1 00:00:00,240 --> 00:00:28,080 Speaker 1: Ridiculous History is a production of I Heart Radio. Wilberg. 2 00:00:28,560 --> 00:00:31,680 Speaker 1: Welcome back to the show Ridiculous Historians. As always, thank 3 00:00:31,720 --> 00:00:35,680 Speaker 1: you so much for tuning in. This is part two 4 00:00:36,479 --> 00:00:40,800 Speaker 1: of our two part series on the strange, beautiful, touching, 5 00:00:41,120 --> 00:00:46,360 Speaker 1: cinematic and hoax written story of Clever Hans, available on 6 00:00:46,520 --> 00:00:51,840 Speaker 1: video on demand in December, starring Daniel day Lewis as 7 00:00:52,040 --> 00:00:56,400 Speaker 1: Older Hans, Finn wolf Heard as younger Hans, um Gary 8 00:00:56,440 --> 00:01:02,560 Speaker 1: Oldman as the Professor Easten, Yes, yes, indeed, and who 9 00:01:02,560 --> 00:01:08,440 Speaker 1: else who do we say, Christoph Vaults as his nemesis, folks, 10 00:01:09,000 --> 00:01:13,160 Speaker 1: Let's get to it. Of course, there's gonna be skeptics saying, 11 00:01:13,800 --> 00:01:16,480 Speaker 1: come on, guys, it's a horse. There's gotta be where's 12 00:01:16,480 --> 00:01:19,559 Speaker 1: the gimmick, where's the twist? We gotta find this because again, 13 00:01:19,600 --> 00:01:22,039 Speaker 1: like to your point been, you know, some people like 14 00:01:22,160 --> 00:01:25,000 Speaker 1: this as kind of like a light bit of entertainment, 15 00:01:25,040 --> 00:01:27,280 Speaker 1: But if you really get down to the nitty gritty 16 00:01:27,319 --> 00:01:29,880 Speaker 1: of what this might mean for us as a species, 17 00:01:30,760 --> 00:01:32,840 Speaker 1: that's when things start to get a little heavy. So 18 00:01:32,920 --> 00:01:38,360 Speaker 1: there was a commission assembled, the Hans Commission, because psychologists, 19 00:01:38,440 --> 00:01:42,640 Speaker 1: zoologists and other experts in different fields that had you know, 20 00:01:42,760 --> 00:01:46,119 Speaker 1: something to gain or lose from this being the real deal. 21 00:01:46,480 --> 00:01:50,920 Speaker 1: Were assembled um studies and animal cognition. Uh and and 22 00:01:50,960 --> 00:01:54,080 Speaker 1: there you know the way they process information. We're not 23 00:01:54,240 --> 00:01:58,200 Speaker 1: really a thing. So this was very much looked at 24 00:01:58,240 --> 00:02:01,760 Speaker 1: as an opportunity to kind of figure out how far 25 00:02:01,880 --> 00:02:04,440 Speaker 1: this actually went and was it real. Yeah, and this 26 00:02:04,480 --> 00:02:07,960 Speaker 1: is where we introduce see Lloyd Morgan, one of the 27 00:02:08,000 --> 00:02:11,840 Speaker 1: more skeptical people in the crowd. See Lloyd Morgan is 28 00:02:12,000 --> 00:02:16,040 Speaker 1: a British psychologist that is responsible for something known as 29 00:02:16,240 --> 00:02:21,360 Speaker 1: Morgan's cannon. This is a fundamental sort of precept of 30 00:02:22,000 --> 00:02:27,519 Speaker 1: psychology comparative animal psychology. See Lloyd Morgan says in new 31 00:02:27,600 --> 00:02:31,520 Speaker 1: cases in animal activity to be interpreting in terms of 32 00:02:31,639 --> 00:02:38,959 Speaker 1: higher psychological processes, because he thinks higher mental abilities can 33 00:02:39,040 --> 00:02:44,480 Speaker 1: only be remotely considered as explanations if faculties that are 34 00:02:44,639 --> 00:02:48,160 Speaker 1: lower in the scale of evolution and development cannot explain it. 35 00:02:48,520 --> 00:02:51,400 Speaker 1: So he's saying, like, before you say that this horse 36 00:02:51,880 --> 00:02:55,160 Speaker 1: can think and can read, you need to prove that 37 00:02:55,200 --> 00:02:58,440 Speaker 1: the horse is not doing all of the other things 38 00:02:58,480 --> 00:03:01,280 Speaker 1: that we know a horse can do, like be trained, 39 00:03:01,600 --> 00:03:05,240 Speaker 1: for example. Uh. And that's why the German Board of 40 00:03:05,360 --> 00:03:09,480 Speaker 1: education starts, you know, as you said, nol, the Hans Commission. 41 00:03:09,760 --> 00:03:12,960 Speaker 1: The Hans Commission is like I want to see a 42 00:03:13,000 --> 00:03:17,679 Speaker 1: movie where they're super heroes. Oh, it's a real rugus gallery, dude, 43 00:03:17,720 --> 00:03:20,280 Speaker 1: give it to us. Yeah, we've got a veterinarian, we've 44 00:03:20,280 --> 00:03:24,359 Speaker 1: got a circus manager, a calvary officer, a gaggle of 45 00:03:24,440 --> 00:03:28,639 Speaker 1: school teachers, and the director of the zoological gardens kind 46 00:03:28,680 --> 00:03:33,480 Speaker 1: of like the the boss of the Berlin Zoo exactly. Uh. 47 00:03:33,480 --> 00:03:38,160 Speaker 1: And so they have hearings, right, Um, they hear witnesses, 48 00:03:38,280 --> 00:03:44,000 Speaker 1: they observe the horses kind of routines. And in nineteen 49 00:03:44,200 --> 00:03:49,600 Speaker 1: o four, the conclusion of the Hans Commission says that 50 00:03:49,640 --> 00:03:55,680 Speaker 1: there were no tricks or secret signals involved in Hans's performance, 51 00:03:55,720 --> 00:04:02,360 Speaker 1: and that they believe that his ability, his display of 52 00:04:02,920 --> 00:04:08,680 Speaker 1: cognition and intelligence of human level, were in fact legit. Yeah, 53 00:04:08,880 --> 00:04:11,560 Speaker 1: they double that. That's not you know, that's not the 54 00:04:11,600 --> 00:04:15,080 Speaker 1: answer that most people would expect, right we We would 55 00:04:15,080 --> 00:04:17,800 Speaker 1: not imagine that all these experts would get together and 56 00:04:17,880 --> 00:04:23,560 Speaker 1: conclude yep, no, horses. Horses are basically teenagers without thumbs. 57 00:04:23,600 --> 00:04:25,840 Speaker 1: That is what a horse is. Now, they are all 58 00:04:25,920 --> 00:04:28,000 Speaker 1: kinds of questions we have to answer should we still 59 00:04:28,040 --> 00:04:31,919 Speaker 1: eat them? Is it slavery? Uh? If we use a 60 00:04:32,000 --> 00:04:35,400 Speaker 1: horse on a farm, things like that. And this is 61 00:04:35,440 --> 00:04:41,280 Speaker 1: where we meet one person who's not happy with the commission. 62 00:04:41,640 --> 00:04:45,080 Speaker 1: This guy is functioning kind of like a conspiracy theorist 63 00:04:45,400 --> 00:04:49,800 Speaker 1: in the post Hans Commission world. He's a psychologist. Noel, 64 00:04:49,800 --> 00:04:51,760 Speaker 1: I'll probably need your help with this name. I'm gonna 65 00:04:51,800 --> 00:04:57,760 Speaker 1: defer to your German aptitudes here. Oscar funks Yeah, funks. Yeah, 66 00:04:57,800 --> 00:05:01,640 Speaker 1: the p is silent p f u mgst Oscar funksts. 67 00:05:02,120 --> 00:05:03,960 Speaker 1: I did kind of make a piece down there because 68 00:05:03,960 --> 00:05:06,880 Speaker 1: it's fun. But yeah. He's a psychologist who worked in 69 00:05:06,960 --> 00:05:10,000 Speaker 1: a lab, one of the labs headed by one of 70 00:05:10,040 --> 00:05:12,000 Speaker 1: the commission members. So he got way to this and 71 00:05:12,120 --> 00:05:16,480 Speaker 1: was like, NAHOI this is horsepucky. Literally, he decided to 72 00:05:16,520 --> 00:05:18,599 Speaker 1: get to the bottom of this further because he wasn't 73 00:05:18,640 --> 00:05:21,040 Speaker 1: having it, which is interesting because your right bend, like 74 00:05:21,279 --> 00:05:25,200 Speaker 1: at this point the matter is closed. He's basically you know, 75 00:05:25,600 --> 00:05:29,159 Speaker 1: boxing windmills right at this point. Um, And he looks 76 00:05:29,200 --> 00:05:31,839 Speaker 1: like a crazy person because they have all these the brightest, 77 00:05:31,880 --> 00:05:35,560 Speaker 1: the best and brightest you know, horse experts in the 78 00:05:35,600 --> 00:05:39,360 Speaker 1: world have decided yeah, that that Hans is in fact 79 00:05:40,160 --> 00:05:44,160 Speaker 1: a very clever boy indeed. Uh. And also you gotta 80 00:05:44,200 --> 00:05:45,839 Speaker 1: wonder too, like how it came off was like, do 81 00:05:45,839 --> 00:05:48,600 Speaker 1: you really can't we just have nice things, you know Allscar, 82 00:05:49,040 --> 00:05:50,880 Speaker 1: can't you just leave well enough alone? But he couldn't 83 00:05:50,920 --> 00:05:55,360 Speaker 1: leave well enough alone indeed, But he know it's great 84 00:05:55,360 --> 00:05:58,360 Speaker 1: bed he designed some pretty clever experience himself because he 85 00:05:58,400 --> 00:06:01,080 Speaker 1: was also a clever boy. And and um, he wanted 86 00:06:01,080 --> 00:06:06,120 Speaker 1: to make sure that von Austin wasn't like feeding Hans 87 00:06:06,200 --> 00:06:09,640 Speaker 1: answers giving him secret hand signals, which you know, the 88 00:06:09,680 --> 00:06:13,160 Speaker 1: Commission had already addressed that no hand signals were a 89 00:06:13,160 --> 00:06:14,800 Speaker 1: part of it. But he wanted to be doubly sure, 90 00:06:14,839 --> 00:06:17,960 Speaker 1: so he removed von Austin from the situation and made 91 00:06:17,960 --> 00:06:20,640 Speaker 1: sure that he wasn't the one asking the questions. So 92 00:06:20,680 --> 00:06:22,720 Speaker 1: he got that all out of the way. This is 93 00:06:22,760 --> 00:06:25,599 Speaker 1: when he gets really interesting and really smart. Uh. And like, 94 00:06:25,600 --> 00:06:27,720 Speaker 1: I don't even know how he thought of this, or 95 00:06:28,080 --> 00:06:30,520 Speaker 1: Havan Austin thought of this in the first place, but 96 00:06:30,880 --> 00:06:34,240 Speaker 1: he decided that maybe it was possible the horse was 97 00:06:34,279 --> 00:06:40,960 Speaker 1: getting something in line with like nonverbal context clues or 98 00:06:41,040 --> 00:06:46,360 Speaker 1: like you know, tone change or body language, um posture, 99 00:06:46,520 --> 00:06:50,880 Speaker 1: even uh the way you know, inflection of words. So 100 00:06:51,160 --> 00:06:53,320 Speaker 1: in order to do that, he made sure that the 101 00:06:53,400 --> 00:06:56,200 Speaker 1: person asking the question did not know the answer to 102 00:06:56,240 --> 00:06:59,080 Speaker 1: the question, or at least the way that it was worded, etcetera. 103 00:06:59,160 --> 00:07:00,880 Speaker 1: Maybe you could unpas that a little bit better, but 104 00:07:00,920 --> 00:07:03,560 Speaker 1: I'm sort of not quite seeing how that would help. 105 00:07:03,920 --> 00:07:07,640 Speaker 1: Here's what he did, Uh, he explains the procedure of 106 00:07:07,680 --> 00:07:10,960 Speaker 1: the test. We have this as a direct quote from Fungst. 107 00:07:12,000 --> 00:07:16,520 Speaker 1: He says, Van Osten would whisper number in the horse's ear, 108 00:07:16,880 --> 00:07:21,040 Speaker 1: just like twenty, right, and nobody else would have heard 109 00:07:21,080 --> 00:07:28,840 Speaker 1: that number. Then Foodst would whisper another number in Hans's ear, 110 00:07:29,480 --> 00:07:33,880 Speaker 1: and for any centiphiles here in the film adaptation, I like, 111 00:07:34,040 --> 00:07:37,320 Speaker 1: I really want us to have von oast and whispering 112 00:07:37,320 --> 00:07:40,200 Speaker 1: in like one ear and then Foodst coming in in 113 00:07:40,280 --> 00:07:45,480 Speaker 1: the other ear. For the post I want Hans center frame. 114 00:07:45,960 --> 00:07:47,920 Speaker 1: And then maybe we could do like a beautiful mind 115 00:07:48,280 --> 00:07:52,120 Speaker 1: kind of special effect here. Uh, You're You're welcome, Hollywood. 116 00:07:52,160 --> 00:07:54,200 Speaker 1: And what would the movie be called? Clever Hans or 117 00:07:54,320 --> 00:07:57,320 Speaker 1: just go for the gut punch with just Hans. I 118 00:07:57,360 --> 00:07:59,840 Speaker 1: don't know yet, you know, I think there's like a 119 00:08:00,000 --> 00:08:04,800 Speaker 1: beautiful hoof beautiful mind kind of rip off. Maybe it's 120 00:08:04,880 --> 00:08:06,520 Speaker 1: um the way, what do you got? You got one? 121 00:08:06,600 --> 00:08:08,880 Speaker 1: You know, Casey's got Casey made a cake, he made 122 00:08:08,880 --> 00:08:11,200 Speaker 1: a face. I really just like Hans and like all 123 00:08:11,320 --> 00:08:15,160 Speaker 1: like a very seriously considered fond and like like a 124 00:08:15,200 --> 00:08:19,920 Speaker 1: December opening. Yes, yeah, I really like that. Um. Horse 125 00:08:19,960 --> 00:08:22,560 Speaker 1: sense is an expression that you hear sometimes, but I 126 00:08:22,560 --> 00:08:24,560 Speaker 1: feel like that takes it in a completely different direction. 127 00:08:24,640 --> 00:08:27,440 Speaker 1: So yeah, horse Sense is maybe a little more of 128 00:08:27,440 --> 00:08:30,000 Speaker 1: a fun movie. And I think we're talking about serious 129 00:08:30,040 --> 00:08:36,440 Speaker 1: cinema here, right. Uh, gotta gotta Gary Oldman as the 130 00:08:36,480 --> 00:08:41,640 Speaker 1: horse as the horse, No, Daniel Daniel day Lewis as 131 00:08:41,679 --> 00:08:45,240 Speaker 1: the horse as the horse his greatest performance. Yes, And 132 00:08:45,440 --> 00:08:48,200 Speaker 1: and Gary Oldman as von Austin for sure. Who would 133 00:08:48,240 --> 00:08:51,000 Speaker 1: be our boy Funks who's kind of the Maybe that 134 00:08:51,040 --> 00:08:54,400 Speaker 1: would be Um, who's the guy from Inglorious Bastards? Christoph 135 00:08:54,440 --> 00:08:57,960 Speaker 1: Waltz would be funkst Gary Oldman as von Austin and 136 00:08:58,080 --> 00:09:01,120 Speaker 1: Daniel day Lewis as Hans. I like it. I like it. 137 00:09:01,240 --> 00:09:04,160 Speaker 1: Let's let's continue. Now picture those amazing actors in your 138 00:09:04,160 --> 00:09:12,240 Speaker 1: head when we talk about this test. So since each 139 00:09:12,480 --> 00:09:17,240 Speaker 1: experiment or only knew the number they were individually saying 140 00:09:17,360 --> 00:09:22,440 Speaker 1: into Hans's ear. That would mean logically, if Hans could add, 141 00:09:22,880 --> 00:09:25,600 Speaker 1: he would be the only person who knew the answer, 142 00:09:25,800 --> 00:09:30,000 Speaker 1: the only horse person who knew the answer. So in 143 00:09:30,240 --> 00:09:34,240 Speaker 1: thirty one test when they did that method and then 144 00:09:34,280 --> 00:09:39,040 Speaker 1: they checked back out of those thirty one tests, Hans 145 00:09:39,440 --> 00:09:43,160 Speaker 1: was incorrect most of the time. He was only right 146 00:09:43,240 --> 00:09:46,720 Speaker 1: three times. But when they did another thirty one test 147 00:09:47,120 --> 00:09:50,960 Speaker 1: where both of the experimenters knew the numbers that they 148 00:09:50,960 --> 00:09:55,120 Speaker 1: were giving to the horse, he was correct twenty nine 149 00:09:55,160 --> 00:09:58,440 Speaker 1: times out of thirty one. So something's happening. If he's 150 00:09:58,480 --> 00:10:01,680 Speaker 1: really doing math, it's would not matter that the two 151 00:10:01,720 --> 00:10:05,959 Speaker 1: people suggesting numbers don't know the numbers the other person suggesting. 152 00:10:06,080 --> 00:10:07,760 Speaker 1: Does that make sense? It does make sense, but I 153 00:10:07,760 --> 00:10:11,760 Speaker 1: still quite understand how von Austin pulled it off. That's 154 00:10:11,800 --> 00:10:18,040 Speaker 1: some pretty genius, uh, you know, subtle kind of trickery there, right. So, 155 00:10:18,160 --> 00:10:22,079 Speaker 1: folks also found that when a questioner stood farther away 156 00:10:22,720 --> 00:10:25,520 Speaker 1: uh than than Hans was used to um, he had 157 00:10:25,559 --> 00:10:27,920 Speaker 1: trouble correctly answering the questions as well, which you know, 158 00:10:27,960 --> 00:10:30,360 Speaker 1: you could just achieve these getting yelled at a lot 159 00:10:30,400 --> 00:10:32,240 Speaker 1: in his ear holes. I mean maybe that the old 160 00:10:32,280 --> 00:10:34,560 Speaker 1: boys like lost a little bit of hearing. By this point. 161 00:10:34,720 --> 00:10:36,319 Speaker 1: I kind of feel bad for Hans at this point, 162 00:10:36,360 --> 00:10:37,959 Speaker 1: don't you guys. He seems like he's really getting put 163 00:10:38,000 --> 00:10:40,240 Speaker 1: through the wringer, you know. More and more, I'm thinking 164 00:10:40,280 --> 00:10:43,559 Speaker 1: maybe a younger actor for the horse, maybe like Finn 165 00:10:43,559 --> 00:10:47,360 Speaker 1: wolf Hard from Stranger Things. Well maybe no, maybe we 166 00:10:47,360 --> 00:10:52,680 Speaker 1: can have him play young Hans, and then the Lewis 167 00:10:52,679 --> 00:10:54,880 Speaker 1: steps said and plays old Hall. I actually like thin 168 00:10:54,960 --> 00:10:57,320 Speaker 1: wolf Hard as a young Daniel day Lewis. They have 169 00:10:57,360 --> 00:11:01,080 Speaker 1: a similar kind of uh kind of makes sream like, 170 00:11:01,160 --> 00:11:03,320 Speaker 1: you know, look to them. I don't know. Yeah, yeah, 171 00:11:03,440 --> 00:11:06,600 Speaker 1: we want the life of the horse entire anyway, Yeah, 172 00:11:06,640 --> 00:11:11,080 Speaker 1: you're right. No, the he quick foods quickly finds that 173 00:11:11,760 --> 00:11:16,120 Speaker 1: every test he conducts that has a level of scientific 174 00:11:16,200 --> 00:11:22,040 Speaker 1: rigor ultimately indicates that Hans is not doing this math 175 00:11:22,520 --> 00:11:25,880 Speaker 1: on his own. And when they conduct tests that are 176 00:11:25,920 --> 00:11:34,240 Speaker 1: controlling for possible intervening variables, Hans fails miserably. His his 177 00:11:34,360 --> 00:11:37,600 Speaker 1: memory is found to be average as far as what 178 00:11:37,640 --> 00:11:40,440 Speaker 1: we know about horses at that time and now, so 179 00:11:40,640 --> 00:11:45,120 Speaker 1: it's it seems cognitively impossible that Hans can be as 180 00:11:45,160 --> 00:11:48,480 Speaker 1: clever as we are being told he is. And what 181 00:11:48,559 --> 00:11:52,040 Speaker 1: they find, at least what Foods finds in his investigation here, 182 00:11:52,440 --> 00:11:58,400 Speaker 1: is that Hans seems entirely dependent on external stimuli from 183 00:11:58,520 --> 00:12:02,480 Speaker 1: whomever is asking the question. So he's maybe not great 184 00:12:02,600 --> 00:12:06,480 Speaker 1: at doing math, but he's top notch at reading people, 185 00:12:06,760 --> 00:12:11,319 Speaker 1: just like you know, like a a cold read psychic exactly. 186 00:12:11,360 --> 00:12:14,000 Speaker 1: But I still don't quite understand the how you would 187 00:12:14,080 --> 00:12:19,280 Speaker 1: use external stimuli to like get him to seemingly, you know, uh, 188 00:12:19,320 --> 00:12:22,840 Speaker 1: independently solved like complex math problems. But I think we've 189 00:12:22,840 --> 00:12:25,079 Speaker 1: got a little bit more information that might help clear 190 00:12:25,120 --> 00:12:29,680 Speaker 1: some of that up. So Funks noticed that the questioner's 191 00:12:29,800 --> 00:12:33,480 Speaker 1: everything from from breathing to posture to facial ticks and 192 00:12:33,559 --> 00:12:38,760 Speaker 1: expressions and eyebrow you know, tension, things like that, Um, 193 00:12:38,960 --> 00:12:44,600 Speaker 1: they changed each time the hoof was tapped. So the 194 00:12:44,600 --> 00:12:48,479 Speaker 1: way I'm reading this is that the horse was observing 195 00:12:48,640 --> 00:12:52,280 Speaker 1: the changes of all of those external stimuli. Um. And 196 00:12:52,280 --> 00:12:54,600 Speaker 1: when we say external stimula, we're not talking about somebody 197 00:12:54,640 --> 00:12:57,160 Speaker 1: feeding him the right answer. We're literally talking about the 198 00:12:57,200 --> 00:13:01,800 Speaker 1: horse observing the question er, uh, with every clop of 199 00:13:01,840 --> 00:13:05,920 Speaker 1: the hoof and interpreting when um, he had reached the 200 00:13:06,000 --> 00:13:09,240 Speaker 1: correct number of clops, right, And because there's such a 201 00:13:09,320 --> 00:13:11,640 Speaker 1: build up, especially like you know, let's say the answer 202 00:13:11,720 --> 00:13:14,600 Speaker 1: was like twenty or something. I mean, you could very 203 00:13:14,679 --> 00:13:17,280 Speaker 1: quickly realize when you know, And we talked about that 204 00:13:17,360 --> 00:13:20,839 Speaker 1: tension building earlier, right even for an audience, that who oh, 205 00:13:21,000 --> 00:13:22,640 Speaker 1: is this gonna be the one? Is this gonna be 206 00:13:22,679 --> 00:13:25,560 Speaker 1: the one? And then to say, okay, he's there, then 207 00:13:25,760 --> 00:13:28,400 Speaker 1: there's a relaxing I don't know exactly what this horse 208 00:13:28,440 --> 00:13:30,400 Speaker 1: was looking at, but I think I'm reading that correctly. 209 00:13:30,400 --> 00:13:33,960 Speaker 1: Would would you agree? Ben? Yeah? Yeah, nineteen, you see 210 00:13:34,000 --> 00:13:35,960 Speaker 1: the tension billing for the horse, and then you get 211 00:13:36,000 --> 00:13:40,880 Speaker 1: to twenty, and then people probably signal their delight too early. 212 00:13:41,000 --> 00:13:44,520 Speaker 1: They're like, wow, we got to twenty. Wow, you know 213 00:13:44,600 --> 00:13:46,400 Speaker 1: what I mean. But the horse would have kept doing 214 00:13:46,440 --> 00:13:50,360 Speaker 1: that to thirty two or forty three. It's just it's 215 00:13:50,400 --> 00:13:55,480 Speaker 1: it's tapping until it sees people happy, basically, is the argument. 216 00:13:55,840 --> 00:14:00,520 Speaker 1: And so Foods learns to read these bodies use the 217 00:14:00,640 --> 00:14:04,760 Speaker 1: same way that he imagines Hans is, and so Foods 218 00:14:04,880 --> 00:14:07,960 Speaker 1: puts himself in the horse's position, which is great for 219 00:14:08,000 --> 00:14:11,600 Speaker 1: the film and he uh, he carries out tests and 220 00:14:11,600 --> 00:14:13,720 Speaker 1: he says, okay, I'll play the part of the horse. 221 00:14:13,840 --> 00:14:18,880 Speaker 1: Casey to your point, he's working on his horse sense, right. 222 00:14:19,840 --> 00:14:22,560 Speaker 1: The thing that he finds is that he can do 223 00:14:22,600 --> 00:14:25,480 Speaker 1: these tests too, and he doesn't necessarily have to know math. 224 00:14:25,720 --> 00:14:28,240 Speaker 1: He just has to kind of tap until he sees 225 00:14:28,280 --> 00:14:33,200 Speaker 1: people reacting and then boom. Uh. And what's the reason 226 00:14:33,280 --> 00:14:38,000 Speaker 1: this is working so well is because people are unaware 227 00:14:38,080 --> 00:14:41,120 Speaker 1: that they're expressing these cues. This is a big problem 228 00:14:41,280 --> 00:14:46,200 Speaker 1: animal training and cognition experiments even today. Uh, you know, 229 00:14:46,360 --> 00:14:49,760 Speaker 1: von Ostin, I think we've established he's not some flam 230 00:14:49,760 --> 00:14:53,640 Speaker 1: flam guy. He's not a con artist. He probably doesn't 231 00:14:53,680 --> 00:14:57,160 Speaker 1: know the signals that he's giving Hans. Can I interject 232 00:14:57,320 --> 00:15:01,120 Speaker 1: one little bit of Hollywood ization for movie adaptation here? 233 00:15:01,960 --> 00:15:05,920 Speaker 1: I would put forth that Funks gets so obsessed with 234 00:15:06,000 --> 00:15:08,960 Speaker 1: this and it's starting to go a little mad. He 235 00:15:09,080 --> 00:15:12,960 Speaker 1: dresses up in a horse costume while doing these tests 236 00:15:13,280 --> 00:15:15,800 Speaker 1: so he can really put himself in the mindset of 237 00:15:15,840 --> 00:15:19,360 Speaker 1: clever Hans. That's what I'm thinking. I'm picturing, you know, 238 00:15:19,480 --> 00:15:24,760 Speaker 1: like a confrontational in front of the bathroom mirror scene 239 00:15:24,920 --> 00:15:29,720 Speaker 1: where he's like putting a rioting champ in his mouth. 240 00:15:30,680 --> 00:15:34,720 Speaker 1: He's got some homemade ears. Uh yeah, I think we're 241 00:15:34,760 --> 00:15:38,320 Speaker 1: on the same page. Now. What's fascinating about this, which 242 00:15:38,360 --> 00:15:41,960 Speaker 1: is pretty cool as we're as we're building twere epilogue here, 243 00:15:42,440 --> 00:15:47,040 Speaker 1: is that Funds successfully proved that Hans was not in 244 00:15:47,120 --> 00:15:55,360 Speaker 1: fact doing math. How Whoever, he accidentally proved that Hans 245 00:15:56,000 --> 00:15:59,920 Speaker 1: was incredibly intelligent in one aspect and one of bill 246 00:16:00,000 --> 00:16:03,080 Speaker 1: to you, in one skill set, which was reading people. 247 00:16:03,400 --> 00:16:06,920 Speaker 1: He was better at reading people than foodst was, then 248 00:16:07,120 --> 00:16:10,040 Speaker 1: Ron Ousten was. Then most of the Germans in the crowd. 249 00:16:10,080 --> 00:16:13,040 Speaker 1: You think they would have then immediately recruited him to 250 00:16:13,120 --> 00:16:16,080 Speaker 1: be in like interrogation rooms, you know, when they're like 251 00:16:16,120 --> 00:16:19,280 Speaker 1: trying to figure out if like a purpose lying, they 252 00:16:19,280 --> 00:16:22,120 Speaker 1: would just consult the horse, bring the horse, bringing in 253 00:16:22,160 --> 00:16:31,000 Speaker 1: the horse. So essentially, I mean, folks proved what he 254 00:16:31,040 --> 00:16:33,320 Speaker 1: set out to prove, but he actually found a little 255 00:16:33,360 --> 00:16:36,560 Speaker 1: bit of magic along the way. That's the thing, guys, 256 00:16:36,600 --> 00:16:40,320 Speaker 1: This story isn't Yeah, this story isn't completely devoid of 257 00:16:40,360 --> 00:16:43,320 Speaker 1: like this horse was very special and to your point, 258 00:16:43,400 --> 00:16:46,000 Speaker 1: Ben von Austin probably didn't know that. He really just 259 00:16:46,040 --> 00:16:47,760 Speaker 1: thought he had a special boy on his hand, a 260 00:16:47,880 --> 00:16:50,840 Speaker 1: real clever Hans. And then what folks determined was, no, 261 00:16:51,080 --> 00:16:54,560 Speaker 1: he was not intelligent like a human, but sure as 262 00:16:54,600 --> 00:16:56,400 Speaker 1: hell was more observant than a lot of them, because 263 00:16:56,440 --> 00:16:57,880 Speaker 1: that's something I think we could all get better at, 264 00:16:57,880 --> 00:17:01,080 Speaker 1: as being observants of our surrounding and of like being 265 00:17:01,080 --> 00:17:03,960 Speaker 1: able to read the room. And Hans was an absolute 266 00:17:04,000 --> 00:17:07,920 Speaker 1: expert at that. So this is where I take poetic license. Um, 267 00:17:08,119 --> 00:17:11,119 Speaker 1: we're gonna tell you what actually happens in the real world. 268 00:17:11,200 --> 00:17:13,879 Speaker 1: And then i'd like, if if you guys will indulge me, 269 00:17:14,200 --> 00:17:17,919 Speaker 1: tell you what I see happening in our film the 270 00:17:18,040 --> 00:17:23,600 Speaker 1: December release Hans. So despite the fact that foods pretty 271 00:17:23,680 --> 00:17:28,520 Speaker 1: much proves what's happening, Clever Hans remains a sensation. Von 272 00:17:28,600 --> 00:17:33,480 Speaker 1: Osten continues touring this amazing horse throughout the country of Germany. 273 00:17:33,800 --> 00:17:37,640 Speaker 1: He's still pulling crowds, getting butts and seats, etcetera. Uh, 274 00:17:38,119 --> 00:17:41,000 Speaker 1: what's one thing that I think is very interesting? Von 275 00:17:41,080 --> 00:17:46,080 Speaker 1: Osten never charges for these exhibitions. He genuinely wants to 276 00:17:46,240 --> 00:17:50,000 Speaker 1: share the gift of Clever Hans with the world, and 277 00:17:50,160 --> 00:17:54,480 Speaker 1: von Osten does this until he passes away in nineteen nine, 278 00:17:55,000 --> 00:18:00,399 Speaker 1: and Hans goes through a series of owners. Ultimately, he 279 00:18:00,480 --> 00:18:03,960 Speaker 1: is drafted by Germany to serve in World War One 280 00:18:04,160 --> 00:18:07,120 Speaker 1: in nineteen fourteen, which they did not call World War 281 00:18:07,200 --> 00:18:12,040 Speaker 1: one at that time. God, this is taking a harrowing turn. 282 00:18:12,800 --> 00:18:16,520 Speaker 1: So like this horse wasn't used to being ridden. He 283 00:18:16,680 --> 00:18:19,359 Speaker 1: was like a show horse. Like beyond that, he was 284 00:18:19,400 --> 00:18:23,560 Speaker 1: like a much guarded, you know, piece, like a national treasure. 285 00:18:23,920 --> 00:18:25,160 Speaker 1: And now all of a sudden, what do you mean, 286 00:18:25,200 --> 00:18:27,679 Speaker 1: like so he's they're literally riding him into battle? Like 287 00:18:27,720 --> 00:18:29,960 Speaker 1: what what? What are they doing with Hans? That he 288 00:18:30,000 --> 00:18:34,239 Speaker 1: would potentially, as legend, would have it pass away on 289 00:18:34,280 --> 00:18:36,440 Speaker 1: the field of battle? What were they doing with him? 290 00:18:36,520 --> 00:18:39,480 Speaker 1: And he could have been he could have been riding horse. 291 00:18:39,560 --> 00:18:42,400 Speaker 1: Maybe not he was in raping stallion, but he could 292 00:18:42,440 --> 00:18:46,720 Speaker 1: have also been pulling munitions or wagons or food supply trains, 293 00:18:47,000 --> 00:18:51,400 Speaker 1: things like that. There are several different positions he could 294 00:18:51,440 --> 00:18:54,240 Speaker 1: have filled as a military horse. But you're right. He 295 00:18:54,320 --> 00:18:58,880 Speaker 1: is rumored to have been killed in action in nineteen sixteen. However, 296 00:18:59,560 --> 00:19:02,320 Speaker 1: he lived is on today. He's more famous, if you 297 00:19:02,320 --> 00:19:04,439 Speaker 1: think about it, than a lot of humans who are 298 00:19:04,480 --> 00:19:09,200 Speaker 1: alive when he was alive because Hans is in psychology 299 00:19:09,280 --> 00:19:13,639 Speaker 1: textbooks today. It's the clever Hans effect, named after this 300 00:19:13,720 --> 00:19:17,480 Speaker 1: horse and the idea. The clever Hans effect describes when 301 00:19:17,520 --> 00:19:21,800 Speaker 1: an experiment er gets seemingly correct answers from a an 302 00:19:21,840 --> 00:19:26,320 Speaker 1: animal or a human being by giving them unconscious cues, 303 00:19:26,800 --> 00:19:32,440 Speaker 1: and this creates a very convincing illusion of intelligent thoughts. 304 00:19:33,640 --> 00:19:36,800 Speaker 1: We've seen the clever Hans effect in drug sniffing dogs. 305 00:19:37,280 --> 00:19:40,400 Speaker 1: You've seen skeptics raise the specter of this effect when 306 00:19:40,440 --> 00:19:44,320 Speaker 1: they don't believe someone who says I've taught my primate 307 00:19:45,080 --> 00:19:49,679 Speaker 1: to speak and understand sign language to a you know, 308 00:19:49,920 --> 00:19:53,080 Speaker 1: a certain degree, or like this parrot isn't just repeating 309 00:19:53,119 --> 00:19:57,119 Speaker 1: what I say. It understands me. Good night, you'd be good. 310 00:19:57,160 --> 00:19:59,680 Speaker 1: I love you, that story, that kind of stuff. I'm 311 00:19:59,720 --> 00:20:01,199 Speaker 1: a good example from when I was a kid. I 312 00:20:01,280 --> 00:20:05,080 Speaker 1: distinctly remember being way too young to really be able 313 00:20:05,119 --> 00:20:08,480 Speaker 1: to read properly, but impressing my mom, making her think 314 00:20:08,520 --> 00:20:11,080 Speaker 1: that I was reading by just reciting one fish, two fish, 315 00:20:11,160 --> 00:20:13,239 Speaker 1: red fish, blue fish, and looking at the book as 316 00:20:13,240 --> 00:20:15,760 Speaker 1: though I were reading the words, but it was just memorization. 317 00:20:16,760 --> 00:20:18,760 Speaker 1: Totally had her going. She thought I was a genius. 318 00:20:18,880 --> 00:20:21,920 Speaker 1: She couldn't have been more wrong. Have you told her? No, dude, 319 00:20:21,920 --> 00:20:23,800 Speaker 1: I wanted to be proud, want my mommy to love me. Dude, 320 00:20:23,800 --> 00:20:27,440 Speaker 1: I'm not gonna shadow delusions now. It's too late for that. 321 00:20:27,520 --> 00:20:30,320 Speaker 1: I mean unless she listens to the podcast, which she does, 322 00:20:30,560 --> 00:20:34,879 Speaker 1: so sorry, mom, your your secret is uh is safe 323 00:20:34,920 --> 00:20:39,640 Speaker 1: with me and hopefully with our fellow ridiculous historians listening along. 324 00:20:39,880 --> 00:20:42,000 Speaker 1: We tease this earlier, and maybe this is a good 325 00:20:42,000 --> 00:20:44,720 Speaker 1: way for us to to begin wrapping up the story 326 00:20:44,720 --> 00:20:48,760 Speaker 1: of Hans, because although the horse has passed from this 327 00:20:48,880 --> 00:20:54,560 Speaker 1: mortal plane, Uh, the clever Hans effect remains a hallmark 328 00:20:54,720 --> 00:20:59,080 Speaker 1: of psychological thought. And we are learning so much more 329 00:20:59,160 --> 00:21:03,680 Speaker 1: about intelligence. It's we actually know relatively little about intelligence. 330 00:21:03,680 --> 00:21:07,200 Speaker 1: In the first place, We as a species still don't 331 00:21:07,240 --> 00:21:13,359 Speaker 1: have a super solid on definition of intelligence. And we 332 00:21:13,440 --> 00:21:16,280 Speaker 1: know that animals that we once thought were just you know, 333 00:21:16,359 --> 00:21:18,879 Speaker 1: like plain Jane kind of, it's an animal, what are 334 00:21:18,880 --> 00:21:21,320 Speaker 1: you gonna do? They turned out to be incredibly intelligent, 335 00:21:21,400 --> 00:21:23,200 Speaker 1: just maybe not in the same way as us. And 336 00:21:23,200 --> 00:21:25,400 Speaker 1: and then you know, like we mentioned before, like you mentioned, Ben, 337 00:21:25,480 --> 00:21:28,720 Speaker 1: that clever Hans effect lives on today in psychology. It's 338 00:21:28,720 --> 00:21:31,840 Speaker 1: something that's even been observed in drug sniffing dogs, where 339 00:21:31,880 --> 00:21:35,080 Speaker 1: like cues from the handler UH can be picked up 340 00:21:35,080 --> 00:21:38,520 Speaker 1: by dogs and resulting in like them signaling that you know, 341 00:21:38,640 --> 00:21:42,960 Speaker 1: there's drugs when that's not the case of the false positive. UM. 342 00:21:43,000 --> 00:21:46,080 Speaker 1: And here's another thing too, in terms of research. UH, 343 00:21:46,119 --> 00:21:48,720 Speaker 1: it turns out that there's some new research that has 344 00:21:49,000 --> 00:21:51,760 Speaker 1: recently come to light that would suggest that Funkst was 345 00:21:51,880 --> 00:21:57,120 Speaker 1: right and horses actually can read human expressions. UH. Psychologists 346 00:21:57,160 --> 00:22:02,119 Speaker 1: studied how twenty eight different horses reacted to seeing pictures 347 00:22:02,160 --> 00:22:06,639 Speaker 1: of positive versus negatively positive like big old grins and 348 00:22:06,720 --> 00:22:12,240 Speaker 1: negativism assuming like frowns UM and happy and angry photographs 349 00:22:12,240 --> 00:22:15,359 Speaker 1: of two unfamiliar male faces. And then they looked at 350 00:22:15,400 --> 00:22:19,080 Speaker 1: their spontaneous reactions to the photos without any training, and 351 00:22:19,160 --> 00:22:22,880 Speaker 1: found that when the horses looked at angry faces UH, 352 00:22:22,920 --> 00:22:25,879 Speaker 1: they used more of their left eye UM, which is 353 00:22:25,880 --> 00:22:30,159 Speaker 1: associated with perceiving negative stimuli. UM. They also had marked 354 00:22:30,359 --> 00:22:35,040 Speaker 1: increases in heart rate UM and also showed more stress 355 00:22:35,080 --> 00:22:39,159 Speaker 1: related behaviors. UH. And it was published on the tenth 356 00:22:39,160 --> 00:22:45,040 Speaker 1: of February Biology Letters. Yeah, so we the story of 357 00:22:45,560 --> 00:22:50,479 Speaker 1: intelligence in living things continues today. It hasn't really ended. 358 00:22:50,840 --> 00:22:55,120 Speaker 1: We know that further claims of animal intelligence are much 359 00:22:55,119 --> 00:22:59,400 Speaker 1: harder to dismiss than those of Clever Hawns. Like I, 360 00:22:59,400 --> 00:23:03,840 Speaker 1: I allude it to the brilliant parrot Alex, close associate 361 00:23:03,880 --> 00:23:08,640 Speaker 1: with the scientist Irene Pepperberg. Alex appeared to understand thousands 362 00:23:08,640 --> 00:23:13,119 Speaker 1: of words and syntax and grammar. Uh but and was 363 00:23:13,200 --> 00:23:15,280 Speaker 1: capable of doing a lot of things that Clever Hans 364 00:23:15,359 --> 00:23:18,680 Speaker 1: was purported to be capable of doing. But it's difficult 365 00:23:18,720 --> 00:23:22,360 Speaker 1: to dismiss these cases. Also, I'm just I know we're 366 00:23:22,400 --> 00:23:25,040 Speaker 1: going out where at the end of time. Corvids are amazing. 367 00:23:25,840 --> 00:23:29,560 Speaker 1: Octopuses are so massively intelligent. If they lived for more 368 00:23:29,600 --> 00:23:32,480 Speaker 1: than two years at a stretch, they would be running 369 00:23:32,640 --> 00:23:35,440 Speaker 1: some stuff. I just recently read did you know octopuses 370 00:23:35,760 --> 00:23:40,240 Speaker 1: have been documented building neighborhoods? True story? It doesn't surprise me. 371 00:23:40,320 --> 00:23:44,280 Speaker 1: Cephalopods never cease to amaze me. And so that's that's 372 00:23:44,280 --> 00:23:48,000 Speaker 1: where we are. That is the story of Clever Hans, 373 00:23:48,040 --> 00:23:53,760 Speaker 1: the real inspiration perhaps for Mr ed uh that is, 374 00:23:54,080 --> 00:23:57,280 Speaker 1: that is what actually happens with Clever Hans. Here's the 375 00:23:57,320 --> 00:23:59,360 Speaker 1: way I want the film to end, though, I want 376 00:23:59,400 --> 00:24:03,560 Speaker 1: the film to and with Hans appearing to go to 377 00:24:03,680 --> 00:24:07,440 Speaker 1: World War One. So Clever Hans gets drafted, but he's 378 00:24:07,480 --> 00:24:11,960 Speaker 1: too clever and he's actually working for like military intelligence, 379 00:24:12,160 --> 00:24:16,000 Speaker 1: but he's conflicted about it because he doesn't like playing 380 00:24:16,040 --> 00:24:18,520 Speaker 1: this role as you know, one of the bad guys. 381 00:24:18,920 --> 00:24:21,280 Speaker 1: And so I want Clever Hans to like fake his 382 00:24:21,400 --> 00:24:26,000 Speaker 1: death and then to emigrate to America where he picks 383 00:24:26,080 --> 00:24:30,159 Speaker 1: up a job in Hollywood, and the post credit like 384 00:24:30,280 --> 00:24:33,639 Speaker 1: mid credit stinger is his first appearance as Mr ed 385 00:24:33,800 --> 00:24:36,720 Speaker 1: Boom cut print. I think it's like we're building an 386 00:24:36,720 --> 00:24:39,760 Speaker 1: extended Hans universe here. I love it so much, Ben, 387 00:24:39,800 --> 00:24:42,560 Speaker 1: and I can't wait. I think this should be part 388 00:24:42,600 --> 00:24:45,399 Speaker 1: of the extended r This History universe that includes our 389 00:24:45,720 --> 00:24:49,480 Speaker 1: reboot of the Craft involving Fudge. And then we've got 390 00:24:49,520 --> 00:24:53,639 Speaker 1: this Clever Hans biopic starting a powerhouse cast and Daniel 391 00:24:53,680 --> 00:24:57,600 Speaker 1: de Lewis coming back again again again from retirement to 392 00:24:57,680 --> 00:25:00,320 Speaker 1: give a powerhouse performance as a as a who that 393 00:25:00,400 --> 00:25:03,040 Speaker 1: can do math or can he? You'll have to watch 394 00:25:03,040 --> 00:25:05,879 Speaker 1: the movie to find that or help us make the 395 00:25:05,920 --> 00:25:09,840 Speaker 1: movie if we want to hear your suggestions. Thank you, 396 00:25:09,880 --> 00:25:12,439 Speaker 1: as always so much for tuning in. We hope that 397 00:25:12,480 --> 00:25:15,919 Speaker 1: you enjoyed today's episode. Uh, this is my excuse to 398 00:25:15,960 --> 00:25:18,280 Speaker 1: ask for pictures of your pets because I love to 399 00:25:18,320 --> 00:25:20,560 Speaker 1: see them. Let us know if your pet has any 400 00:25:20,720 --> 00:25:27,320 Speaker 1: idiosyncrasies or hidden cognitive talents. Thanks as always to Gabe Lousia, 401 00:25:27,600 --> 00:25:32,040 Speaker 1: and thanks to you, Casey Pegram Casey, if you had 402 00:25:32,160 --> 00:25:35,200 Speaker 1: all the time wishes. It feels weird to say wishes 403 00:25:35,320 --> 00:25:38,359 Speaker 1: or horses here, but you guys know what I'm talking about, Casey, 404 00:25:38,400 --> 00:25:40,360 Speaker 1: and you as well know if you could have any 405 00:25:40,359 --> 00:25:43,200 Speaker 1: pet in the world, what would it be? Hamster already 406 00:25:43,240 --> 00:25:47,000 Speaker 1: got it living the dream? What did you say, Casey 407 00:25:47,160 --> 00:25:50,960 Speaker 1: Clever Hans, Oh, specifically that horse? Yeah? Why not? I 408 00:25:51,000 --> 00:25:53,840 Speaker 1: mean he seems cool, a lot of upkeep, bro. And 409 00:25:53,880 --> 00:25:59,040 Speaker 1: also he's dead, so well we're we're talking uh perfect 410 00:25:59,080 --> 00:26:03,840 Speaker 1: world here. So he does in the hearts and minds 411 00:26:03,880 --> 00:26:06,760 Speaker 1: of all of us, and that includes even the most 412 00:26:06,840 --> 00:26:11,240 Speaker 1: dastardly among us like Jonathan Strickling, the Quister, Christopher hauciotas 413 00:26:11,240 --> 00:26:14,840 Speaker 1: here in spirit, Alex Williams, who composed our theme, and 414 00:26:14,880 --> 00:26:18,400 Speaker 1: of course in your heart, Ben and your heart Casey 415 00:26:18,640 --> 00:26:29,080 Speaker 1: and mine. We'll see you next time, folks. For more podcasts. 416 00:26:29,080 --> 00:26:31,080 Speaker 1: For my heart Radio, visit the i heart Radio app, 417 00:26:31,119 --> 00:26:34,199 Speaker 1: Apple podcasts, or wherever you listen to your favorite shows.