English Acquisition IA k , IIA f , 2011 12 ( 14 ) ( ) - - PowerPoint PPT Presentation

SLIDE 1

2011/07/12 (火)

English Acquisition IAk, IIAf, 2011 第12回 (全14回)

黒田 航 (非常勤)

Tuesday, July 12, 2011

SLIDE 2

講義資料のWebページ

✤ URL

✤ http://clsl.hi.h.kyoto-u.ac.jp/~kkuroda/lectures.html

✤ 予習や復習に使って下さい ✤ 解答もこのページから入手可能

Tuesday, July 12, 2011

SLIDE 3

ボーナス試験

✤ 最期の授業 7/26 は任意参加のボーナス試験です

✤ 出席回数の足りない人は任意でないです

✤ 授業でやったのと同じ課題を行なう

✤ ハズレがアタリに ✤ アタリはアタリのまま

✤ 出題範囲

✤ L1, L2, L4, L6, L7 ✤ 全部The Feynman Lectures on Physicsのところ Tuesday, July 12, 2011

SLIDE 4

任意参加でない人たち

✤ 今のままではFの方々

✤ E1Ak ✤ 中島 裕貴 ✤ EA2Af ✤ 藤本 拡二

✤ 気をつけた方がよい方々

✤ EA1Ak ✤ 中尾 健太郎, 松田 朋也 ✤ EA2Af ✤ 中村陽一郎, 原 将樹, 西河 拓哉, 武藤 弘平

Tuesday, July 12, 2011

SLIDE 5

本日の予定

✤ 前半30分

• 1. L11の聞き取り課題の結果の報告
• 2. 正解の解説

✤ 休憩5分 ✤ 後半40分

• TEDを使った聴き取り訓練の3回目 (L12)
• Temple Gradin: The world needs all kinds of mind
• 主題
• 自閉症 (autism), 創造性 (creativity), 脳科学 (brain science)

Tuesday, July 12, 2011

SLIDE 6

L11の結果 (Laurie Santos: A monkey market as irrational as ours から)

Tuesday, July 12, 2011

SLIDE 7

L11の得点分布 1Ak,2Af

✤ 参加者: 45人

✤ 平均点: 58.09; 標準偏差: 10.80 ✤ 最高点: 82.00; 最低点: 30.00 ✤ n = 50

✤ 得点グループ

✤ 50点が中心のグループ ✤ 60点後半が中心のグループ ✤ 75点後半が中心のグループ

Tuesday, July 12, 2011

SLIDE 8

L11の得点分布 1Ak

✤ 受講者数: 28

✤ 平均点: 29.34/n [58.68] 点

✤

標準偏差: 5.11/n [10.22] 点

✤ 最高点: 38.00/n [76.00] 点 ✤ 最低点: 18.50/n [37.00] 点

✤

n = 50

✤ 得点グループ

✤ 60点後半が中心のグループ ✤ 75点後半が中心のグループ

Tuesday, July 12, 2011

SLIDE 9

L11の得点分布 2Af

✤ 受講者数: 17

✤

平均点: 28.56/n [57.12] 点

✤

標準偏差: 5.98/n [11.97] 点

✤

最高点: 41.00/n [82.00] 点

✤

最低点: 15.00/n [30.00] 点

✤

n = 50

✤ 得点グループ

✤

50点が中心のグループ

✤

60点が中心のグループ

✤

80点後半が中心のグループ

Tuesday, July 12, 2011

SLIDE 10

平均得点の履歴

Tuesday, July 12, 2011

SLIDE 11

ボーナス試験の出題範囲

✤ L1, L2, L4, L6, L7

✤ 全部The Feynman Lectures on Physicsのところ

Tuesday, July 12, 2011

SLIDE 12

L11の正解率分布 1Ak,2Af

✤ 参加者: 45人

✤ 平均: 0.71; 標準偏差: 0.07 ✤ 最高: 0.87; 最低: 0.55

✤ 正答率のグループ

✤ 0.7後半が中心のグループ Tuesday, July 12, 2011

SLIDE 13

L11の正答率分布 1Ak

✤ 参加者: 28人

✤ 平均: 0.73; 標準偏差: 0.12 ✤ 最高: 0.87; 最低: 0.24

✤ 正答率のグループ

✤ 0.8が中心のグループ Tuesday, July 12, 2011

SLIDE 14

L11の正答率分布 2Af

✤ 参加者: 17人

✤ 平均: 0.74; 標準偏差: 0.08 ✤ 最高: 0.90; 最低: 0.54

✤ 正答率のグループ

✤ 0.5が中心のグループ ✤ 0.7が中心のグループ ✤ 0.9が中心のグループ

Tuesday, July 12, 2011

SLIDE 15

平均正解率の履歴

Tuesday, July 12, 2011

SLIDE 16

L11の解答 (Laurie Santos: A monkey market as irrational as ours)

Tuesday, July 12, 2011

SLIDE 17

誤りの傾向

✤

• 1. earn

✤

• 2. go

✤

• 3. comes => counts

✤

• 4. make => maked

✤

• 5. flip => full, foot,

food

✤

• 6. lose => have, tell,

keep

✤

• 7. reach => get, go

✤

• 8. having => hurry,

have

✤

• 9. choose => use,

you

✤

• 10. varies => very,

barely

✤

• 11. seems => is, see,

seen, sense, since, scene

✤

• 12. relative =>

raddle

✤

• 13. options

✤

• 14. last

✤

• 15. play

✤

• 16. at => out

✤

• 17. between

✤

• 18. experiencing =>

experience

✤

• 19. both

✤

• 20. extra => actura

✤

• 21. bonus

✤

• 22. risk => lisk

✤

• 23. guys

✤

• 24. psyched => site,

sight

✤

• 25. monkeys =>

monkey

✤

• 26. irrational = rush

(ed), around

✤

• 27. treat => three,

nature, naturally

✤

• 28. some

✤

• 29. systematically

✤

• 30. thought

✤

• 31. dumb => down,

done

✤

• 32. investors

✤

• 33. wanted => want

✤

• 34. tweak

✤

• 35. evolutionary =>

additionary

✤

• 36. capuchin => put,

pu

✤

• 37. old

✤

• 38. strategies

✤

• 39. shut => shout,

shot, shaut, show

✤

• 40. built

✤

• 41. your

✤

• 42. hard

✤

• 43. supposed =>

possible, post(ing)

✤

• 44. smart

✤

• 45. flew => full, fool

✤

• 46. wearing => in,

really

✤

• 47. means

✤

• 48. said => set

✤

• 49. recognize

✤

• 50. we => review,

you

Tuesday, July 12, 2011

SLIDE 18

01/14

✤ Sounds great, but you get one more choice to [1. earn] a little

bit more money. And here’s your choice: you can either be risky, in which case I’m going to flip one of these monkey tokens. If it comes up heads, you’re going to get a thousand dollars more. If it comes up tails, you get nothing. So it’s a chance to get more, but it’s pretty risky. Your other option is a bit safe. Your just going to get some money for sure. I’m just going to give you 500

• bucks. You can stick it in your wallet and use it immediately. So

see what your intuition is here. Most people actually [2. go] with the play-it-safe option. Most people say, why should I be risky when I can get 1,500 dollars for sure? This seems like a good bet. I’m going to go with that. You might say, eh, that’s not really irrational. People are a little risk-averse. So what?

Tuesday, July 12, 2011

SLIDE 19

02/14

✤ Well, the “so what?” [3. comes] when start thinking about the

same problem set up just a little bit differently. So now imagine that I give each and every one of you 2,000 dollars— 20 crisp hundred dollar bills. Now you can buy double to stuff you were going to get before. Think about how you’d feel sticking it in your wallet. And now imagine that I have you [4. make] another choice But this time, it’s a little bit worse. Now, you’re going to be deciding how you’re going to lose money, but you’re going to get the same choice. You can either take a risky loss— so I’ll [5. flip] a coin. If it comes up heads, you’re going to actually lose a

• lot. If it comes up tails, you [6. lose] nothing, you’re fine, get to

keep the whole thing— or you could play it safe, which means you have to [7. reach] back into your wallet and give me five of those $100 bills, for certain.

Tuesday, July 12, 2011

SLIDE 20

03/14

✤ And I’m seeing a lot of furrowed brows out there. So

maybe you’re [8. having] the same intuitions as the subjects that were actually tested in this, which is when presented with these options, people don’t [9. choose] to play it safe. They actually tend to go a little risky. The reason this is irrational is that we’ve given people in both situations the same choice. It’s a 50/50 shot of a thousand or 2,000, or just 1,500 dollars with certainty. But people’s intuitions about how much risk to take [10. varies] depending on where they started with.

Tuesday, July 12, 2011

SLIDE 21

04/14

✤ So what’s going on? Well, it turns out that this [11. seems]

to be the result of at least two biases that we have at the psychological level. One is that we have a really hard time thinking in absolute terms. You really have to do work to figure out, well, one option’s a thousand, 2,000; one is 1,500. Instead, we find it very easy to think in very [12. relative] terms as options change from one time to another. So we think of things as, “Oh, I’m going to get more,” or “Oh, I’m going to get less.” This is all well and good, except that changes in different directions actually affect whether

• r not we think [13. options] are good or not. And this

leads to the second bias, which economists have called loss aversion.

Tuesday, July 12, 2011

SLIDE 22

05/14

✤ The idea is that we really hate it when things go into the red.

We really hate it when we have to lose out on some money. And this means that sometimes we’ll actually switch our preferences to avoid this. What you saw in that [14. last] scenario is that subjects get risky because they want the small shot that there won’t be any loss. That means when we’re in a risk mindset —excuse me, when we’re in a loss mindset, we actually become more risky, which can actually be really

• worrying. These kinds of things [15. play] out in lots of bad

ways in humans. They’re why stock investors hold onto losing stocks longer —because they’re evaluating them in relative

• terms. They’re why people in the housing market refused to sell

their house —because they don’t want to sell [16. at] a loss.

Tuesday, July 12, 2011

SLIDE 23

06/14

✤ The question we were interested in is whether the monkeys show

the same biases. If we set up those same scenarios in our little monkey market, would they do the same thing as people? And so this is what we did, we gave the monkeys choices [17. between] guys who were safe —they did the same thing every time —or guys who were risky —they did things differently half the time. And then we gave them options that were bonuses —like you guys did in the first scenario —so they actually have a chance more, or pieces where they were [18. experiencing] losses —they actually thought they were going to get more than they really got.

✤ And so this is what this looks like. We introduced the monkeys to

two new monkey salesmen. The guy on the left and right [19. both] start with one piece of grape, so it looks pretty good.

Tuesday, July 12, 2011

SLIDE 24

07/14

✤ But they’re going to give the monkeys bonuses. The guy on

the left is a safe bonus. All the time, he adds one, to give the monkeys two. The guy on the right is actually a risky bonus. Sometimes the monkeys get no bonus —so this is a bonus of

• zero. Sometimes the monkeys get two [20. extra]. For a big

bonus, now they get three. But this is the same choice you guys just faced. Do the monkeys actually want to play it safe and then go with the guy who’s going to do the same thing on every trial, or do they want to be risky and try to get a risky, but big, bonus, but risk the possibility of getting no [21. bonus]. People here played it safe. [It] turns out, the monkeys play it safe too. Qualitatively and quantitatively, they choose exactly the same way as people, when tested in the same thing.

Tuesday, July 12, 2011

SLIDE 25

08/14

✤ You might say, well, maybe the monkeys just don’t like [22.

risk]. Maybe we should see how they do with losses. And so we ran a second version of this. Now, the monkeys meet two guys who aren’t giving them bonuses; they’re actually giving them less than they expect. So they look like they’re starting out with a big amount. These are three grapes; the monkey’s really psyched for this. But now they learn these [23. guys] are going to give them less than they expect. They guy on the left is a safe loss. Every single time, he’s going to take one of these away and give the monkeys just two. the guy on the right is the risky loss. Sometimes he gives no loss, so the monkeys are really [24. psyched], but sometimes he actually gives a big loss, taking away two to give the monkeys only one.

Tuesday, July 12, 2011

SLIDE 26

9/14

✤ And so what do the [25. monkeys] do? Again, same choice; they

can play it safe for always getting two grapes every single time,

• r they can take a risky bet and choose between one and three.

The remarkable thing to us is that, when you give monkeys this choice, they do the same [26. irrational] thing that people do. They actually become more risky depending on how the experimenters started. This is crazy because it suggests that the monkeys too are evaluating things in relative terms and actually treating losses differently than they [27. treat] gains.

✤ So what does all of this mean? Well, what we’ve shown is that,

first of all, we can actually give the monkeys a financial currency, and they do very similar things with it.

Tuesday, July 12, 2011

SLIDE 27

10/14

✤ They do [28. some] of the smart things we do, some of the

kind of not so nice things we do, like steal it and so on. But they also do some of the irrational things we do. They [29. systematically] get things wrong and in the same ways that we

• do. This is the first take-home message of the Talk, which is

that if you saw the beginning of this and you [30. thought],

• h, I’m totally going to go home and hire a capuchin monkey

financial adviser. They’re way cuter than the one at ... you know— Don’t do that; they’re probably going to be just as [31. dumb] as the human one you already have.

✤ So, you know, a little bad —Sorry, sorry, sorry. A little bad for

monkey [32. investors].

Tuesday, July 12, 2011

SLIDE 28

11/14

✤ But of course, you know, the reason you’re laughing is bad for

humans too. Because we’ve answered the question we started out

• with. We [33. wanted] to know where these kinds of errors came
• from. And we started with the hope that maybe we can sort of

tweak our financial institutions, [34. tweak] our technologies to make ourselves better. But what we’ve learn is that these biases might be a deeper part of us than that. In fact, they might be due to the very nature of our [35. evolutionary] history. You know, maybe it’s not just humans at the right side of this chain that’s dunce-y. Maybe it’s sort of dunce-y all the way back. And this, if we believe the [36. capuchin] monkey results, means that these dunce-y strategies might be 35 million years old. That’s a long time for a strategy to potentially get changed around — really, really [37. old].

Tuesday, July 12, 2011

SLIDE 29

12/14

✤ What do we know about other old [38. strategies] like this? Well,

• ne thing we know is that they tend to be really hard to
• vercome. You know, think of our evolutionary predilection for

eating sweet things, fatty things like cheesecake. You can’t just [39. shut] that off. You can’t just look at the dessert cart as say, “No, no, no. That looks disgusting to me.” We’re just [40. built]

• differently. We’re going to perceive it as a good thing to go after.

My guess is that the same thing is going to be true when humans are perceiving different financial decisions. When you’re watching [41. your] stocks plummet into the red, when you’re watching your house price go down, you’re not going to be able to see that in anything but old evolutionary terms. This means that the biases that lead investors to do badly, that lead to the foreclosure crisis are going to be really [42. hard] to overcome.

Tuesday, July 12, 2011

SLIDE 30

13/14

✤ So that’s the bad news. The question is: is there any good news?

I’m [43. supposed] to be up here telling you the good news. Well, the good news, I think, is what I started with at the beginning of the talk, which is that humans are not only smart; we’re really inspirationally [44. smart] to the rest of the animals in the biological kingdom. We’re so good at overcoming our biological limitations— you know, I [45. flew] over here in an

• airplane. I didn’t have to try to flap my wings. I’m [46. wearing]

contact lenses now so that I can see all of you. I don’t have to rely on my own near-sightedness. We actually have all of these cases where we overcome our biological limitations through technology and other [47. means], seemingly pretty easily. But we have to recognize that we have those limitations.

Tuesday, July 12, 2011

SLIDE 31

14/14

✤ And here’s the rub. It was Camus who once [48. said]

that, “Man is the only species who refuses to be what he really is.” But the irony is that it might only be in recognizing our limitations that we can really actually

• vercome them. The hope is that you all will think about

your limitations, not necessarily as unovercomable, but to [49. recognize] them, accept them and then use the world of design to actually figure them out. That might be the only way that [50. we] will really be able to achieve our own human potential and really be the noble species we hope to all be.

✤ Thank you. (Applause)

Tuesday, July 12, 2011

SLIDE 32

TEDを使った聞き取りL12

✤ Temple Grandin: The world needs all kinds of mind の前半

✤ 今日の課題の長さ: 9分

✤ 穴埋め方式

✤ 長い目のユニットごとに2回反復 ✤ 課題として大変みたいなので，間を空けます

Tuesday, July 12, 2011