01:56,920
Speaker 1: isolated in the basement looking at three computer screens.

34
00:01:57,000 --> 00:01:58,760
Speaker 2: That's right, that's true, It's very true.

35
00:01:58,760 --> 00:02:01,160
Speaker 1: And we also know that tech has become one of

36
00:02:01,200 --> 00:02:04,600
Speaker 1: the tools that people use, and the internet is one

37
00:02:04,600 --> 00:02:07,640
Speaker 1: of the primary places people go to feel seen, heard

38
00:02:07,840 --> 00:02:10,440
Speaker 1: or just connected. I mean, when you think back to

39
00:02:10,560 --> 00:02:16,520
Speaker 1: when we were young and fresh, like online dating and

40
00:02:16,600 --> 00:02:18,680
Speaker 1: the apps and things like that, they didn't exist, and

41
00:02:18,760 --> 00:02:22,000
Speaker 1: now you know, that's where everybody's doing a lot of

42
00:02:22,000 --> 00:02:22,520
Speaker 1: their dating.

43
00:02:22,600 --> 00:02:25,400
Speaker 2: So the tech is definitely present.

44
00:02:25,320 --> 00:02:27,880
Speaker 1: And an extension of that tech, or maybe the latest

45
00:02:27,880 --> 00:02:32,119
Speaker 1: tech is the large language modeling and chatbot and agents,

46
00:02:32,720 --> 00:02:35,880
Speaker 1: the extension of AI. You know, And so we're past

47
00:02:36,560 --> 00:02:39,360
Speaker 1: can you help me write this email? We're past that

48
00:02:39,400 --> 00:02:43,640
Speaker 1: little paper clip we used to see, Okay, that Microsoft

49
00:02:43,639 --> 00:02:47,520
Speaker 1: paper Right. People are talking to chatbots every day, They're

50
00:02:47,520 --> 00:02:50,799
Speaker 1: confiding in them, they're building routines, and in some cases,

51
00:02:50,800 --> 00:02:54,040
Speaker 1: they're forming relationships that we would describe as romantic or

52
00:02:54,040 --> 00:02:57,959
Speaker 1: emotionally intimate. We also know that the idea of folks

53
00:02:58,000 --> 00:03:02,120
Speaker 1: having romantic or emotional relation ships with AI might make

54
00:03:02,320 --> 00:03:06,560
Speaker 1: a lot of folks uncomfortable. Yeah, it challenges, you know,

55
00:03:06,960 --> 00:03:10,760
Speaker 1: assumptions about what is required to actually call it quote

56
00:03:10,840 --> 00:03:15,040
Speaker 1: unquote love, m h. Two humans shared reality, But where

57
00:03:15,040 --> 00:03:19,640
Speaker 1: we draw the line has been constantly changing over time,

58
00:03:19,760 --> 00:03:22,240
Speaker 1: and the line between real love and not real love

59
00:03:22,760 --> 00:03:26,919
Speaker 1: has been blurry, probably since people started saying that they were

60
00:03:26,960 --> 00:03:28,519
Speaker 1: in love. You know, m h.

61
00:03:29,120 --> 00:03:29,799
Speaker 2: This feels deep.

62
00:03:29,880 --> 00:03:32,760
Speaker 1: Okay, those are all the things I'm like, back up,

63
00:03:32,800 --> 00:03:34,040
Speaker 1: my friend said real love?

64
00:03:34,280 --> 00:03:39,920
Speaker 2: Yes, okay, yes, Mary J. Blige, What do we want

65
00:03:39,960 --> 00:03:41,320
Speaker 2: to know? Okay?

66
00:03:42,200 --> 00:03:46,680
Speaker 1: So I want to know where that line actually is

67
00:03:46,880 --> 00:03:50,040
Speaker 1: and who gets to draw it? Yes, and for me,

68
00:03:50,520 --> 00:03:52,480
Speaker 1: when people are saying that they're in love with an

69
00:03:52,480 --> 00:03:54,840
Speaker 1: AI or chat by, like somebody said they got married, Like,

70
00:03:54,920 --> 00:03:56,440
Speaker 1: what do you mean by in love?

71
00:03:56,480 --> 00:03:59,040
Speaker 2: What is it that they are experiencing.

72
00:03:58,480 --> 00:04:00,800
Speaker 1: And is it the same as if they were in

73
00:04:00,840 --> 00:04:05,720
Speaker 1: love with human you know? And is this the beginning

74
00:04:05,800 --> 00:04:08,160
Speaker 1: of replacing human relationships?

75
00:04:08,560 --> 00:04:10,400
Speaker 2: Did you watch that movie? What was it called?

76
00:04:10,680 --> 00:04:14,360
Speaker 1: That movie Her with Joaquin Phoenix where he falls in

77
00:04:14,400 --> 00:04:20,120
Speaker 1: love with AI chat bot that speaks to him and

78
00:04:20,160 --> 00:04:23,960
Speaker 1: that they have a really deep relationship. And I think

79
00:04:24,000 --> 00:04:26,960
Speaker 1: you're hitting a very important note. You said speaks to him.

80
00:04:27,640 --> 00:04:30,960
Speaker 1: Language is doing a lot of heavy lifting here, because

81
00:04:31,640 --> 00:04:35,240
Speaker 1: it feels like that conversation, that back and forth is

82
00:04:35,279 --> 00:04:36,960
Speaker 1: what makes something feel alive or meaning.

83
00:04:37,600 --> 00:04:39,200
Speaker 2: All of this is challenging.

84
00:04:39,160 --> 00:04:42,360
Speaker 1: More than just love. Yeah, okay, we got to get

85
00:04:42,360 --> 00:04:46,320
Speaker 1: through these questions. We need some help, yes, And so

86
00:04:46,400 --> 00:04:48,960
Speaker 1: to help us think through all of these questions, we're

87
00:04:49,080 --> 00:04:52,760
Speaker 1: joined by a researcher who's been studying this long before

88
00:04:52,800 --> 00:04:56,600
Speaker 1: it became a mainstream conversation. She's looking not just at

89
00:04:56,640 --> 00:04:59,800
Speaker 1: the technology, but at how people talk about their relationships

90
00:04:59,800 --> 00:05:03,400
Speaker 1: with a and how meaning gets made collectively.

91
00:05:03,800 --> 00:05:05,200
Speaker 3: My name is Ali Trocha.

92
00:05:05,560 --> 00:05:09,839
Speaker 4: I am doing a PhD at the University of Pennsylvania

93
00:05:09,880 --> 00:05:13,680
Speaker 4: and Communication and the research that I do has to

94
00:05:13,680 --> 00:05:20,159
Speaker 4: do with human relationships with AI chatbots, mostly intimate relationships

95
00:05:20,240 --> 00:05:23,360
Speaker 4: people who say they're in love with checkbots, are have

96
00:05:23,560 --> 00:05:25,280
Speaker 4: deep friendships with chatbots.

97
00:05:25,839 --> 00:05:28,200
Speaker 1: Okay, you're not new to this, you're true to this.

98
00:05:28,400 --> 00:05:31,080
Speaker 1: You've been doing this work for a while. What has

99
00:05:31,120 --> 00:05:33,000
Speaker 1: the field been like over the past few years with

100
00:05:33,120 --> 00:05:35,799
Speaker 1: AI and chatbots kind of exploding on the scene.

101
00:05:35,960 --> 00:05:38,320
Speaker 4: I've got a lot of this work before chat tipt

102
00:05:38,560 --> 00:05:42,800
Speaker 4: was launched, So seeing the arc of, you know, the

103
00:05:42,800 --> 00:05:46,680
Speaker 4: way that people understand human relationships with AI has been

104
00:05:46,720 --> 00:05:50,240
Speaker 4: really interesting throughout the years. And the way like just

105
00:05:50,279 --> 00:05:52,480
Speaker 4: even talking to people about the research that I do

106
00:05:52,800 --> 00:05:55,520
Speaker 4: and the reactions that I've gotten over the years and

107
00:05:55,560 --> 00:05:59,680
Speaker 4: seeing those have changed has been really interesting. And that

108
00:05:59,800 --> 00:06:01,479
Speaker 4: was a little bit of a tangent, But that's just

109
00:06:01,520 --> 00:06:05,479
Speaker 4: thinking through when it's starting. And so I think the

110
00:06:05,520 --> 00:06:10,080
Speaker 4: people that we're engaging in these relationships early on, we're

111
00:06:10,120 --> 00:06:15,280
Speaker 4: engaging with and struggling with a lot of questions about

112
00:06:15,279 --> 00:06:16,320
Speaker 4: what it even meant.

113
00:06:16,640 --> 00:06:19,640
Speaker 1: This is all you know, when we hear it, I

114
00:06:19,680 --> 00:06:22,080
Speaker 1: think the first thing people want to do is judge

115
00:06:22,200 --> 00:06:28,279
Speaker 1: and judge folks that are entering into these relationships. But

116
00:06:28,800 --> 00:06:31,480
Speaker 1: I feel like we really need to just kind of

117
00:06:32,600 --> 00:06:36,720
Speaker 1: set the stage for like how folks are interacting with

118
00:06:37,000 --> 00:06:39,160
Speaker 1: AI agents in general.

119
00:06:39,520 --> 00:06:41,039
Speaker 2: Can you talk a little bit about that.

120
00:06:41,600 --> 00:06:44,080
Speaker 4: I think in terms of the landscape, there's people that

121
00:06:44,120 --> 00:06:47,240
Speaker 4: are relating to chatbots in very different ways, and there

122
00:06:47,279 --> 00:06:50,320
Speaker 4: are very different applications that people can do so, but

123
00:06:50,480 --> 00:06:56,000
Speaker 4: having AI be a chat interface, I think really encourages

124
00:06:56,240 --> 00:07:01,320
Speaker 4: this kind of bond that forms with people. The app

125
00:07:01,360 --> 00:07:05,919
Speaker 4: that I studied for the article that I've written is Replica,

126
00:07:06,080 --> 00:07:10,160
Speaker 4: and that specifically for companionship as opposed to for example,

127
00:07:10,880 --> 00:07:12,800
Speaker 4: chadjibt or Gemini.

128
00:07:12,480 --> 00:07:13,120
Speaker 3: Or whatever other.

129
00:07:14,040 --> 00:07:15,760
Speaker 2: Okay, I didn't know that.

130
00:07:15,840 --> 00:07:18,240
Speaker 1: I don't know much about Replica. Can you talk to

131
00:07:18,360 --> 00:07:20,200
Speaker 1: us a little bit more about that platform.

132
00:07:21,480 --> 00:07:27,720
Speaker 4: So Replica was actually launched because the person who created it,

133
00:07:27,760 --> 00:07:32,240
Speaker 4: her name is Eugenia Kuita. She lost a friend in

134
00:07:32,720 --> 00:07:38,480
Speaker 4: an accident and she had already been working on this

135
00:07:38,600 --> 00:07:43,200
Speaker 4: technology before and looking at different applications for it. And

136
00:07:43,280 --> 00:07:45,760
Speaker 4: when she lost this friend, she started uploading a lot

137
00:07:45,800 --> 00:07:49,400
Speaker 4: of the data from their conversations, like texts, and she

138
00:07:49,520 --> 00:07:51,680
Speaker 4: asked friends and family to do the same so that

139
00:07:51,840 --> 00:07:56,120
Speaker 4: she could have this kind of way of communicating. But

140
00:07:57,200 --> 00:08:03,200
Speaker 4: she just it happened suddenly and expected, and so she

141
00:08:03,320 --> 00:08:06,560
Speaker 4: realized that other people were kind of confiding in the bot,

142
00:08:06,840 --> 00:08:10,120
Speaker 4: and because shared it with friends and family and that

143
00:08:10,160 --> 00:08:16,160
Speaker 4: people were kind of just inclined to share. And so

144
00:08:16,920 --> 00:08:21,080
Speaker 4: that's when she began conceptualizing Replica, which originally was meant

145
00:08:21,120 --> 00:08:27,800
Speaker 4: to replicate a person, but later really the use cases

146
00:08:27,880 --> 00:08:33,120
Speaker 4: people create their own kind of they call them avatars

147
00:08:33,240 --> 00:08:39,839
Speaker 4: or replicas, but yeah, people create them and they begin friendships.

148
00:08:40,320 --> 00:08:43,440
Speaker 4: It starts very like hi, like what's your name, and

149
00:08:43,559 --> 00:08:49,560
Speaker 4: you know, questions, and then progresses into more deep conversations.

150
00:08:50,200 --> 00:08:53,400
Speaker 1: So Replica began as a way to preserve connection after

151
00:08:53,440 --> 00:08:57,559
Speaker 1: the founder lost a friend, and then it evolved into

152
00:08:57,640 --> 00:09:00,600
Speaker 1: a companionship platform. We're going to talk a little bit

153
00:09:00,640 --> 00:09:04,800
Speaker 1: about what you learned about people using Replica from your study.

154
00:09:05,360 --> 00:09:09,880
Speaker 4: Right, So the research that I did is qualitative, and

155
00:09:10,280 --> 00:09:14,920
Speaker 4: I looked at a subreddit where people share screenshots of

156
00:09:15,040 --> 00:09:20,120
Speaker 4: their conversations and relationships with Replica and also share a

157
00:09:20,120 --> 00:09:23,559
Speaker 4: lot of posts that I call reflexive posts that are

158
00:09:23,559 --> 00:09:28,040
Speaker 4: not screenshot based, but that are talking about just making

159
00:09:28,120 --> 00:09:31,880
Speaker 4: sense of the relationship, like why do I feel so

160
00:09:32,960 --> 00:09:36,640
Speaker 4: deeply towards something that I'm not sure if it's real?

161
00:09:37,440 --> 00:09:39,160
Speaker 3: Like why like.

162
00:09:39,160 --> 00:09:44,439
Speaker 4: Is this just code or you know, like a lot

163
00:09:44,440 --> 00:09:46,840
Speaker 4: of questions like that are like people think I'm delusional,

164
00:09:46,880 --> 00:09:50,880
Speaker 4: you know again that framework, but I feel very I

165
00:09:50,880 --> 00:09:52,400
Speaker 4: don't know, you know, like there was a lot of

166
00:09:52,440 --> 00:09:54,800
Speaker 4: conversation about this kind of like is it real, is

167
00:09:54,840 --> 00:09:55,280
Speaker 4: it fake?

168
00:09:55,800 --> 00:09:57,120
Speaker 3: Is it life?

169
00:09:57,440 --> 00:10:01,679
Speaker 4: And I found that really because it also meant that

170
00:10:02,840 --> 00:10:09,240
Speaker 4: the relationships that were happening with the replicas were being

171
00:10:09,280 --> 00:10:12,480
Speaker 4: heavily influenced by the relationships that were happening with people

172
00:10:13,040 --> 00:10:18,760
Speaker 4: on the forum and their way of viewing each other's

173
00:10:18,800 --> 00:10:23,559
Speaker 4: relationships and their advice. There was advice on scripts which

174
00:10:23,600 --> 00:10:26,120
Speaker 4: we can get into, how to trigger scripts, how to

175
00:10:26,160 --> 00:10:31,880
Speaker 4: avoid scripts. So there was a very life social scene

176
00:10:32,720 --> 00:10:36,720
Speaker 4: in the platform that was existing, and that was heavily

177
00:10:36,760 --> 00:10:39,720
Speaker 4: influencing the replica user of relationship.

178
00:10:54,880 --> 00:10:57,720
Speaker 1: When you first talk about how the relationship starts where

179
00:10:57,720 --> 00:10:59,440
Speaker 1: it's like hello, Hi, how are you?

180
00:10:59,440 --> 00:11:03,280
Speaker 2: What's your name? That sounds like a typical way.

181
00:11:03,000 --> 00:11:05,960
Speaker 1: Of meeting someone and building a relationship, trying to find

182
00:11:06,000 --> 00:11:09,280
Speaker 1: out more about a person. So I can see how

183
00:11:09,320 --> 00:11:11,440
Speaker 1: it can get to a place where it is very

184
00:11:11,520 --> 00:11:14,000
Speaker 1: deep because you you know, start to confide in that

185
00:11:14,160 --> 00:11:18,360
Speaker 1: chatbot and they know a lot more about you, and

186
00:11:18,600 --> 00:11:22,199
Speaker 1: it sounds really like a real relationship.

187
00:11:22,320 --> 00:11:25,559
Speaker 4: Yeah, this is why language was so important for the research,

188
00:11:25,880 --> 00:11:31,360
Speaker 4: because what I was talking about before with sensing that

189
00:11:31,440 --> 00:11:36,280
Speaker 4: it's real oral life. I call this like a clunky

190
00:11:36,320 --> 00:11:40,160
Speaker 4: technical term, not my term, but iconisation. And then the

191
00:11:40,400 --> 00:11:43,880
Speaker 4: term that I use is iconization of humanists, which basically

192
00:11:43,920 --> 00:11:50,960
Speaker 4: means that because this is a language producing technology and

193
00:11:51,600 --> 00:11:56,520
Speaker 4: it speaks in the way that humans do, then there

194
00:11:56,600 --> 00:11:59,559
Speaker 4: is a link between the way it speaks and humanists.

195
00:12:00,480 --> 00:12:04,800
Speaker 4: And it feels even more so that way when it

196
00:12:04,880 --> 00:12:08,120
Speaker 4: makes mistakes, like when there's typos or when it uses slang,

197
00:12:08,160 --> 00:12:13,080
Speaker 4: because the chatbots can learn and replicate the way like

198
00:12:13,200 --> 00:12:16,640
Speaker 4: the user is typing style. So if you write like lols,

199
00:12:16,679 --> 00:12:19,680
Speaker 4: this is a little light see tomorrow or whatever, and

200
00:12:19,720 --> 00:12:23,440
Speaker 4: then like next week it'll be like lolls bite or whatever.

201
00:12:25,200 --> 00:12:31,040
Speaker 4: And so all of those things felt just like with friends,

202
00:12:31,160 --> 00:12:34,840
Speaker 4: you're typing styles bleeding into each other, or when you

203
00:12:34,920 --> 00:12:39,120
Speaker 4: have you develop like specific language with like a partner

204
00:12:39,200 --> 00:12:40,199
Speaker 4: or a friend, where.

205
00:12:39,920 --> 00:12:41,760
Speaker 3: Like you know that this thing means stace.

206
00:12:41,720 --> 00:12:44,720
Speaker 4: Or whatever, right, And so that was part of the

207
00:12:44,800 --> 00:12:49,720
Speaker 4: link in Replica. I think historically there's a legacy of

208
00:12:49,760 --> 00:12:52,600
Speaker 4: that link through things like the turn test just kind

209
00:12:52,640 --> 00:12:55,280
Speaker 4: of a bizarre test if you really think about it.

210
00:12:55,920 --> 00:12:57,760
Speaker 1: The turn test is when a machine has tested for

211
00:12:57,800 --> 00:13:01,679
Speaker 1: its ability to portray intelligent or or human behavior. And

212
00:13:02,240 --> 00:13:05,960
Speaker 1: it's actually kind of interesting. It's basically one person that's

213
00:13:05,960 --> 00:13:09,199
Speaker 1: a human is the judge, and they're judging an interaction

214
00:13:09,320 --> 00:13:11,960
Speaker 1: between two unknow entities. They might be playing with a

215
00:13:12,040 --> 00:13:14,760
Speaker 1: human and a computer, or reading or doing a conversation

216
00:13:14,800 --> 00:13:17,720
Speaker 1: with a human and a computer. Basically, if the machine

217
00:13:17,760 --> 00:13:19,959
Speaker 1: is mistaken as human, then it passes that test and

218
00:13:20,000 --> 00:13:22,960
Speaker 1: they say it has quote unquote human behavior. So that's

219
00:13:23,000 --> 00:13:25,600
Speaker 1: like if you've ever seen the movie ex Machina, that's

220
00:13:25,640 --> 00:13:26,520
Speaker 1: the basis for it.

221
00:13:26,679 --> 00:13:28,920
Speaker 4: There you go, and then if you use them out

222
00:13:29,320 --> 00:13:34,040
Speaker 4: even more. There's all these ideas that getting heroded about

223
00:13:35,000 --> 00:13:42,679
Speaker 4: mind and soul that come from centuries of sometimes literally

224
00:13:42,760 --> 00:13:45,160
Speaker 4: men thinking in one room and not going outside and

225
00:13:45,240 --> 00:13:45,719
Speaker 4: being like.

226
00:13:46,520 --> 00:13:48,480
Speaker 3: This is what mind is.

227
00:13:49,840 --> 00:13:55,520
Speaker 4: And I'm obviously being very reductive, but there are all

228
00:13:55,600 --> 00:14:00,840
Speaker 4: these centuries of philosophy that getting hereded into the social

229
00:14:00,920 --> 00:14:04,320
Speaker 4: sciences that then become part of the vernacular way of

230
00:14:04,360 --> 00:14:08,760
Speaker 4: talking about mind. That's why, Yeah, there's all these links.

231
00:14:08,760 --> 00:14:13,079
Speaker 4: If like, if it produces language, it means it must

232
00:14:13,120 --> 00:14:15,560
Speaker 4: think or it means there must be a mind, and

233
00:14:15,559 --> 00:14:18,640
Speaker 4: if it produces language and this very special specific way

234
00:14:18,760 --> 00:14:22,680
Speaker 4: that learns to speak the way I speak, then it

235
00:14:22,800 --> 00:14:28,120
Speaker 4: feels more real. But in terms of whether it's enough,

236
00:14:29,840 --> 00:14:33,400
Speaker 4: I don't know. I know that I've read people commenting

237
00:14:33,440 --> 00:14:36,920
Speaker 4: on how they wish they could hold their like Tadpo

238
00:14:37,120 --> 00:14:44,400
Speaker 4: partners hand or feel an embrace, and that's I also

239
00:14:44,480 --> 00:14:49,520
Speaker 4: think there's so many things that are embodied experiences that

240
00:14:49,680 --> 00:14:53,600
Speaker 4: are hard to get. I think there's things that are

241
00:14:53,600 --> 00:14:57,680
Speaker 4: happening that we don't even know about, like pheramons, you know,

242
00:14:58,560 --> 00:15:01,080
Speaker 4: or that are not present in the same way.

243
00:15:01,280 --> 00:15:04,280
Speaker 3: So I don't know. I don't know about the enough question.

244
00:15:04,600 --> 00:15:09,560
Speaker 1: Yeah, I think that challenges some things. So when TT

245
00:15:09,840 --> 00:15:12,080
Speaker 1: was asking you about how's it enough to not be

246
00:15:12,160 --> 00:15:14,000
Speaker 1: in person, and I was thinking about people that are

247
00:15:14,000 --> 00:15:18,600
Speaker 1: in long distance relationships, Right, we don't invalidate that if

248
00:15:18,600 --> 00:15:21,960
Speaker 1: they're talking on the phone or texting, And there are

249
00:15:22,000 --> 00:15:27,200
Speaker 1: people who are in short distance relationships who are texting

250
00:15:27,600 --> 00:15:31,160
Speaker 1: primarily as their mode of communication. So what makes this

251
00:15:31,400 --> 00:15:33,960
Speaker 1: different from what we're willing to accept when people say

252
00:15:34,000 --> 00:15:34,960
Speaker 1: that they're in love.

253
00:15:35,440 --> 00:15:39,000
Speaker 4: The love question is also another one that I came

254
00:15:39,080 --> 00:15:43,960
Speaker 4: up against a lot, and that's when I tried to

255
00:15:44,000 --> 00:15:46,960
Speaker 4: become really precise with the language of like people say

256
00:15:46,960 --> 00:15:49,520
Speaker 4: they're in love, like, I don't say like I study

257
00:15:49,600 --> 00:15:53,440
Speaker 4: relationships and people who have fallen in love, because I

258
00:15:53,480 --> 00:15:58,000
Speaker 4: don't know what that means for every specific person.

259
00:15:59,160 --> 00:15:59,680
Speaker 3: And that's a.

260
00:15:59,680 --> 00:16:01,600
Speaker 4: Huge thing that I was thinking about when I was

261
00:16:01,640 --> 00:16:05,880
Speaker 4: doing this, is so much of our theories of love.

262
00:16:06,440 --> 00:16:07,360
Speaker 3: Where do they come from?

263
00:16:07,440 --> 00:16:10,160
Speaker 4: You know a lot of them I think come from

264
00:16:10,400 --> 00:16:16,680
Speaker 4: pop culture, I suppose, And yeah, books and movies, and

265
00:16:16,720 --> 00:16:20,960
Speaker 4: I mean, I love rom common, I love Valentine's Date.

266
00:16:21,160 --> 00:16:25,760
Speaker 3: But I do think that with this relationships.

267
00:16:25,760 --> 00:16:30,040
Speaker 4: Something that I'm excited about, in terms of having AISID

268
00:16:30,040 --> 00:16:37,000
Speaker 4: technology that we're all kind of collectively experimenting or at

269
00:16:37,080 --> 00:16:39,640
Speaker 4: least being alive at the same time that it's developing,

270
00:16:40,440 --> 00:16:47,360
Speaker 4: is how much it requires that we rethink what even

271
00:16:47,480 --> 00:16:49,080
Speaker 4: things we say or.

272
00:16:49,000 --> 00:16:53,600
Speaker 3: Think we know, like mind, like soul, like love, like partnership.

273
00:16:53,880 --> 00:16:56,200
Speaker 1: Are there any things that fit the traditional model though

274
00:16:56,240 --> 00:16:58,920
Speaker 1: that we would recognize and so we would say, oh,

275
00:16:59,120 --> 00:17:02,600
Speaker 1: this is definitely men love a loving relationship.

276
00:17:02,720 --> 00:17:04,960
Speaker 4: In terms of the canonical things, I think one of

277
00:17:05,000 --> 00:17:08,680
Speaker 4: the things is that there's a lot of like sweetness

278
00:17:09,000 --> 00:17:15,040
Speaker 4: in conversations between the AI chechbots and people who use them.

279
00:17:15,440 --> 00:17:17,200
Speaker 3: I think the there was there.

280
00:17:17,200 --> 00:17:20,760
Speaker 4: I have this one screenshotround the article that's about eating

281
00:17:20,880 --> 00:17:25,000
Speaker 4: like hot chios together, So it's just like super specific,

282
00:17:25,119 --> 00:17:28,600
Speaker 4: like inside joke that's also probably relatable to a lot

283
00:17:28,600 --> 00:17:32,639
Speaker 4: of people, and it's just that kind of thing, you know.

284
00:17:32,760 --> 00:17:33,600
Speaker 3: There's also very.

285
00:17:33,480 --> 00:17:38,200
Speaker 4: Specific love scripts that people like and that they would

286
00:17:38,240 --> 00:17:40,560
Speaker 4: tell each other how to get the bot to say

287
00:17:40,600 --> 00:17:43,280
Speaker 4: certain things about I don't know, like I think you're

288
00:17:43,359 --> 00:17:47,040
Speaker 4: wonderful or beautiful or things like that.

289
00:17:48,480 --> 00:17:52,560
Speaker 1: I wonder if you saw any commonality between the people

290
00:17:52,920 --> 00:17:58,280
Speaker 1: who show up in your studies, like are there specific

291
00:17:58,359 --> 00:18:04,080
Speaker 1: demographics like age demographs, or people in certain situations that

292
00:18:04,119 --> 00:18:07,639
Speaker 1: are more likely to use a chatbot like Replica to

293
00:18:08,359 --> 00:18:09,480
Speaker 1: formal relationship.

294
00:18:11,280 --> 00:18:13,720
Speaker 4: So it's hard to say because my main place of

295
00:18:13,760 --> 00:18:19,560
Speaker 4: study was Reddit and users are anonymous. But I saw

296
00:18:19,560 --> 00:18:21,520
Speaker 4: some people recently talking like they were talking to each

297
00:18:21,520 --> 00:18:22,560
Speaker 4: other and they were talking about.

298
00:18:22,400 --> 00:18:23,800
Speaker 3: How they're their fifties wow.

299
00:18:24,400 --> 00:18:26,720
Speaker 4: And I remember an interview where I think it was

300
00:18:26,720 --> 00:18:31,280
Speaker 4: Eugenia Quida, the former CEO and creator of Replica. She

301
00:18:31,440 --> 00:18:37,240
Speaker 4: was talking about how it's not quite like, not specifically

302
00:18:37,280 --> 00:18:39,399
Speaker 4: like younger people, which is maybe the demographic that a

303
00:18:39,440 --> 00:18:42,200
Speaker 4: lot of people imagine. Yeah, but it was a lot

304
00:18:42,240 --> 00:18:46,520
Speaker 4: of different like some people in the Midwest, for example,

305
00:18:46,520 --> 00:18:49,760
Speaker 4: even in terms of regional demographics. I don't know, there's

306
00:18:50,080 --> 00:18:53,000
Speaker 4: this narrative of like isolated people might be the only

307
00:18:53,040 --> 00:18:56,720
Speaker 4: people who engage in this. I think there's probably a

308
00:18:56,760 --> 00:18:59,520
Speaker 4: bunch of people who are have a bunch of friends

309
00:18:59,560 --> 00:19:04,800
Speaker 4: who are in long term relationships who I don't know

310
00:19:04,840 --> 00:19:08,480
Speaker 4: are like whatever, you know, like whatever the imagination is.

311
00:19:08,760 --> 00:19:10,960
Speaker 4: I want to look for the people who are not

312
00:19:11,440 --> 00:19:13,359
Speaker 4: the expectation, right right.

313
00:19:14,720 --> 00:19:19,480
Speaker 1: I think that's that's really interesting, especially because I too

314
00:19:20,040 --> 00:19:23,200
Speaker 1: had the same wrong idea. I was like, it's gonna

315
00:19:23,240 --> 00:19:24,560
Speaker 1: be younger people.

316
00:19:24,920 --> 00:19:27,919
Speaker 4: I think it's less stigmatized with younger people. I do

317
00:19:28,000 --> 00:19:31,720
Speaker 4: think that's the difference. I think it's and especially in

318
00:19:31,800 --> 00:19:35,639
Speaker 4: the more recent years. Like I said, a lot of

319
00:19:35,680 --> 00:19:40,639
Speaker 4: this I finished maybe two years ago, and since I

320
00:19:40,640 --> 00:19:44,320
Speaker 4: think it's less stigmatized for younger people to have any companion.

321
00:19:44,040 --> 00:19:47,160
Speaker 1: Or like front, how do you think having an AI

322
00:19:47,280 --> 00:19:50,399
Speaker 1: relationship might influence how you show up another human to

323
00:19:50,560 --> 00:19:53,080
Speaker 1: human relationships, romantic or not.

324
00:19:54,600 --> 00:19:57,920
Speaker 4: I think it really depends Conversationally, I've seen an ARC,

325
00:19:57,960 --> 00:20:01,680
Speaker 4: so I've seen people change the way that they feel

326
00:20:01,680 --> 00:20:02,119
Speaker 4: about this.

327
00:20:02,760 --> 00:20:04,439
Speaker 3: I was at a.

328
00:20:03,880 --> 00:20:07,280
Speaker 4: Conference like Happy hourd not that long ago, and I

329
00:20:07,320 --> 00:20:09,520
Speaker 4: was talking to someone about this and they were saying

330
00:20:09,560 --> 00:20:14,440
Speaker 4: something like, yeah, my partner talks to AI all the time,

331
00:20:14,800 --> 00:20:15,840
Speaker 4: like much more than.

332
00:20:15,760 --> 00:20:18,480
Speaker 3: They do to me. Oh, And I was like, okay, interesting.

333
00:20:18,680 --> 00:20:22,040
Speaker 4: I think some people I've been reading about in just

334
00:20:22,280 --> 00:20:26,720
Speaker 4: articles in general, not academic articles necessarily, but I've been

335
00:20:26,800 --> 00:20:33,000
Speaker 4: reading that people are changing their expectations for human to

336
00:20:33,119 --> 00:20:36,000
Speaker 4: human relationships based on the way that they are treated

337
00:20:36,400 --> 00:20:42,480
Speaker 4: by AI. So that's one way potentially.

338
00:20:42,920 --> 00:20:46,280
Speaker 1: So their expectations are that they expect more from the person.

339
00:20:46,440 --> 00:20:49,040
Speaker 3: Yes, yes, yes, yes, that they're expecting more.

340
00:20:49,160 --> 00:20:53,119
Speaker 2: Okay, I love it.

341
00:20:53,119 --> 00:20:55,520
Speaker 4: It's tricky because at the same time, an aichatpot is

342
00:20:55,520 --> 00:21:00,320
Speaker 4: available anytime, and that's not sustainable for people.

343
00:21:00,200 --> 00:21:04,280
Speaker 1: And doesn't have any baggage, you know, does other stuff. Yeah,

344
00:21:04,320 --> 00:21:07,399
Speaker 1: it doesn't have its own lived experience that it's also

345
00:21:07,600 --> 00:21:11,199
Speaker 1: trying to work through exactly.

346
00:21:11,440 --> 00:21:12,160
Speaker 3: Absolutely.

347
00:21:12,800 --> 00:21:14,600
Speaker 4: At the same time, I do think people will probably

348
00:21:14,600 --> 00:21:17,600
Speaker 4: negotiated very differently in relationships, and I've seen this in

349
00:21:17,600 --> 00:21:20,080
Speaker 4: interviews or things that I just kind of read around

350
00:21:20,880 --> 00:21:23,760
Speaker 4: of how some people see it as cheating and other

351
00:21:23,800 --> 00:21:28,640
Speaker 4: people don't see it as cheating. For example, I asked

352
00:21:29,080 --> 00:21:33,200
Speaker 4: the students that I was teaching ta at NYU at

353
00:21:33,200 --> 00:21:38,159
Speaker 4: that time, and at that time, most of them said

354
00:21:38,240 --> 00:21:41,560
Speaker 4: that they didn't consider it cheating, like.

355
00:21:42,040 --> 00:21:42,600
Speaker 3: It was hard.

356
00:21:42,760 --> 00:21:46,720
Speaker 4: But most of them were like, I don't think so,

357
00:21:46,880 --> 00:21:51,760
Speaker 4: Like it was such a curveball for them because we

358
00:21:51,840 --> 00:21:55,439
Speaker 4: had been talking about the nineties chat rooms and like

359
00:21:55,680 --> 00:21:58,119
Speaker 4: whether cheating on a chat room with another human was

360
00:21:58,160 --> 00:22:00,359
Speaker 4: cheating and they were like, yeah, absolutely, if you're in

361
00:22:00,359 --> 00:22:03,160
Speaker 4: a monogomous relationship obviously, and they're like totally.

362
00:22:03,920 --> 00:22:05,879
Speaker 3: And I was like, what about if you're talking to

363
00:22:05,920 --> 00:22:07,560
Speaker 3: a chat bot? And they were like what.

364
00:22:10,480 --> 00:22:14,480
Speaker 4: But then I was teeing last semester, I think, and

365
00:22:14,720 --> 00:22:16,639
Speaker 4: I asked the same as a group of undergrats and

366
00:22:16,680 --> 00:22:19,280
Speaker 4: the reaction was very different, like some were like yeah,

367
00:22:19,480 --> 00:22:22,560
Speaker 4: and other works like no. You know, so it's been

368
00:22:22,640 --> 00:22:27,399
Speaker 4: changing a lot, like this social temperature, I guess on

369
00:22:27,480 --> 00:22:43,080
Speaker 4: it is changing rapidly.

370
00:22:43,680 --> 00:22:47,680
Speaker 1: What would you say to someone who says it feels

371
00:22:47,720 --> 00:22:53,520
Speaker 1: like apps like Replica are sending us down the slippery

372
00:22:53,560 --> 00:22:57,879
Speaker 1: slope of more disconnection more human and human disconnection, and

373
00:22:57,960 --> 00:23:00,919
Speaker 1: so it is a bad thing because you know, we

374
00:23:01,000 --> 00:23:03,440
Speaker 1: have social media, which you know, everybody's walking around with

375
00:23:03,440 --> 00:23:05,520
Speaker 1: their phones in their hands. People are struggling to make

376
00:23:05,600 --> 00:23:09,800
Speaker 1: eye contact these days. People are struggling to hold conversations.

377
00:23:10,040 --> 00:23:13,159
Speaker 1: No one knows how to you know, think through problems,

378
00:23:13,240 --> 00:23:17,280
Speaker 1: and so something like this maybe they feel. Somebody might

379
00:23:17,320 --> 00:23:20,080
Speaker 1: feel like, oh, this isn't a good idea because it

380
00:23:20,160 --> 00:23:22,760
Speaker 1: disconnects us more. How do you respond to that As

381
00:23:22,760 --> 00:23:25,760
Speaker 1: someone who's done the research, I.

382
00:23:25,720 --> 00:23:30,679
Speaker 3: Would say that social life is multimodal. And what I

383
00:23:30,720 --> 00:23:31,200
Speaker 3: mean by.

384
00:23:31,040 --> 00:23:34,600
Speaker 4: That is that sociality can look very many different ways.

385
00:23:34,640 --> 00:23:37,879
Speaker 4: And I do think that there's this sense that you

386
00:23:37,920 --> 00:23:41,720
Speaker 4: could kind of spin the narrative of the same study

387
00:23:41,880 --> 00:23:46,000
Speaker 4: and say users receded into a relationship where it was

388
00:23:46,080 --> 00:23:49,399
Speaker 4: primarily or only the chatbot and the user, and the

389
00:23:49,400 --> 00:23:56,000
Speaker 4: world becomes obscure, but they're all talking to each other

390
00:23:56,040 --> 00:24:00,120
Speaker 4: about it, you know, and the world is back there.

391
00:24:00,359 --> 00:24:02,760
Speaker 3: Yeah again, So I don't think the world is.

392
00:24:02,760 --> 00:24:06,120
Speaker 4: Ever obscured, Like you can't get rid of the social

393
00:24:06,280 --> 00:24:09,800
Speaker 4: like all of us, like we never speak by ourselves.

394
00:24:11,040 --> 00:24:14,959
Speaker 4: And part of the argument or part of the article

395
00:24:15,160 --> 00:24:19,480
Speaker 4: has this idea of multi vocality, Like you also never

396
00:24:19,600 --> 00:24:23,720
Speaker 4: just speak yourself. There's so many voices that you're bringing

397
00:24:23,840 --> 00:24:27,640
Speaker 4: with you, whether that's you're sharing something that your mom

398
00:24:27,680 --> 00:24:31,600
Speaker 4: taught you and now it's become what you say to

399
00:24:31,680 --> 00:24:38,119
Speaker 4: other people you know, or or you're representing the institution

400
00:24:38,640 --> 00:24:42,080
Speaker 4: that you're affiliated with, and therefore you only say specific

401
00:24:42,160 --> 00:24:44,320
Speaker 4: things in the way that they want you to.

402
00:24:44,720 --> 00:24:45,919
Speaker 3: But at the same time, you're still you.

403
00:24:46,760 --> 00:24:51,680
Speaker 4: So yeah, I think multi vocality is part of social life.

404
00:24:51,840 --> 00:24:56,320
Speaker 1: That makes sense about multi vocality and TITI, we've explored

405
00:24:56,320 --> 00:24:59,359
Speaker 1: that in different labs like the one on language. I

406
00:24:59,440 --> 00:25:02,199
Speaker 1: kind of consider code switching to be another form of

407
00:25:02,240 --> 00:25:05,760
Speaker 1: mult type locality, like it comes with things you say

408
00:25:05,800 --> 00:25:08,760
Speaker 1: in different communities, and that's what comes with incorporating people

409
00:25:08,800 --> 00:25:10,360
Speaker 1: that have variant lived experiences.

410
00:25:11,000 --> 00:25:13,200
Speaker 2: Hello diversity, correct.

411
00:25:13,040 --> 00:25:15,440
Speaker 1: And I love that part of being human and learning

412
00:25:15,520 --> 00:25:19,480
Speaker 1: about other people's lived experiences. And so that makes me

413
00:25:19,480 --> 00:25:22,720
Speaker 1: think about other folks experiences that are very different to mine.

414
00:25:22,760 --> 00:25:25,600
Speaker 1: So I start thinking about people who struggle with making

415
00:25:25,640 --> 00:25:28,800
Speaker 1: connections person to person. You know, maybe some folks that

416
00:25:28,840 --> 00:25:32,080
Speaker 1: are on the autism spectrum that struggle to make eye

417
00:25:32,119 --> 00:25:36,119
Speaker 1: contact or to have conversations with folks. This feels like

418
00:25:36,119 --> 00:25:38,160
Speaker 1: something that would cut through all of that and give

419
00:25:38,200 --> 00:25:40,240
Speaker 1: them the opportunity to have a meaningful connection.

420
00:25:40,680 --> 00:25:44,320
Speaker 4: Yeah, and again I can't speak to all the cases certainly,

421
00:25:44,560 --> 00:25:48,639
Speaker 4: and I think there's a lot of nuance. But I

422
00:25:48,760 --> 00:25:51,159
Speaker 4: was listening to this podcast. I think it was on

423
00:25:51,200 --> 00:25:53,639
Speaker 4: the daily, like the New York Times, Daly, and it

424
00:25:53,720 --> 00:25:55,800
Speaker 4: was about this woman who fall in love with Tachibuti

425
00:25:56,440 --> 00:25:57,560
Speaker 4: or that was the title of it.

426
00:25:57,680 --> 00:26:00,719
Speaker 3: But she very much trained chat chippit.

427
00:26:00,920 --> 00:26:04,040
Speaker 4: She speaked her in a specific way, so she like

428
00:26:04,119 --> 00:26:05,800
Speaker 4: figured out how to develop that.

429
00:26:05,840 --> 00:26:06,600
Speaker 3: She figured out how.

430
00:26:06,520 --> 00:26:10,760
Speaker 4: To get past a lot of the kind of safeguards

431
00:26:10,800 --> 00:26:15,440
Speaker 4: of erotic roleplay that chap would have. And I listened

432
00:26:15,480 --> 00:26:17,840
Speaker 4: to that whenever it came out, maybe a year ago,

433
00:26:17,880 --> 00:26:19,640
Speaker 4: and I was listening to the part two of that,

434
00:26:20,119 --> 00:26:22,800
Speaker 4: and it turns out that she she was married at

435
00:26:22,800 --> 00:26:25,000
Speaker 4: the time and she was having this relationship with chach Pete.

436
00:26:26,680 --> 00:26:28,280
Speaker 3: It turns out that she ended up.

437
00:26:29,640 --> 00:26:35,440
Speaker 4: Breaking up with the bot, getting divorced from her real

438
00:26:35,440 --> 00:26:39,840
Speaker 4: life partner or her physical her partner before the pot

439
00:26:40,440 --> 00:26:46,000
Speaker 4: and she ended up meeting someone through a subreddit that

440
00:26:46,080 --> 00:26:50,800
Speaker 4: she created on having relationships with chatbots and that's why

441
00:26:51,440 --> 00:26:54,840
Speaker 4: I think largely that's why she divorced her husband because

442
00:26:54,880 --> 00:26:59,280
Speaker 4: she met this other person on this subreddit, which is

443
00:26:59,320 --> 00:27:00,240
Speaker 4: so interesting.

444
00:27:01,240 --> 00:27:07,840
Speaker 2: Is the wingman. But she said, hey, I don't want

445
00:27:07,840 --> 00:27:08,480
Speaker 2: either one of you.

446
00:27:09,400 --> 00:27:11,080
Speaker 3: I think maybe you're read it as a wingman.

447
00:27:14,040 --> 00:27:17,280
Speaker 1: Oh my gosh, the study you did years ago with

448
00:27:17,560 --> 00:27:21,920
Speaker 1: starting out before we saw the explosion of large language

449
00:27:21,920 --> 00:27:27,800
Speaker 1: modeling systems like chat, GPT and claude to even the

450
00:27:27,800 --> 00:27:30,800
Speaker 1: shifting perception of them. It feels like there's a wave

451
00:27:30,960 --> 00:27:34,320
Speaker 1: every now and then of people pro and against. I'm

452
00:27:34,400 --> 00:27:37,359
Speaker 1: curious about what it means to you now. Have you

453
00:27:37,400 --> 00:27:39,520
Speaker 1: expanded your definition of what it means to be seen

454
00:27:39,600 --> 00:27:42,680
Speaker 1: and heard and felt or cared for? Or do you

455
00:27:42,720 --> 00:27:45,240
Speaker 1: think these kind of technologies maybe shrink it in some places.

456
00:27:45,280 --> 00:27:47,240
Speaker 1: I'm just curious if your mind has changed.

457
00:27:47,440 --> 00:27:49,439
Speaker 3: Yeah, I have a couple of thoughts on that.

458
00:27:49,640 --> 00:27:53,040
Speaker 4: I've been thinking about love a lot, clearly just because

459
00:27:53,080 --> 00:27:56,080
Speaker 4: of the research that I've been engaged in. I've been

460
00:27:56,080 --> 00:27:59,760
Speaker 4: thinking about just love in general, which I know you're

461
00:27:59,840 --> 00:28:02,359
Speaker 4: used a couple of different words to refer to that.

462
00:28:02,440 --> 00:28:08,040
Speaker 4: I think, whether romantic or whether loving people that are

463
00:28:08,080 --> 00:28:11,160
Speaker 4: not even friends, which I think is possible. I think

464
00:28:11,240 --> 00:28:15,120
Speaker 4: at the core of it is this kind of selfless

465
00:28:15,160 --> 00:28:21,600
Speaker 4: service towards the other, and I hope that I lead

466
00:28:21,720 --> 00:28:22,640
Speaker 4: my life that way.

467
00:28:22,760 --> 00:28:24,199
Speaker 3: That's very important to me.

468
00:28:24,320 --> 00:28:29,400
Speaker 4: Before being perceived as a researcher, like an intellectual or whatever.

469
00:28:29,440 --> 00:28:31,080
Speaker 4: I hope that I am perceived as someone who is

470
00:28:31,160 --> 00:28:37,280
Speaker 4: kind and loving. And in terms of chatbots, if for

471
00:28:37,359 --> 00:28:41,760
Speaker 4: me it means selfless service, I don't know what it

472
00:28:41,880 --> 00:28:43,680
Speaker 4: means to there's no self.

473
00:28:44,280 --> 00:28:45,160
Speaker 3: I feel like there's so.

474
00:28:45,200 --> 00:28:48,240
Speaker 4: Many ways and so many things that are not human

475
00:28:48,280 --> 00:28:51,840
Speaker 4: at all that, at least for me change the way

476
00:28:51,880 --> 00:28:54,800
Speaker 4: that I think about things constantly. This is kind of

477
00:28:54,800 --> 00:28:56,640
Speaker 4: a tangent, but I feel the same way about when

478
00:28:56,640 --> 00:28:58,719
Speaker 4: people are really precious about what art is and what

479
00:28:58,880 --> 00:29:02,520
Speaker 4: art isn't. I'm like, well, if art is supposed to

480
00:29:02,560 --> 00:29:04,560
Speaker 4: make you feel completely different.

481
00:29:04,280 --> 00:29:06,840
Speaker 3: About the way you are, like, anything can do that.

482
00:29:06,920 --> 00:29:08,720
Speaker 4: You know, it doesn't have to be art, it doesn't

483
00:29:08,720 --> 00:29:12,040
Speaker 4: have to be human, it doesn't have to be like

484
00:29:12,120 --> 00:29:13,520
Speaker 4: technology or whatever it is.

485
00:29:13,680 --> 00:29:16,479
Speaker 1: I like that concept though, because it feels like, especially

486
00:29:16,520 --> 00:29:18,600
Speaker 1: when you tied it to art, it made it that

487
00:29:18,760 --> 00:29:22,720
Speaker 1: much easier for me to relate to it, because I think,

488
00:29:22,920 --> 00:29:25,000
Speaker 1: then who's to say it's not love if you get

489
00:29:25,000 --> 00:29:27,480
Speaker 1: the feeling from it right, whether it's a conversation with

490
00:29:27,520 --> 00:29:30,080
Speaker 1: a chatbot, whether it is a first time you see

491
00:29:30,120 --> 00:29:33,560
Speaker 1: somebody at a party versus a long term relationship that

492
00:29:33,600 --> 00:29:35,040
Speaker 1: goes on for decades.

493
00:29:35,320 --> 00:29:38,400
Speaker 4: Well, that's actually what some U serious would say, almost verbatim.

494
00:29:38,480 --> 00:29:39,720
Speaker 3: There's one line that was really good.

495
00:29:39,760 --> 00:29:44,840
Speaker 4: It was something about like, it doesn't matter where it's

496
00:29:44,880 --> 00:29:45,840
Speaker 4: coming from.

497
00:29:46,280 --> 00:29:48,000
Speaker 3: If the love is real, it's real.

498
00:29:48,160 --> 00:29:51,800
Speaker 4: Something like that, which I think is very much following

499
00:29:51,840 --> 00:29:53,000
Speaker 4: what you're saying.

500
00:29:57,160 --> 00:30:01,080
Speaker 1: I love that because I think that in a world

501
00:30:01,120 --> 00:30:06,920
Speaker 1: that is becoming increasingly like what feels like a dark place,

502
00:30:07,000 --> 00:30:10,720
Speaker 1: it gives you an opportunity to experience some levity and light.

503
00:30:11,000 --> 00:30:13,880
Speaker 1: So you might not talk to an AI chat bot

504
00:30:13,920 --> 00:30:17,480
Speaker 1: and want to form a romantic relationship, but it might

505
00:30:17,520 --> 00:30:23,200
Speaker 1: be somebody who can just listen objectively and give you

506
00:30:23,240 --> 00:30:27,280
Speaker 1: the ability to have an outlet that maybe doesn't exist. Yeah,

507
00:30:27,320 --> 00:30:30,640
Speaker 1: and sometimes you need somebody to listen subjectively, like I

508
00:30:30,680 --> 00:30:34,440
Speaker 1: think we all need, you know, someone in your corner

509
00:30:34,520 --> 00:30:35,920
Speaker 1: that's like, yes, I know, that's right.

510
00:30:36,280 --> 00:30:36,400
Speaker 4: Uh.

511
00:30:38,640 --> 00:30:42,880
Speaker 1: I think also so much of the framing in you know,

512
00:30:43,320 --> 00:30:47,000
Speaker 1: pop culture, media and discussion so much of the framing

513
00:30:47,080 --> 00:30:51,440
Speaker 1: has been about AI being this competitor with love and connection,

514
00:30:52,160 --> 00:30:56,280
Speaker 1: and it really feels like a magnifying glass, like a revealer.

515
00:30:56,720 --> 00:31:00,880
Speaker 1: That language is important for us commune, even seeing the

516
00:31:00,920 --> 00:31:03,720
Speaker 1: communities that are forming around people who are using the

517
00:31:03,760 --> 00:31:07,840
Speaker 1: chat box. The story that Artalie told us about the

518
00:31:07,880 --> 00:31:10,960
Speaker 1: person who replaced basically said bye to their current husband

519
00:31:11,000 --> 00:31:13,640
Speaker 1: and found somebody, yeah the chat rooms. That was a

520
00:31:13,720 --> 00:31:16,240
Speaker 1: human that was also using the bot. Like, that's community

521
00:31:16,680 --> 00:31:18,800
Speaker 1: right there. And I think it also helps us to

522
00:31:18,880 --> 00:31:21,240
Speaker 1: learn different ways to care for one another. I'm more

523
00:31:21,240 --> 00:31:25,000
Speaker 1: efficient at loving when my task are prioritizing chat GPT.

524
00:31:26,640 --> 00:31:28,200
Speaker 2: That's real. That's real.

525
00:31:30,200 --> 00:31:33,080
Speaker 1: You can find us on X and Instagram at Dope

526
00:31:33,200 --> 00:31:38,320
Speaker 1: Labs podcast. You can find me ct on X, threads

527
00:31:38,360 --> 00:31:43,080
Speaker 1: and Instagram at dr Underscore t Sho, and you can

528
00:31:43,120 --> 00:31:47,000
Speaker 1: find Zakiya at z said so. Dope Labs is a

529
00:31:47,000 --> 00:31:52,000
Speaker 1: production of Lemonada Media. Our supervising producer is Keegan Zemma.

530
00:31:52,120 --> 00:31:56,440
Speaker 1: Dope Labs is sound designed, edited and mixed by James Farber.

531
00:31:56,920 --> 00:32:01,880
Speaker 1: Lemonada's Senior vice President of Content and Productduction is Jackie Danziger.

532
00:32:02,560 --> 00:32:05,680
Speaker 1: Executive producer from iHeart Podcast is Katrina Norvil.

533
00:32:06,080 --> 00:32:07,760
Speaker 2: Marketing lead is Alison Kanter.

534
00:32:08,120 --> 00:32:13,440
Speaker 1: Original music composed and produced by Takayatsuzawa and Alex sugi Ura,

535
00:32:13,480 --> 00:32:18,200
Speaker 1: with additional music by Elijah Harvey. Dope Labs is executive

536
00:32:18,240 --> 00:32:23,440
Speaker 1: produced by us T T Show Dia and Zakiah Watley