318. Autism, Academics, and Animals | Dr. Temple Grandin

[0] Hello, everyone.

[1] I'm usually excited to have whoever I'm talking to that day on my show because I pick people I'm excited about talking to, but I'm particularly excited about my guest today.

[2] Dr. Temple Grandin, Temple Grandin revolutionized the animal handling industry over the last 40 years and has done more for animal welfare in a practical sense than anybody that I know of and perhaps anybody on the planet.

[3] I think you could make a case for that.

[4] She's a remarkable person.

[5] I saw her first in Tucson, Arizona.

[6] I'll talk about that a little bit in our interview.

[7] She gave one of the most compelling presentations I'd ever seen in an academic setting at a conference on consciousness and saw that about 15 years ago.

[8] And ever since then, I'd really been wanting to meet her and I got to do that today, so that's so exciting.

[9] So I'll just give you a brief bio and we'll pop into the interview.

[10] Dr. Temple Grandin is a professor of animal sciences at Colorado State University.

[11] Facilities she is designed for handling livestock are used by companies all around the world.

[12] Her work has been instrumental in implementing animal welfare auditing programs now used by McDonald's, Wendy's, Whole Foods, and many other major corporations.

[13] She has appeared on numerous shows across platforms such as 2020 Larry King Live and Primetime.

[14] Dr. Grandin is also a show.

[15] an accomplished author, with books such as thinking and pictures, livestock handling and transport, and the autistic brain.

[16] A few of her other publications, Animals in Translation, as well as visual thinking, have even made it to the New York Times bestseller list.

[17] In 2017, Dr. Grandin was inducted into the National Women's Hall of Fame, and in 2022, she was honored once again as a Colorado State Distinguished Professor.

[18] We're going to walk through her book today and we're going to learn what she has to say now about thinking.

[19] Let's start with visual thinking and language.

[20] So do you want to tell people about your realization, about different thought patterns?

[21] When I was in my 20s, I thought everybody thought in pictures the way I thought.

[22] I didn't know that other people thought in words until I was in my late 30s.

[23] Now, you've already mentioned, how do I categorize?

[24] Well, I'll explain as a child how I learned to categorizing with individual pictures.

[25] So as a very young child, I categorized cats, dogs, and horses by size, because in our neighborhood at that time, there were no cattle, and there were no small dogs.

[26] Then a dog sent came into my neighborhood, and she's the same size as a cat.

[27] cat.

[28] And I remember looking at the doxen, she was a black doxent, and trying to figure out now what features does she share with the dog?

[29] She barks.

[30] Her nose shape is the same as a dog, and she smells like a dog.

[31] So I had to take other sensory -based things like smell and what the dog sounded like to put the dachshund in the dog category.

[32] So the way I formed category, says I have to have a bunch of information.

[33] Let's take the cat category.

[34] And you look at a leopard's face, a lion's face, and even a house cat's face, there's similarities.

[35] And they also smell all the same too.

[36] If you go to the zoo, you can smell how they are different.

[37] So the first step for abstract thinking is put making categories.

[38] So when I finally figured out, that other people did not think in pictures.

[39] If I ask most people, visualize your own home, your dog, or your car, you will do it because you're so familiar with that.

[40] But one time at an autism conference, when I was in my late 30s, I asked a speech therapist think about a church steeple, and I was shocked that the only image he saw was a very vague two lines like this, where I see specific churches.

[41] They come up like a series of, well, back then, 35 -millimeter slides.

[42] Now, the PowerPoint slides.

[43] And then I can start, as I see more and more of these churches, I can put them into New England type category, stone cathedral type.

[44] Looks like a warehouse, and it has a little plastic steeple type.

[45] I can make finer categories as I get more and more specific images.

[46] It's bottom -up thinking.

[47] And I learned that that's exactly how an artificial intelligence program diagnoses melanoma cancer.

[48] It's given a training set of 2 ,000 melanomas and another training set of every kind of skin rash and mosquito bite and affected whatever.

[49] And then it learns to categorize melanoma from non -melanoma.

[50] And that was very insightful to me when I learned that that's how the simple type of artificial intelligence programs work.

[51] diagnosing something like melanoma.

[52] So let me ask you, when I'm thinking something through, now I can think in pictures, and if I'm building something or trying to design something to build, then I tend to think in pictures.

[53] But I would say 90 % of the time my proclivity is to think in words, and I would say in part that's because my word thinking is so domic.

[54] It just suppresses the image thinking.

[55] And so a lot of my thinking, I would also say, takes the form of something like internal argumentation.

[56] So I'll ask myself a question.

[57] I'll think up an answer in words.

[58] And then I'll think up a bunch of reasons why that answer isn't sufficient.

[59] And then I'll conduct an internal argument.

[60] And that's occupying me continually, like 16 hours a day nonstop.

[61] And it's been like that ever since I've.

[62] was two years old, except for those times, let's say.

[63] So, yeah, so how do you, do you conduct internal arguments or like what, what accounts for the, so part of the creativity in my thinking is the outcome of these arguments, but you're thinking in pictures, so you're not having internal arguments.

[64] Nope.

[65] What's the stream of your thought like?

[66] Well, when it comes to things like designing equipment, I often will kind of a lot of equipment design, someone gets an idea from something else.

[67] And one of my other books I wrote about the inventor of Velcro, and he saw how Burdocks stuck on his clothes, you know, cockle burrs on those kind of things stuck on his clothes.

[68] And that's where he got the idea for making Velcro.

[69] That would be visual thinking.

[70] the burdocks and Velcro, they've got similarities on how they stick together.

[71] In designing equipment, I can just see how it operates.

[72] I worked with welders that had 20 patents each that barely graduated from high school, but they could build any kind of a machine and invent industrial machinery.

[73] They just see it in their head.

[74] Right now, will you see, okay, so I read Nikolai Tesla's, biography a long while back and it was extremely interesting and he claimed and I have no reason to disbelieve him that entire inventions machines would pop into the theater of his imagination detailed out to the point where he knew the angles on the screws that held the metal together and he would try to write them down in something approximately draw them out in something approximating something that you could make a blueprint out of, let's say, in that much detail.

[75] And sometimes a new invention would pop into his head so quickly that it would obliterate the previous one.

[76] He had to work very quickly to keep up.

[77] And so there's that incredible fluency in visualization.

[78] But then, as I said, in the verbal world, I'll think of argument and counter arguments.

[79] When you're thinking of industrial design, do you think of the object that you're attempting to design and then multiple variants of it and test them against each other?

[80] Or does it just come to you as a solution for a given problem?

[81] It almost sort of just pops into my head.

[82] I also see mechanical abnormalities.

[83] I remember walking in and someone made a cardboard, old -fashioned locomotive.

[84] You know, and the wheels have those links between them.

[85] And I go, they drew that wrong.

[86] Wheels are not going to turn.

[87] You know, and it was just a cartoon train for a party.

[88] But I immediately noticed that they didn't draw it right.

[89] The other thing is, is my thinking's associative.

[90] All right, give me a key word.

[91] Pretend I'm Google for images.

[92] Not something I can see in here with books and papers all around and photography equipment and stuff all around me, but something kind of a creative key word, and I'll tell you how I access my memory for that key word.

[93] So with regard, so my wife has a very powerful visual imagination.

[94] She's able to do all sorts of remarkable things with it.

[95] And one of the things that strikes me as highly probable is that her capacity for visual imagery is a lot more intense than my.

[96] Yes.

[97] And so, like, I was a fairly vivid dreamer for years, especially when I was reading Carl Jung's work in graduate school.

[98] Don't seem to dream much now or not, well, I don't remember them much now.

[99] When I do think in pictures, it's not as vivid as seeing the real world.

[100] It's maybe 5 % of that.

[101] It's sort of, it's, well, it just doesn't have that intensity.

[102] And you and you?

[103] No, it's very, very, very.

[104] vivid.

[105] And while you were setting up all the camera equipment, here I found, here's a whole bunch of papers.

[106] More papers I found online supporting a lot of the things that are in the book.

[107] I just got surfing around.

[108] And boy, you can sometimes find some great stuff when you look at the citations.

[109] No, but it's very, very vivid.

[110] It's completely vivid.

[111] Now, when you mentioned the word imagination.

[112] I remember going to a long time ago, Disney World, a kind of a ride that had imagination with people and dirigible and things like that.

[113] Then I visited a studio where Disney made a whole bunch of their stuff.

[114] I'm now seeing that.

[115] Yes, I'm now seeing a non -disclosure agreement, so I can't tell you what I did there.

[116] But now I'm seeing a very interesting discussion we had about designing things where you're designing things there's the decoration part of it and then there's the mechanical part of a machine.

[117] Of course at an amusement part you won't have decorations but you also rides have to mechanically work.

[118] They're kind of two separate things and were kind of done by two separate departments.

[119] You also spoke in your book about your ability to see things out of place.

[120] And so one of the things that characterizes autism is the fact that at least some autistic people are not very happy when they walk into a room, say that they're familiar with, and one thing is out of place.

[121] So, for example, an autistic child might walk into a dining room, and one of the chairs is, you know, tilted 45 degrees to the right or to the left instead of being put straight in.

[122] And what seems to happen, correct me if you feel that I'm wrong, is that the fact that that chair is now askew means that the entire room is different in some important and emotionally significant way.

[123] So there's this response to an anomaly.

[124] I don't have that issue.

[125] That's not an issue for me. But if there's one pixel off on an electronic sign, I will notice that.

[126] I remember one time walking into the airport with somebody else and the United Ticket counter sign was a whole row of television monitors.

[127] And there must have been 20 TV monitors making the word united over and over again.

[128] And one of the screens was scrambled, the whole screen.

[129] And I immediately saw it.

[130] And I said to the person beside me, did you see that that sign was messed up?

[131] No, they did not see it.

[132] And they were right beside me when we walked in.

[133] I immediately saw it now that it upset me, no. I just noticed that the sign was scrambled.

[134] Right.

[135] But it didn't upset you.

[136] So, yeah, so that's that interesting.

[137] So for me, I think I can detect anomalies visually.

[138] So, for example, one of the things I learned to do when I was setting up my house and renovating places and setting up my offices, like arranging my local environment, was to sit in the room and become meditative in some sense and then to feel out what was bothering me about the room, like what ugly feature might pop out, what part of it needed to be attended to, right?

[139] And I think I was tuning myself to detect what was abnormal in relationship to the underlying aesthetic or the pattern of the room.

[140] But that pops out for you almost instantaneously.

[141] When, for me, anomaly detection is mostly verbal again.

[142] It's like, oh, think up an argument and then think up counter arguments, and if one argument and the other don't jive, if they're contradictory, then that pops out for me. Well, it's sort of like I fly all the time, so like I know when the pilots do the checklist.

[143] And like we push back and we just take too long to turn.

[144] I'm going, uh -oh, we're going to have an air traffic control delay.

[145] And I can often predict that before they announce it.

[146] And I also can, I'm very conscious of, on the biggest airplane, when they start the little gentle push to push it back from the gate, I can feel it on the biggest aircraft there is.

[147] Right.

[148] And I...

[149] All right, so now...

[150] I just want to get there, and I'm going, oh, please push back.

[151] But it's sort of like, I don't get upset about it.

[152] It's just anything that's not routine.

[153] I instantly notice it.

[154] And I go, oh, crap, I see a vest that says tech ops.

[155] We may have a delayed flight.

[156] Now, that brings up another thing I want to talk about.

[157] In the last month, I've had, okay, a mechanic come on a plane, not twice, and both mechanics had gray hair.

[158] And this brings up a major issue that's in my book about skill loss, especially skill loss with mechanical things.

[159] I've been on a lot of questionable elevators and escalators lately that definitely needed servicing.

[160] And what's happening, and this is a lot of, in my screened -out chapter, is the kids are getting screened out of these trades because they've taken the shop classes out of the schools 20 years ago, and we have so many higher math requirements that you don't need for something like fixing elevators that the kids are playing video games in the basement on an autism diagnosis instead of fixing elevators.

[161] There's a relationship here between what goes on with industrial things and what's going on at school, which is a major, major thing that I'm interested.

[162] in talking about.

[163] Yeah, so let's talk about that a little bit.

[164] That's one of the things that popped out for me from your book.

[165] So I was trying to think that through.

[166] So you make the claim, as you just laid out, that our education system and maybe our entire culture, as it's hypothetically deindustrializing, is actually working against the best interests of those who think mechanically, those who think in pictures, and those who can do hands -on work.

[167] Well, yeah, and here's a paper I just dug off of Google Scholar on visual object ability, a new dimension of nonverbal intelligence.

[168] And what a lot of educators don't understand is that object visualization, especially on solving mechanical problems, it is a different way of thinking.

[169] I worked with people that barely graduated from high school, stutterers.

[170] They'd be labeled autistic today.

[171] They'd be in special ed.

[172] But they had big metal working shops and 20 patents each for mechanically complicated equipment that they are selling around the world.

[173] And this is something that educators just don't get it.

[174] Right.

[175] And the reason why I wrote this book, I'll tell you what was the reason, in 2019, just before COVID shut everything down, I went to four places, and I realized the magnitude of the skill loss.

[176] The first one was a pork processing plant where most of the equipment came from Holland.

[177] I went to another pork processing plant, equipment coming from Holland.

[178] Then I went to a poultry processing plant where all of the specialized equipment came from Holland, in a hundred shipping containers.

[179] And then I went to the Steve Jobs Theater and the structural glass walls are from Italy and Germany.

[180] Then, after reading more stuff, I found out that the state -of -the -art, electronic chip -making machine comes from Holland.

[181] And that goes back to their educational system.

[182] They don't stick their nose up at the high -end skilled trades and look at it sort of like a lesser form of intelligence.

[183] When the kids get to about ninth grade, they can go university route or they can go tech route.

[184] And I want to emphasize high -end skilled trades, where you're really using that visual thinking for mechanical devices.

[185] So I was trying to think through why this might be happening.

[186] So let me offer some hypotheses to you, and you tell me what you think about this.

[187] So first of all, we have learned, and you draw on Simon Baron Cohen's work in your book.

[188] We have learned that there is a difference, and we can try to map this on to verbal thinking versus imagistic thinking.

[189] Simon Baron Cohen talked about systemizing versus empathizing, and he considers that something akin to the continuum between autistic thinking and normal thinking.

[190] So the autistic types are more systematizing, and my suspicions are they're also the ones who are more likely to think in images in the manner that you describe.

[191] Wait a minute.

[192] Now we've got two kinds of thinking in images.

[193] And there's a nice paper that just came out relatively recently, seeing and thinking and pictures to review of visual information processing that came out in 2018.

[194] I'd like to keep my stuff up to date.

[195] Now, I think in photorealistic pictures where the more mathematical type of thinking thinks in patterns.

[196] See, in your brain, you've got circuits for what is something.

[197] Okay, so I see a dog and I go, yeah, that's a dog.

[198] or I've got some china ceramic cattle on my coffee table here.

[199] Okay, and I just look at the animals and name them.

[200] Then the visual spatial is, where is something?

[201] Where are you located in space?

[202] There are actually two different kinds of visualization.

[203] And I have a whole chapter in Visual Thinking book about this and research to back this up.

[204] now the visual spatial type pattern thinking or sort of where is something in space those kids do well in math so they're going to stem right but let me tell you what's going on out in the food processing planes the people I worked with in the big steel shops now that a lot of is closed down we are paying the price now for taking out the shop classes on designed mechanically clever equipment the people I worked with in me we never worked on boilers of refrigeration We don't understand that stuff.

[205] That requires a lot more mathematical thinking or the load on the roof so the factory doesn't fall down if we get two feet of snow.

[206] You see, then I have seen this division of engineering labor in every single meat company I have worked with.

[207] They're all the same on that.

[208] So do you think that's a matter of, like, let's say, something approximating focal depth?

[209] So is it possible that the first kind of people that you talked about are, are dealing at the object level itself.

[210] So they're dealing, say, with a boiler or with a particular piece of equipment, whereas the other types are dealing with the relationship between pieces of equipment?

[211] No, no, you don't think that's it?

[212] No, I think it's just real simple.

[213] It's, you just see the objects.

[214] And then after you work, you see an object visualizer gets better and better at designing mechanical equipment, the more things you go out and see.

[215] Like when I started working, my designing cattle handling facilities, I went to every feed yard in Arizona, and I worked cattle.

[216] And I go, this kind of a design doesn't work.

[217] This worked, so then I took all the good bits and, like, recombine them.

[218] It's bottom -up thinking, the more stuff I get exposed to, whether it's cattle handling facility, or maybe I'll look at how water flows through something.

[219] And then you watch how cattle move.

[220] I'd like to look at drone footage.

[221] And a lot of that resembles water flow.

[222] and the visual spatial, they see patterns.

[223] It's actually very different.

[224] And what we're losing is the object visualizer.

[225] That person that can just, you see, I'm very aware of things like I go in an elevator now that hasn't been serviced, and it's scraping in the shaft, you better believe it.

[226] Right, right, right.

[227] I hear it.

[228] And I go, they haven't serviced that elevator.

[229] And I was at a fancy hotel recently.

[230] and the bellhop goes, oh, it skips that floor.

[231] We have to get that floor on the way down.

[232] Yeah, a real nice hotel, major city.

[233] Right, right.

[234] Okay, so let me, I don't quite understand that distinction yet, so I'm going to push you a little bit more on that.

[235] So on the visual side, you have the visual spatial types, if I'm remembering this correctly, and that's the category that you fall into.

[236] And then you have people who are, what are they higher up on the abstract?

[237] attraction chain in some sense, the ones who can think more mathematically?

[238] No, but basically, object visualizers, I can tell you this from experience.

[239] We're good at mechanical devices, art, photography.

[240] I have talked to many, many photographers because I do a lot of interviews.

[241] Find out they're dyslexic, they're about flunked out of school, and fortunately somebody introduced them to photography.

[242] And the other thing that my kind of mind's good at is animals.

[243] Then you're visual spatial, mathematics, algebra, I can't do algebra.

[244] There's nothing there to visualize.

[245] Mathematics, calculus.

[246] I took a computer programming course when I was in college.

[247] I couldn't do it.

[248] I had to drop it.

[249] I was exposed to the same exact computer that Bill Gates had.

[250] He could do it, and I had to drop the class.

[251] You know, these are the things that the more mathematical pattern thinking mind is good at.

[252] And some of these really smart kids, they can just look at algebra formulas and just see it.

[253] They don't have to do it step by step.

[254] They just see it.

[255] And that's how they think.

[256] And then the teachers try to make them do it step by step.

[257] That gets the kids frustrated.

[258] You know, they don't think the same one.

[259] Right.

[260] And my thinking is also associative.

[261] I tend to jump around.

[262] But there's a logic to the association.

[263] And I think the best way to illustrate that associative kind of thinking is give me a single keyword like I'm Google for images.

[264] And think up a creative keyword.

[265] And I will tell you exactly how my mind associates.

[266] associates and how my mind can get off the subject, but there is a logic to the getting off of the subject.

[267] So give me a key word, a single keyword.

[268] Okay, how about rose?

[269] Okay, I'm seeing some rose bushes that we had in our backyard when I was a child, and we had a lot of thorns on them.

[270] And we also like dig around in the grass that was back there, so now I'm seeing the grass behind our house.

[271] when we used to go play in it.

[272] I'd catch some insects sometimes.

[273] Okay, now you can see how it's jumping around.

[274] I don't have that big a visual library of roses.

[275] So then I tend to then go to something else.

[276] How about cows?

[277] Cows, all right.

[278] Now, I'm seeing like 10 cow statues right here in front of me. and so obviously those are coming up in my mind just recently I tend to bring up recent memories I visited with a black Angus bull that was a pet and he wasn't very happy with us because we didn't bring him any carrots so my friend gave him one of those disgusting soy protein bars and he goes, ugh, I'm not going to eat that I wouldn't eat it no matter how much we tried to feed it to him and he was annoyed because we didn't bring him any carrots Okay, then I'm getting, now I'm on the, now I've got the carrot word in my head, and when I was in fourth grade, I used my singer sew handy to sew green crepe paper, so students could be carrots, and I made the green carrot tops out of green crepe paper.

[279] So that's how I got.

[280] Interesting.

[281] Okay.

[282] So talking to you, talking to you that way reminds me very much of what used to happen in my therapy sessions when I was helping people interpret their dreams.

[283] And so dreams have the same quality of thought that your thought had when you just put it on display there.

[284] So because the dream tends to be an intermingling.

[285] So imagine there's a center category, and the nature of the category is somewhat unclear.

[286] Maybe that's partly what the dream is trying to puzzle out.

[287] But what you get is a web of associations, some of which are autobiographical, that are sort of circulating around a main theme.

[288] And partly what you do when you analyze a dream is you walk through all the associated images.

[289] You also ask the person to let their mind loose, to generate more associations, and then you try to use the associational web to triangulate on the central theme, and to haul out the gist.

[290] And the gist of that array of images would be something like the interpretation of the dream.

[291] If you get it right, then it snaps into piece, They think, oh, yes, that's definitely what that was about.

[292] But the dream is attempting to put something together, you know, that has a central categorical structure.

[293] Well, there also are sensory things because, you know, I have some balance issues.

[294] So I often get dreams where I'm like riding a bike down a hill that's super steep like that, and I wish I wasn't doing that.

[295] And I know that that has to do with the fact that I have balance issues.

[296] I don't think it means anything.

[297] But I'm always up on some high place that I wish I'm.

[298] I wasn't up on, and I've got to try to walk down it.

[299] And then I have other dreams where I can see it might have some meaning and other times where it doesn't.

[300] But the other thing with my thinking, when I'm working on design work, I can control the associations.

[301] I can control them.

[302] I've had before, you know, there's now 3D simulations.

[303] Okay, let's say the company that's building this plant wants to show off how their equipment works, they can do a 3D simulation showing how the equipment works.

[304] I can remember sitting in a conference room when we were trying to discuss how to do some conveyors and the other guys there were coming up with ideas for the conveyors.

[305] And I go, no, no, if you do that, you're going to yank the rails out of the ceiling.

[306] Oh, no, no, no, that won't work.

[307] They were almost using my mind like a 3D CAD program that was animated.

[308] And I could test run in my head on these different conveyors.

[309] So let's go back to the issue of, say, taking shop class out of schools.

[310] So Barron Cohen talked about systematizers versus empathizers.

[311] Yeah, but what Barron Cohen did, he left out the object visualizers.

[312] He was looking more at the mathematical visual space and pattern thinkers.

[313] I agree with them about systematizing and verbal.

[314] But the object visualizers.

[315] But he didn't differentiate.

[316] didn't differentiate the systematizers properly.

[317] That should be more differentiated in your view.

[318] The systemitizers would have two categories, the object visualizer and the visual spatial.

[319] And a big mistake in a lot of perceptual studies is that they're not differentiating them.

[320] And some people, there's some verbal people in psychology that don't want to believe this stuff exists.

[321] Just while you were setting up the cameras, I downloaded six new abstracts that aren't even in my book on this that show that they are different.

[322] Right, okay.

[323] Got him right here on my lap.

[324] So Cohen also talks about gender differences in relationship to this continuous.

[325] So we can break the continuum to two parts on the one end.

[326] And it is the case that autism tends to be preferentially a male disorder, although there are females as well.

[327] But so that's systematizing mode of thinking that you've differentiated into the two categories, also tends to be gender stereotype to some degree at a biological level.

[328] I avoid that issue as to controversial, because right now I'm interested in one thing at the age of 75 of helping the students who think differently get into really good careers where they can have satisfying lives.

[329] And I avoid the controversial stuff.

[330] Yeah, well, I'm not so much interested in the controversy.

[331] I'm interested in trying to address the issue of why shop courses, for example, have been taken out of schools.

[332] Now, we do know that schools are predominantly run by women, and women are more likely to be empathizing.

[333] No, I think it's less likely to be systematizing.

[334] So I'm wondering if there's a gender issue going on there and a prejudice against a certain way of thinking.

[335] Okay.

[336] What's that?

[337] I think that one of the reason they took out the shop classes, they kind of just go, everybody's going to go the university route and cost.

[338] Good shop classes cost a lot of money.

[339] Now people are starting to put shop classes back in, and you know what they're finding?

[340] They can't find anybody to teach the shop classes.

[341] I just heard about a brand new, beautiful welding shop built here in Colorado at a community college, and they can't find somebody to teach it even after they drop the university requirement.

[342] And I can tell you right now, we need people that do these things before the power grid and the water systems fall.

[343] apart.

[344] I'll tell you that stuff I care about.

[345] Right.

[346] Right.

[347] Right.

[348] Yeah.

[349] Well, it's, okay, so you, well, virtualization.

[350] Now, do you think virtualization has also played a role in this?

[351] I mean, the systematizing types.

[352] Some of the 3D drawings I see it wrong, and that's not going to fix some of the serious problems we got with infrastructure right now.

[353] And you need both kinds of thinkers.

[354] Like, one of the things I've got in my book is where a bridge fell down in Minneapolis.

[355] And the work, workers were complaining.

[356] They were worried that when they were working on this bridge, it was going to collapse.

[357] Well, I looked up that bridge collapse, and I saw all the twisted metal, and I took one look at that, and I went, it's too light, it's too cheap.

[358] That was just from looking at the pictures.

[359] Then I found the engineering report on why that bridge fell down, and they cheated on the gusset plates that hold the beams together, and they were way thinner than the spec.

[360] But I had already looked at the pictures and said that bridge is to light, it's cheap, before I read any engineering report.

[361] So how was it in your life that you attained the practical knowledge necessary to facilitate your thinking?

[362] So we're talking about how you think in the vision.

[363] I'll tell you how you do it.

[364] It's real simple.

[365] You've got to get out and experience all kinds of stuff.

[366] Because the more information you put in the database, the better you get.

[367] and going back to teaching a computer how to diagnose melanoma, you had to give it like a couple of thousand melanoma examples and a couple of thousand mosquito bites, infected boils and everything else, examples.

[368] In other words, as I got older and I got more and more information in my database, I could think better and better and better than I could make smaller categories of things.

[369] Now, a lot of the people that I worked with in construction that build equipment for me, that's used in every large beef plant now in the year, US.

[370] Some one of them started, and some of them would definitely be autistic.

[371] One of them started out working on cars.

[372] Another one took a single welding class, and now he's selling mechanical equipment all over the world, started with a tiny shop that then grew into a big shop.

[373] And what's happening now is the little shops are not forming.

[374] And that's why we're importing all this equipment from Holland and Italy.

[375] because when you look at their educational system and I looked it up again recently online and Italy actually has three routes university route, tech route, mechanical, and art route now like for their fashion industry and the Holland and Netherlands you can go either university route or tech route and that's why they're making the state -of -the -art chip -making machine that we don't make.

[376] Right.

[377] And I'm not talking potato chips, I'm talking electronic chips.

[378] Right.

[379] I wonder if this is also a consequence of people increasingly moving away from farms.

[380] You know, because when you're on a farm, you'd have to do a lot of hands -on stuff.

[381] You have to do a lot of fence repair.

[382] You've got to take care of your own machinery.

[383] And, you know, as you move into the urban environment, everything, in some sense, even in the real world, is virtualized because you can always call on other people to do the day -to -day things that you need to keep the infrastructure.

[384] Well, I agree.

[385] A lot of fun, you know, kids are growing up to date, totally.

[386] removed from the practical.

[387] And one of the things I talk about in the visual thinking book is I've talked to a doctor, and he told me he had trouble training interns to saw up cuts because the interns had never used scissors as a young child.

[388] I had a student in my class that had never used a tape measure to measure anything.

[389] And they're totally removed from the world of the practical.

[390] Where are those kids that came off the farms, yes.

[391] had to figure out how to fix things.

[392] Absolutely.

[393] But I think what's happening now in the schools are things are getting so verbal and they're going absolutely crazy on math requirements.

[394] Because I know people at 20 patents and they could basically do sixth grade arithmetic.

[395] That I could do, because I can relate that back to real things.

[396] And things like...

[397] Do you know of any research pertaining on how the more, the people people who visualize objects might be assessed for their ability?

[398] Yes, and there's a whole...

[399] There's a whole chapter in here.

[400] There's a whole chapter in here, and I never can pronounce their names, right, Blank and Culva, and I never can say the names correctly.

[401] But I have a whole list of references in there where the difference between the object visualizer and the visual spatial is being assessed.

[402] And there's a whole bunch of references on that.

[403] Now, I have to look these names up because I can't pronounce them correctly.

[404] Let me find a reference list here for Chapter 2.

[405] Okay, it's Blazhenkova.

[406] I've got one, two, three references in here from Blazhenkova on types of creativity.

[407] And then the other big reference, I have lots of references.

[408] would be Kozhevnikov if she's got tradeoffs object versus spatial visualization reviewing the visual verbal dimension evidence for two types of visualizers that's another paper spatial versus object visualization a new characterization of visual cognitive style that's three papers right there from Kohesnikov that are in my reference list and I've got a lot of references where their actual tests were done when I go through the citation lists I just went in and we're working on the children's edition of the book right now and one of the copy editors had a query about a reference and I had to look that up and then I decided to just type in object visualizer at Visual Spatial into Google Scholar again and find the same old papers, and then I found some citations.

[409] It's kind of a cool paper here in a journal Cognition.

[410] It's an old paper, actually, visual objectability, a new dimension of nonverbal intelligence.

[411] I know from working in factories, I spent 25 years in heavy construction, and that is something that I don't think many teachers have done that, and seeing how these guys think.

[412] Big, complicated cargo plants, IBP plants, which are now Tyson, Monfort plans, and that company is now JBS, figuring out complicated things with equipment.

[413] It's a different type of intelligence.

[414] And I think it's when I worked on the book with Betsy Lerner, my super verbal co -writer who helped me organize things, and she had someone come in to fix a bunch of stuff in her house.

[415] And after we had discussed this, Betsy was telling me, well, I watched how he figured out how to fix the stones on the chimney.

[416] I had never really thought about it before, but she'd watched how he did things.

[417] And then she started to understand there's a form of intelligence there that's absolutely not verbal when she watched a person she hired to fix stuff in her house.

[418] Right, right.

[419] Yeah, well, you can imagine something, and this did pop into my mind visually, can imagine somebody who's trying to put together a stone chimney has to rotate the stones to make sure that there's going, like a Tetris game, that's a good way of thinking about it.

[420] I was thinking then again, because I'm thinking in images now that we're talking, I was thinking about my young grandson, he's only two years old.

[421] He had his Legos laid out in front of him.

[422] And when I was a kid, I played a lot with Legos, and I played a fair bit with this mechano set that was like a junior engineering set.

[423] And it was certainly the case that working with Legos was nonverbal because you're rotating shapes in space and having them fit in.

[424] into one another towards some design end.

[425] And that's a nice kind of hands -on learning and exposure to different mechanical principles.

[426] And so do you have recommendations for people who want to help their children train their visual spatial and object visualization abilities?

[427] Let's get them out of building things.

[428] The big mistake I see with a lot of kids is they're super good with Legos.

[429] They don't think to introduce tools.

[430] I was using tools by second grade.

[431] I was not using a saw, but I was using hammer, screwdriver, and pliers.

[432] I was taught how to use them safely.

[433] I've got another book of children's projects called Calling All Mines, where I described bird kites that I spent hours with tinkering to get them to work, tigree with parachutes to get them to open up more easily.

[434] Kids today are totally separated in the world of physical things.

[435] They're not getting out and observing stuff out in nature.

[436] You know, this is part of the problem.

[437] And I just went to a veterinary school where the students are so far removed practical things that they give them dexterity skills and surgical skills.

[438] They have these plastic tote boxes and they put children's puzzles inside them and they've got to just reach in and, by feel, put these children's puzzles together.

[439] Because when they were in kindergarten, they never did this.

[440] right right yeah well my my parents told me that when i was four my favorite toy was a screwdriver and that i used to take all the cupboard doors off the cupboards in the kitchens and so i was introduced to tools at a very early age and that there's a real practical utility in that too because now if i visualize a project in my house shelving or something like that or any or any uh construction project of any sort well i can visualize the array of tools that's necessary to make that come about, and then I have the tools at hand and I know how to use them.

[441] And that is a, well, it's also, I really find that kind of work calming and engrossing.

[442] Well, the problem is, is we got kids growing up today, totally removed from the world of the practical.

[443] They don't use tools.

[444] They don't use scissors.

[445] I had a student in a class who had never used a ruler or tape measure to measure anything ever.

[446] I think that's a problem because if you haven't done practical things then you don't understand how to fix things okay like two years ago they had a horrible mess where the power you know like a bunch of different power stations froze well I never heard so much abstract gubbledygook about that because the way I would work on fixing it would be all right let's look at each power station what piece of equipment actually froze that I never saw anything written in the press that described, okay, what froze in this plant?

[447] What frozen this plant?

[448] Because my inclination would be to kind of rank them on, okay, a turbine hall that froze, I can build a building over it.

[449] That's an easy one.

[450] You know, a whole bunch of gas wells froze.

[451] That's going to be like really difficult to fix.

[452] But you see, nothing's abstract because, okay, if I'm going to try to figure out how to fix it, I don't really want to argue who owns some.

[453] I'm not interested in the politics.

[454] I would just rank the power stations on expensiveness and difficulty to winterize and say exactly what piece of equipment froze.

[455] And you know how I can find out?

[456] You let me loosen there, away from the managers, I'll find the maintenance shop, they'll show me everything.

[457] And I know enough about equipment that they can't BS me. Right.

[458] So maybe part of the advantage to that more visual form of processing is also its association with that kind of practical particularization.

[459] That's right.

[460] That's right.

[461] Now, on the other hand, on the other hand, I have no idea how to balance a power grid.

[462] That's a job for the mathematicians.

[463] You see, this is where we need to work together and in a complementary factor in a complementary way.

[464] And I tell people in big corporations, I've done a lot of talks for businesses, your first step is that you've got to recognize different kinds of thinking exists.

[465] And let's take another example.

[466] Recently, I visited two really nice dairies up in Quebec, Canada, that have the robotic milking machines where the cow can go in.

[467] She decides when she wants to get milk and get fed. And both dairies had actually made some good mechanical modifications on that equipment, which the equipment company finally adopted.

[468] But one of the dairy producers said to me, I stop it like a computer stuff.

[469] I don't mess with the program.

[470] That's somebody else's job to work on the software.

[471] But the mechanical parts of the device, they figured out ways to improve it.

[472] Yeah.

[473] It's like a hierarchy.

[474] You can imagine a hierarchy of generalization with the highest resolution, lowest level, being the particulars of a given machine.

[475] Then you can imagine people like specialized to operate at different levels of the hierarchy.

[476] Maybe the verbal types are operating.

[477] at the highest possible level of abstraction.

[478] But they lose that particularization.

[479] That's right.

[480] That's basically right.

[481] Because the verbalizer tends to overgeneralize.

[482] One of the papers that are reviewed in my book on visual thinking was an interesting study where high school students that came like for school specializing in the arts, another school specializing in the sciences, and another one especially in the humanities, which would be more verbal, on those teams of students and their assignment was to create a new planet.

[483] So the art students heavily visualizing they made a planet with crystals on it.

[484] Another one made a skyscraper planet.

[485] And then the more mathematical science students just painted a round, made a round ball and described the gravity and the atmosphere, you know, kind of boring pictures.

[486] And the verbal thinkers started write it down and then they go, oh, wait a minute, It was supposed to draw the planet, so they made kind of splotchy stuff on it.

[487] But the thing that was interesting is that the art minds, more my kind of mind and the mathematical minds, they had big planning sessions on how to design their planet, where the verbal thinkers, they didn't do any planning.

[488] You see, this is the problem.

[489] The verbal thinker would get big, broad concepts or something we need to do.

[490] Right.

[491] But how do you actually implement those concepts?

[492] There's no detail there.

[493] Now, in food safety, we have a thing that I really like.

[494] It's called Hazard Analysis Critical Control Points.

[495] So let's say I'm out there in a sea of things I can do.

[496] Well, I can't do all that stuff.

[497] See, now the critical control point, let's say in food safety, in a food factory, I can't measure microbes and bacteria on everything in that plant.

[498] I have to pick out the places where I'm most likely to have control.

[499] contamination.

[500] That would be the critical control points.

[501] And one of them is doorknobs.

[502] Yeah, that's why some places, food factories, have automatic doors, because that gets rid of touching the door.

[503] Yeah, well, one of the things that I always found a relief in working with engineers is that they were good, and I can see it in the terms that you're describing, they were very good at rank ordering practices.

[504] practical priorities, right?

[505] And that seems to be part of this particularization.

[506] So I have this company, it's a software company that sells personality tests and writing programs for people to help them plan their lives.

[507] And my business partners and engineer, although he's also very intelligent verbally, he's more intelligent non -verbally.

[508] And he knows these systems right from the code upward at every level of their machine.

[509] instantiation.

[510] And so the huge advantage to that is that if anything ever goes wrong, he knows exactly what goes wrong and he knows exactly how to fix it.

[511] It's particularized down to the point where that makes action possible, eh?

[512] And that's part of the problem with the verbal abstraction is that it makes sense conceptually, but that doesn't mean that it's detailed to the point where it's actually implementable.

[513] And then it's like a pseudo -knowledge, because it sounds like you've got the picture right.

[514] But when you actually try to implement it, you find out that it's really a hollow shell of conceptualization.

[515] Well, I kind of look at like this is why when I learned about the food safety concept of hazard analysis critical control points, or let's just call it critical control points.

[516] So I've got a big sea of stuff out there.

[517] What's the really important thing?

[518] Okay, now I only think in specific examples.

[519] let's take frozen Texas power stations.

[520] The critical control point is, and I want it, like in two sentences, what piece of equipment froze?

[521] And then you can very easily figure out the ones that'll be easy to winter ice.

[522] And I've actually talked to somebody who installs gas wells, and it only costs $5 ,000 to winterize a well when you build it to retrofits a complete mess.

[523] He also said, you have to have to have some.

[524] and knows how to turn the valves.

[525] He said, that's me. I call him the guy in the pickup.

[526] And that person in that pickup truck is not getting enough credit.

[527] He knows how to turn those valves.

[528] Right.

[529] Yeah, so if you conceptualize that verbally, you end up saying something like a bad winter storm took out the Texas power grid.

[530] And that sort of sounds like you've said something, but it's nothing like saying, well, the grid is made out of 200 different like industrial assemblies, each of those is made of a variety of parts that's differentially susceptible to winter.

[531] All right, well, that's still gobbledy -cook because, first of all, they wouldn't have 200 separate power stations.

[532] You know, it's more like 10, something like that.

[533] And I would just let's, we'll write down the name of the station because I don't really care who owns it.

[534] And what we used to do with meatpacking plants when we were doing welfare audits, is we'd always call them by their town names because you're auditing that particular plant.

[535] And I'd say, well, this power station had a frozen turbine hall.

[536] That's an easy one to fix.

[537] There was a coal fire that froze.

[538] Well, they freeze up where you have a cold dumps in.

[539] That's probably fairly easy to fix.

[540] And if, you know, 50 gas wells froze up the feet of plant, that's going to be a mess to fix.

[541] But, you see, as I talk about these things, I see it, and I happen to know what some of the equipment looks like.

[542] You see, that also makes me a better troubleshooter.

[543] You know, if I know what stuff looks like, you see, this is where you've got to put things in my database.

[544] But I worked 25 years out in factories on heavy construction stuff, so I know what a lot of stuff looks like.

[545] Right.

[546] So it means in some sense that to solve the problem is you take the verbal representation.

[547] So the verbal representation is a storm took out the Texas power grid, and then you say, well, there's 10 key components to the Texas power grid, so that differentiates that.

[548] And then you say, in each of the 10 systems, there are critically vulnerable points that are specifically sensitive to cold weather.

[549] We need to differentiate and find out what those key ones are.

[550] Then we have to differentiate that further.

[551] You say, now, okay, now when I first started my work, there was no Google Earth.

[552] Well, the first thing I'd do, probably Google Earth and Street View, the power stations.

[553] And the other thing I've learned, if I want to get accurate information, I don't, you don't talk to the managers, you've got to get down in the shop.

[554] And then the shop guys have to be not worried about getting fired.

[555] That's another nasty issue that I'm going to have to deal with.

[556] But, you know, let's say I get three shop guys together, and we've, okay, my industry, say when we get rid of all the suits, You know, and that's going to be the managers and the verbal thinkers.

[557] They won't talk in front of suits.

[558] They're afraid they're going to lose their jobs.

[559] You know, and this is something I know from all the years I've worked in this stuff, and then they'll take you out there and show you what froze.

[560] And then, oh, there's creative things.

[561] I've talked to a guy who worked at a power plant, and there was this one sensor, very important electronic sensor, and it'd get cold.

[562] And when it got cold, he put plastic garbage bags over it.

[563] and I'm going, well, I think we need to have something a little more permanent to keep that sensor warm than black plastic garbage bags.

[564] And that's what I told them.

[565] Yeah, so that issue that the guys with the hands -on knowledge have to worry about being fired is interesting too because it seems like, so they have this extremely detailed knowledge that's practical about how these systems operate.

[566] And what happens is if they bring that knowledge up the abstraction hierarchy, what they're doing in some sense is pointing out the manner in which they're superiors, their hypothetical superior, a lot of detailed knowledge.

[567] A very big problem I've had is they're worried about losing their jobs.

[568] Yeah.

[569] But you really want to solve the problem, they need to be able to talk to you freely because they're the ones that will tell you.

[570] exactly what froze.

[571] Right.

[572] Well, the question is, why would their attempts to bring their practical reality to bear as they move information up the information hierarchy, why would that threaten people to the point where they would be intimidated in relationship to their job?

[573] I mean, why is there this gap, this psychological gap between the practical and the abstract?

[574] I mean, you'd think that the managers would be calling on these people all the time.

[575] You've got to drag those suits out of the office, too, just when things are working normally.

[576] And so they get a better understanding of what the practical people are doing.

[577] Now, my animal welfare work, one of the things where I made some of the biggest difference in animal welfare work is auditing programs I helped develop with McDonald's Wendy's and Burger King back over 20 years ago.

[578] And in this situation, we were taking vice president -level managers out to the plan.

[579] And they'd have these undercover boss moments, just like that show.

[580] I'll never forget the day when the McDonald's vice president saw a half -dead dairy cow go into their product.

[581] And he goes, yeah, we got some things here we have to fix.

[582] You see, before it was all an abstraction, spreadsheets, numbers.

[583] Okay, animal welfare, give it to lawyers, give it to the public.

[584] relations department.

[585] But when they came out of the office and they saw something bad, now it was real.

[586] Now they had to act.

[587] It was no longer abstract anymore.

[588] There seems to be a kind of pride in that abstraction in some sense.

[589] I mean, I've also noticed that highly intellectual people, and maybe those are ones who think primarily in words, tend to be rather dismissive of the intelligence of more practical people, like working people.

[590] And that's, I come from a working class environment, so although I've hung around verbal people most of my life, so I can see that dichotomy.

[591] Do you have any sense of why it is that the more abstract thinkers are, have a proclivity, contemptuous of the practical.

[592] Because they used to say, okay, the kids that are like failing in high school, stupid kids go and shop.

[593] Well, I can tell you right now, I work big metal fabrication companies owned by these so -called stupid people.

[594] And what they, they were inventing equipment.

[595] They had 20 patents, and they were very proud of their patents, and one of them made posters out of them, put them up all over his place.

[596] It's a different kind of intelligence.

[597] And it's not, you know, there's things they can do that the verbal thinkers can't do.

[598] And what I'm really interested in is we need all the different kinds of minds.

[599] Because one of the problems with my kind of thinker, since I'm associative, is the point in a company, let's say I had a matter.

[600] fabrication shop, I'd have to hire a verbal thinker just to run the business, the payroll, ordering materials, things, all of that part of it.

[601] Do you think it's a competition?

[602] Do you think it's a competition for status between different forms of neurodiversity?

[603] I mean, if I can claim that my intelligence is paramount, that increases my social status in some sense, right?

[604] You can imagine there's a competition for that broadly going on in society.

[605] What I have found is when you got the verbal thinkers out in the world.

[606] the field.

[607] Their eyes got opened.

[608] That the important thing is you've got to drag the suits out of the office.

[609] I've done a whole lot of that.

[610] And let me tell you, they changed.

[611] Okay, I've done a lot of work on supply chain management.

[612] And when there's supply chain disasters like a factory burning up in a clothing industry is disgusting industry.

[613] They need to clean up a lot of stuff.

[614] A factory burns up 100 people selling blue jeans.

[615] Well, the suits didn't get out of the office and see what was going on in these factories until there was a disaster, the one they should have been preventing a disaster like that.

[616] Right.

[617] Well, yeah.

[618] So once you build up hierarchical organizations, it's very easy for the people who are operating near the top of the abstraction chain not to pay attention to the details.

[619] And hopefully the details are working out so well that you don't have to pay attention to them.

[620] I mean, that's, in some sense, the point of building a hierarchical organization.

[621] But what you need to do, obviously the managers can't be doing every job out there in a plant, but they need to have enough contact with the field.

[622] And I'm going to use the field, be like the factory floor, farming, you know, waterworks, any of these kind of things.

[623] so they understand that there can be things bad going on.

[624] But I tell business managers, and I've talked to many big corporations, computer companies, steel companies, pharmaceutical companies, that the first step is realizing that different kinds of thinking exist and that they can work together in complementary ways.

[625] And you actually need the whole team.

[626] You need the whole team.

[627] because we're kind of disorganized and associational.

[628] I'm going to need a verbal thinker if I got a really big business to keep the business going.

[629] So what do you think of the suppositions, and you talk about them a bit in your book, that the visual versus verbal modes of cognition map to some degree onto hemispheric specialization and that the right is more oriented towards the right hemispheres more oriented, broadly speaking, toward the kind of thinking that dominates your mind?

[630] Yeah, but broadly speaking, that's true.

[631] You know, they're exceptions to some of that stuff.

[632] But the thing that I want to talk about is right now I'm seeing too many kids that are dyslexic, autistic, or whatever.

[633] I'm ending up playing video games on a disability check when they could be photographers.

[634] I've got four -person crew here right now doing this filming.

[635] And that's an interesting career.

[636] Or they could be designing mechanical equipment.

[637] And they never get an opportunity to do photography art or mechanical equipment.

[638] Because they kind of look at them as these stupid kids.

[639] Right, right.

[640] Okay, so there's a privileging of the semantic, and that's partly because it's cheaper, it's easier, it's detached from the world in some sense.

[641] How do you think we should redesign schools for, say, kindergarten kids and elementary kids in some practical way you tend to think practically?

[642] What do you think would be a good start?

[643] Well, like in the 50s, when I went to school, we had all kinds of craft projects.

[644] I was learning to use little blunt scissors, probably in first grade.

[645] I'd be putting all the hands -on classes back into schools, and that's going to include theater, music, cooking, sewing.

[646] When I went to elementary school, I loved art, sewing, and woodworking.

[647] And if I hadn't had those classes, I would have hated elementary school.

[648] And I loved sewing.

[649] And when I was in fourth grade, I had a singer sew handy, a toy sewing machine that actually sewed, and it was one of my favorite things, because I could make things with it.

[650] Kids are not doing enough of that kind of stuff today.

[651] Right.

[652] Okay.

[653] So there's a return to, there's a need for a return.

[654] turn to the practical in some sense on both sides of the gender spectrum with regards to tools, with the sewing with scissors.

[655] Now I went, when I was doing a book signing for visual thinking, I went to a physics lab in Harvard.

[656] This room was labeled physics lab and they had all kinds of 3D printers in there, but they also had a sewing machine and they also had a station for crocheting.

[657] This is the building labeled engineering department at Harvard.

[658] Maybe they're realizing they've got to get them doing some hands -on things.

[659] This is when I did the book signing for this.

[660] It was part of the book tour.

[661] The other thing I've noticed, I stayed, I got into some interesting places.

[662] I stayed at this hotel where they, in Evansville, Illinois, where they had textbooks in the rooms from the 1930s.

[663] I wish I'd had more time to look at it.

[664] And I pulled out an electrical engineering book, and it had a lot of math on it, but it was much more applied.

[665] They'd say, oh, this is how this is the generator works.

[666] This is the math that goes with it.

[667] But it would describe how the generator actually worked.

[668] It was much more applied.

[669] And now the physiology book that I had in the 70s, you know, explain how the kidney works, how the heart works, and then explain the chemistry.

[670] Now I look at a physiology book, and it's much more verbal, a lot more math and chemistry.

[671] But how does the kidney actually work?

[672] I still have my old Duke's Physiology of Domestic Animals from 1970.

[673] And I want to go back and compare that to the Duke's physiology now.

[674] And it's like we're taking the practical out.

[675] I just got an email yesterday from the U .K. That they wanted to take a technology and design course out of a high school.

[676] You see, I think what's happening now is mathematics is totally taking over.

[677] Yes, we need mathematics.

[678] because my kind of mind is not going to touch boilers and refrigeration in that food processing plant.

[679] That's a job for the mathematicians.

[680] But what we're losing is the object visualizer.

[681] Right, right, right.

[682] Yeah, well, I wonder, too, if part of this is the fact that, you know, for a long time in our society, a lot of this practical machinery just worked.

[683] And so we could afford to ignore it in some abstract sense, right?

[684] because our cars worked and our power grids worked, and we could take all of this low -level infrastructure for granted.

[685] Now, that meant there were a lot of people on the shop floors who were busily working, making sure it worked.

[686] But it did mean that we had the luxury to engage in abstract specialization, and maybe we could fall prey to the psychological tendency to just dismiss all that.

[687] Well, you see, when they first started, about 20 years ago, is when they started taking shop classes out of the school.

[688] Well, you can get away with that for a while.

[689] And then the people I've worked with, I'm gray now, are retiring.

[690] They're retiring out, and they're not getting replaced.

[691] That's happening with elevator and escalator mechanics.

[692] That's happening with airplane mechanics.

[693] And I'm seeing that more and more and more and more as I travel.

[694] These are three things that I see all the time, and they are getting gray.

[695] Right, right.

[696] So, yeah, the retirement problems.

[697] going to be, the retirement problem is going to be a big one.

[698] When it comes to industry, there's two gigantic mistakes that were made, shutting down in -house engineering shops.

[699] 20 years ago, we had this huge metal working shop called the Montfort Fab Shop, and it was part of the engineering of a company called Montfort, so they no longer exist now.

[700] Well, that's been shut down.

[701] And then at the same time, we took out shop classes.

[702] Now, in the short run, it was cheaper for these companies to just farm out engineering work they need to do in their plan.

[703] Yeah, that works fine until the shops retire out.

[704] And now what's happened, like I can't give you the name of the company, but I have a client right now where the one shop that's left is ripping people off at five times the price.

[705] And that's happening right now.

[706] Right.

[707] Do you see any positive consequences of computer technology for object visualizers and for the people who are working more in the visual spatial end of things?

[708] Well, it's definitely useful to, you know, like the visualization and stuff you can do on computers.

[709] But that doesn't replace real things.

[710] Let me tell you, power grid, I lay awake at night about that, and that's so fragile that I'm not, I'm not going to go into any detail, because it's too fragile.

[711] and I'm not going to discuss the things that I visualize and lay awake at night about the power grid.

[712] Because it's just too fragile.

[713] Okay, I'm curious about that.

[714] Why not discuss them?

[715] Because I don't want to give people that have bad intentions any information on how to hurt the power grid.

[716] Okay, okay, okay, I see.

[717] That is the reason.

[718] Right.

[719] Because it's very easy to hurt it, and I don't want to give out any information that would help someone.

[720] somebody damaged the power grid.

[721] So I don't discuss the details here.

[722] But I'm seeing them right now.

[723] Right, right, right.

[724] Yeah, well, that's part of that ability to think about critical points of failure that is so much characteristic of engineering mind.

[725] I know where the critical points of failure are, and I'm not going to discuss them.

[726] Right, right.

[727] So we can all be thankful that you're not a terrorist.

[728] Yeah, I'll be thankful I'm not a criminal.

[729] Yes, exactly.

[730] Exactly.

[731] Yeah, well, I've always often been afraid when thinking along the same lines that you're describing of just exactly how fragile things are in that regard and how much someone with a good imagination, how much damage they could do if they targeted things properly.

[732] It is really quite frightening to apprehend.

[733] Well, that's why there's certain things about the power grid I am not going to discuss.

[734] And I'm seeing three big fat critical control points right now.

[735] I'm seeing them in my mind.

[736] they make me crutch.

[737] Right.

[738] So could we talk a little bit about the specifics of your work?

[739] I remember one of the stories you told at this Tucson conference was about, you talked about cows that they would do such things as go into a field and look at a, if you left a briefcase on the field, for example, the cows would eventually come and look at it.

[740] Yeah, that's right.

[741] A cows in a line might be stopped by something like a Coke bottle in their path.

[742] And so you used your ability to think like animals to design systems for animal handling that were much more humane.

[743] So could you walk us through that a little bit?

[744] Well, the first work I did with cattle was in the 70s in Arizona when I didn't even know that I was a visual thinker and other people were not a visual thinker.

[745] And I noticed that if there was a coat hung on the fence, the cattle would stop.

[746] if there was a shadow or reflection off a vehicle.

[747] So I got down in the shoots to see what they were seeing and I would take pictures down inside the shoot.

[748] And people thought that was kind of crazy.

[749] But now I, like right just recently, did start up at a really big plant.

[750] And at 10 o 'clock in the morning, everything was working fine.

[751] And then at 3 o 'clock in the afternoon, and a big shadow appeared.

[752] I called the spider monster.

[753] And it was just a shadow.

[754] Well, these cattle decided they weren't going to walk over that, so they'll have to build a roof over the façadey so that the cattle can't see the spider monster.

[755] The other thing I show people how to do is watch your lead animal.

[756] Your lead animal will come up and stop and look at the thing they don't like.

[757] The same plant on the night shift, okay, the shadow monster wouldn't be there.

[758] The guy calls me and he goes, they go halfway up to shoot and stop.

[759] All right, what do I do?

[760] Now bring up a nice, calm bunch of cattle.

[761] Watch your leader really carefully.

[762] He'll look right at the thing he doesn't like.

[763] And there was an LED light on the corner of a building.

[764] And they took that down, and then everything worked fine.

[765] How do you identify the leader?

[766] Well, there's always a leader when, all right, let's say I take a 20 head of cattle out of a pan.

[767] There's a lead animal that walks out first.

[768] usually one of the more bold animals, not the dominant animal.

[769] The dominant animal that pushes the others away from the feed trough, he's in the middle of the herd, or she's in the middle of the herd.

[770] But the leader will come out of the pen first, and the other cat will follow.

[771] And it's just the first animal in the group is the leader.

[772] It's that simple.

[773] You see, as we're talking about that, I'm seeing it.

[774] Okay, so is that leader stable across instances of leadership, and is that associated with this ability to find what's a normalist and to deal with?

[775] Well, in cattle that have lived together for a while tend to stay in the same order.

[776] You know, years ago, when ear tags came out that were sequentially numbered, in other words, you could just buy a package of ear tags labeled 1 through 200, and they put them on their cattle.

[777] And one of the things that surprised ranchers, when maybe 200 cattle came back the following year to go through the shoots to get vaccinated, they were coming through in almost the same order.

[778] Now, that's a group of cattle that lived together.

[779] Okay, is there something...

[780] Okay, so you made the observation that the lead animal will stop and look at the thing that he doesn't like.

[781] And so are the other animals...

[782] But also that lead animal wasn't the physically dominant animal.

[783] He's got some other characteristics.

[784] The animal is dominant at pushing others away from the water trough or the feed trough.

[785] But once the lead animal walks, the other cattle usually will follow.

[786] Same thing was shape.

[787] The other animals will usually follow.

[788] Right.

[789] So you remove the distractions that the lead animals reacting to.

[790] And at this particular plant, we had two things we had to get rid of.

[791] We had to get rid of the spider monster shadow.

[792] And we had to get rid of an LED light that was on the corner of a building.

[793] So do you have any sense of why the other animals come to rely on the level?

[794] lead animal?

[795] Like, what's the lead animal being selected for?

[796] Or is it just a first mover?

[797] What's the nature of this lead animal?

[798] You see, there's different levels of fear in animals genetically.

[799] Some animals are more bold, other animals are more shy.

[800] Or you can call those high and low fear.

[801] And the animal that's more bold is more likely to be the leader than the animal that's more anxious.

[802] And And, you know, a bunch of cattle that have lived together all the time, you know, there'll be certain animals that tend to be the leaders.

[803] And then you've got the great big one with the giant horns and she shoves everybody else away from the feed trough.

[804] There's something that's very profound about that because you're laying out the fact that it isn't the dominant animal that leads.

[805] No. And that it's the animal that's exploratory and somewhat willing to take risks that leads.

[806] That's right.

[807] But also that the...

[808] that the lead animal will spot an anomaly, right, like the spider monster that you're describing.

[809] And so it's not like they're so bold that they're completely without fear.

[810] They're still acting cautiously in some sense.

[811] All right, so you can walk the lead animal down a shoot and you can see what it's going to see.

[812] And you can actually do that because you go down there and do it, but you also think that way.

[813] You've got to bring your cat up really calmly to see because if you bring them up at a run, then the leader just turns back and you don't know what it's reacting to.

[814] Oh, yeah.

[815] I said to him now bring him up nice and calm, watch the leader come up the shoot, and when he stops, he'll look right at the thing he doesn't like.

[816] And he looked at the LED light on the corner of the building.

[817] Then they texted me a picture of it, and they got rid of that, and that fixed the problem.

[818] Now, have you developed some sort of picture of the class of things that stop cats?

[819] Yes, I have.

[820] You talked about the spider mall.

[821] Okay, so tell me what sort of things tend to stop.

[822] cattle.

[823] I have pictures.

[824] I have checklists of things to look for.

[825] Reflections on water.

[826] At this particular plant, there was a gate handle that jiggled.

[827] And it was right by the shoot entrance.

[828] I said that needs to be fixed.

[829] So this gate handle doesn't vibrate.

[830] So what's common?

[831] What's common about the things that stop cattle in their tracks?

[832] Or can you extract out of commonality?

[833] Well, let's look at, let's look at Cattle's a prey species animal.

[834] So you're looking for things that might be a danger.

[835] Some little bits of rapid movement set them off.

[836] And something that's sort of like shouldn't be there.

[837] Like you can put a white plastic bottle in the entrance of the chute, and they'll about shut a meat plant down.

[838] They'll just keep turning back away from it, turning back away from it.

[839] Right.

[840] So they're looking for something that doesn't.

[841] fit the environmental pattern, and that's probably doing something like activating predator detection.

[842] Well, that's right.

[843] It's like, you know, they're looking for stuff that, you know, a movement in the bushes, maybe that's a mountain lion or a wolf, some little movement in the bushes.

[844] The other thing about new experiences, if you take something like camera equipment, cattle love camera equipment, you put an expensive camera in the middle of the pasture, they will come up and knock it over and lick it to death.

[845] That's what they will do.

[846] See, things that are novel are attractive when the animal can voluntarily approach and scary, if you suddenly shove it in their face.

[847] You suddenly shove it in their face, then it's scary.

[848] Right.

[849] And so the best way to introduce new things to cattle is to let them voluntarily approach it.

[850] I don't know how many times people say to me, my horse was fine at home, he went crazy at the show.

[851] Well, you've got a lot of novel stuff there, like flags, for example.

[852] So you better get your horse used to flags before you go there.

[853] And the best way to get them used to flags would be to decorate the pasture with flags and let your animal walk up and voluntarily approach them.

[854] Right, right.

[855] Well, you know, that's exactly what you do in psychotherapy when you're trying to help people overcome a phobia, right?

[856] So if someone's afraid of an elevator and won't get in it, that often happens with agoraphobia.

[857] What you do is you say to them, okay, let's start by imagining elevators.

[858] So that's going to make you a bit nervous.

[859] But imagine an elevator at some distance that doesn't make you uncomfortable.

[860] Okay.

[861] Okay, and then you say, okay, well, now you've done that.

[862] See if you can move yourself in your mind closer to the elevator door.

[863] And then you keep doing that, but it has to be voluntary.

[864] It's 100 % absolutely necessary for it to be.

[865] Okay, so maybe you run them through this imaginable exposure therapy.

[866] And then you say, okay, for our next session, and what we're going to do is we're going to go out in the hallway.

[867] You know, that elevator you wouldn't take.

[868] We're going to go out in the hallway.

[869] We're going to stand 200 feet away from the elevator, and you're just going to look at it if you can't.

[870] And so they'll do that.

[871] It has to be voluntary, and then you can get them 150 feet away and 100 feet away, and soon they'll be right up to the elevator door.

[872] I was very anxious in my 20s, and I got terrified of airplanes because I was an extremely scary emergency landing when I was a senior in high school.

[873] They put the slides down and the whole thing, very, very scary.

[874] And one of the ways I got over that is I had to make aviation interesting.

[875] And when I got the ride in the cockpit of a plane flying Holstein Heifers to Puerto Rico, that made it interesting.

[876] You make something scary interesting.

[877] Because I know another thing they do on the elevator phobias is they show them how the safety mechanisms work, that the elevator's not going to fall down the shaft.

[878] Yeah, well, you know, you even compel that interest to some degree.

[879] So, for example, once you get a phobic person inside an elevator, what they'll tend to do is look at their feet.

[880] And so you say to them, look, quit looking at your feet, look at each corner of the elevator, look at all the numbers, look at the display panel, like you have to facilitate their voluntary visual exploration.

[881] And to some degree, what you're doing is you're calling out their interest, say, attend to all of these things as if they're interesting.

[882] And then that's how they familiarize themselves with the elevator.

[883] And they also note that, well, they're in there.

[884] Because you have to look at the elevator to know you're in an elevator, right?

[885] Literally, you have to move your eyes and point at all the different parts of the elevator.

[886] And the more that you can help people do that at a high level of detailed resolution voluntarily, the more likely they are not only to become less afraid of the elevator, is that that actually isn't what happens, is you actually train them in a form of exploratory bravery because what you teach them is that if they use their eyes voluntarily to scan what they're afraid of, they'll become braver.

[887] And then that generalizes to all sorts of other instances too.

[888] So if you train someone to be less afraid of an elevator, they're much less afraid of other things as well.

[889] Well, that's right.

[890] And the thing that we're seeing, I'm seeing now in dogs, you know, we have very strict lease laws here.

[891] And there's more problems with dogs being afraid of the veterinarian because they haven't been out experiencing enough stuff like strange people touching them, for example, just going to lots of different places.

[892] You know, this is the reason why when they train service dog puppies, you take them everywhere so that there's almost nothing that will frighten them.

[893] Yes.

[894] Yeah, well, that's the same.

[895] argument you were making earlier about the fact that to train people practically, we have to put them in a lot of different practical hands -on situations so that they can generalize across all those instances.

[896] And so experience that's too narrow is too restrictive.

[897] Well, when I get worried that we're going to have people making policy on all kinds of important stuff when they're so far removed from the world of the practical.

[898] You see, we need to have both because the problem with us practical people is we're not organized enough.

[899] That's where just about every tech company has to hire a suit eventually, just to keep the company organized.

[900] Somebody's got to pay the payroll.

[901] Somebody's got to pay the taxes.

[902] Somebody has to make sure the rent is paid.

[903] You know, if they need more office space, then they've got to go out and go shopping for office space.

[904] You know, there's a, we really do need all the different kinds of minds.

[905] Well, when I look at the ideological solutions that are being put forward to the world's problems continually, I do wonder the same thing you're wondering about, which is, is this empty ideological representation a consequence of the fact that the people who are doing this have no practical experience at all?

[906] It's like they're not thinking at the level of detail.

[907] Well, I think that it's a problem because when I worked originally, this was over 20 years ago, with McDonald's Burger King and Wendy's, and they took the top managers out into the field and implemented the auditing program.

[908] It was interesting to see how the animal welfare issue went from an abstraction.

[909] Give it to legal.

[910] Give it to public relations to something real that they really needed to address.

[911] You know, half -dead animals going into your products, not okay.

[912] Right, right, right.

[913] A broken, stunning equipment is totally terrible and not okay.

[914] And that's mainly a management problem, and failure to do maintenance.

[915] And when I worked on that in 1999, I got five journal articles published on this.

[916] I saw more change than I'd seen in my whole career when these big companies were inspecting these plants.

[917] But I figured out a very simple scoring system.

[918] If you couldn't shoot 95 % of those cattle dead on the first shot, you failed a McDonald's audit.

[919] It was that simple.

[920] Some very simple critical control points.

[921] If you had more than 3 % of your cattle beller in their heads off when you're handling them, you failed the McDonald's audit.

[922] Okay, so why did that turn out to be the critical issue?

[923] Well, the broken stunners were a big issue.

[924] Now, on the handling, I figured out a way to score that.

[925] That's very simple, vocalization.

[926] If you're poking cattle with too many electric prods or you're slamming doors on them or whatever, they're going to be bellerun their heads off.

[927] And I better not hear any bellerent coming out of the place where they kill them.

[928] I hear Belleran coming out of there.

[929] Somebody needs to get kicked off the approved supplier list.

[930] It's that simple.

[931] That's one of the critical control.

[932] Right.

[933] So you used animal distress as an indication of efficiency of process.

[934] Okay, can you walk us through some of your designs?

[935] I mean, you designed these circular cattle enclosures as well to calm them down.

[936] The circular designs are really nice, but I'm also very proud of the fact.

[937] There were 75 plants on the McDonald's, approved supplier list.

[938] Only three had to buy fancy expensive equipment.

[939] Everybody else we fixed with management.

[940] Yeah, three managers had to be removed.

[941] I call that managerectomy.

[942] A lot of non -slip flooring had to go in because one of the things we measure is slipping and falling.

[943] And lighting, cattle are scared of the dark, training people to move smaller groups of animals and put a solid side up so they don't see the vehicles passing by.

[944] and these very simple changes.

[945] We were able to fix some of the older places.

[946] I used all my design ability to figure out how to make some of the older facilities work even though they did not have the fancy new equipment.

[947] And then we had three plants.

[948] Only three plants had to do a front -end remodel that was very, very expensive.

[949] That's three out of 75.

[950] I'm really proud of that.

[951] That's all the big pork meat plants in the U .S. Right.

[952] So tell me, tell me, Tell me what your goals were.

[953] Okay, so let's walk this through at the level of detail.

[954] So why don't you tell people about how these cattle handling plants work, broadly speaking, from the time the cattle arrived until the time they were processed, let's say.

[955] And then how are you brought in to fix them?

[956] Well, unloading a truck.

[957] Make sure you have a non -slip unloading ramp.

[958] Open the gates up, let them out.

[959] You do not need to scream at them, pound on the vehicle, or stick electric pads through the holes in the side of the truck.

[960] So let the cattle just get off, and they will.

[961] And then they should walk quietly out of the truck if they got a scale, weigh them on a scale, and then quietly walk into a holding pen and get a drink of water.

[962] Maybe you'll lay down.

[963] Now when it's time to go up to the plant, somebody should come down and bring a group of 20 out, not a group of 50, and you quietly walk them up the alley to where they get to where the round crowd pen is.

[964] and the whole thing should be in a calm walk without slipping and falling and without mooing and bellering and almost no electric rods.

[965] And it should all be very calm walking is what it should be.

[966] Right, and how many plants did you go analyze?

[967] We had 75 plants on the approved supplier list and only three of them had to have extensive renovations.

[968] But we did have three plants where the plant manager had to be removed.

[969] Right.

[970] And so in those cases, yeah, why did you remove the managers?

[971] Well, the ones where we were able to get rid of the plant manager was the corporate ones.

[972] The plant, then we had one plant that we used to call the problem child.

[973] And management was family, and we couldn't get rid of it.

[974] And that plant would like, you know, fail an audit and then pass an audit.

[975] But management has to decide that they're going to do things right.

[976] you can have the best equipment, and it's not going to work if it's not managed.

[977] In fact, before we started these audits, I had a lot of equipment out in the field.

[978] Lots of equipment.

[979] Half my clients tore it up and wrecked.

[980] And what the customer inspections and audits did is force the plant to manage the stuff they had, either brand new fancy stuff or older stuff.

[981] And so how broadly did your innovation spread and how rapidly, And what were the consequences of that for the meat handling industry in general?

[982] Well, the auditing program was within six months, as in the year of 1999, was adopted by McDonald's, Wendy's, and Burger King.

[983] And that covers just about all the big beef plants.

[984] And I saw more improvement than I'd seen in a 25 -year career prior to that.

[985] People were no longer using broken equipment.

[986] They were moving smaller groups of animals.

[987] things were kept repaired and employees were better supervised.

[988] And boy, it made a big difference.

[989] So why do you think you were able to do this?

[990] I mean, you obviously can solve the problem practically, but how are you able to make your way in the corporate world in a manner that actually resulted A, in people listening to you, and B, and changes actually being made?

[991] Because that's quite a remarkable combination of unlikely achievements.

[992] All right, let's start off.

[993] I started out with equipment.

[994] This was in my 20s.

[995] And I found that selling equipment was much easier than getting people to manage equipment correctly.

[996] And early in my career I made the mistake that a lot of young engineers make.

[997] I thought I could make a self -managing cattle handling facility.

[998] That is BS.

[999] And I got a lot of systems out there.

[1000] The other thing that helped me to get systems out into the industry is I wrote about them.

[1001] And I wrote about them in the meat industry.

[1002] and cattle industry trade press, wrote all kinds of articles just about how to do it.

[1003] So now I had a lot of equipment out there.

[1004] Center track restrainer and lots of lots of these big plants had one.

[1005] It's a piece of equipment I developed with the guys in the shops that I've talked to you about earlier.

[1006] But half my clients tore it up and wrecked it.

[1007] Then I worked with a lady named Janet Riley at the American Meat Institute, and I came up with this very, very simple scoring system for evaluating meatpacking plants.

[1008] And we wrote it up in our guidelines.

[1009] Nobody used it for two years.

[1010] Then McDonald's approached me to implement their animal welfare auditing program.

[1011] And it started out taking vice president -level managers out of the office.

[1012] They saw some bad stuff.

[1013] And it started out as little training program.

[1014] They already had food safety auditors.

[1015] in the plants, auditing them.

[1016] That was already being done.

[1017] And so I took the trains of food safety auditors to do the animal welfare audit.

[1018] And within six months, I saw more change that I had seen in my whole career prior to that.

[1019] Then Wendy's got on board.

[1020] Then Burger King got on board.

[1021] And I made sure that everybody used the exact same score.

[1022] So it was absolutely clear.

[1023] It was like traffic rules.

[1024] You know, they measure speeding.

[1025] We measured how many.

[1026] localizations the cattle did.

[1027] We measured how many animals fell down.

[1028] Those things were measured.

[1029] And the plants had to make certain numbers.

[1030] It was absolutely clear.

[1031] There were five critical control points.

[1032] And they had to do all five of them to pass the audit.

[1033] I sometimes can't believe I pulled it off.

[1034] It worked me on my wildest dreams.

[1035] But it was absolutely practical.

[1036] Right, right.

[1037] Yeah, well, it is quite a remarkable thing to pull off to be able to make that kind of change in the corporate world so quickly.

[1038] That's really quite remarkable.

[1039] The other reason I was able to make change, I practiced reverse conflict of interest.

[1040] I had a lot of expensive equipment already out in the plants.

[1041] I bent over backwards in the older facilities to figure out how to make that older facility work without buying expensive equipment.

[1042] Let me tell you, non -slip flooring, it can work wonders.

[1043] Now, we did quite a lot of that.

[1044] Right, right.

[1045] But that's not, that's not expensive equipment.

[1046] And I'm really proud of the fact that I took some of the older facilities and we made them work.

[1047] And then we did have three, only three, out of 75 plants that had to build an expensive front -end remodel.

[1048] And that was very expensive.

[1049] So what would you say if you had to put it into a few phrases, you weren't obviously pursuing mere narrow profit at that time, not that there's anything wrong with profit.

[1050] You were serving some other goal.

[1051] I was serving the goal of improving animal welfare, and I've been over backwards to do reverse conflict of interest.

[1052] And I tried to take some of those older facilities, some of them are a bit shabby, and make them work with simple changes like repairs, non -slip flooring, changing the lighting, and three plants had to have the plant manager removed.

[1053] And that solved the problem.

[1054] So why were you concerned?

[1055] Why were you so concerned with animal welfare, and how would you define animal welfare?

[1056] Why did that become paramount in your hierarchy of goals?

[1057] Well, one of the reasons why I started working on the equipment is the way cattle were being handled was horrible.

[1058] You know, electric prods on 100 % of them falling down, crashing into things, people screaming at them.

[1059] Cattle handling in the 80s was terrible.

[1060] Absolutely terrible.

[1061] And I saw that as something that I could fix.

[1062] Now, I talk to a lot of young people today that want to, you know, do activism about some specific thing, and it's way too broad.

[1063] I want justice in the world, for example.

[1064] Right, yes, yes.

[1065] It might be something they would say.

[1066] Yes, yes.

[1067] And I say, why don't you do something more targeted, like using DNA to show that this prisoner was falsely accused?

[1068] You see, now that's something a lot more targeted that you can actually do.

[1069] Yes, absolutely.

[1070] And I think that is a huge problem with the way that kids are trained morally.

[1071] universities, is that that grandiose, vague activism replaces the actual practicalities of problem -solving that you're describing that actually make a difference.

[1072] Why do you think it was that animal suffering stood out for you?

[1073] Is it partly because you can think like animals?

[1074] Like, why do you think it was?

[1075] Well, how would you like to get shocked with electric prods and be slipping and falling and crashing in defenses and things like that?

[1076] You'd be terrified.

[1077] and my goal was to improve how the cattle were treated.

[1078] When I talked to students about activism, I said, what I worked on wasn't everything bad happening to animals.

[1079] I worked on something targeted.

[1080] The thing that I'm seeing now with young people that want to make a difference, they say, I want to have justice in the world.

[1081] Or I want to, like, animals are treated terrible.

[1082] We've got to do something about it.

[1083] And I'm saying, you're going to be more effective.

[1084] if you pick out something relatively targeted.

[1085] I worked on cattle handling to start with.

[1086] That's not everything to do with animals.

[1087] Yes, exactly.

[1088] Or the example of using DNA to show that this criminal was innocent.

[1089] That's something much more doable and targeted that you can actually do.

[1090] Right.

[1091] So how was it that the suffering of animals in meat tracking, in meat packing plants came to your attention to begin with?

[1092] So you said the suffering, you found that?

[1093] Unbearable.

[1094] First of all, it started out, when I went out to the feedyards handling cattle back in the 70s, there was a lot of really horrible cattle handling.

[1095] And I made a mistake in the beginning that a lot of young engineers make.

[1096] They think technology can solve all their problems.

[1097] And I mistakenly believed that I could build a self -managing cattle handling facility.

[1098] That's nonsense.

[1099] I know that now.

[1100] That's nonsense.

[1101] Good equipment makes good handling better, but it doesn't replace management.

[1102] And what the auditing program did is it forced people to manage the facilities.

[1103] And why were you at the cattle handling facilities to begin with?

[1104] I mean, was this part of your academic training, or was this part of the fact that you'd grown up on a farm?

[1105] Well, I got interested in and got to go out to my aunt's ranch, and this brings up the other things, students get interested in stuff they get exposed to.

[1106] It's that simple.

[1107] One of the people I profiled in visual thinking was Michelangelo.

[1108] Grubby little 12 -year -old dropped out of school.

[1109] But he was running around all the churches seeing great art, and he grew up with stone -cutting tools.

[1110] Okay, that's the exposure.

[1111] Then he started making some stuff, and then an artist took him in as an apprentice.

[1112] That's mentoring.

[1113] Good careers start first with exposure.

[1114] And the other reason why I'm so concerned about taking all the hands -on stuff out of the school, schools, is those things like, let's say, theater, for example, expose students.

[1115] I didn't care about being in the play, but I loved making scenery and costumes that I love to do.

[1116] Now, that's something that can become a career.

[1117] So let me, we're running out of time on this segment.

[1118] Let me ask you one more question, and then maybe I'll sum up our discussion for everybody or try to extract out the gist.

[1119] You think primarily in pictures, but you're also an extremely effective verbal communicator.

[1120] you've written a number of books, you can obviously talk your way into corporate environments and help people walk through the complex process of restructuring, say, animal handling, on a pretty much on a national scale.

[1121] How do you think you've been able to develop your verbal ability?

[1122] Like, what did you do to manage that?

[1123] All right, it goes back to when I was seven years old.

[1124] In my neighborhood, all the kids, when they were seven, when the parents had a party, you had to put your good clothes on.

[1125] Greet the guests and serve the snacks.

[1126] Be little hosts and That's what you had to do.

[1127] I sold candy for charity.

[1128] That helped me on talking to people.

[1129] The other thing I figured out very early on is back doors into jobs.

[1130] And most people don't see this.

[1131] In the HBO movie Temple Grandin, there's a scene where I go up to the editor of our State Farm magazine, and I get his card.

[1132] Because I knew if I wrote for that magazine, that would help my career.

[1133] That's a back door.

[1134] Writing.

[1135] I did a lot of writing.

[1136] this how to handle cattle, how to design facilities.

[1137] And I was so happy when one of my very early articles got picked up by two other magazines.

[1138] You know, and it had made the national scene.

[1139] Of course, this is all, you know, pre -internet.

[1140] And then that press pass got me into all kinds of meetings that helped me to get into my next self -made internship with a swift plant.

[1141] I recognized the back doors.

[1142] Most people don't recognize the back doors.

[1143] But lots of good jobs are gotten through.

[1144] the back door.

[1145] Right.

[1146] So you allied your ability to concentrate on focal details practically with the ability and the willingness to communicate at all sorts of different levels verbally.

[1147] You were able to bring both of those together.

[1148] Well, you see, that's getting too abstract for me. I just go, okay, I got the card.

[1149] Within a week, I had done a master's thesis on cattle behavior in different types of squeeze shoots, and I sent them a good article, and they published it.

[1150] Then, I went back to them and said, maybe I could just write something for you every month.

[1151] I just walked into the office and asked that job.

[1152] So I did that as a volunteer for about three or four months, and then they started paying me. I wasn't shy to walk up and ask.

[1153] Right, right.

[1154] So you developed a communication expertise and a communication network at the same time that you were trying to implement your practical solutions, and both of those facilitated each other.

[1155] Well, in the very beginning, I wasn't even designing facilities, and then I was just visiting all these feedyards and writing for the magazine.

[1156] And that press pass got me into all kinds of places.

[1157] I recognized the value of that press pass.

[1158] It got me into meetings in the 70s with $600 registration fees.

[1159] I was no way I could have afforded that.

[1160] It was a 70s.

[1161] Right, right, right.

[1162] So what are you working on now?

[1163] You finished this new book.

[1164] that came out in 2022.

[1165] What are you doing now?

[1166] Well, I'm very interested in seeing the kids who think differently get into good careers.

[1167] And that's going to be a major emphasis of the things that I do now.

[1168] There are a lot of speaking engagements, a lot of interviews like this, because I want to see those kids that are different, get into good jobs.

[1169] Okay, if they're object visualizer like me, maybe an art job, maybe photography job, or a job building things.

[1170] if they're the more mathematical, visual spatial, a good programming job, a good mathematics or chemistry job where you need the mathematics.

[1171] There's too many kids that think differently.

[1172] Some of them are just kind of going nowhere.

[1173] I want to see them get into good careers and do things that will be constructive in the world.

[1174] Do something constructive.

[1175] So we're going to switch over to the additional half an hour that I produced for the Daily Wire Plus platform to delve into some of the biographical details of your life.

[1176] Before we close, I'd like to just sort of wander over the territory that we've covered and see if there's anything else, see if you think this is a reasonable summary, and if there's anything else you want to add.

[1177] I've been talking with Dr. Temple Grandin today, who's developed a spectacular career in modifying animal handling and also managed a lot on the more purely intellectual intellectual front as well in terms of conceptualization of information processing.

[1178] We talked a lot today about the difference in the ways that people think, concentrating mostly on the distinction between visual thinkers who tend to be more practical and detail -oriented and who can be broadly differentiated into two categories, and those would be object visualizers and people who think more visual spatially and mathematically, contrasting them with people who think more verbally.

[1179] We talked a fair bit about the prioritization of more verbal and abstract thinking at the cost of this practical thinking and training in that practical thinking.

[1180] We discussed how that's affected the school system and broader culture.

[1181] We discussed the dangers that poses to the integrity of our society as we lose the people who have the hands -on knowledge.

[1182] We talked about the psychological danger that poses to people who think more practically, concretely, and visually who are in -school systems that are optimized for the verbal thinkers.

[1183] We talked about Temple's career at the detail level, ameliorating the suffering of animals that across, like nationally and internationally, as it turned out, partly because she decided not to chase mere generalities, but to focus on an actual problem, which was the suffering of actual animals in actual plants, was willing to focus her emotional concerns on something that was practical and to marry that with a strategy that involve particularization and visualization and verbal communication and practical interactions with corporations.

[1184] And also, we close that with a discussion of the fact that what she's doing now is trying to bring to people's attention in podcasts like this, the fact that we seem to be working contrary to our own best interests by not building educational facilities that help optimize the ability of visual thinkers to function but also for society more broadly to take advantage of the talents and skills of those people in innovation and in the maintenance of the infrastructure that we already have around us.

[1185] And so I think that about summarizes what we talked about today.

[1186] Is there anything you want to add to that?

[1187] That definitely kind of summarizes that we need all the different kinds of minds.

[1188] And when we understand that different people think differently, they can work in teams where they can collaborate and have complementary skills.

[1189] I think that's something that's really important.

[1190] Also, the thing I want to, one thing I would do with the schools is I'd put a lot lot of the hands -on classes back in, like art, sewing, woodworking, shop, welding, auto mechanics, theater, because these are all things that expose kids to things that can become possible careers, too.

[1191] Right, and those are all things that have to be done in an embodied sense.

[1192] You actually have to, it's not purely abstract.

[1193] Any of that.

[1194] No, it's not abstract.

[1195] None of those things are abstract.

[1196] Yeah, well, that's, I suppose, a danger of moving so much education online as well as that it's going to increase the degree to the abstractions are dealt with.

[1197] When I went to did the book signing for visual thinking, I told you about the electrical engineering book from the 30s I found in this unique hotel room.

[1198] But I also got put in the office of a professor in political science, and I looked at some of those books.

[1199] And it was so abstract theories about politics.

[1200] I didn't even understand it.

[1201] It had nothing to do with right or left.

[1202] It had to do with just abstractions that were so abstract, it made no sense to me. And I'm going, oh, I wouldn't want this person in charge of figuring out what you're doing with the power grid.

[1203] You know, I remember at this Tucson conference where I first saw you speak, after you spoke, very practical talk, very much like the one that you delivered today when we were talking, a philosophy student got up because there were a lot of abstract thinkers at this consciousness conference and asked you something extremely abstract and philosophical.

[1204] And you did exactly what I would expect a good engineer to do, which was to say, you know, I really don't understand anything that you just said.

[1205] I don't know how to associate it with anything practical, and I'm completely unable to answer your question, which I thought was just, it was ridiculously comical.

[1206] And I also thought, what would you say, well -targeted?

[1207] Because it was the case that, you know, you had been talking about real practical realities, your ability to think like an animal, the fact that you had taken these practical steps to ameliorate animal suffering and that that had been so consequential and so of obvious worth.

[1208] And then you were faced with this flight into abstraction and did what engineers always do, which is something like, well, yeah, but I don't understand that.

[1209] What does it mean practically?

[1210] Which is a really good question.

[1211] It's a question that should be asked of abstract thinkers all the time.

[1212] What are the devils in the details here that you're overlooking?

[1213] How much do you know about the systems that you're abstractly representing?

[1214] And the answer to that is usually almost nothing.

[1215] Well, it's sort of like, you know, we need all the three different bases, you know, different kinds of minds.

[1216] You need the object visualizers.

[1217] We'll go to get the arts, mechanical, and photography and animals.

[1218] You need the visual spatial, mathematicians, computer programmers, chemists, things that require mathematics, and we need the verbal thinkers because they're going to help organize things.

[1219] You see, you need all three different kinds of minds, and they should work together in a complementary fashion.

[1220] All right, well, that's a good place to end this segment, I would say.

[1221] I'm going to go, thank you to everyone on YouTube and the Associated Podcasts for your time and attention.

[1222] I hope you found this discussion interesting and engaging and practically useful as well.

[1223] I'm going to switch over to the DailyWire Plus platform, and I'm going to talk to Dr. Temple Grand and a little bit more on the biographical end.

[1224] I want to lay out how her interest in the issues that she did pursue professionally made themselves manifest in her life.

[1225] Hello, everyone.

[1226] I would encourage you to continue listening to my conversation with my guest on DailyWireplus .com.