WEBVTT 00:00:00.000 --> 00:00:02.000 I think I'll start out and just talk a little bit about 00:00:02.000 --> 00:00:04.000 what exactly autism is. 00:00:04.000 --> 00:00:07.000 Autism is a very big continuum 00:00:07.000 --> 00:00:10.000 that goes from very severe -- the child remains non-verbal -- 00:00:10.000 --> 00:00:13.000 all the way up to brilliant scientists and engineers. 00:00:13.000 --> 00:00:15.000 And I actually feel at home here, 00:00:15.000 --> 00:00:17.000 because there's a lot of autism genetics here. 00:00:17.000 --> 00:00:19.000 You wouldn't have any... 00:00:19.000 --> 00:00:23.000 (Applause) NOTE Paragraph 00:00:23.000 --> 00:00:25.000 It's a continuum of traits. 00:00:25.000 --> 00:00:28.000 When does a nerd turn into 00:00:28.000 --> 00:00:30.000 Asperger, which is just mild autism? 00:00:30.000 --> 00:00:33.000 I mean, Einstein and Mozart 00:00:33.000 --> 00:00:35.000 and Tesla would all be probably diagnosed 00:00:35.000 --> 00:00:37.000 as autistic spectrum today. 00:00:37.000 --> 00:00:40.000 And one of the things that is really going to concern me is 00:00:40.000 --> 00:00:43.000 getting these kids to be the ones that are going to invent 00:00:43.000 --> 00:00:45.000 the next energy things, 00:00:45.000 --> 00:00:49.000 you know, that Bill Gates talked about this morning. NOTE Paragraph 00:00:49.000 --> 00:00:51.000 OK. Now, if you want to understand 00:00:51.000 --> 00:00:53.000 autism, animals. 00:00:53.000 --> 00:00:55.000 And I want to talk to you now about different ways of thinking. 00:00:55.000 --> 00:00:58.000 You have to get away from verbal language. 00:00:58.000 --> 00:01:00.000 I think in pictures, 00:01:00.000 --> 00:01:03.000 I don't think in language. 00:01:03.000 --> 00:01:05.000 Now, the thing about the autistic mind 00:01:05.000 --> 00:01:08.000 is it attends to details. 00:01:08.000 --> 00:01:10.000 OK, this is a test where you either have to 00:01:10.000 --> 00:01:12.000 pick out the big letters, or pick out the little letters, 00:01:12.000 --> 00:01:14.000 and the autistic mind picks out the 00:01:14.000 --> 00:01:16.000 little letters more quickly. NOTE Paragraph 00:01:16.000 --> 00:01:20.000 And the thing is, the normal brain ignores the details. 00:01:20.000 --> 00:01:22.000 Well, if you're building a bridge, details are pretty important 00:01:22.000 --> 00:01:25.000 because it will fall down if you ignore the details. 00:01:25.000 --> 00:01:28.000 And one of my big concerns with a lot of policy things today 00:01:28.000 --> 00:01:30.000 is things are getting too abstract. 00:01:30.000 --> 00:01:32.000 People are getting away from doing 00:01:32.000 --> 00:01:34.000 hands-on stuff. 00:01:34.000 --> 00:01:36.000 I'm really concerned that a lot of the schools have taken out 00:01:36.000 --> 00:01:38.000 the hands-on classes, 00:01:38.000 --> 00:01:40.000 because art, and classes like that, 00:01:40.000 --> 00:01:42.000 those are the classes where I excelled. NOTE Paragraph 00:01:42.000 --> 00:01:44.000 In my work with cattle, 00:01:44.000 --> 00:01:47.000 I noticed a lot of little things that most people don't notice 00:01:47.000 --> 00:01:49.000 would make the cattle balk. Like, for example, 00:01:49.000 --> 00:01:52.000 this flag waving, right in front of the veterinary facility. 00:01:52.000 --> 00:01:55.000 This feed yard was going to tear down their whole veterinary facility; 00:01:55.000 --> 00:01:57.000 all they needed to do was move the flag. 00:01:57.000 --> 00:02:00.000 Rapid movement, contrast. 00:02:00.000 --> 00:02:02.000 In the early '70s when I started, I got right down 00:02:02.000 --> 00:02:04.000 in the chutes to see what cattle were seeing. 00:02:04.000 --> 00:02:07.000 People thought that was crazy. A coat on a fence would make them balk, 00:02:07.000 --> 00:02:10.000 shadows would make them balk, a hose on the floor ... 00:02:10.000 --> 00:02:12.000 people weren't noticing these things -- 00:02:12.000 --> 00:02:14.000 a chain hanging down -- 00:02:14.000 --> 00:02:16.000 and that's shown very, very nicely in the movie. NOTE Paragraph 00:02:16.000 --> 00:02:18.000 In fact, I loved the movie, how they 00:02:18.000 --> 00:02:20.000 duplicated all my projects. That's the geek side. 00:02:20.000 --> 00:02:23.000 My drawings got to star in the movie too. 00:02:23.000 --> 00:02:25.000 And actually it's called "Temple Grandin," 00:02:25.000 --> 00:02:27.000 not "Thinking In Pictures." NOTE Paragraph 00:02:27.000 --> 00:02:29.000 So, what is thinking in pictures? It's literally movies 00:02:29.000 --> 00:02:31.000 in your head. 00:02:31.000 --> 00:02:33.000 My mind works like Google for images. 00:02:33.000 --> 00:02:36.000 Now, when I was a young kid I didn't know my thinking was different. 00:02:36.000 --> 00:02:38.000 I thought everybody thought in pictures. 00:02:38.000 --> 00:02:40.000 And then when I did my book, "Thinking In Pictures," 00:02:40.000 --> 00:02:43.000 I start interviewing people about how they think. 00:02:43.000 --> 00:02:45.000 And I was shocked to find out that 00:02:45.000 --> 00:02:47.000 my thinking was quite different. Like if I say, 00:02:47.000 --> 00:02:49.000 "Think about a church steeple" 00:02:49.000 --> 00:02:51.000 most people get this sort of generalized generic one. 00:02:51.000 --> 00:02:53.000 Now, maybe that's not true in this room, 00:02:53.000 --> 00:02:57.000 but it's going to be true in a lot of different places. 00:02:57.000 --> 00:02:59.000 I see only specific pictures. 00:02:59.000 --> 00:03:03.000 They flash up into my memory, just like Google for pictures. 00:03:03.000 --> 00:03:05.000 And in the movie, they've got a great scene in there 00:03:05.000 --> 00:03:09.000 where the word "shoe" is said, and a whole bunch of '50s and '60s shoes 00:03:09.000 --> 00:03:11.000 pop into my imagination. NOTE Paragraph 00:03:11.000 --> 00:03:13.000 OK, there is my childhood church, 00:03:13.000 --> 00:03:16.000 that's specific. There's some more, Fort Collins. 00:03:16.000 --> 00:03:18.000 OK, how about famous ones? 00:03:18.000 --> 00:03:21.000 And they just kind of come up, kind of like this. 00:03:21.000 --> 00:03:24.000 Just really quickly, like Google for pictures. 00:03:24.000 --> 00:03:26.000 And they come up one at a time, 00:03:26.000 --> 00:03:28.000 and then I think, "OK, well maybe we can have it snow, 00:03:28.000 --> 00:03:30.000 or we can have a thunderstorm," 00:03:30.000 --> 00:03:33.000 and I can hold it there and turn them into videos. NOTE Paragraph 00:03:33.000 --> 00:03:36.000 Now, visual thinking was a tremendous asset 00:03:36.000 --> 00:03:39.000 in my work designing cattle-handling facilities. 00:03:39.000 --> 00:03:41.000 And I've worked really hard on improving 00:03:41.000 --> 00:03:43.000 how cattle are treated at the slaughter plant. 00:03:43.000 --> 00:03:46.000 I'm not going to go into any gucky slaughter slides. 00:03:46.000 --> 00:03:48.000 I've got that stuff up on YouTube if you want to look at it. 00:03:48.000 --> 00:03:52.000 But, one of the things that I was able to do in my design work 00:03:52.000 --> 00:03:54.000 is I could actually test run 00:03:54.000 --> 00:03:56.000 a piece of equipment in my mind, 00:03:56.000 --> 00:03:59.000 just like a virtual reality computer system. 00:03:59.000 --> 00:04:01.000 And this is an aerial view 00:04:01.000 --> 00:04:04.000 of a recreation of one of my projects that was used in the movie. 00:04:04.000 --> 00:04:06.000 That was like just so super cool. 00:04:06.000 --> 00:04:08.000 And there were a lot of kind of Asperger types 00:04:08.000 --> 00:04:11.000 and autism types working out there on the movie set too. 00:04:11.000 --> 00:04:13.000 (Laughter) 00:04:13.000 --> 00:04:15.000 But one of the things that really worries me 00:04:15.000 --> 00:04:19.000 is: Where's the younger version of those kids going today? 00:04:19.000 --> 00:04:22.000 They're not ending up in Silicon Valley, where they belong. 00:04:22.000 --> 00:04:25.000 (Laughter) 00:04:25.000 --> 00:04:30.000 (Applause) NOTE Paragraph 00:04:30.000 --> 00:04:33.000 Now, one of the things I learned very early on because I wasn't that social, 00:04:33.000 --> 00:04:37.000 is I had to sell my work, and not myself. 00:04:37.000 --> 00:04:39.000 And the way I sold livestock jobs 00:04:39.000 --> 00:04:42.000 is I showed off my drawings, I showed off pictures of things. 00:04:42.000 --> 00:04:44.000 Another thing that helped me as a little kid 00:04:44.000 --> 00:04:46.000 is, boy, in the '50s, you were taught manners. 00:04:46.000 --> 00:04:48.000 You were taught you can't pull the merchandise off the shelves 00:04:48.000 --> 00:04:50.000 in the store and throw it around. NOTE Paragraph 00:04:50.000 --> 00:04:53.000 Now, when kids get to be in third or fourth grade, 00:04:53.000 --> 00:04:56.000 you might see that this kid's going to be a visual thinker, 00:04:56.000 --> 00:04:58.000 drawing in perspective. Now, I want to 00:04:58.000 --> 00:05:00.000 emphasize that not every autistic kid 00:05:00.000 --> 00:05:02.000 is going to be a visual thinker. 00:05:02.000 --> 00:05:06.000 Now, I had this brain scan done several years ago, 00:05:06.000 --> 00:05:08.000 and I used to joke around about having a 00:05:08.000 --> 00:05:10.000 gigantic Internet trunk line 00:05:10.000 --> 00:05:12.000 going deep into my visual cortex. 00:05:12.000 --> 00:05:14.000 This is tensor imaging. 00:05:14.000 --> 00:05:16.000 And my great big internet trunk line 00:05:16.000 --> 00:05:18.000 is twice as big as the control's. 00:05:18.000 --> 00:05:20.000 The red lines there are me, 00:05:20.000 --> 00:05:24.000 and the blue lines are the sex and age-matched control. 00:05:24.000 --> 00:05:26.000 And there I got a gigantic one, 00:05:26.000 --> 00:05:28.000 and the control over there, the blue one, 00:05:28.000 --> 00:05:32.000 has got a really small one. NOTE Paragraph 00:05:32.000 --> 00:05:34.000 And some of the research now is showing 00:05:34.000 --> 00:05:38.000 is that people on the spectrum actually think with primary visual cortex. 00:05:38.000 --> 00:05:41.000 Now, the thing is, the visual thinker's just one kind of mind. 00:05:41.000 --> 00:05:44.000 You see, the autistic mind tends to be a specialist mind -- 00:05:44.000 --> 00:05:48.000 good at one thing, bad at something else. 00:05:48.000 --> 00:05:50.000 And where I was bad was algebra. And I was never allowed 00:05:50.000 --> 00:05:52.000 to take geometry or trig. 00:05:52.000 --> 00:05:55.000 Gigantic mistake: I'm finding a lot of kids who need to skip algebra, 00:05:55.000 --> 00:05:57.000 go right to geometry and trig. NOTE Paragraph 00:05:57.000 --> 00:06:00.000 Now, another kind of mind is the pattern thinker. 00:06:00.000 --> 00:06:02.000 More abstract. These are your engineers, 00:06:02.000 --> 00:06:04.000 your computer programmers. 00:06:04.000 --> 00:06:06.000 Now, this is pattern thinking. That praying mantis 00:06:06.000 --> 00:06:08.000 is made from a single sheet of paper -- 00:06:08.000 --> 00:06:10.000 no scotch tape, no cuts. 00:06:10.000 --> 00:06:13.000 And there in the background is the pattern for folding it. 00:06:13.000 --> 00:06:15.000 Here are the types of thinking: 00:06:15.000 --> 00:06:18.000 photo-realistic visual thinkers, like me; 00:06:18.000 --> 00:06:22.000 pattern thinkers, music and math minds. 00:06:22.000 --> 00:06:24.000 Some of these oftentimes have problems with reading. 00:06:24.000 --> 00:06:26.000 You also will see these kind of problems 00:06:26.000 --> 00:06:29.000 with kids that are dyslexic. 00:06:29.000 --> 00:06:31.000 You'll see these different kinds of minds. 00:06:31.000 --> 00:06:34.000 And then there's a verbal mind, they know every fact about everything. NOTE Paragraph 00:06:34.000 --> 00:06:36.000 Now, another thing is the sensory issues. 00:06:36.000 --> 00:06:40.000 I was really concerned about having to wear this gadget on my face. 00:06:40.000 --> 00:06:43.000 And I came in half an hour beforehand 00:06:43.000 --> 00:06:45.000 so I could have it put on and kind of get used to it, 00:06:45.000 --> 00:06:48.000 and they got it bent so it's not hitting my chin. 00:06:48.000 --> 00:06:51.000 But sensory is an issue. Some kids are bothered by fluorescent lights; 00:06:51.000 --> 00:06:54.000 others have problems with sound sensitivity. 00:06:54.000 --> 00:06:57.000 You know, it's going to be variable. NOTE Paragraph 00:06:57.000 --> 00:07:01.000 Now, visual thinking gave me a whole lot of insight 00:07:01.000 --> 00:07:03.000 into the animal mind. 00:07:03.000 --> 00:07:06.000 Because think about it: An animal is a sensory-based thinker, 00:07:06.000 --> 00:07:10.000 not verbal -- thinks in pictures, 00:07:10.000 --> 00:07:13.000 thinks in sounds, thinks in smells. 00:07:13.000 --> 00:07:16.000 Think about how much information there is there on the local fire hydrant. 00:07:16.000 --> 00:07:19.000 He knows who's been there, when they were there. 00:07:19.000 --> 00:07:22.000 Are they friend or foe? Is there anybody he can go mate with? 00:07:22.000 --> 00:07:25.000 There's a ton of information on that fire hydrant. 00:07:25.000 --> 00:07:29.000 It's all very detailed information, 00:07:29.000 --> 00:07:31.000 and, looking at these kind of details 00:07:31.000 --> 00:07:33.000 gave me a lot of insight into animals. NOTE Paragraph 00:07:33.000 --> 00:07:37.000 Now, the animal mind, and also my mind, 00:07:37.000 --> 00:07:39.000 puts sensory-based information 00:07:39.000 --> 00:07:41.000 into categories. 00:07:41.000 --> 00:07:43.000 Man on a horse 00:07:43.000 --> 00:07:45.000 and a man on the ground -- 00:07:45.000 --> 00:07:47.000 that is viewed as two totally different things. 00:07:47.000 --> 00:07:50.000 You could have a horse that's been abused by a rider. 00:07:50.000 --> 00:07:52.000 They'll be absolutely fine with the veterinarian 00:07:52.000 --> 00:07:55.000 and with the horseshoer, but you can't ride him. 00:07:55.000 --> 00:07:58.000 You have another horse, where maybe the horseshoer beat him up 00:07:58.000 --> 00:08:00.000 and he'll be terrible for anything on the ground, 00:08:00.000 --> 00:08:03.000 with the veterinarian, but a person can ride him. 00:08:03.000 --> 00:08:05.000 Cattle are the same way. 00:08:05.000 --> 00:08:07.000 Man on a horse, 00:08:07.000 --> 00:08:09.000 a man on foot -- they're two different things. 00:08:09.000 --> 00:08:11.000 You see, it's a different picture. 00:08:11.000 --> 00:08:14.000 See, I want you to think about just how specific this is. NOTE Paragraph 00:08:14.000 --> 00:08:18.000 Now, this ability to put information into categories, 00:08:18.000 --> 00:08:21.000 I find a lot of people are not very good at this. 00:08:21.000 --> 00:08:23.000 When I'm out troubleshooting equipment 00:08:23.000 --> 00:08:25.000 or problems with something in a plant, 00:08:25.000 --> 00:08:29.000 they don't seem to be able to figure out, "Do I have a training people issue? 00:08:29.000 --> 00:08:31.000 Or do I have something wrong with the equipment?" 00:08:31.000 --> 00:08:33.000 In other words, categorize equipment problem 00:08:33.000 --> 00:08:35.000 from a people problem. 00:08:35.000 --> 00:08:38.000 I find a lot of people have difficulty doing that. 00:08:38.000 --> 00:08:41.000 Now, let's say I figure out it's an equipment problem. 00:08:41.000 --> 00:08:43.000 Is it a minor problem, with something simple I can fix? 00:08:43.000 --> 00:08:46.000 Or is the whole design of the system wrong? 00:08:46.000 --> 00:08:49.000 People have a hard time figuring that out. NOTE Paragraph 00:08:49.000 --> 00:08:51.000 Let's just look at something like, you know, 00:08:51.000 --> 00:08:53.000 solving problems with making airlines safer. 00:08:53.000 --> 00:08:55.000 Yeah, I'm a million-mile flyer. 00:08:55.000 --> 00:08:57.000 I do lots and lots of flying, 00:08:57.000 --> 00:09:00.000 and if I was at the FAA, 00:09:00.000 --> 00:09:04.000 what would I be doing a lot of direct observation of? 00:09:04.000 --> 00:09:06.000 It would be their airplane tails. 00:09:06.000 --> 00:09:09.000 You know, five fatal wrecks in the last 20 years, 00:09:09.000 --> 00:09:13.000 the tail either came off or steering stuff inside the tail broke 00:09:13.000 --> 00:09:15.000 in some way. 00:09:15.000 --> 00:09:17.000 It's tails, pure and simple. 00:09:17.000 --> 00:09:19.000 And when the pilots walk around the plane, guess what? They can't see 00:09:19.000 --> 00:09:21.000 that stuff inside the tail. 00:09:21.000 --> 00:09:23.000 You know, now as I think about that, 00:09:23.000 --> 00:09:26.000 I'm pulling up all of that specific information. 00:09:26.000 --> 00:09:29.000 It's specific. See, my thinking's bottom-up. 00:09:29.000 --> 00:09:33.000 I take all the little pieces and I put the pieces together like a puzzle. NOTE Paragraph 00:09:33.000 --> 00:09:35.000 Now, here is a horse that was deathly afraid 00:09:35.000 --> 00:09:37.000 of black cowboy hats. 00:09:37.000 --> 00:09:39.000 He'd been abused by somebody with a black cowboy hat. 00:09:39.000 --> 00:09:42.000 White cowboy hats, that was absolutely fine. 00:09:42.000 --> 00:09:45.000 Now, the thing is, the world is going to need 00:09:45.000 --> 00:09:47.000 all of the different kinds of minds 00:09:47.000 --> 00:09:49.000 to work together. 00:09:49.000 --> 00:09:52.000 We've got to work on developing all these different kinds of minds. 00:09:52.000 --> 00:09:55.000 And one of the things that is driving me really crazy, 00:09:55.000 --> 00:09:57.000 as I travel around and I do autism meetings, 00:09:57.000 --> 00:10:00.000 is I'm seeing a lot of smart, geeky, nerdy kids, 00:10:00.000 --> 00:10:03.000 and they just aren't very social, 00:10:03.000 --> 00:10:05.000 and nobody's working on developing their interest 00:10:05.000 --> 00:10:07.000 in something like science. NOTE Paragraph 00:10:07.000 --> 00:10:10.000 And this brings up the whole thing of my science teacher. 00:10:10.000 --> 00:10:13.000 My science teacher is shown absolutely beautifully in the movie. 00:10:13.000 --> 00:10:15.000 I was a goofball student. When I was in high school 00:10:15.000 --> 00:10:18.000 I just didn't care at all about studying, 00:10:18.000 --> 00:10:21.000 until I had Mr. Carlock's science class. 00:10:21.000 --> 00:10:24.000 He was now Dr. Carlock in the movie. 00:10:24.000 --> 00:10:27.000 And he got me challenged 00:10:27.000 --> 00:10:30.000 to figure out an optical illusion room. 00:10:30.000 --> 00:10:32.000 This brings up the whole thing of you've got to show kids 00:10:32.000 --> 00:10:34.000 interesting stuff. 00:10:34.000 --> 00:10:37.000 You know, one of the things that I think maybe TED ought to do 00:10:37.000 --> 00:10:40.000 is tell all the schools about all the great lectures that are on TED, 00:10:40.000 --> 00:10:42.000 and there's all kinds of great stuff on the Internet 00:10:42.000 --> 00:10:44.000 to get these kids turned on. 00:10:44.000 --> 00:10:47.000 Because I'm seeing a lot of these geeky nerdy kids, 00:10:47.000 --> 00:10:50.000 and the teachers out in the Midwest, and the other parts of the country, 00:10:50.000 --> 00:10:52.000 when you get away from these tech areas, 00:10:52.000 --> 00:10:54.000 they don't know what to do with these kids. 00:10:54.000 --> 00:10:56.000 And they're not going down the right path. NOTE Paragraph 00:10:56.000 --> 00:10:58.000 The thing is, you can make a mind 00:10:58.000 --> 00:11:01.000 to be more of a thinking and cognitive mind, 00:11:01.000 --> 00:11:04.000 or your mind can be wired to be more social. 00:11:04.000 --> 00:11:06.000 And what some of the research now has shown in autism 00:11:06.000 --> 00:11:08.000 is there may by extra wiring back here, 00:11:08.000 --> 00:11:11.000 in the really brilliant mind, and we lose a few social circuits here. 00:11:11.000 --> 00:11:15.000 It's kind of a trade-off between thinking and social. 00:11:15.000 --> 00:11:17.000 And then you can get into the point where it's so severe 00:11:17.000 --> 00:11:20.000 you're going to have a person that's going to be non-verbal. 00:11:20.000 --> 00:11:22.000 In the normal human mind 00:11:22.000 --> 00:11:25.000 language covers up the visual thinking we share with animals. NOTE Paragraph 00:11:25.000 --> 00:11:28.000 This is the work of Dr. Bruce Miller. 00:11:28.000 --> 00:11:31.000 And he studied Alzheimer's patients 00:11:31.000 --> 00:11:33.000 that had frontal temporal lobe dementia. 00:11:33.000 --> 00:11:36.000 And the dementia ate out the language parts of the brain, 00:11:36.000 --> 00:11:41.000 and then this artwork came out of somebody who used to install stereos in cars. 00:11:41.000 --> 00:11:45.000 Now, Van Gogh doesn't know anything about physics, 00:11:45.000 --> 00:11:47.000 but I think it's very interesting 00:11:47.000 --> 00:11:49.000 that there was some work done to show that 00:11:49.000 --> 00:11:51.000 this eddy pattern in this painting 00:11:51.000 --> 00:11:54.000 followed a statistical model of turbulence, 00:11:54.000 --> 00:11:56.000 which brings up the whole interesting idea 00:11:56.000 --> 00:11:58.000 of maybe some of this mathematical patterns 00:11:58.000 --> 00:12:00.000 is in our own head. NOTE Paragraph 00:12:00.000 --> 00:12:02.000 And the Wolfram stuff -- I was taking 00:12:02.000 --> 00:12:04.000 notes and I was writing down all the 00:12:04.000 --> 00:12:06.000 search words I could use, 00:12:06.000 --> 00:12:10.000 because I think that's going to go on in my autism lectures. 00:12:10.000 --> 00:12:12.000 We've got to show these kids interesting stuff. 00:12:12.000 --> 00:12:14.000 And they've taken out the autoshop class 00:12:14.000 --> 00:12:16.000 and the drafting class and the art class. 00:12:16.000 --> 00:12:19.000 I mean art was my best subject in school. NOTE Paragraph 00:12:19.000 --> 00:12:21.000 We've got to think about all these different kinds of minds, 00:12:21.000 --> 00:12:24.000 and we've got to absolutely work with these kind of minds, 00:12:24.000 --> 00:12:27.000 because we absolutely are going to need 00:12:27.000 --> 00:12:30.000 these kind of people in the future. 00:12:30.000 --> 00:12:32.000 And let's talk about jobs. 00:12:32.000 --> 00:12:34.000 OK, my science teacher got me studying 00:12:34.000 --> 00:12:37.000 because I was a goofball that didn't want to study. 00:12:37.000 --> 00:12:39.000 But you know what? I was getting work experience. 00:12:39.000 --> 00:12:41.000 I'm seeing too many of these smart kids who haven't learned basic things, 00:12:41.000 --> 00:12:43.000 like how to be on time. 00:12:43.000 --> 00:12:45.000 I was taught that when I was eight years old. 00:12:45.000 --> 00:12:48.000 You know, how to have table manners at granny's Sunday party. 00:12:48.000 --> 00:12:51.000 I was taught that when I was very, very young. 00:12:51.000 --> 00:12:54.000 And when I was 13, I had a job at a dressmaker's shop 00:12:54.000 --> 00:12:56.000 sewing clothes. 00:12:56.000 --> 00:12:59.000 I did internships in college, 00:12:59.000 --> 00:13:02.000 I was building things, 00:13:02.000 --> 00:13:05.000 and I also had to learn how to do assignments. NOTE Paragraph 00:13:05.000 --> 00:13:09.000 You know, all I wanted to do was draw pictures of horses when I was little. 00:13:09.000 --> 00:13:11.000 My mother said, "Well let's do a picture of something else." 00:13:11.000 --> 00:13:13.000 They've got to learn how to do something else. 00:13:13.000 --> 00:13:15.000 Let's say the kid is fixated on Legos. 00:13:15.000 --> 00:13:18.000 Let's get him working on building different things. 00:13:18.000 --> 00:13:20.000 The thing about the autistic mind 00:13:20.000 --> 00:13:22.000 is it tends to be fixated. 00:13:22.000 --> 00:13:24.000 Like if a kid loves racecars, 00:13:24.000 --> 00:13:26.000 let's use racecars for math. 00:13:26.000 --> 00:13:29.000 Let's figure out how long it takes a racecar to go a certain distance. 00:13:29.000 --> 00:13:33.000 In other words, use that fixation 00:13:33.000 --> 00:13:36.000 in order to motivate that kid, that's one of the things we need to do. 00:13:36.000 --> 00:13:39.000 I really get fed up when they, you know, the teachers, 00:13:39.000 --> 00:13:42.000 especially when you get away from this part of the country, 00:13:42.000 --> 00:13:44.000 they don't know what to do with these smart kids. 00:13:44.000 --> 00:13:46.000 It just drives me crazy. NOTE Paragraph 00:13:46.000 --> 00:13:48.000 What can visual thinkers do when they grow up? 00:13:48.000 --> 00:13:51.000 They can do graphic design, all kinds of stuff with computers, 00:13:51.000 --> 00:13:56.000 photography, industrial design. 00:13:56.000 --> 00:13:58.000 The pattern thinkers, they're the ones that are going to be 00:13:58.000 --> 00:14:01.000 your mathematicians, your software engineers, 00:14:01.000 --> 00:14:05.000 your computer programmers, all of those kinds of jobs. 00:14:05.000 --> 00:14:08.000 And then you've got the word minds. They make great journalists, 00:14:08.000 --> 00:14:11.000 and they also make really, really good stage actors. 00:14:11.000 --> 00:14:13.000 Because the thing about being autistic is, 00:14:13.000 --> 00:14:16.000 I had to learn social skills like being in a play. 00:14:16.000 --> 00:14:19.000 It's just kind of -- you just have to learn it. NOTE Paragraph 00:14:19.000 --> 00:14:22.000 And we need to be working with these students. 00:14:22.000 --> 00:14:24.000 And this brings up mentors. 00:14:24.000 --> 00:14:27.000 You know, my science teacher was not an accredited teacher. 00:14:27.000 --> 00:14:29.000 He was a NASA space scientist. 00:14:29.000 --> 00:14:31.000 Now, some states now are getting it to where 00:14:31.000 --> 00:14:33.000 if you have a degree in biology, or a degree in chemistry, 00:14:33.000 --> 00:14:36.000 you can come into the school and teach biology or chemistry. 00:14:36.000 --> 00:14:38.000 We need to be doing that. 00:14:38.000 --> 00:14:40.000 Because what I'm observing is 00:14:40.000 --> 00:14:42.000 the good teachers, for a lot of these kids, 00:14:42.000 --> 00:14:44.000 are out in the community colleges, 00:14:44.000 --> 00:14:47.000 but we need to be getting some of these good teachers into the high schools. NOTE Paragraph 00:14:47.000 --> 00:14:50.000 Another thing that can be very, very, very successful is 00:14:50.000 --> 00:14:53.000 there is a lot of people that may have retired 00:14:53.000 --> 00:14:56.000 from working in the software industry, and they can teach your kid. 00:14:56.000 --> 00:14:59.000 And it doesn't matter if what they teach them is old, 00:14:59.000 --> 00:15:02.000 because what you're doing is you're lighting the spark. 00:15:02.000 --> 00:15:05.000 You're getting that kid turned on. 00:15:05.000 --> 00:15:08.000 And you get him turned on, then he'll learn all the new stuff. 00:15:08.000 --> 00:15:10.000 Mentors are just essential. 00:15:10.000 --> 00:15:12.000 I cannot emphasize enough 00:15:12.000 --> 00:15:15.000 what my science teacher did for me. 00:15:15.000 --> 00:15:18.000 And we've got to mentor them, hire them. NOTE Paragraph 00:15:18.000 --> 00:15:20.000 And if you bring them in for internships in your companies, 00:15:20.000 --> 00:15:23.000 the thing about the autism, Asperger-y kind of mind, 00:15:23.000 --> 00:15:26.000 you've got to give them a specific task. Don't just say, "Design new software." 00:15:26.000 --> 00:15:28.000 You've got to tell them something a lot more specific: 00:15:28.000 --> 00:15:31.000 "Well, we're designing a software for a phone 00:15:31.000 --> 00:15:33.000 and it has to do some specific thing. 00:15:33.000 --> 00:15:35.000 And it can only use so much memory." 00:15:35.000 --> 00:15:37.000 That's the kind of specificity you need. NOTE Paragraph 00:15:37.000 --> 00:15:39.000 Well, that's the end of my talk. 00:15:39.000 --> 00:15:41.000 And I just want to thank everybody for coming. 00:15:41.000 --> 00:15:43.000 It was great to be here. NOTE Paragraph 00:15:43.000 --> 00:15:55.000 (Applause) NOTE Paragraph 00:15:55.000 --> 00:15:58.000 Oh, you've got a question for me? OK. 00:15:58.000 --> 00:15:59.000 (Applause) NOTE Paragraph 00:15:59.000 --> 00:16:03.000 Chris Anderson: Thank you so much for that. 00:16:03.000 --> 00:16:05.000 You know, you once wrote, I like this quote, 00:16:05.000 --> 00:16:07.000 "If by some magic, autism had been 00:16:07.000 --> 00:16:10.000 eradicated from the face of the Earth, 00:16:10.000 --> 00:16:13.000 then men would still be socializing in front of a wood fire 00:16:13.000 --> 00:16:15.000 at the entrance to a cave." NOTE Paragraph 00:16:15.000 --> 00:16:17.000 Temple Grandin: Because who do you think made the first stone spears? 00:16:17.000 --> 00:16:20.000 The Asperger guy. And if you were to get rid of all the autism genetics 00:16:20.000 --> 00:16:22.000 there would be no more Silicon Valley, 00:16:22.000 --> 00:16:24.000 and the energy crisis would not be solved. 00:16:24.000 --> 00:16:27.000 (Applause) NOTE Paragraph 00:16:27.000 --> 00:16:29.000 CA: So, I want to ask you a couple other questions, 00:16:29.000 --> 00:16:31.000 and if any of these feel inappropriate, 00:16:31.000 --> 00:16:33.000 it's okay just to say, "Next question." 00:16:33.000 --> 00:16:35.000 But if there is someone here 00:16:35.000 --> 00:16:37.000 who has an autistic child, 00:16:37.000 --> 00:16:39.000 or knows an autistic child 00:16:39.000 --> 00:16:42.000 and feels kind of cut off from them, 00:16:42.000 --> 00:16:44.000 what advice would you give them? NOTE Paragraph 00:16:44.000 --> 00:16:46.000 TG: Well, first of all, you've got to look at age. 00:16:46.000 --> 00:16:48.000 If you have a two, three or four year old 00:16:48.000 --> 00:16:50.000 you know, no speech, no social interaction, 00:16:50.000 --> 00:16:52.000 I can't emphasize enough: 00:16:52.000 --> 00:16:56.000 Don't wait, you need at least 20 hours a week of one-to-one teaching. 00:16:56.000 --> 00:16:59.000 You know, the thing is, autism comes in different degrees. 00:16:59.000 --> 00:17:01.000 There's going to be about half the people on the spectrum 00:17:01.000 --> 00:17:03.000 that are not going to learn to talk, and they're not going to be working 00:17:03.000 --> 00:17:06.000 Silicon Valley, that would not be a reasonable thing for them to do. NOTE Paragraph 00:17:06.000 --> 00:17:08.000 But then you get the smart, geeky kids 00:17:08.000 --> 00:17:10.000 that have a touch of autism, 00:17:10.000 --> 00:17:12.000 and that's where you've got to get them turned on 00:17:12.000 --> 00:17:14.000 with doing interesting things. 00:17:14.000 --> 00:17:17.000 I got social interaction through shared interest. 00:17:17.000 --> 00:17:21.000 I rode horses with other kids, I made model rockets with other kids, 00:17:21.000 --> 00:17:23.000 did electronics lab with other kids, 00:17:23.000 --> 00:17:25.000 and in the '60s, it was gluing mirrors 00:17:25.000 --> 00:17:28.000 onto a rubber membrane on a speaker to make a light show. 00:17:28.000 --> 00:17:31.000 That was like, we considered that super cool. NOTE Paragraph 00:17:31.000 --> 00:17:33.000 CA: Is it unrealistic for them 00:17:33.000 --> 00:17:35.000 to hope or think that that child 00:17:35.000 --> 00:17:38.000 loves them, as some might, as most, wish? NOTE Paragraph 00:17:38.000 --> 00:17:40.000 TG: Well let me tell you, that child will be loyal, 00:17:40.000 --> 00:17:42.000 and if your house is burning down, they're going to get you out of it. NOTE Paragraph 00:17:42.000 --> 00:17:45.000 CA: Wow. So, most people, if you ask them 00:17:45.000 --> 00:17:47.000 what are they most passionate about, they'd say things like, 00:17:47.000 --> 00:17:50.000 "My kids" or "My lover." 00:17:50.000 --> 00:17:53.000 What are you most passionate about? NOTE Paragraph 00:17:53.000 --> 00:17:55.000 TG: I'm passionate about that the things I do 00:17:55.000 --> 00:17:57.000 are going to make the world a better place. 00:17:57.000 --> 00:17:59.000 When I have a mother of an autistic child say, 00:17:59.000 --> 00:18:01.000 "My kid went to college because of your book, 00:18:01.000 --> 00:18:03.000 or one of your lectures," that makes me happy. NOTE Paragraph 00:18:03.000 --> 00:18:06.000 You know, the slaughter plants, I've worked with them 00:18:06.000 --> 00:18:08.000 in the '80s; they were absolutely awful. 00:18:08.000 --> 00:18:12.000 I developed a really simple scoring system for slaughter plants 00:18:12.000 --> 00:18:14.000 where you just measure outcomes: How many cattle fell down? 00:18:14.000 --> 00:18:16.000 How many cattle got poked with the prodder? 00:18:16.000 --> 00:18:18.000 How many cattle are mooing their heads off? 00:18:18.000 --> 00:18:20.000 And it's very, very simple. 00:18:20.000 --> 00:18:22.000 You directly observe a few simple things. 00:18:22.000 --> 00:18:24.000 It's worked really well. I get satisfaction out of 00:18:24.000 --> 00:18:27.000 seeing stuff that makes real change 00:18:27.000 --> 00:18:29.000 in the real world. We need a lot more of that, 00:18:29.000 --> 00:18:31.000 and a lot less abstract stuff. 00:18:31.000 --> 00:18:38.000 (Applause) NOTE Paragraph 00:18:38.000 --> 00:18:40.000 CA: When we were talking on the phone, one of the things you said that 00:18:40.000 --> 00:18:42.000 really astonished me was you said one thing 00:18:42.000 --> 00:18:46.000 you were passionate about was server farms. Tell me about that. NOTE Paragraph 00:18:46.000 --> 00:18:49.000 TG: Well the reason why I got really excited when I read about that, 00:18:49.000 --> 00:18:52.000 it contains knowledge. 00:18:52.000 --> 00:18:54.000 It's libraries. 00:18:54.000 --> 00:18:56.000 And to me, knowledge is something 00:18:56.000 --> 00:18:58.000 that is extremely valuable. So, maybe, over 10 years ago 00:18:58.000 --> 00:19:00.000 now our library got flooded. 00:19:00.000 --> 00:19:02.000 And this is before the Internet got really big. 00:19:02.000 --> 00:19:04.000 And I was really upset about all the books being wrecked, 00:19:04.000 --> 00:19:06.000 because it was knowledge being destroyed. 00:19:06.000 --> 00:19:08.000 And server farms, or data centers 00:19:08.000 --> 00:19:11.000 are great libraries of knowledge. NOTE Paragraph 00:19:11.000 --> 00:19:14.000 CA: Temple, can I just say it's an absolute delight to have you at TED. NOTE Paragraph 00:19:14.000 --> 00:19:17.000 TG: Well thank you so much. Thank you. 00:19:17.000 --> 00:19:23.000 (Applause)