1 00:00:00,200 --> 00:00:02,400 Speaker 1: Hey, please take a second and leave us a review 2 00:00:02,480 --> 00:00:06,279 Speaker 1: on Apple Podcasts, Spotify, or wherever you listen to the podcast. 3 00:00:06,960 --> 00:00:11,360 Speaker 1: Thanks a lot. Hey, welcome to Sign Stuff, a production 4 00:00:11,480 --> 00:00:14,680 Speaker 1: of iHeartRadio I'm More Cham and today we're answering the 5 00:00:14,760 --> 00:00:18,800 Speaker 1: question can we communicate with animals? Can you have an 6 00:00:18,840 --> 00:00:22,400 Speaker 1: actual conversation with your cat or a real dialogue with 7 00:00:22,520 --> 00:00:25,959 Speaker 1: your dog? And could we use AI to talk to 8 00:00:26,040 --> 00:00:30,040 Speaker 1: whales and elephants. We're going to talk to the woman 9 00:00:30,080 --> 00:00:33,640 Speaker 1: who started the worldwide movement to teach pats to talk, 10 00:00:33,880 --> 00:00:36,640 Speaker 1: and we're going to talk to an animal cognitive scientist 11 00:00:36,840 --> 00:00:40,640 Speaker 1: about what we know about animal communication. So get ready 12 00:00:40,680 --> 00:00:43,800 Speaker 1: to chat with jihuahua's and gap with gibbons as we 13 00:00:43,880 --> 00:00:47,160 Speaker 1: answer the question can we communicate with animals? 14 00:00:52,440 --> 00:00:52,640 Speaker 2: Hey? 15 00:00:52,640 --> 00:00:56,280 Speaker 1: Everyone, So I'm not a conspiracy theorist, but recently I 16 00:00:56,400 --> 00:01:00,200 Speaker 1: learned there's a worldwide movement to teach pets to talk. 17 00:01:00,000 --> 00:01:03,240 Speaker 1: Tens of thousands of people around the world are teaching 18 00:01:03,280 --> 00:01:06,480 Speaker 1: their cats and dogs and rabbits and even lizards to 19 00:01:06,560 --> 00:01:10,039 Speaker 1: use words and even put together sentences. And once you 20 00:01:10,120 --> 00:01:12,600 Speaker 1: learn what some of these animals have to say, I 21 00:01:12,640 --> 00:01:14,840 Speaker 1: think you're going to be surprised. So We're going to 22 00:01:14,880 --> 00:01:17,600 Speaker 1: talk to two people today. One is the woman who 23 00:01:17,640 --> 00:01:21,400 Speaker 1: started this worldwide movement, and the other is a Conicis 24 00:01:21,480 --> 00:01:25,039 Speaker 1: scientist who's been researching this phenomenon. Will start with the 25 00:01:25,080 --> 00:01:28,800 Speaker 1: founder of the movement, Christina Hunger. Miss Hunger was a 26 00:01:28,840 --> 00:01:32,399 Speaker 1: speech therapist who worked with kids when she wondered one day, 27 00:01:32,640 --> 00:01:35,600 Speaker 1: what if I helped my dog to speak. Here's my 28 00:01:35,640 --> 00:01:40,480 Speaker 1: interview with Christina Hunger. Well, thank you for joining us, 29 00:01:40,520 --> 00:01:41,119 Speaker 1: Miss Hunger. 30 00:01:41,319 --> 00:01:43,880 Speaker 3: Yes, thank you for having me. My name is Christina Hunger. 31 00:01:43,959 --> 00:01:46,800 Speaker 3: I'm a speech language pathologist and I'm the founder of 32 00:01:46,880 --> 00:01:50,000 Speaker 3: Hunger for Words, which is the whole talking pet movement. 33 00:01:50,640 --> 00:01:54,160 Speaker 1: Amazing. Can you describe what Hunger for Words and the 34 00:01:54,200 --> 00:01:55,480 Speaker 1: Talking Pet movement are? 35 00:01:55,720 --> 00:01:58,920 Speaker 3: Yes. So, as a speech therapist, I worked with kids, 36 00:01:58,960 --> 00:02:01,520 Speaker 3: and in my jobularly, I worked with a lot of 37 00:02:01,600 --> 00:02:05,160 Speaker 3: kids who had different disabilities and disorders and couldn't actually 38 00:02:05,200 --> 00:02:09,320 Speaker 3: talk with verbal speech. They used communication devices instead, and 39 00:02:09,400 --> 00:02:12,720 Speaker 3: so that really inspired everything that I discovered that dogs 40 00:02:12,720 --> 00:02:13,400 Speaker 3: were capable of. 41 00:02:13,919 --> 00:02:17,240 Speaker 1: What did you know about animal communication before you had 42 00:02:17,360 --> 00:02:18,440 Speaker 1: this idea? 43 00:02:18,680 --> 00:02:21,799 Speaker 3: Very little? And I think that's why I was able 44 00:02:21,919 --> 00:02:24,920 Speaker 3: to see this from a new perspective. I knew that 45 00:02:25,000 --> 00:02:28,120 Speaker 3: dogs understood words because I had a dog growing up. 46 00:02:28,240 --> 00:02:31,600 Speaker 3: But then once I brought my puppy Stella home, I 47 00:02:31,680 --> 00:02:34,200 Speaker 3: was really observing her from this new perspective as a 48 00:02:34,240 --> 00:02:37,480 Speaker 3: speech therapist and saw how quickly she was picking up 49 00:02:37,480 --> 00:02:38,600 Speaker 3: on the words we were saying. 50 00:02:38,880 --> 00:02:41,000 Speaker 1: I guess you mean like if you tell a dog 51 00:02:41,120 --> 00:02:44,040 Speaker 1: sit or a rollover, or would you like to go 52 00:02:44,120 --> 00:02:45,880 Speaker 1: for a walk, and they get excited, then you have 53 00:02:45,960 --> 00:02:48,000 Speaker 1: the sense that they understand you exactly. 54 00:02:48,120 --> 00:02:50,840 Speaker 3: And so I knew that these associations were possible, but 55 00:02:50,919 --> 00:02:54,400 Speaker 3: I didn't know how much dogs were capable of understanding. 56 00:02:54,440 --> 00:02:57,160 Speaker 3: I just knew that something was there now. 57 00:02:57,200 --> 00:02:59,799 Speaker 1: In her work as a speech therapist, because Hunger work 58 00:03:00,120 --> 00:03:03,680 Speaker 1: kids with disabilities who were non verbal or couldn't talk, 59 00:03:03,880 --> 00:03:06,400 Speaker 1: and she would often use devices that the kids would 60 00:03:06,440 --> 00:03:08,920 Speaker 1: press a button on or have a screen on to 61 00:03:09,000 --> 00:03:13,560 Speaker 1: say words. And this gave her an idea, did you 62 00:03:13,760 --> 00:03:16,639 Speaker 1: explicitly think to yourself, huh, I wonder what would happen 63 00:03:16,760 --> 00:03:20,120 Speaker 1: if I tried to teach my dog more words using 64 00:03:20,120 --> 00:03:20,920 Speaker 1: these devices. 65 00:03:21,000 --> 00:03:24,280 Speaker 3: I had this very clear epiphany moment where I was 66 00:03:24,320 --> 00:03:28,000 Speaker 3: watching my puppy Stella, seeing how she was understanding words. 67 00:03:28,080 --> 00:03:31,120 Speaker 3: I was knowing you know, remembering that dog's understand words. 68 00:03:31,160 --> 00:03:34,240 Speaker 3: And I was also watching how she was already communicating. 69 00:03:34,440 --> 00:03:37,400 Speaker 3: She would bark at me to get attention. She would 70 00:03:37,440 --> 00:03:39,800 Speaker 3: pot her water dish and it was empty, and I 71 00:03:39,880 --> 00:03:42,240 Speaker 3: was like, she's doing so many things that kids do 72 00:03:42,440 --> 00:03:44,960 Speaker 3: right before they start talking. I was like, I was 73 00:03:45,200 --> 00:03:47,640 Speaker 3: in a speech therapy session right now, I would be saying, 74 00:03:47,760 --> 00:03:50,240 Speaker 3: they're probably going to start talking soon. So I had 75 00:03:50,280 --> 00:03:54,280 Speaker 3: this light bulb moment. If dogs understand words, they just 76 00:03:54,320 --> 00:03:56,680 Speaker 3: need a different way to say words, like, could I 77 00:03:56,800 --> 00:03:59,720 Speaker 3: make a device for Stella and teach her to say 78 00:03:59,720 --> 00:04:01,880 Speaker 3: words if she had a way to say them? And 79 00:04:01,920 --> 00:04:02,840 Speaker 3: that's where it all started. 80 00:04:04,080 --> 00:04:06,320 Speaker 1: Now did you actually make a device or did you so? 81 00:04:06,440 --> 00:04:09,600 Speaker 3: My first thought was could I use something that already 82 00:04:09,600 --> 00:04:12,080 Speaker 3: exists that I use with kids. Most of the devices 83 00:04:12,160 --> 00:04:15,280 Speaker 3: kids would use their fingers to tap a very small icon, 84 00:04:15,440 --> 00:04:17,640 Speaker 3: like on an iPad or a tablet, but I thought 85 00:04:17,640 --> 00:04:20,320 Speaker 3: that would be too tricky with her paw and her nose. 86 00:04:20,480 --> 00:04:23,640 Speaker 3: So then I found just some simple, recordable buttons and 87 00:04:23,680 --> 00:04:26,600 Speaker 3: then adapted them eventually and put them all together on 88 00:04:26,600 --> 00:04:29,840 Speaker 3: one big board for her, which was then her communication device. 89 00:04:29,960 --> 00:04:32,480 Speaker 3: So I wanted, like the easiest way to test it out. 90 00:04:32,800 --> 00:04:35,680 Speaker 1: Whoah, you didn't think like I need an iPad the 91 00:04:35,760 --> 00:04:39,240 Speaker 1: size of a table. Her Stella just made me think 92 00:04:39,279 --> 00:04:40,839 Speaker 1: of what would happen if you give a dog a 93 00:04:40,880 --> 00:04:45,000 Speaker 1: phone and the internet? Yeah, right, look up treats all 94 00:04:45,000 --> 00:04:45,320 Speaker 1: the time. 95 00:04:45,480 --> 00:04:47,800 Speaker 3: Yeah, really different parks that they want to go to. 96 00:04:49,360 --> 00:04:52,640 Speaker 1: So Miss Hunger basically gave her puppy Stella a giant 97 00:04:52,800 --> 00:04:57,200 Speaker 1: keyboard had big colored buttons that, when press would say 98 00:04:57,200 --> 00:05:02,400 Speaker 1: a pre recorded word like water or walk. Okay, so 99 00:05:02,400 --> 00:05:04,200 Speaker 1: you got the system, you put it in your house 100 00:05:04,279 --> 00:05:06,479 Speaker 1: for Stella, and then what happened? How did you get started? 101 00:05:06,640 --> 00:05:06,760 Speaker 2: So? 102 00:05:06,960 --> 00:05:09,320 Speaker 3: I started just with a few words. At first, I 103 00:05:09,400 --> 00:05:11,640 Speaker 3: just thought like could I teach her to say a 104 00:05:11,680 --> 00:05:15,200 Speaker 3: few different words to maybe express like some needs that 105 00:05:15,240 --> 00:05:19,920 Speaker 3: she has. So I started with outside, play, water, and 106 00:05:19,960 --> 00:05:23,000 Speaker 3: then eventually I added like eat and walk. And for 107 00:05:23,279 --> 00:05:25,640 Speaker 3: about a month I did the same thing that I 108 00:05:25,640 --> 00:05:28,080 Speaker 3: would do with kids every day. I just used the 109 00:05:28,120 --> 00:05:31,560 Speaker 3: buttons as I was talking. So whenever I was saying outside, 110 00:05:31,600 --> 00:05:34,000 Speaker 3: I would push the button, show her which one it was, 111 00:05:34,600 --> 00:05:37,039 Speaker 3: also say it with my verbal speech, and then take 112 00:05:37,040 --> 00:05:40,359 Speaker 3: her outside. And it did not work right away. It 113 00:05:40,400 --> 00:05:43,640 Speaker 3: took a good month before she started using the buttons 114 00:05:43,680 --> 00:05:45,360 Speaker 3: and really was even interested in them. 115 00:05:45,560 --> 00:05:49,400 Speaker 1: Wow. Initially she totally didn't even think it was a 116 00:05:49,440 --> 00:05:50,479 Speaker 1: thing to pay attention to. 117 00:05:50,600 --> 00:05:52,520 Speaker 3: Oh yeah, for the first two weeks, she didn't even 118 00:05:52,600 --> 00:05:53,479 Speaker 3: look at them. 119 00:05:54,120 --> 00:05:58,279 Speaker 1: So for weeks her dog Stella would just ignore the buttons. 120 00:05:58,640 --> 00:06:00,839 Speaker 1: And I think it's safe to say that anyone of 121 00:06:00,920 --> 00:06:03,320 Speaker 1: us would have just given up by now, but Miss 122 00:06:03,400 --> 00:06:07,120 Speaker 1: Hunger's unique background as a speech therapist told her to 123 00:06:07,200 --> 00:06:10,800 Speaker 1: keep trying. And then one day something happened. 124 00:06:12,120 --> 00:06:15,039 Speaker 3: And then about three weeks and she literally just looked 125 00:06:15,040 --> 00:06:17,280 Speaker 3: at the button for the first time and then looked 126 00:06:17,360 --> 00:06:20,120 Speaker 3: up at me, and I was so excited. And then 127 00:06:20,200 --> 00:06:22,360 Speaker 3: within a week of that moment is when she started 128 00:06:22,440 --> 00:06:23,600 Speaker 3: using it for the first time. 129 00:06:23,920 --> 00:06:27,240 Speaker 1: Whoa. It happened quickly once she had that realization of 130 00:06:27,240 --> 00:06:27,960 Speaker 1: what it was. 131 00:06:28,279 --> 00:06:31,040 Speaker 3: So after about a month, the first word she said 132 00:06:31,120 --> 00:06:33,760 Speaker 3: was outside. And when she said outside with her button, 133 00:06:33,839 --> 00:06:36,280 Speaker 3: she went outside and went to the bathroom immediately. So 134 00:06:36,320 --> 00:06:38,799 Speaker 3: that was really exciting because it wasn't just like pressing 135 00:06:38,800 --> 00:06:41,400 Speaker 3: it to explore. So then I was wondering, you know, 136 00:06:41,720 --> 00:06:44,520 Speaker 3: is she going to use outside for everything that she 137 00:06:44,680 --> 00:06:48,400 Speaker 3: needs or what's going to happen here. But the next 138 00:06:48,480 --> 00:06:51,040 Speaker 3: day she started using her play button when she wanted 139 00:06:51,080 --> 00:06:53,680 Speaker 3: to play, and then I think within a week she 140 00:06:53,720 --> 00:06:56,320 Speaker 3: started using water whenever her water dish was empty. 141 00:06:56,640 --> 00:06:58,240 Speaker 1: I imagine you got very excited. 142 00:06:58,400 --> 00:07:02,760 Speaker 3: Oh yeah, I was really really excited when she sat 143 00:07:02,800 --> 00:07:05,760 Speaker 3: outside for the first time, But it actually wasn't until 144 00:07:05,880 --> 00:07:09,800 Speaker 3: an unexpected milestone and I started getting like really excited 145 00:07:10,000 --> 00:07:12,840 Speaker 3: and shocked. And that was just a couple of months 146 00:07:12,840 --> 00:07:16,480 Speaker 3: after that, she started using words for different purposes that 147 00:07:16,560 --> 00:07:20,280 Speaker 3: I hadn't taught her, like the same what buttons, but 148 00:07:20,480 --> 00:07:23,240 Speaker 3: in situations that I had never modeled. And that's when 149 00:07:23,280 --> 00:07:27,040 Speaker 3: my speech therapist s brain really started going crazy with 150 00:07:27,200 --> 00:07:27,920 Speaker 3: the potential. 151 00:07:28,520 --> 00:07:31,360 Speaker 1: Okay, this part is important. We'll get into the signs 152 00:07:31,400 --> 00:07:34,960 Speaker 1: of using words in different contexts and something called productivity 153 00:07:35,120 --> 00:07:39,640 Speaker 1: in sentence structure later in the program. Oh what do 154 00:07:39,640 --> 00:07:41,720 Speaker 1: you mean she used buttons for different purposes? 155 00:07:41,840 --> 00:07:44,800 Speaker 3: So, like I had always just modeled water when her 156 00:07:44,800 --> 00:07:46,800 Speaker 3: water dish was empty or when I was filling up 157 00:07:46,800 --> 00:07:50,160 Speaker 3: her water bowl. But one day I was watering my plants, 158 00:07:50,240 --> 00:07:53,000 Speaker 3: which Stella always really liked watching me do, and she 159 00:07:53,040 --> 00:07:55,240 Speaker 3: walked all the way out of the room down the 160 00:07:55,280 --> 00:07:58,080 Speaker 3: hall to her buttons and said water, and so I 161 00:07:58,120 --> 00:08:00,320 Speaker 3: was like, oh, okay, she mut sneed water. I walked 162 00:08:00,320 --> 00:08:02,320 Speaker 3: down the hall looked at her water bowl. It was 163 00:08:02,360 --> 00:08:04,679 Speaker 3: totally full, and she didn't take a drink of water. 164 00:08:05,040 --> 00:08:07,960 Speaker 3: She just came back and kept watching me water my plants. 165 00:08:08,400 --> 00:08:09,080 Speaker 2: Wow. 166 00:08:09,320 --> 00:08:10,760 Speaker 1: Stella wanted to kind of show off. 167 00:08:10,880 --> 00:08:12,560 Speaker 3: Yeah, I like water. That's what she's doing. 168 00:08:12,680 --> 00:08:16,320 Speaker 1: I know what that is exactly. There's a button for that, right. 169 00:08:16,200 --> 00:08:19,000 Speaker 3: And it was just so much more about connection in 170 00:08:19,040 --> 00:08:22,200 Speaker 3: that moment than just saying a button or pushing a 171 00:08:22,200 --> 00:08:25,120 Speaker 3: button to get something. She was using a word just 172 00:08:25,160 --> 00:08:26,320 Speaker 3: to connect and share. 173 00:08:27,480 --> 00:08:29,040 Speaker 1: How did people around you react? 174 00:08:29,360 --> 00:08:31,720 Speaker 3: It was at that point where they started to be 175 00:08:31,880 --> 00:08:34,320 Speaker 3: like amazed as well, Like my friends would come over 176 00:08:34,679 --> 00:08:37,079 Speaker 3: and Stella would hit the buy button when it was 177 00:08:37,120 --> 00:08:38,880 Speaker 3: getting too late and she wanted to go to bed 178 00:08:39,040 --> 00:08:40,160 Speaker 3: and she wanted them to leave. 179 00:08:40,760 --> 00:08:43,640 Speaker 1: No kidding, Yeah, I could use a button like that 180 00:08:43,760 --> 00:08:44,680 Speaker 1: when I have people over. 181 00:08:45,040 --> 00:08:46,880 Speaker 3: Right, very functional. 182 00:08:47,400 --> 00:08:49,720 Speaker 1: After about a year or so of teaching her dog, 183 00:08:49,800 --> 00:08:52,880 Speaker 1: Stella this hunger, decided this was something that couldn't just 184 00:08:52,920 --> 00:08:56,480 Speaker 1: stay in her living room, so she started a blog. 185 00:08:56,880 --> 00:08:59,240 Speaker 1: She would write about what her dog was learning and 186 00:08:59,280 --> 00:09:02,800 Speaker 1: her perspective as a speech therapist, and she posted videos 187 00:09:02,800 --> 00:09:06,439 Speaker 1: of Stella using the buns to talk. And at first 188 00:09:06,640 --> 00:09:11,199 Speaker 1: there were about five hundred people reading this blog, and at. 189 00:09:11,000 --> 00:09:14,600 Speaker 3: That point she was using about thirty different words, combining 190 00:09:14,600 --> 00:09:17,840 Speaker 3: words together to create her own phrases short sentences, And 191 00:09:17,880 --> 00:09:20,840 Speaker 3: that's when I started this blog. One of the people 192 00:09:20,960 --> 00:09:23,880 Speaker 3: in the audience had a family member who was a 193 00:09:23,880 --> 00:09:26,480 Speaker 3: speech therapist, and she happened to share one of my 194 00:09:26,559 --> 00:09:29,760 Speaker 3: blog posts on her personal Facebook, and then this reporter 195 00:09:30,160 --> 00:09:32,400 Speaker 3: saw it and reached out and was like, this is 196 00:09:32,640 --> 00:09:34,720 Speaker 3: absolutely incredible. I want to write a story on it. 197 00:09:34,880 --> 00:09:37,680 Speaker 3: We did an interview and it just blew up in 198 00:09:37,720 --> 00:09:41,040 Speaker 3: a way that I never could have anticipated or been 199 00:09:41,120 --> 00:09:45,000 Speaker 3: prepared for. Like it was trending around the world. I 200 00:09:45,040 --> 00:09:48,240 Speaker 3: went from five hundred followers to five hundred thousand in 201 00:09:48,320 --> 00:09:49,599 Speaker 3: less than two weeks. 202 00:09:49,640 --> 00:09:51,640 Speaker 1: Oh, that's incredible. 203 00:09:51,800 --> 00:09:54,080 Speaker 3: It was insane, truly insane. 204 00:09:54,160 --> 00:09:57,360 Speaker 1: How did you feel when this wave of attention and 205 00:09:57,480 --> 00:09:59,840 Speaker 1: people following you? How did you process that? 206 00:10:00,160 --> 00:10:03,640 Speaker 3: It was of course very exciting. I again, never in 207 00:10:03,640 --> 00:10:06,880 Speaker 3: my wildest dreams thought it would reach that level of awareness. 208 00:10:06,960 --> 00:10:09,440 Speaker 3: I'm not going to lie. It was extremely overwhelming. Like 209 00:10:09,480 --> 00:10:13,120 Speaker 3: I was getting thousands of messages and emails. Reporters had 210 00:10:13,200 --> 00:10:15,240 Speaker 3: figured out how to look up my number, outs getting 211 00:10:15,320 --> 00:10:17,480 Speaker 3: house all the time, and like I was just a 212 00:10:17,520 --> 00:10:20,680 Speaker 3: normal speech therapist, working my normal job and just getting 213 00:10:20,960 --> 00:10:25,320 Speaker 3: flooded with everything, and suddenly it's like once it's out there, 214 00:10:25,360 --> 00:10:26,280 Speaker 3: there's no going back. 215 00:10:29,080 --> 00:10:30,920 Speaker 1: All right. When we come back, we're going to talk 216 00:10:30,920 --> 00:10:34,120 Speaker 1: about this global movement that miss Hunger started that has 217 00:10:34,120 --> 00:10:38,560 Speaker 1: people teaching their cats, dogs, goats, and even horses do 218 00:10:38,880 --> 00:10:41,280 Speaker 1: use buttons to talk. And then we're going to talk 219 00:10:41,320 --> 00:10:44,200 Speaker 1: to these scientists that has taken this idea to the 220 00:10:44,320 --> 00:10:48,680 Speaker 1: next level. Stay with us, you're listening to sign stuff, 221 00:11:01,920 --> 00:11:07,120 Speaker 1: Welcome back. We're talking about whether animals can communicate. And 222 00:11:07,200 --> 00:11:10,320 Speaker 1: we started with the movement sparked by Christina Hunger's blog 223 00:11:10,640 --> 00:11:13,440 Speaker 1: where she wrote about teaching her dog Stella how to 224 00:11:13,520 --> 00:11:14,760 Speaker 1: use buttons to talk. 225 00:11:16,120 --> 00:11:18,960 Speaker 3: Where where what weird? 226 00:11:19,600 --> 00:11:20,160 Speaker 1: Yeah? 227 00:11:20,280 --> 00:11:23,400 Speaker 3: Weirds? 228 00:11:24,520 --> 00:11:28,080 Speaker 1: The blog went viral and since then people around the 229 00:11:28,120 --> 00:11:31,400 Speaker 1: world have jumped on to teach their pets to use 230 00:11:31,440 --> 00:11:35,120 Speaker 1: the same buttons. So he started with dogs, but I 231 00:11:35,120 --> 00:11:37,800 Speaker 1: imagine people out there have tried it with other pets. 232 00:11:37,920 --> 00:11:40,880 Speaker 1: My friend does it with a cat. What are some 233 00:11:40,960 --> 00:11:43,560 Speaker 1: of the other animals. You've heard people try the song. 234 00:11:43,760 --> 00:11:47,280 Speaker 3: I've seen people teach pigs to talk with buttons, some 235 00:11:47,520 --> 00:11:52,160 Speaker 3: farm animals, cows, goats, horses. I've actually worked with someone 236 00:11:52,200 --> 00:11:54,800 Speaker 3: who's teaching her horse and that was really cool as well. 237 00:11:54,880 --> 00:11:57,800 Speaker 3: So it's been just amazing to see that once the 238 00:11:57,840 --> 00:12:00,600 Speaker 3: idea was out there, people are just running with it 239 00:12:00,679 --> 00:12:02,840 Speaker 3: and trying it in all different areas. 240 00:12:02,960 --> 00:12:03,240 Speaker 2: Wow. 241 00:12:03,360 --> 00:12:04,760 Speaker 1: Which is the chattiest animal? 242 00:12:05,720 --> 00:12:08,800 Speaker 3: I think dogs still from my knowledge at this point, 243 00:12:08,840 --> 00:12:10,920 Speaker 3: but cats have been very chatty as well. 244 00:12:11,160 --> 00:12:14,120 Speaker 1: Dogs that live with us are more eager to talk 245 00:12:14,160 --> 00:12:14,520 Speaker 1: to us. 246 00:12:14,760 --> 00:12:17,400 Speaker 3: Yeah, they're hearing us talk all the time. Oh, it's 247 00:12:17,440 --> 00:12:19,840 Speaker 3: just a unique bond between a human and a dog. 248 00:12:20,000 --> 00:12:22,320 Speaker 1: What are some things you've heard of other dogs doing? 249 00:12:22,800 --> 00:12:25,319 Speaker 3: Like one of my training clients recently had a really 250 00:12:25,360 --> 00:12:28,960 Speaker 3: cool story where her dog said hurt with a button 251 00:12:29,040 --> 00:12:31,240 Speaker 3: and then potty with a button, and she took her 252 00:12:31,280 --> 00:12:32,680 Speaker 3: to the vet the next day and she had a 253 00:12:32,679 --> 00:12:37,080 Speaker 3: bladder infection, something she would not have even known. Whow 254 00:12:37,120 --> 00:12:40,520 Speaker 3: So to be able to express with that level of 255 00:12:40,559 --> 00:12:43,920 Speaker 3: clarity something that was wrong and then get help immediately, 256 00:12:44,080 --> 00:12:47,360 Speaker 3: I mean, that's a game changer for the future of 257 00:12:47,400 --> 00:12:47,880 Speaker 3: pet care. 258 00:12:48,320 --> 00:12:51,920 Speaker 1: Oh, incredible. What's the funniest thing Stella has said to you? 259 00:12:52,760 --> 00:12:56,560 Speaker 3: The funniest and most heartbreaking when she's upset with me? 260 00:12:56,800 --> 00:12:59,680 Speaker 3: She has said this several times over the year, love 261 00:12:59,720 --> 00:13:07,679 Speaker 3: you No, no, Yeah. 262 00:13:07,400 --> 00:13:09,040 Speaker 1: That blows my vine, Christina. 263 00:13:09,160 --> 00:13:09,520 Speaker 2: I know. 264 00:13:09,840 --> 00:13:12,640 Speaker 3: It's like I never would have thought by introducing a 265 00:13:12,640 --> 00:13:15,320 Speaker 3: love you button that I would someday be hearing love 266 00:13:15,360 --> 00:13:20,120 Speaker 3: you know sometime. But when she gets upset, still pull 267 00:13:20,160 --> 00:13:21,840 Speaker 3: that card sometimes love you know. 268 00:13:22,120 --> 00:13:24,600 Speaker 1: Whow It makes me wonder, what did you do? Christina? 269 00:13:25,280 --> 00:13:26,840 Speaker 3: It would just be like I didn't go to the 270 00:13:26,880 --> 00:13:30,520 Speaker 3: park or didn't say enough attention to her after she 271 00:13:30,559 --> 00:13:31,559 Speaker 3: had asked for something. 272 00:13:32,000 --> 00:13:33,560 Speaker 1: Just made me think of my teenage daughter. 273 00:13:35,600 --> 00:13:37,480 Speaker 3: A lot of drama plans the door shut. 274 00:13:37,760 --> 00:13:43,200 Speaker 1: Yes, maybe I should get my teenage daughter some buttons. 275 00:13:43,679 --> 00:13:46,479 Speaker 1: All right, now, we're going to dive into the signs 276 00:13:46,520 --> 00:13:50,040 Speaker 1: of animal communication. As you might imagine, still, it was 277 00:13:50,080 --> 00:13:53,199 Speaker 1: not the first non human animal ever to be trained 278 00:13:53,360 --> 00:13:56,800 Speaker 1: to use signals to talk to humans, and so to 279 00:13:56,840 --> 00:13:59,920 Speaker 1: get a wider view what we know from animal study 280 00:14:00,200 --> 00:14:03,760 Speaker 1: in current research, I reached out to Professor Federico Rossano. 281 00:14:04,080 --> 00:14:06,960 Speaker 1: I can't get to scientists from the University of California, 282 00:14:07,000 --> 00:14:12,240 Speaker 1: San Diego, who specializes in communication between humans and animals. 283 00:14:12,600 --> 00:14:16,800 Speaker 1: He has several interesting projects, including the largest citizen science 284 00:14:16,800 --> 00:14:20,840 Speaker 1: study on bun pressing pets, and he's involved in efforts 285 00:14:20,880 --> 00:14:24,960 Speaker 1: to use AI to decode how whales and monkeys talk 286 00:14:25,000 --> 00:14:27,720 Speaker 1: to each other. But first I wanted to know the 287 00:14:27,800 --> 00:14:32,800 Speaker 1: history of scientists communicating with animals. Well, thank you, doctor 288 00:14:32,880 --> 00:14:35,320 Speaker 1: Rosanna for joining us, Thank you for having me. So 289 00:14:35,400 --> 00:14:37,640 Speaker 1: I was hoping you could start by just giving us 290 00:14:37,640 --> 00:14:41,280 Speaker 1: a broad history of when did we start getting interested 291 00:14:41,320 --> 00:14:42,800 Speaker 1: in communicating with animals. 292 00:14:43,120 --> 00:14:45,960 Speaker 2: Well, it's a very interesting question because I believe we've 293 00:14:46,000 --> 00:14:49,240 Speaker 2: always been interested in communicating with animals. There are many 294 00:14:49,280 --> 00:14:52,560 Speaker 2: cultures that believe, for example, animals have souls and so 295 00:14:52,600 --> 00:14:54,920 Speaker 2: you can communicate with them. He can think about all 296 00:14:54,920 --> 00:14:57,760 Speaker 2: the fables for kids from two hundred years ago and 297 00:14:57,840 --> 00:15:02,520 Speaker 2: even more where we attribute to animals intelligence or emotions, 298 00:15:02,840 --> 00:15:05,720 Speaker 2: and so in that sense, the idea that animals might 299 00:15:05,800 --> 00:15:09,160 Speaker 2: have cognitive abilities and even things that they are trying 300 00:15:09,160 --> 00:15:12,040 Speaker 2: to communicate as existed for a long long time. 301 00:15:13,320 --> 00:15:16,480 Speaker 1: According to doctor Rossano, a scientist in the last century 302 00:15:16,720 --> 00:15:20,720 Speaker 1: started to wonder to what extent animals can use language 303 00:15:20,960 --> 00:15:24,080 Speaker 1: and whether it's the thing that really makes humans different 304 00:15:24,240 --> 00:15:27,360 Speaker 1: from other animals. Now, one of the first people to 305 00:15:27,440 --> 00:15:30,200 Speaker 1: make the case that maybe humans are not that different 306 00:15:30,200 --> 00:15:34,040 Speaker 1: from other animals in terms of language was Jane Goodall. 307 00:15:35,240 --> 00:15:38,080 Speaker 2: One of the first one was Jane Goodle that clearly 308 00:15:38,160 --> 00:15:41,560 Speaker 2: told us, look, these chance are communicating with each other, 309 00:15:41,640 --> 00:15:44,560 Speaker 2: and clearly they have gestions and they have facial expression, 310 00:15:44,600 --> 00:15:47,360 Speaker 2: they have signals that they convey to each other that 311 00:15:47,520 --> 00:15:50,440 Speaker 2: seem to be meaningful, they seem to be relevant. And 312 00:15:50,880 --> 00:15:54,000 Speaker 2: so once you start showing that actually wild animals might 313 00:15:54,040 --> 00:15:57,280 Speaker 2: have a code to communicate with each other, then opens 314 00:15:57,360 --> 00:16:01,440 Speaker 2: up a completely new possibility. Maybe, just like humans are 315 00:16:01,480 --> 00:16:05,880 Speaker 2: thousands of languages, maybe animals each species as at least 316 00:16:05,920 --> 00:16:08,680 Speaker 2: one code that they can use to communicate with each other. 317 00:16:09,240 --> 00:16:11,920 Speaker 2: And now the challenges can we crack this code? 318 00:16:12,480 --> 00:16:16,120 Speaker 1: The next step side this tried was to teach animals words, 319 00:16:16,160 --> 00:16:19,360 Speaker 1: but they quickly found almost no animals had the ability 320 00:16:19,640 --> 00:16:21,680 Speaker 1: to pronounce words like humans. 321 00:16:22,680 --> 00:16:24,440 Speaker 2: And so the next step was, well, what if we 322 00:16:24,520 --> 00:16:26,960 Speaker 2: teach them sign language. And a lot of animals and 323 00:16:27,040 --> 00:16:30,440 Speaker 2: these did learn sun language or at least quite a few words. 324 00:16:30,480 --> 00:16:33,440 Speaker 1: And this is referring to Coco for example, was Coco 325 00:16:33,520 --> 00:16:34,720 Speaker 1: in the seventies. 326 00:16:34,240 --> 00:16:36,680 Speaker 2: Coco was later, and Coco was in the eighties and 327 00:16:36,800 --> 00:16:37,560 Speaker 2: early nineties. 328 00:16:38,400 --> 00:16:41,720 Speaker 1: Coco, by the way, was a famous gorilla passed away 329 00:16:41,800 --> 00:16:44,360 Speaker 1: in twenty eighteen. They were said to have a sign 330 00:16:44,520 --> 00:16:48,200 Speaker 1: language vocabulary of over a thousand words. 331 00:16:48,280 --> 00:16:50,520 Speaker 2: There were several others. One of the most famous one 332 00:16:50,640 --> 00:16:52,960 Speaker 2: was Washow was a champ that I had learned actually 333 00:16:53,040 --> 00:16:55,320 Speaker 2: quite a lot of gestures. And one of the things 334 00:16:55,320 --> 00:16:57,200 Speaker 2: that I find most fascinating is he had learned a 335 00:16:57,200 --> 00:16:59,280 Speaker 2: lot of gestures, but one of the signs he could 336 00:16:59,320 --> 00:17:02,280 Speaker 2: never learn was why. It's like, how do you even 337 00:17:02,320 --> 00:17:05,480 Speaker 2: teach why? Like? What is it? What is it? The Youngaha? Anyway, 338 00:17:05,560 --> 00:17:08,080 Speaker 2: the interesting thing was some of these animals seem to 339 00:17:08,160 --> 00:17:10,919 Speaker 2: be able to learn a few underwards and use the 340 00:17:11,280 --> 00:17:15,080 Speaker 2: signs in a way that potentially was interesting. But some 341 00:17:15,240 --> 00:17:20,280 Speaker 2: scholars said, look is the equivalent of just Pavlov's dog bell. 342 00:17:22,359 --> 00:17:24,960 Speaker 1: Okay, here we get to the first big issue in 343 00:17:25,000 --> 00:17:28,679 Speaker 1: the study of teaching animals to communicate, and that is 344 00:17:28,800 --> 00:17:31,159 Speaker 1: if you teach a dog or a cat or a 345 00:17:31,200 --> 00:17:34,320 Speaker 1: gorilla to use a bun or a hand sign that 346 00:17:34,520 --> 00:17:37,360 Speaker 1: means food, and they get a treat every time they 347 00:17:37,440 --> 00:17:41,080 Speaker 1: use it. Are they really learning language or are they 348 00:17:41,160 --> 00:17:44,040 Speaker 1: just learning that if you press that button they get food. 349 00:17:44,720 --> 00:17:48,159 Speaker 1: This is called stimulus response. You might have heard of 350 00:17:48,240 --> 00:17:51,960 Speaker 1: Pavlov's dogs, where they taught dogs to expect food every 351 00:17:52,000 --> 00:17:56,000 Speaker 1: time their trainer rings a bell. Well, here are the 352 00:17:56,080 --> 00:18:01,000 Speaker 1: lingering questions surrounding examples like Washo the champoor, Coco the gorilla, 353 00:18:01,200 --> 00:18:04,720 Speaker 1: or Stella the dog. Is whether you're really proving that 354 00:18:04,880 --> 00:18:08,200 Speaker 1: animals can use language in the same way that we 355 00:18:08,320 --> 00:18:11,520 Speaker 1: use language. And so the science shifted gears and it 356 00:18:11,680 --> 00:18:15,280 Speaker 1: tried a couple of different directions. 357 00:18:14,880 --> 00:18:17,080 Speaker 2: And so in the early eighties, basically there was the 358 00:18:17,160 --> 00:18:19,520 Speaker 2: decision that this switcher should kind of be stopped. It 359 00:18:19,680 --> 00:18:22,840 Speaker 2: wasn't really helpful in anyway. Some people continued, but the 360 00:18:22,880 --> 00:18:25,040 Speaker 2: field kind of moved in three directions that I think 361 00:18:25,080 --> 00:18:28,800 Speaker 2: we're very interesting. So one was, well, what if we 362 00:18:28,840 --> 00:18:32,280 Speaker 2: actually tried to look at their natural communicative systems? Right, 363 00:18:32,680 --> 00:18:35,520 Speaker 2: So there's a famous paper from nineteen eighty on the 364 00:18:35,600 --> 00:18:38,720 Speaker 2: vever monkey alarm calls that basically says, hey, if you 365 00:18:38,720 --> 00:18:41,960 Speaker 2: look at vever monkeys, they have these different vocalizations that 366 00:18:42,000 --> 00:18:47,439 Speaker 2: seem to be associated to different types of predators. Like ego, leopard, snake, 367 00:18:48,040 --> 00:18:49,960 Speaker 2: and so the idea was, what if actually they have 368 00:18:50,080 --> 00:18:52,840 Speaker 2: something like words, So maybe we should look more at 369 00:18:52,880 --> 00:18:56,400 Speaker 2: the spontaneous communicative system and what they used to communicate 370 00:18:56,440 --> 00:18:59,520 Speaker 2: with each other instead of teaching them human language. 371 00:19:00,359 --> 00:19:03,720 Speaker 1: That's one direction, looking at the language that animals use 372 00:19:03,760 --> 00:19:06,679 Speaker 1: on their own instead of trying to teach them a language, 373 00:19:06,920 --> 00:19:09,520 Speaker 1: and later on we'll talk about how doctor Rossano is 374 00:19:09,640 --> 00:19:11,640 Speaker 1: using AI to figure that out. 375 00:19:12,440 --> 00:19:15,240 Speaker 2: The second direction was what if we look at animals 376 00:19:15,240 --> 00:19:18,440 Speaker 2: that can actually learn hum of vocalization and so, for example, 377 00:19:18,480 --> 00:19:21,720 Speaker 2: you can train a parrot to start reproducing the words 378 00:19:21,760 --> 00:19:24,880 Speaker 2: in that way, it's not just teaching them sign language. 379 00:19:24,880 --> 00:19:27,760 Speaker 2: But you can have animals that we know our vocal learners, 380 00:19:28,040 --> 00:19:29,960 Speaker 2: and if they can learn new sounds, maybe they can 381 00:19:30,040 --> 00:19:32,639 Speaker 2: also start putting them together in ways that might be 382 00:19:32,720 --> 00:19:33,440 Speaker 2: more flexible. 383 00:19:33,560 --> 00:19:33,720 Speaker 3: Right. 384 00:19:34,480 --> 00:19:37,080 Speaker 2: So, indeed, there was amazing research that was done on 385 00:19:37,240 --> 00:19:41,960 Speaker 2: vocalizations and teaching parrots, for example the constant of sameness 386 00:19:42,160 --> 00:19:44,320 Speaker 2: or colors and things like numbers. 387 00:19:44,840 --> 00:19:48,520 Speaker 1: Here the most famous example is Alex, the talking great 388 00:19:48,600 --> 00:19:52,639 Speaker 1: parrot trained by doctor Irene Pepperberg that had a vocabulary 389 00:19:52,800 --> 00:19:55,880 Speaker 1: of over one hundred words I could count and name 390 00:19:55,960 --> 00:19:59,720 Speaker 1: shapes and colors. Alex lived thirty one years then pass 391 00:19:59,720 --> 00:20:02,920 Speaker 1: away in twenty oh seven. Then there's the third direction 392 00:20:03,240 --> 00:20:06,400 Speaker 1: that the science of animal communication took, and this one 393 00:20:06,480 --> 00:20:08,119 Speaker 1: will seem familiar. 394 00:20:08,720 --> 00:20:11,679 Speaker 2: The third direction was, what if instead of trying to 395 00:20:11,720 --> 00:20:14,720 Speaker 2: do this training that is unclear with sign language and 396 00:20:14,760 --> 00:20:17,600 Speaker 2: what exactly do they know, we try to use something 397 00:20:17,600 --> 00:20:20,800 Speaker 2: there's a lot more automated, kind of like a touchscreen, 398 00:20:20,920 --> 00:20:23,760 Speaker 2: like almost like a keyboard that you can actually push 399 00:20:23,800 --> 00:20:26,840 Speaker 2: buttons in and then combine and create sequences. So this 400 00:20:26,960 --> 00:20:31,640 Speaker 2: had already started in the seventies, but it became particularly prominent, 401 00:20:31,680 --> 00:20:36,280 Speaker 2: for example with famous bernobos like Kanzi that died actually 402 00:20:36,560 --> 00:20:39,239 Speaker 2: very recently. And so the idea was, what if we 403 00:20:39,320 --> 00:20:43,040 Speaker 2: use these devices that had been used previously with long 404 00:20:43,080 --> 00:20:46,000 Speaker 2: global humans to kind of learn to communicate, for example, 405 00:20:46,040 --> 00:20:48,080 Speaker 2: that you want the start of food, or that you 406 00:20:48,280 --> 00:20:51,840 Speaker 2: want a specific object or you want to play. And 407 00:20:51,880 --> 00:20:54,440 Speaker 2: so the idea is they learn to associate a specific 408 00:20:54,560 --> 00:20:57,240 Speaker 2: button with the concept and then they can push it 409 00:20:57,280 --> 00:20:59,720 Speaker 2: when they want it. But then you can start combining 410 00:20:59,720 --> 00:21:02,480 Speaker 2: some those things and try to produce things that look 411 00:21:02,560 --> 00:21:05,880 Speaker 2: like scient instance, and so Canzi, for example, could use 412 00:21:06,000 --> 00:21:09,960 Speaker 2: a keyboard that has several hundred of this science. And similarly, 413 00:21:10,080 --> 00:21:13,120 Speaker 2: that was what done with dolphins, where there were dolphins 414 00:21:13,119 --> 00:21:15,479 Speaker 2: that actually could learn to use some symbols to request 415 00:21:15,520 --> 00:21:17,680 Speaker 2: for things. This was done with one dog in two 416 00:21:17,720 --> 00:21:18,400 Speaker 2: thousand and eight. 417 00:21:19,600 --> 00:21:22,280 Speaker 1: Yes, this is the Pushbunton idea that's part of the 418 00:21:22,320 --> 00:21:26,199 Speaker 1: recent talking pet movement. Back then scientists even tried it 419 00:21:26,320 --> 00:21:29,440 Speaker 1: with dolphins. But here we run into the second big 420 00:21:29,480 --> 00:21:33,400 Speaker 1: issue in animal communication research, that is that often these 421 00:21:33,440 --> 00:21:36,400 Speaker 1: studies have a sample size of one. 422 00:21:37,720 --> 00:21:41,360 Speaker 2: What happens is we're just taking usually one animal, maybe two. 423 00:21:41,800 --> 00:21:45,240 Speaker 2: We spent hours and hours and hours and hours training them, 424 00:21:45,320 --> 00:21:49,400 Speaker 2: often removing them from the natural environment, and what we 425 00:21:49,800 --> 00:21:52,480 Speaker 2: get out of this is like this one subject that 426 00:21:52,640 --> 00:21:55,919 Speaker 2: possibly is a genius, possibly is the flukes, and we 427 00:21:55,960 --> 00:21:58,440 Speaker 2: don't really know right, It's like, it's it real. Imagine 428 00:21:58,440 --> 00:22:00,879 Speaker 2: if like you, as a scientist, spend your entire career 429 00:22:01,280 --> 00:22:03,880 Speaker 2: just training this one animal to show that they can 430 00:22:03,880 --> 00:22:07,720 Speaker 2: do something amazing. You can see how there's skepticism, there's concerns, 431 00:22:07,720 --> 00:22:09,800 Speaker 2: and maybe you might have an interest in making sure 432 00:22:09,840 --> 00:22:11,960 Speaker 2: that the abilities are emphasized. 433 00:22:12,040 --> 00:22:13,600 Speaker 1: It's an an equals one. 434 00:22:13,720 --> 00:22:17,040 Speaker 2: Exactly, It's an equal one often of animals that have 435 00:22:17,080 --> 00:22:20,440 Speaker 2: been removed from the natural environment, is what you're getting 436 00:22:20,680 --> 00:22:24,160 Speaker 2: representative of what any animal in the wild could possibly 437 00:22:24,200 --> 00:22:27,080 Speaker 2: communicate about, or is it just like this one that 438 00:22:27,160 --> 00:22:30,600 Speaker 2: you spend years and years training that ends up being 439 00:22:30,640 --> 00:22:31,320 Speaker 2: able to do this. 440 00:22:31,880 --> 00:22:34,560 Speaker 1: So that's the second issue in studying whether we can 441 00:22:34,640 --> 00:22:38,800 Speaker 1: communicate with animals, and studies where there's one scientist that 442 00:22:38,920 --> 00:22:42,280 Speaker 1: spends a long time teaching one animal to communicate, there 443 00:22:42,280 --> 00:22:45,280 Speaker 1: are lots of questions of whether this applies to all 444 00:22:45,359 --> 00:22:48,560 Speaker 1: animals in that species or whether the animal can only 445 00:22:48,640 --> 00:22:53,160 Speaker 1: speak to that one person. Although, as doctor Rosseno says, 446 00:22:53,400 --> 00:22:57,000 Speaker 1: a sample of n equals one is still something. 447 00:22:57,800 --> 00:23:00,520 Speaker 2: As a scientist, it's like any equal one, it's not 448 00:23:00,840 --> 00:23:03,920 Speaker 2: an equals deal. Like if you have a flying pig, 449 00:23:04,600 --> 00:23:05,560 Speaker 2: you have a flying pig. 450 00:23:05,600 --> 00:23:08,440 Speaker 4: I mean, it's something that we should know about, right aside, 451 00:23:08,720 --> 00:23:11,880 Speaker 4: these pigs can fly. Pigs can fly, like it's possible, right, 452 00:23:11,880 --> 00:23:13,520 Speaker 4: So it's like if all of a sudden you have 453 00:23:13,640 --> 00:23:17,000 Speaker 4: one bonobo that can start doing things and nobody else 454 00:23:17,160 --> 00:23:20,880 Speaker 4: could even imagine they could do it is worth knowing, right, 455 00:23:20,920 --> 00:23:23,520 Speaker 4: It's like we should yeah, yeah, at least investigative photo 456 00:23:23,880 --> 00:23:24,399 Speaker 4: all right. 457 00:23:24,320 --> 00:23:26,840 Speaker 1: We'll get to the last issue, figuring out if we 458 00:23:26,880 --> 00:23:29,439 Speaker 1: can communicate with animals, and then we'll talk about the 459 00:23:29,480 --> 00:23:34,160 Speaker 1: idea of using AI to possibly translate what animals are 460 00:23:34,160 --> 00:23:38,680 Speaker 1: saying for us. Stick with us. We'll be right back, 461 00:23:51,960 --> 00:23:56,040 Speaker 1: and we're back. We're talking about whether we can communicate 462 00:23:56,080 --> 00:24:00,600 Speaker 1: with animals, and so far we've learned the answer is yes. 463 00:24:01,440 --> 00:24:05,000 Speaker 1: Pet owners can communicate with their dogs or cats using buns. 464 00:24:05,320 --> 00:24:08,240 Speaker 1: You can teach apes to use sign language, and you 465 00:24:08,280 --> 00:24:11,280 Speaker 1: can even teach a parrot to count and tell you 466 00:24:11,320 --> 00:24:14,760 Speaker 1: what color something is. But the answer is also sort 467 00:24:14,760 --> 00:24:18,560 Speaker 1: of no. We don't know for sure yet whether we 468 00:24:18,640 --> 00:24:22,879 Speaker 1: can ever truly communicate with an animal beyond simple words 469 00:24:23,040 --> 00:24:26,920 Speaker 1: or concepts. An animal's ability to use buns or sign 470 00:24:27,000 --> 00:24:32,120 Speaker 1: language could just be learned behavior like Pavlov's dogs, for example. 471 00:24:32,240 --> 00:24:35,920 Speaker 1: A famous cautionary tale in animal studies is the story 472 00:24:36,080 --> 00:24:37,680 Speaker 1: of Clever Haunts. 473 00:24:39,800 --> 00:24:42,240 Speaker 2: So there's this famous horse that at the beginning of 474 00:24:42,280 --> 00:24:45,960 Speaker 2: the twentieth century was claimed to be able to do 475 00:24:46,080 --> 00:24:50,200 Speaker 2: mathematical operations, so additions and subtractions, and so the idea 476 00:24:50,400 --> 00:24:53,359 Speaker 2: was this horse became super famous and people were paying 477 00:24:53,359 --> 00:24:55,560 Speaker 2: money to go watch the horse, and so it would 478 00:24:55,560 --> 00:24:59,720 Speaker 2: be something like, okay, Hans, what is five plus two? 479 00:25:00,080 --> 00:25:02,600 Speaker 2: And so you hear Hans kind of knocking his hoof 480 00:25:02,560 --> 00:25:06,560 Speaker 2: from the ground, and when he gets to like five 481 00:25:07,080 --> 00:25:10,760 Speaker 2: six seven, and then it would stop and people just 482 00:25:10,800 --> 00:25:15,480 Speaker 2: you know, start clapping and being amazed. But god, but 483 00:25:15,560 --> 00:25:18,439 Speaker 2: what happened was that Hans was very good at picking 484 00:25:18,520 --> 00:25:21,760 Speaker 2: up cues from the audience in terms of when he 485 00:25:21,920 --> 00:25:24,800 Speaker 2: was hitting the right number. So people were all of 486 00:25:24,840 --> 00:25:28,480 Speaker 2: a sudden smiling when he was the correct answer, and 487 00:25:28,520 --> 00:25:30,720 Speaker 2: so he was kind of like slowly hitting the holes 488 00:25:31,080 --> 00:25:33,240 Speaker 2: until he got the correct one. I see you smile. 489 00:25:33,400 --> 00:25:36,320 Speaker 2: Now I'm done. Obviously he couldn't do math. He was 490 00:25:36,560 --> 00:25:38,080 Speaker 2: just picking up cues. 491 00:25:38,160 --> 00:25:41,680 Speaker 1: It's almost a little more impressive than counting yes. 492 00:25:41,920 --> 00:25:44,480 Speaker 2: So that's a funny thing. So clever haunts as a 493 00:25:44,600 --> 00:25:48,040 Speaker 2: term has been used in almost a derogatory way to 494 00:25:48,160 --> 00:25:51,040 Speaker 2: refer to people believe the animals can do things that 495 00:25:51,160 --> 00:25:52,320 Speaker 2: really they cannot do. 496 00:25:53,960 --> 00:25:57,359 Speaker 1: Now, doctor Rossana has two interesting projects he's involved in. 497 00:25:57,720 --> 00:26:01,000 Speaker 1: The first is that he's the lead researcher basically the 498 00:26:01,040 --> 00:26:05,359 Speaker 1: scientific side of the Talking pet movement, doing science on 499 00:26:05,400 --> 00:26:09,200 Speaker 1: a massive scale. The second project is that he's using 500 00:26:09,240 --> 00:26:13,720 Speaker 1: AI to study how animals communicate in the wild. We'll 501 00:26:13,720 --> 00:26:15,679 Speaker 1: talk about the Talking Pet project first. 502 00:26:16,840 --> 00:26:20,760 Speaker 2: And so this thing started because a speech language pathologist 503 00:26:20,800 --> 00:26:24,280 Speaker 2: in twenty nineteen. This went viral and then a clips online. 504 00:26:24,320 --> 00:26:26,159 Speaker 2: I'm not on social media, so I didn't even know, 505 00:26:26,320 --> 00:26:29,119 Speaker 2: but basically a colleague asked me, you know, would you 506 00:26:29,200 --> 00:26:30,920 Speaker 2: like to do this? I thought it was going to 507 00:26:30,960 --> 00:26:34,159 Speaker 2: be a lot side project, and I media realized a 508 00:26:34,160 --> 00:26:36,680 Speaker 2: lot of people thought this was a terrible idea. So 509 00:26:37,040 --> 00:26:39,760 Speaker 2: I had a lot of colleagues telling me, what are 510 00:26:39,800 --> 00:26:42,000 Speaker 2: you doing. Didn't you know that we stopped doing the 511 00:26:42,080 --> 00:26:45,719 Speaker 2: cameray so thirty years ago, fuckty years ago, And I 512 00:26:45,760 --> 00:26:48,080 Speaker 2: was like, yeah, because we were doing with chips. But 513 00:26:48,480 --> 00:26:50,960 Speaker 2: now there's are dogs. Well let's look into this and 514 00:26:51,040 --> 00:26:54,560 Speaker 2: let's see what happens. We now have ten thousand dogs, 515 00:26:54,840 --> 00:26:57,240 Speaker 2: and actually every week we keep getting an out of 516 00:26:57,240 --> 00:27:00,320 Speaker 2: twenty thirty dogs signed up and seven hunderd cat in 517 00:27:00,359 --> 00:27:03,480 Speaker 2: the study from forty seven countries, and just to give 518 00:27:03,480 --> 00:27:07,399 Speaker 2: you an idea, we get one million. Buttom presses pretty 519 00:27:07,440 --> 00:27:08,200 Speaker 2: much every month. 520 00:27:08,880 --> 00:27:12,320 Speaker 1: Yes, there are ten thousand dogs and owners signed up. 521 00:27:12,640 --> 00:27:15,400 Speaker 1: And if you go to the University of California, San Diego, 522 00:27:15,600 --> 00:27:19,440 Speaker 1: Comparative Condition Lab website. You can sign up to potentially 523 00:27:19,480 --> 00:27:22,280 Speaker 1: be on the study too. So what have they learned 524 00:27:22,320 --> 00:27:25,400 Speaker 1: so far from these thousands of dogs and cats? 525 00:27:26,600 --> 00:27:28,480 Speaker 2: One other thing I love is you can see what 526 00:27:28,560 --> 00:27:31,160 Speaker 2: buttons are pressed the mass and if you are a dog, 527 00:27:31,760 --> 00:27:33,639 Speaker 2: what do you think is the button they press the 528 00:27:33,680 --> 00:27:39,359 Speaker 2: moss freak, food free, and then it's outside and then 529 00:27:39,400 --> 00:27:41,840 Speaker 2: it's play. And so you're like, yeah, does it sound 530 00:27:41,880 --> 00:27:45,120 Speaker 2: like a dog? Yeah, that seems very reasonable. My favorite 531 00:27:45,160 --> 00:27:47,640 Speaker 2: thing is we're now looking at the cat data. One 532 00:27:47,640 --> 00:27:50,400 Speaker 2: of the top five buttons for cats is. 533 00:27:50,800 --> 00:27:55,719 Speaker 4: No, I'm not gonna do it anyway. 534 00:27:56,080 --> 00:27:58,600 Speaker 2: But the idea is, you know, once you have thousands 535 00:27:58,600 --> 00:28:02,120 Speaker 2: of these animals and try to do a bunch of things. 536 00:28:02,560 --> 00:28:04,800 Speaker 1: Okay, here are some of the things doctor Rossanna has 537 00:28:04,880 --> 00:28:09,199 Speaker 1: learned about what cats and dogs communicate. The first is 538 00:28:09,200 --> 00:28:13,040 Speaker 1: that apparently dogs do care about you. 539 00:28:13,960 --> 00:28:16,800 Speaker 2: And what I've learned by looking at what they communicate about, 540 00:28:16,920 --> 00:28:20,360 Speaker 2: in addition to food, water, playings on, is that these 541 00:28:20,359 --> 00:28:24,920 Speaker 2: are social animals, and social animals often ask about where 542 00:28:24,920 --> 00:28:26,600 Speaker 2: are the people that used to be in the house 543 00:28:26,640 --> 00:28:29,440 Speaker 2: And I'm not currently in the house, somebody is gone, 544 00:28:29,800 --> 00:28:33,480 Speaker 2: where is that? When the cat dies, they keep asking 545 00:28:33,520 --> 00:28:36,280 Speaker 2: about where is the cat? And when you are out 546 00:28:36,280 --> 00:28:39,479 Speaker 2: of the house, they might ask about you. And so 547 00:28:39,520 --> 00:28:42,000 Speaker 2: they think about you, and they think about the ones 548 00:28:42,040 --> 00:28:43,920 Speaker 2: around you, and they think about the other animals they 549 00:28:43,920 --> 00:28:47,200 Speaker 2: live with. And it's kind of obvious and yet mind 550 00:28:47,200 --> 00:28:49,680 Speaker 2: blowing to be reminded that, like maybe the same way 551 00:28:49,720 --> 00:28:51,920 Speaker 2: in which you care for them, they care for you too, 552 00:28:52,680 --> 00:28:53,920 Speaker 2: And it isn't that nice to know? 553 00:28:55,480 --> 00:28:58,600 Speaker 1: So you're seeing this in the data that this is 554 00:28:58,640 --> 00:29:01,000 Speaker 1: not a fluid that one does did it? Three dogs? 555 00:29:01,000 --> 00:29:01,280 Speaker 1: Did it? 556 00:29:01,920 --> 00:29:03,640 Speaker 2: No? I mean you see it in the data. You 557 00:29:03,680 --> 00:29:06,640 Speaker 2: see that many of them ask about humans that are 558 00:29:06,720 --> 00:29:10,280 Speaker 2: not at them, including the experimentals, Like the experimental will 559 00:29:10,320 --> 00:29:12,160 Speaker 2: be there that will give them treats and stuff, and 560 00:29:12,200 --> 00:29:15,040 Speaker 2: then they will ask later it's like where is the 561 00:29:15,480 --> 00:29:19,520 Speaker 2: treat to human? What is the treat to you? And 562 00:29:19,760 --> 00:29:22,680 Speaker 2: they also communicate a lot about how they're feeling, being 563 00:29:22,920 --> 00:29:26,800 Speaker 2: scared or being frustrated, or being dealing with something that 564 00:29:26,920 --> 00:29:29,720 Speaker 2: is bothering them. And especially you know when some of 565 00:29:29,720 --> 00:29:32,200 Speaker 2: the animals they live with ee and you see them 566 00:29:32,240 --> 00:29:36,240 Speaker 2: asking when they're sick. So we have examples of some 567 00:29:36,320 --> 00:29:40,520 Speaker 2: of them saying they're concerned about some other animals, maybe 568 00:29:40,560 --> 00:29:42,840 Speaker 2: because they're limping or they seem to be sluggish and 569 00:29:42,960 --> 00:29:46,280 Speaker 2: so on. And I think the idea is these are animals, 570 00:29:46,320 --> 00:29:50,480 Speaker 2: they have some level of empathy and they care about others. 571 00:29:51,320 --> 00:29:54,240 Speaker 1: The other interesting thing doctor Rossano and his team have 572 00:29:54,360 --> 00:29:58,400 Speaker 1: found is related to the last issue in the animal communication, 573 00:29:58,920 --> 00:30:03,200 Speaker 1: and that is whether animals can use words in new ways. 574 00:30:03,640 --> 00:30:07,080 Speaker 1: This is a concept called productivity. You might be able 575 00:30:07,120 --> 00:30:10,040 Speaker 1: to teach an animal that certain buns or signs mean 576 00:30:10,120 --> 00:30:13,640 Speaker 1: certain concepts, but a true test of whether animals can 577 00:30:13,680 --> 00:30:17,240 Speaker 1: really understand language is whether they can mix words to 578 00:30:17,480 --> 00:30:21,720 Speaker 1: name something they've never seen before. And apparently some dogs 579 00:30:21,800 --> 00:30:22,440 Speaker 1: can't do this. 580 00:30:23,240 --> 00:30:25,640 Speaker 2: We have one of the dogs started using the combination 581 00:30:25,880 --> 00:30:28,760 Speaker 2: water bone water bond and the owner was like, I 582 00:30:28,760 --> 00:30:31,960 Speaker 2: don't know what you're asking for, until they realized that 583 00:30:32,080 --> 00:30:35,880 Speaker 2: water bone was ice, and so they start giving them ice. 584 00:30:36,280 --> 00:30:38,959 Speaker 2: And once they introduce the bottom ice, they stopped pushing 585 00:30:38,960 --> 00:30:41,360 Speaker 2: the combination water bone because now they have the water 586 00:30:41,360 --> 00:30:41,680 Speaker 2: for it. 587 00:30:41,800 --> 00:30:46,720 Speaker 1: Right, So dogs can put together words to make new meanings, 588 00:30:46,960 --> 00:30:49,280 Speaker 1: does that mean they understand language? 589 00:30:49,720 --> 00:30:52,840 Speaker 2: So the issue is there's a lot of anecdotal reports 590 00:30:52,920 --> 00:30:55,360 Speaker 2: and I've seen clips of course of animals using these 591 00:30:55,400 --> 00:30:58,360 Speaker 2: things in a way that seem to be contextually appropriate 592 00:30:58,400 --> 00:31:02,960 Speaker 2: and conveying productivity. But as a scientist, ideally you want 593 00:31:02,960 --> 00:31:05,720 Speaker 2: to test it. The issue when you see clips and 594 00:31:05,760 --> 00:31:08,800 Speaker 2: so on is that you never know if it was like, oh, 595 00:31:08,920 --> 00:31:11,240 Speaker 2: did you actually train this? Was there some other way 596 00:31:11,280 --> 00:31:14,200 Speaker 2: in which you recreated this scenario and now you filmed it. 597 00:31:14,720 --> 00:31:17,600 Speaker 2: Whatever you see on TikTok on YouTube these days, you're like, 598 00:31:17,760 --> 00:31:20,720 Speaker 2: was it really spontaneous or was it made up? So 599 00:31:20,760 --> 00:31:23,840 Speaker 2: the idea is to design studies in which you try 600 00:31:23,840 --> 00:31:26,680 Speaker 2: to elicit those kind of responses, right, So that's what 601 00:31:26,680 --> 00:31:27,320 Speaker 2: we're trying to do. 602 00:31:27,520 --> 00:31:30,479 Speaker 1: As the anecdotes are not enough to show that they 603 00:31:30,520 --> 00:31:31,240 Speaker 1: can do things. 604 00:31:31,480 --> 00:31:35,000 Speaker 2: Anecdotes are informative. If you have all the details of 605 00:31:35,080 --> 00:31:38,840 Speaker 2: those anecdotes, they show that it might be possible. 606 00:31:39,320 --> 00:31:41,240 Speaker 1: I think you're trying to tell me I shouldn't believe 607 00:31:41,280 --> 00:31:42,440 Speaker 1: everything I see on YouTube. 608 00:31:42,520 --> 00:31:48,200 Speaker 2: Correct. Well, I mean it is a very important problem 609 00:31:48,240 --> 00:31:51,719 Speaker 2: for us, and I think anecdotal reports are helpful. Please 610 00:31:52,000 --> 00:31:54,920 Speaker 2: stand them along. But do not think that just because hey, 611 00:31:55,000 --> 00:31:57,560 Speaker 2: one time my dog did this, then it has been 612 00:31:57,640 --> 00:31:59,640 Speaker 2: proven scientifically that that's the truth. 613 00:32:00,320 --> 00:32:02,640 Speaker 1: Okay, The last topic we're going to talk about is 614 00:32:02,880 --> 00:32:07,000 Speaker 1: using AI to understand what animals are saying when they 615 00:32:07,120 --> 00:32:11,840 Speaker 1: talk to each other. Can we decipher their natural communication language? 616 00:32:12,440 --> 00:32:15,680 Speaker 2: Yes. So there's at least two big projects that are 617 00:32:15,720 --> 00:32:20,560 Speaker 2: big collaborations across several scientists that are interested in decoding 618 00:32:20,720 --> 00:32:25,240 Speaker 2: animal communication. One is the Species Project. It started with 619 00:32:25,480 --> 00:32:28,240 Speaker 2: dolphins and whales and so on, and that has now 620 00:32:28,280 --> 00:32:32,200 Speaker 2: expanded to other species. Another project is called Project SETTI 621 00:32:32,520 --> 00:32:36,120 Speaker 2: specifically started with the goal of understanding whales songs. 622 00:32:36,480 --> 00:32:38,880 Speaker 1: And so what are we learning with all these different 623 00:32:39,080 --> 00:32:42,040 Speaker 1: AI understanding language projects. 624 00:32:42,320 --> 00:32:44,320 Speaker 2: Some of the things, for example, we're learning is that 625 00:32:44,560 --> 00:32:47,640 Speaker 2: a lot of animals seem to add signals that would 626 00:32:47,640 --> 00:32:50,240 Speaker 2: be similar to names, like a way of kind of 627 00:32:50,240 --> 00:32:53,560 Speaker 2: referring to this specific individual in the group. And that 628 00:32:53,720 --> 00:32:56,080 Speaker 2: is very interesting. Right, So we didn't know that animals 629 00:32:56,160 --> 00:32:58,080 Speaker 2: might have names for each other, and so this is 630 00:32:58,120 --> 00:33:02,960 Speaker 2: an interesting phenomenon being documented now for dolphins and for elephants. 631 00:33:03,120 --> 00:33:05,440 Speaker 1: Dolphins and elephants have names for each other. 632 00:33:05,680 --> 00:33:09,400 Speaker 2: It's a little symptom, fine, but yes, right. 633 00:33:09,440 --> 00:33:12,960 Speaker 1: The last question I asked our experts was why communicate 634 00:33:13,200 --> 00:33:14,320 Speaker 1: with animals? 635 00:33:14,800 --> 00:33:19,320 Speaker 3: Ooh, I think it's incredible that we can actually hear 636 00:33:19,600 --> 00:33:23,440 Speaker 3: how our animals are experiencing the environment we share with them. 637 00:33:23,720 --> 00:33:27,040 Speaker 3: We can have such a better understanding of what they're 638 00:33:27,040 --> 00:33:29,400 Speaker 3: thinking about, what their needs are, how we can care 639 00:33:29,480 --> 00:33:32,880 Speaker 3: for them, and ultimately, I think it'll help us treat 640 00:33:32,880 --> 00:33:35,600 Speaker 3: our animals a lot better and learn what they've been 641 00:33:35,600 --> 00:33:36,960 Speaker 3: trying to say all these years. 642 00:33:37,120 --> 00:33:39,360 Speaker 1: Yeah, I guess it's a different thing if something is 643 00:33:39,400 --> 00:33:41,560 Speaker 1: actually talking to you, even. 644 00:33:41,320 --> 00:33:44,720 Speaker 3: If people aren't teaching their own pets in their homes, 645 00:33:44,760 --> 00:33:47,960 Speaker 3: just the knowledge that it's possible for a dog to 646 00:33:48,120 --> 00:33:51,760 Speaker 3: use words and create sentences, it's like, Okay, this is 647 00:33:51,800 --> 00:33:54,760 Speaker 3: a very complex creature that is living in my home. 648 00:33:55,120 --> 00:33:57,560 Speaker 3: I think it can give a really good appreciation of 649 00:33:57,600 --> 00:34:00,480 Speaker 3: how smarts our pets are and how much deserve. 650 00:34:01,200 --> 00:34:03,680 Speaker 1: How do we learn more about what you do and 651 00:34:03,800 --> 00:34:06,120 Speaker 1: how to teach our pets how to use this system. 652 00:34:06,400 --> 00:34:08,879 Speaker 3: So my very first book, How Sell Learned to Talk, 653 00:34:09,000 --> 00:34:11,759 Speaker 3: is the whole story of the idea that I had 654 00:34:11,800 --> 00:34:14,640 Speaker 3: all the way through this communication breakthrough and then the 655 00:34:14,680 --> 00:34:18,040 Speaker 3: world learning about it. Then my second book, Your Dog 656 00:34:18,080 --> 00:34:20,800 Speaker 3: Can Talk, is the step by step training guide, and 657 00:34:20,800 --> 00:34:23,640 Speaker 3: then you can find our buttons hunger for words, talking 658 00:34:23,680 --> 00:34:27,399 Speaker 3: pet buttons and any major retailer Amazon, Showy, pet Co 659 00:34:27,760 --> 00:34:29,120 Speaker 3: and get started with your own pet. 660 00:34:30,040 --> 00:34:31,960 Speaker 1: Does it also work with teenage daughters? 661 00:34:33,600 --> 00:34:37,520 Speaker 3: I have seen some applications in the Home for humans 662 00:34:37,640 --> 00:34:40,799 Speaker 3: very fun. So whoever needs the buttons, go ahead and 663 00:34:40,840 --> 00:34:41,680 Speaker 3: set it up. Yeah. 664 00:34:41,840 --> 00:34:44,360 Speaker 1: I bet the most popular button would be the mute button. 665 00:34:44,960 --> 00:34:46,759 Speaker 1: Yeah really, well, thank you so much for joining us, 666 00:34:46,800 --> 00:34:47,239 Speaker 1: MS Hunger. 667 00:34:47,360 --> 00:34:49,760 Speaker 3: Yeah, thanks for having me. It is blast. 668 00:34:50,239 --> 00:34:53,040 Speaker 2: We know that, for example, a dog can smell things 669 00:34:53,160 --> 00:34:55,320 Speaker 2: much better than we can. We know that certain animals 670 00:34:55,360 --> 00:34:57,600 Speaker 2: can hear things that we cannot hear. We know that 671 00:34:57,680 --> 00:35:00,600 Speaker 2: others can see things that we cannot see. There's so 672 00:35:00,640 --> 00:35:04,520 Speaker 2: many abilities that are part of the natural kingdom the 673 00:35:04,600 --> 00:35:09,080 Speaker 2: humans do not quite well. Imagine you're like looking at 674 00:35:09,080 --> 00:35:12,319 Speaker 2: the world in which there's an infinite amount of possibility 675 00:35:12,320 --> 00:35:15,200 Speaker 2: in terms of what animals can do. What if they 676 00:35:15,200 --> 00:35:19,440 Speaker 2: could tell you? Just imagine how different our sense of 677 00:35:19,800 --> 00:35:21,160 Speaker 2: being in this world would be. 678 00:35:21,440 --> 00:35:24,600 Speaker 1: So if we could communicate with them, they could tell us. 679 00:35:24,680 --> 00:35:27,080 Speaker 2: That's the dream, right? What does an elephant know? What 680 00:35:27,120 --> 00:35:29,319 Speaker 2: does the dog know? What does a lion know? What 681 00:35:29,360 --> 00:35:31,279 Speaker 2: does a whale know that we don't know? 682 00:35:31,600 --> 00:35:34,120 Speaker 1: Not? Just what can we learn about them, but what 683 00:35:34,160 --> 00:35:35,239 Speaker 1: can we learn from them? 684 00:35:35,480 --> 00:35:37,600 Speaker 2: What can we learn from them? And how does that 685 00:35:37,920 --> 00:35:41,760 Speaker 2: change es? And so that's my dream. 686 00:35:41,880 --> 00:35:44,480 Speaker 1: All right. We hope you enjoyed that. Please tell your 687 00:35:44,520 --> 00:35:48,240 Speaker 1: dog or cat that I said hi. Thanks for joining us, 688 00:35:48,800 --> 00:35:55,480 Speaker 1: See you next time. You've been listening to Science Stuff. 689 00:35:55,719 --> 00:35:59,840 Speaker 1: Production of iHeartRadio, written and produced by me or Yhm, 690 00:36:00,440 --> 00:36:04,359 Speaker 1: edited by Rose Seguda, Executive producer Jerry Rowland, and audio 691 00:36:04,400 --> 00:36:07,480 Speaker 1: engineer and mixer Kasey Peckram. And you can follow me 692 00:36:07,560 --> 00:36:10,600 Speaker 1: on social media. Just search for PhD Comics and the 693 00:36:10,680 --> 00:36:13,319 Speaker 1: name of your favorite platform. Be sure to subscribe to 694 00:36:13,400 --> 00:36:16,719 Speaker 1: Sign Stuff on the iHeartRadio app, Apple Podcasts, or wherever 695 00:36:16,800 --> 00:36:19,920 Speaker 1: you get your podcasts, and please tell your friends we'll 696 00:36:20,000 --> 00:36:22,160 Speaker 1: be back next Wednesday with another episode.