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[Assistant] When I'm talking about language, I'm meaning, uh, systems like English and Dutch and Walpurgi and Italian and Turkish and Urdu and what we've seen and heard.


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[Assistant] Right now, in class, in the demonstration that preceded the formal lecture.


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[Assistant] Now, you could use language in a different sense. You could use the term language to describe what dogs do, or what chimpanzees do, or birds. You could use language to describe music, talk about musical language, or art, or any communicative system.


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[Assistant] And there's absolutely nothing wrong with that. There's no rule about how you're supposed to use the word language.


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[Assistant] To systems like English and Dutch and American Sign Language in Navajo and so on.


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[Assistant] Once we've made some generalizations about language in this narrow sense we could then ask, and we will ask,


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[Assistant] To what extent do other systems, such as animal communication systems, uhm, relate to this narrower definition? So we could ask in this narrow sense what properties do languages have, and then go on to ask in a broader sense what other communicative systems also possess those properties. Well, some things are obvious about language.


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[Assistant] I began this class with a demonstration that illustrates two very important facts about language. One is that languages all share some deep


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[Assistant] There's no language in the world that you just cannot talk about abstract things with.


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[Assistant] It's not merely that you can't understand it, it could sound strange or look unusual in the case of a sign language.


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[Assistant] And so, any adequate theory of language has to allow for both the commonalities, uhm, and the differences across languages. And this is the puzzle faced by the psychology and cognitive science of language.


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[Assistant] Well, let's start with an interesting claim about language made by Charles Darwin.


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[Assistant] So Darwin writes, man has an instinctive tendency to speak, as we see in the babble of our young children, while no child has an instinctive tendency to bake, brew or write.


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[Assistant] And what Darwin is claiming here, and it's a controversial and interesting claim, is that language, uhm, is special.


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[Assistant] In the course of traveling, cultures encounter other cultures, and they often encounter cultures that are very different from their own.


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[Assistant] But through the course of human history nobody has ever encountered another group of humans that did not have language. Does this show that it's built in? Well, not necessarily. It could be a cultural innovation.


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[Assistant] It could be, for instance, that language is such a good idea that every culture comes across it and develops it.


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[Assistant] Just about every culture uses some sort of utensils to eat food with. A knife and a fork, chopsticks, a spoon, uhm,


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[Assistant] This probably is not because use of eating utensils is human nature, but rather it's because it's just a very useful thing that cultures discover over and over again.


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[Assistant] Well, we know that this probably is not true with regard to language.


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[Assistant] The standard example is people involved in the slave trade.


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[Assistant] The slave trade revolving around tobacco or cotton or coffee or sugar.


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[Assistant] We tend to mix slaves and laborers from different language backgrounds. In part, deliberately so as to avoid the possibility of revolt.


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[Assistant] Uhm, what would happen is these people who were enslaved from different cultures would develop a makeshift communication system so they could talk to one another. And this is called a pidgin. P-I-D-G-I-N. A pidgin. Uhm, and this pidgin was how they would talk.


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[Assistant] And this pigeon was not a language. It was strings of words borrowed from the different languages around them and put together in sort of haphazard ways. The question is what happens to the children who are raised in this society? And you might expect it that they would come to speak a pigeon.


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[Assistant] Terms that we'll understand in a few minutes. Uhm, and this language that they create is called a creole.


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[Assistant] In languages that we know now as Creoles, uhm, the word refers back to their history. That means that they were developed from pigeons.


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[Assistant] What you might have expected would be that children would then use whatever system their adults use. But they don't. They creolize it.


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[Assistant] Has language. Not everybody in this room can ride a bicycle. Not everybody in this room can play chess. But everybody


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[Assistant] There are exceptions, but the exceptions come about due to some sort of brain damage.


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[Assistant] The claim that language is part of human nature, uhm, is supported by neurological studies, some which were referred to in the chapter on the brain that you read earlier.


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[Assistant] Talk about dedicated parts of the brain, uhm, that work for language. And if parts of these brains, if parts, if these parts of the brain are damaged, uhm, you get language deficits or, or aphasias where you might lose the ability to understand or create language. Uhm, more


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[Assistant] Speculatively, there's been some fairly recent work studying the genetic basis of language. Looking at the genes, uh, that are directly responsible for the capacity to learn and use language.


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[Assistant] And one bit of evidence that these genes are implicated is that some unfortunate people have point mutations in these genes. And such people are unable to learn and use language.


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[Assistant] So, in general, there's some support, at least at a very broad level, for the claim that language is in some sense part of human nature. Well, what do we mean by language? What are we talking about when we talk about language? We don't want to restrict ourselves, for instance, to English or French. What do all languages share? Well, all languages are creative. And this means a couple of things.


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[Assistant] When Rene Descartes argued that we are more than merely machines, his best piece of evidence for him was the human capacity for language. No machine could do this, because our capacity for language is unbounded and free. We could say anything we choose to say. We have free will.


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[Assistant] And in fact, language allows us to produce a virtual infinity of sentences. Uhm, so we can create and understand sentences we never heard before. And there are a lot of sentences.


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[Assistant] And what this means is that any theory of language use and language comprehension cannot simply appeal to a list.


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[Assistant] Would anybody volunteer to say a sentence, non-obscene, non-derogatory, that has never been spoken before on earth, ever?


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[Assistant] It's surprisingly easy to get a purple tie on eBay if you don't care much about quality. I could have met no one else in the world who said this before.


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[Assistant] I am upset that one cannot easily download Buffy the Vampire Slayer through iTunes.


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[Assistant] You have rules. You have rules in your head. You've learnt what the words mean.


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[Assistant] There are automatic rules of the same sort we're gonna talk about in the context of visual perception, in that they're implicit and unconscious and not accessible to explicit understanding. Uhm, so for instance, uhm, immediately you read, the pig is eager to eat. Versus, the pig is easy to eat.


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[Assistant] And in a fraction of a second, you know there's an important difference. The pig is eager to eat means, uh, the state of affairs that we're talking about is when the pig does the eating.


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[Assistant] The pig is easy to eat is when the pig is being eaten.


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[Assistant] And you know, without even knowing how you know, that this could mean that Bill knew that John liked Bill.


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[Assistant] Or it could mean that Bill knew that John liked, uh, Fred.


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[Assistant] But it can't mean that Bill knew that John liked John. The natural interpretation fact is that Bill knew that John liked Bill. The two words co-refer. Contrast that with Bill knew that John liked himself, which only has the meaning Bill knew that John liked John. And this is what linguists do for a living.


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[Assistant] You should become a linguist. Uhm, but that's a sort of, those are the sort of phenomena that we're interested in. Now, it gets more complicated. Those are examples from syntax. But language has many structures. Language has structures going from the bottom to the top.


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[Assistant] Which is a system of words or morphemes, basic units of meaning.


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[Assistant] And syntax, which refer to rules and principles that put together words and phrases into meaningful utterances.


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[Assistant] And I want to talk briefly about each of these three parts of language before looking at some other issues. Uhm, I'm indebted here to Steven Pinker's excellent book, The Language Instinct, which provides, I think, a superb discussion of these phenomena, and I'm going to steal some of my examples from Pinker. So, phonology. Phonology is


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[Assistant] The system of sounds that languages have, uhm,


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[Assistant] There's a subset, there's a list, a finite list of possible sounds that language can use. I'm going to put aside for the moment the question of sign languages and how they work. We're going to talk about them in a little bit. Uhm, the idea is that English has about 40.


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[Assistant] So, if you're a native monolingual speaker of English, you hear speech, and each sound you hear is categorized as falling into one of those forty morphemes, sorry, phonemes. So, for example, English has a phoneme of luh, L, and a phoneme of R.


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[Assistant] And so an English speaker can hear the difference between lip and rip.


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[Assistant] You have to use sound signals to figure out the boundaries between the words. Now that, if the only language you've ever heard is English, that's going to seem like a really weird example of a problem because you're listening to me speak and in between each of my words you're hearing a pause.


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[Assistant] Don't be very smart to figure out where one word begins and one word ends. But the pause is a psychological illusion.


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[Assistant] If you were to talk into an oscilloscope that measured your sound vibrations, there are no pauses between the words. Rather the pauses are inserted by your mind.


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[Assistant] You could say, remarkable, French has no pauses between words.


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[Assistant] Which I think is a request for the bathroom. Uhm, but if you don't know Hebrew, there's no pauses. And the truth is, when you each gave your demonstrations, nobody spoke properly. Because nobody spoke, you know, here's the, here's the sentence, glorp, fendle, smug, wuggle.


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[Assistant] Rather you all sounded like blub blub blub blub blub without any pauses. Because I don't know your languages.


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[Assistant] Children come into the world without knowing any specific language.


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[Assistant] And so they have to learn, uhm, pauses. They have to learn to interpret sounds in context. Uhm, and sometimes they make mistakes.


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[Assistant] Uhm, they get problems of segmentation. And there's some illustrations, you can see the mistakes, if they're trying to repeat back something that's already known within a society. So songs are a good example. These are excerpts from children. Uhm, I'll never be your pizza burnin'. Anybody know, figure out what that corresponds to? Beast of burden, very good. A girl with colitis goes by.


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[Assistant] And this is a religious one. Our Father, who art in heaven, hallowed be thy name. Lead us not into Penn Station.


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[Assistant] Because remember I said that typically when you hear a sentence, you manufacture in your mind gaps between the words. Typically, when there's something which is unclear, you'll fill in the gap.


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[Assistant] Uhm, is from the song Super Freak by Rick James.


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[Assistant] I got a big lecture about copyright laws, and this is going to violate most of them.


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[Assistant] Well, it turns out that nobody really knows. Uhm, and it sounds to many people who do top-down interpretation as, to me as well, that she's the kind of girl you read about in Newsweek magazine. But, that makes no sense at all. Given that


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[Assistant] You don't want to bring home to mama and she's, that's not the, and in fact, uhm, if you check the notes on the song, she's in fact the kind of girl you read about in New Wave magazines.


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[Assistant] Now, when you listen to it then, again, knowing that, you hear it that way.


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[Assistant] This top down, this is known as top down processing. Top down processing is an example of, uhm,


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[Assistant] When you know what something is, you hear it that way.


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[Assistant] And this is extremely useful when it comes to filling in gaps, uhm, in, in, in sounds. In normal conversation, if I'm to, to say a sentence,


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[Assistant] You won't hear that as uh, cough, ooze. Rather you hear a sentence. You fill in the gap.


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[Assistant] So top-down processing affects how we hear things. Usually, almost always for the better.


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[Assistant] Morphology is the next level up. Phonology is sounds, morphology is words.


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[Assistant] And human language uses this amazing trick, uhm, described by Ferdinand de Saussure, the great linguist, as the arbitrariness of the sign. And what this means is


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[Assistant] And make a sound or a sign to connect to it. And the link is arbitrary.


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[Assistant] You could use a sign language thing for, uhm, for drink that looks sort of like the act of drinking. But you can't use a sign language word for country that looks like a country. Or for idea that looks like an idea.


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[Assistant] So the way languages work is, it allows for arbitrary naming. It allows for this map between a symbol, say a spoken word, and


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[Assistant] Uh, any sort of thought we wanna use. And those arbitrary mappings, as we come to learn them, make up the vocabulary of a language.


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[Assistant] I'm talking about words, but the more technical term is morpheme. And what a morpheme is, is the smallest meaningful unit in a language.


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[Assistant] Now often this is the same thing as a word. So dog is a word and dog is also a morphine. But not always.


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[Assistant] Because there are single morphemes and then there are words that are composed of many morphemes. So dogs and complained are one word but two morphemes. And what this means is that


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[Assistant] You make the word by putting together two morphemes. To put it differently, in order to know what dogs means, you never had to learn the word dogs. All you had to know is the word dog and the plural morpheme s, and you could put them together to create a word.


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[Assistant] About 60,000 words. I think the proper estimate is closer to 80,000 or 100,000. What this means if you average it out,


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[Assistant] Is that since children start learning their first words at about their first year of life, uhm, they learn about nine new words a day.


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[Assistant] It's not a continuous, uh, nine words every day. It goes up and down depending on the age. But still, the amount of words we know is staggering. How many of you know more than one language pretty fluently?


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[Assistant] Those of you who know other languages might have in your heads 200,000 words or 300,000 words. And you're accessing them in a fraction of a second.


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[Assistant] That won't allow us to communicate complicated ideas. So the final step in the story is syntax. And syntax refers to those rules and principles that allow us to combine


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[Assistant] And the answer is, you have a combinatorial system.


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[Assistant] Now, language is not the only thing in culture or nature that has this sort of combinatorial system. Uhm, music also has a combinatorial system. There's a finite number of notes, but a limitless number of musical compositions. DNA also has this sort of combinatorial system.


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[Assistant] We have a finite number of, I guess, bases or amino acids that could combine to a possible infinity of strings, uh, of DNA strings.


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[Assistant] Well, the infinity mechanism, and many of you will be familiar with this from mathematics or computer science, is recursion.


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[Assistant] And there's a lot to be said about this, but it can be pretty simply illustrated, uhm, in language. So here's an example of a simple language.


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[Assistant] It's not, it's actually close to how linguists describe normal languages, but it's very simple. It has three nouns, Fred, Barney and Woma. And two verbs, thinks and likes. It's a very simple language. And one rule,


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[Assistant] And the way to read this rule is, you make a sentence by taking a noun,


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[Assistant] How many, and then so for instance you get the sentence, Fred likes Wilma. When you do this, how many possible sentences are there? Can we just take a second? Okay, any guesses?


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[Assistant] The same sentence, but now one other sentence.


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[Assistant] This sentence expands to a noun followed by a verb followed by a sentence. And there you get recursion. You have one rule invoking another rule. And then you can get a sentence like, Fred thinks Barney likes woman.


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[Assistant] But you could see the use of recursion in everyday life, in everyday use of language. You could say John hates cheese.


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[Assistant] My roommate heard a rumor that John hates cheese. It disturbed Mary when I told her that my roommate heard a rumor that John hates cheese. I was amazed that it disturbed Mary when I told her that my roommate heard a rumor that John hates cheese. Professor Blumen devoted way too much of his lecture talking about how I was amazed that it disturbed Mary when I told her that my roommate heard a rumor that John hates cheese. It really bothered me that, and, and there's no limit. There's no longest sentence.


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[Assistant] You could keep producing a sentence deeper and deeper in bed until you die.


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[Assistant] Uhm, and this is part of the power of language. Now, the syntactic rules are complicated, and one of the puzzles of syntactic rules, or one of the issues of them, is that different rules can conspire to create the same sentence. So you take a sentence,


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[Assistant] Like, this is a classic line from Groucho Marx. I once shot an elephant in my pajamas.


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[Assistant] How it got into my pajamas, I'll never know. And the humor, such that it is, revolves around the ambiguity of rules that generate it like this, versus like this.


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[Assistant] Poorly thought out headlines and newspaper reports, uhm, that play on, that, that, that inadvertently, uh, have ambiguity.


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[Assistant] Last, last summer, uhm, I was in Seoul, uh, visiting the, visiting Korea University, and the big headline there on the front page was, general arrested for fondling privates. Uhm, now, there actually is, there,


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[Assistant] Ambiguity is actually quite difficult to avoid in the construction and understanding of sentences. It's one of the, it's one of the ways in which it's often difficult to write clearly. And in fact, there's a whole subfield of the law


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[Assistant] Several years ago, a very serious criminal case that rested on a sentence.


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[Assistant] And here's what happened. There were two brothers, one of them retarded, and they get into a robbery and a police officer sees them and points the gun at them.


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[Assistant] And, uh, one of the brothers points a gun at the police officer.


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[Assistant] The police officer shouts for the brother, the non-retarded brother, to drop the gun. As she said, give me the gun. The retarded brother shouted, let him have it. Whereupon the brother shot and killed the police officer. Now the brother who did the shooting was plainly a murderer. What about that brother who shouted, let him have it? Well,


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[Assistant] It depends on how you interpret that sentence. Because the sentence is beautifully ambiguous. It could mean, shoot him, let him have it. Or it could mean, give him the gun, let him have it.


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[Assistant] And in fact, a trial, which I think somebody could, if people know about this, please send me an email. My understanding was he was found guilty.


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[Assistant] And talk about where does all this knowledge come from.


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[Assistant] But I'll stop and answer any questions about material so far. What are your questions? Yes.


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[Assistant] Uh, syntax is a more technical term, but typically, but it means the same thing as grammar.


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[Assistant] Yes, I'm glad, I'm glad you actually asked me about that, because as I said it, I realized it wasn't quite right. The point that was just raised here is, I had said before to everybody who's neurologically normal comes to acquire and learn a language, but what about people who


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[Assistant] Are neurologically normal, but they don't have language around them.


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[Assistant] And in fact, there have been historically some cases of this. Uhm, there's been probably apocryphal stories about children who are raised by wolves or by dogs. There are stories, horrible stories, some in the 20th century, about children who are locked away.


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[Assistant] Uhm, by insane or evil parents and who never learn to speak. There are stories of deaf people.


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[Assistant] Who are within certain societies where nobody signs to them.


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[Assistant] And so they're what's known as linguistic isolates, and they themselves never learn to speak.


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[Assistant] Uhm, and those cases are the dramatic exception. And they do tell you something. They tell you that it's not enough to have a brain for language. Somebody does have to use it with you.


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[Assistant] Interestingly, uhm, it doesn't have to be that many people. So Susan Golden Meadow has studied deaf children that nobody signed to.


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[Assistant] And these children don't just sit there, they create their own language.


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[Assistant] It's not a full-blown language like American Sign Language or Languessis in Québécois.


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[Assistant] It's an interesting question. Uhm, any other questions?


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[Assistant] Uhm, it's a good question. The question is, are there inherent limits in our abilities to come up with grammars? And most linguists would argue yes.


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[Assistant] That languages are highly constrained in how they do things. So for instance, one example is, uhm, there's no language in the world that ever constructs a question by switching the order of words around.


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[Assistant] There's no language in the world that has a rule that says the fifth word has to be a verb.


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[Assistant] And linguists have all these conditions that no language in the world works this way.


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[Assistant] Now, this is, so these are constraints on grammar and they're really interesting because they tell us what's a human nat-, humanly natural language versus what's not a humanly natural language. But notice, even if there is incredible constraints on grammars, still, we could still produce an infinite number of sentences.


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[Assistant] It's just like, if you restrict me to only a subset of numbers, only to odd numbers, uhm, still, there's an infinity of odd numbers.


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[Assistant] So grammar can be restricted, but still give rise to an infinity of possible sentences.


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[Assistant] About the origin of language. Uhm, associated with the guy who we met when we talked about behaviorism, who, uhm, who wrote the review of verbal behavior, the linguist Noam Chomsky. And Chomsky makes this radical claim. And this is that we shouldn't view language learning as learning at all. Instead, we should view it as something similar to growth.


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[Assistant] So he says, no one would take seriously the proposal that human organism learns through experience to have arms rather than wings.


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[Assistant] But if Chomsky is right, you didn't learn to speak English. Rather, what happened is you heard English,


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[Assistant] And, and, but the capacity grew in your head in something a lot more similar to the development of arms or legs or a visual system. Well, should we believe this?


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[Assistant] We know there has to be some effect of the environment shaping language. Obviously, because in order to know English, you have to have heard English. In order to know Dutch, you have had to heard, had to have learned and heard Dutch. And in fact, languages differ in all the ways that we were talking about.


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[Assistant] Uhm, some languages like English have a distinction between L and R, other languages do not. Uhm, for a language like English, that creature there is referred to as the morpheme dog.


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[Assistant] That's a historical accident of English. In French, it's she. And in, and in Greek, it's something else.


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[Assistant] And each of those 6,000 languages and people in the room who know other languages say, yea, in Vietnamese it's this, in Urdu it's this, in Czech it's that.


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[Assistant] Finally, there's syntax. So English is what's known as a subject-verb-object language.


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[Assistant] That means if you want to convey the idea that Bill hit John, you would say, Bill hit John.


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[Assistant] But not all languages work that way. In fact, the majority of languages, more languages, uh, are actually subject-object-verb languages. So you would say, if you wanted to convey that Bill was the hitter and John was hit, Bill-John-hit.


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[Assistant] And all of this has to be learned through exposure to language users.


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[Assistant] It is similar to growth in the way that Chomsky suggests.


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[Assistant] There can be specific impairments of language. Now again, we spoke about them before when talking about the brain. Some of these impairments could be due to trauma.


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[Assistant] One reason that they're interesting is that it illustrates something about human language.


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[Assistant] It is not, it would not be unreasonable for you to think before listening to this lecture. Look.


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[Assistant] All you need to have to learn a language is to be smart.


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[Assistant] Or all you need to have to learn a language is to want to communicate.


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[Assistant] Or all you need to have to learn a language is to be a social person. Wanting to, having the ability to understand others and deal with others.


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[Assistant] But the case of specific language impairments suggests that all of that is wrong.


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[Assistant] Because there are children in this world right now who are plenty smart, who really want to communicate, and who are entirely social creatures, but they can't learn language.


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[Assistant] And this suggests that the ability to learn language and understand language is to some extent separate from these other aspects of mental life. Uhm.


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[Assistant] Continuing on this theme, we also know that language is learned without any sort of feedback or training.


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[Assistant] There are many Americans who believe that they need to teach their children language. There's a huge industry with DVDs and flashcards and all sorts of things designed to teach your children language. And I think many parents believe that if they didn't persist in using these things, their children would never learn to speak. Uhm, but we know that that's not true. We know this isn't true because there are communities uhm, where they uhm, they don't speak to their kids.


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[Assistant] They don't speak to their kids because they don't believe it's important to speak to their kids. Uhm, some linguists would interview, linguists would interview adults in these communities and say, uhm, why don't you speak to your babies?


[User] Please transcribe this text

[Assistant] And these adults would respond, it would be ridiculous to speak to a baby. The baby has nothing to say. You might as well just speak to your dog.


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[Assistant] Americans and Europeans speak to everything and everybody. Uhm, other cultures are more picky and they don't talk to children until the children themselves are talking. Uhm, this doesn't seem to make much of a difference in language learning.


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[Assistant] Some studies have motivated by Chomsky's work, uhm,


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[Assistant] In, uh, in, in Express, sorry, motivated by Chomsky's critique of Skinner's verbal behavior.


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[Assistant] Uhm, the example given by Brown and Hanlon in the classic study in the 1970s is they did all these studies looking at what children say and how parents responded.


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[Assistant] And it turns out parents respond not to the grammatical correctness, but to the


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[Assistant] Affect or cuteness are sociability of the utterance. So for instance, uhm, if a child says to his mother, I loves you mummy.


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[Assistant] A sucking method. Remember, there's a limited number of things babies can do. One of the things they can do is suck. And these babies would suck on a pacifier to hear French. Uhm.


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[Assistant] And they would prefer to hear French than to hear Russian.


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[Assistant] And these investigators claim this is because they had been exposed to, uhm, to French in the first four days of their lives.


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[Assistant] Russian kids sucked harder to hear Russian than they did to French.


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[Assistant] And a baby being raised in France or a baby being raised in Russia knows enough to, uhm, to tell what's his language and what isn't.


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[Assistant] English speaking babies, babies who are born in the United States, can distinguish between English phonemes, like lip and rip, but they can also distinguish between phonemic contrasts, uhm, that are not exemplified in English, such as phonemic contrasts in Czech or Hindi. Yes?


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[Assistant] There's a lot going on in your question. Uhm, the answer to the question, the question was, uhm, your baby's going to coo in Gaga Goo Goo.


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[Assistant] Doesn't matter if you coo and ga-ga-goo-goo back. No. Doesn't make a difference.


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[Assistant] Your hatred towards them was unmotivated.


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[Assistant] If you, if you speak to your children in perfect English, it's very strange.


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[Assistant] And some people have argued it does help their language learning.


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[Assistant] Uhm, and some people have argued instead that what it does is it calms them. They like to hear the music of a smooth voice and so on. But whether or not you do so doesn't seem to make a big difference.


[User] Please transcribe this text

[Assistant] It is very difficult to find any effect of how parents talk to their kids on how their kids learn language, particularly when it comes to babies. So early on, babies can, are sensitive to old phonemes. Uhm, and then that goes away.


[User] Please transcribe this text

[Assistant] Uh, around 12 months of age it goes away. This is one thing you were much better at when you were a baby than you are now. When you were a baby, you were a multilingual fool. You could


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[Assistant] Till you're sensitive just to the language you hear. And this narrowing down is largely in place by about 12 months of age.


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[Assistant] I want to stop at this point to go back to the issue. I promised you I would turn a bit to sign language.


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[Assistant] And I want to describe now a very elegant, I want to show a little film now of a very elegant series of experiments looking at the question of whether babies who are exposed to a sign language babble.


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[Assistant] One of the real surprising findings in my field.


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[Assistant] Over the last 10-20 years has been that the acquisition of sign languages has turned out to be


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[Assistant] Almost exactly the same. In fact, as far as we know, exactly the same as the acquisition of spoken languages. It didn't have to be that way. I mean, it could have been just as reasonable to expect that there'd be an advantage for speech over sign.


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[Assistant] That sign languages may be full-blown languages, but, you know, they just take heart, they're just harder to learn because the brain and the body have adapted for speech. It turns out that this just isn't the case. It turns out that


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[Assistant] Sign and eh, the developmental milestones of sign languages and the developmental milestones of spoken languages are precisely the same.


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[Assistant] They start babbling at the same point, they start using first words, first sentences, first complicated constructions. Uhm, there seems to be no interesting difference between how the brain comes to acquire and use a spoken language versus a sign language.


[User] Please transcribe this text

[Assistant] Around 12 months of age, children, uhm, start using their first words. Uhm, these are words for, uhm,


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[Assistant] They start showing some sensitivity to the order of words, so they know that, you know, dog bites cat is different from cat bites dog.


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[Assistant] Around 18 months of age, they start learning words faster. They start producing little miniature sentences. Uhm, like, you know, want cookie or milk spill.


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[Assistant] Then the, then there's the bad news. Uhm, around seven years of age, uhm, going up


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[Assistant] Through puberty, the ability to learn a language starts to go away.


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[Assistant] Uhm, the best work on this has been done by Alyssa Newport and Sam Supala, uhm, who have studied


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[Assistant] People who have been in the United States for many, many years, like 30, 40 years.


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[Assistant] And seeing how well they have come to speak English.


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[Assistant] And it turns out the big determinant of how well you speak English as an immigrant isn't how smart you are.


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[Assistant] It's not how many family members you have when you're here. It's not your motivation. It's how old you were when you started. It turns out that if you start learning a language,


[User] Please transcribe this text

[Assistant] A second language is where most of the work's been done. Uhm, within the first few years of life you're fine. You'll speak like a native. But then,


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[Assistant] It starts getting worse and worse. And once you hit puberty, suddenly there's huge variation in the abilities you have to learn language. Uhm, it is very rare, for instance, for somebody who has learned English past puberty to speak without an accent.


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[Assistant] Jim Wex in IT upstairs. That's how we met. Office romance.


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[Assistant] Welcome to Cinema Pirate Diso. Tonight's movie is Life is Funny, directed by Judd Apatow. It's based on his life starring his family and ad-libbed by his friends. So for the next three and a half hours, enjoy.


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[Assistant] Did you just pass gas while we were making love?


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[Assistant] I downloaded it off the internet illegally. Illegally.


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[Assistant] Why should a regular guy like me have to spend 15 bucks a ticket so studios can pay huge salaries to the AirBuds and Ray Leotas of the world?


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[Assistant] I now present, direct from the computer of an angry editor at a special effects house, Cosmic Wars Episode 7!


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[Assistant] It's fantastic. The studio let us play in their sandbox. Great, we have a clip! No, no don't show it. There aren't five good seconds in the whole film.


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[Assistant] Guess I'll be getting some extra credit for this.


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[Assistant] Well Bart, is that enough of a sign for ya?


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[Assistant] While no one is suggesting he was an angel, none of us are. That is why God put us on earth and not in heaven.


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[Assistant] Ayyyy, Nico. Ray. Take a seat.


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[Assistant] Hey, Phil. Listen, you know me, and I know you. Nah, I didn't mean nothing by it. Hey, take it easy.


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[Assistant] Luca hangs out in Castle Gardens. Go see him, go get my stuff back so everyone can get paid. Now.


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[Assistant] Okay. Okay. You have my word.


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[Assistant] The discussion from, uhm, last lecture and for about half of this lecture is going to be social psychology. And so we started off by talking about


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[Assistant] Certain fundamental biases in how we see ourselves. We then turn to talk about a bias in how we see other people, the fundamental attribution error.


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[Assistant] If you're, if you're rich, you'll get a better education. If you're smart, people will like you, will like you more if you're attractive and so on. Nobody bring up their papers at this point. They'll collect them at the end of class. Uhm, what I want to talk to


[User] Please transcribe this text

[Assistant] I'm going to ask the teaching fellows to stop anybody from approaching that area. I want to begin by talking about impression formation, how we form impressions of others, and tell you a couple of interesting


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[Assistant] When they're asked for their impressions of the speaker, people are very much biased by what they first assumed.


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[Assistant] And you see me and I'm all kind of bouncing around and everything. You could then confirm this as, look how vivacious and creative he is. If I'm described as somebody who drinks too much, you might think he's an alcoholic.


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[Assistant] If you had to describe to somebody who's insecure and nervous, you could interpret my activity as nervous twitches.


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[Assistant] Somehow, through accident, had a reputation for being a genius. But while in reality he was actually mildly retarded.


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[Assistant] But he would go around and people would ask him his opinions on politics and he would say things like, uh, well, I like being in the garden.


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[Assistant] And, and people would say, would be intimidated by his bold and impetuous stare when actually he just totally didn't know anything. Uhm, so first impressions can shape subsequent impressions, not just when dealing with people.


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[Assistant] And the one thing everybody knew about it was there was a white van involved. Turned out there was no white van at all.


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[Assistant] But in the first incident somebody saw a white van, this was reported in all the newspapers, then every other incident people started seeing the white van. They started looking for them, they started to attend to them. So first impressions matter hugely when dealing with people because it sets the stage for how we interpret everything else. A second finding, building on the first,


[User] Please transcribe this text

[Assistant] Is that we form impressions very fast, very quickly. And this is a literature


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[Assistant] The idea is you don't have to see much of a person to get an impression of what they are. The first studies done on this were actually done on teachers, on university professors.


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[Assistant] So what you do then is the question that these people are interested in, uhm,


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[Assistant] So they show these clips for a full class. Do you have to see them for a full class? Do you have to see them for two classes?


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[Assistant] So after clips of five seconds, people are pretty good at predicting what sort of evaluations that person will have.


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[Assistant] And your roommate, you could evaluate on the big five. You've had a lot of experience with him or her. How much time do you need to co- to evaluate somebody on the five dimensions of personality?


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[Assistant] Everybody's good at it. Gay people are better at it than straight people. And again, you don't need much time. You just need about a second.


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[Assistant] We're talking about the perceptions of other people. How we perceive other people.


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[Assistant] But social psychologists are also interested in the question of what happens to other people as a result of being perceived in a certain way.


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[Assistant] So one question is, what would cause me to perceive somebody as intelligent or stupid? Gay or straight? Anxious or level headed? A second question is, what are the effects of being judged that way?


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[Assistant] And psychologists have coined a term, uhm, talk about self-fulfilling prophecies.


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[Assistant] And the claim here, more specifically, is what's known as the Pygmalion effect. And the Pygmalion effect is, uhm, if I believe you have a certain characteristic,


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[Assistant] Where, where a cold-blooded killer is treated with respect and affection and then she becomes, uhm, a much more warm and, and accessible person. And then she kills a lot of people. But that, but...


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[Assistant] Tons of empirical validity. The classic experiment was by Rosenthal and Jackson, where uhm, they told teachers that some of their kids were really smart.


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[Assistant] And other kids were less, were not really smart. They weren't expected to show a huge jump or spurt in their IQ.


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[Assistant] Uhm, and this was of course trickery. The children were chosen at random.


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[Assistant] And so, the Pygmalion effect shows how our expectations can really matter.


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[Assistant] Is a story that could be told about individuals, but it's also a story that could be told about groups. And this is where I want to end this section on social psychology, by talking about groups.


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[Assistant] A lot of social psychology is concerned with the question of how we think about human groups, and we've already discussed this in the lecture on morality, when we talked about the human dynamic pushing us to think in terms of us versus them. As shown in the Roberts Cave study,


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[Assistant] Showing that from a motivational, emotional standpoint, uhm, it's not difficult for us to think in terms of my group versus your group.


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[Assistant] Often, just is a bad word. To have a stereotype is to have something wrong with you. You might say it's not good to have stereotypes. Psychologists tend to use the term in a broader sense. Uhm, we tend to use the term


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[Assistant] This object over here, you categorize it as a chair. And you recognize that you could probably sit on it. This apple is probably edible. This dog probably barks and has a tail and eats meat and doesn't speak English.


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[Assistant] You might have positive stereotypes, uhm, about certain groups. You might believe some groups are unusually creative or intelligent.


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[Assistant] Even if your own group is Yale students, or your own group is people from France, or your own group is people from such and so college.


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[Assistant] Away from accuracy. One is what we talked about before regarding first impressions, which is a confirmation bias.


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[Assistant] If you believe that homosexuals are effeminate, that gay men are effeminate,


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[Assistant] Uhm, then this is going to shape how you see future gay men. If you see an effeminate gay man, you'll probably say, ah, more evidence for my theory.


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[Assistant] It turns out, uh, in the world of classical music, there's a stereotype of women being simply less proficient than men. They play smaller than men. They don't have the same force, and, and, and they have smaller techniques, they're more temperamental, and so on.


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[Assistant] The test of this, then, is to have blind auditions, where people do their auditions behind a screen, so you can tell whether they're man or a woman, or for that matter, white or black or Asian or whatever.


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[Assistant] It turns out when you do that, women get hired far more. Suggesting that the stereotype is A, incorrect, and B, has a real negative and unfair effect on people, uhm, getting hired.


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[Assistant] A second problem is, uhm, what I was talking about immediately before this, is some of our data are misleading.


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[Assistant] And to the extent these portray, uhm, an unrealistic or unfair or biased perception of the world, we could construct stereotypes that are faithful to the data we're getting, but the data is not representative. Uhm, and so,


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[Assistant] People, for instance, uh, object to the fact that, that when there's Italian Americans on TV, they're often members of the Sopranos, a mobster family. Uh, throughout history, Jews have been upset at the portrayal of Shylock in Merchant of Venice. Not a very nice guy. Uhm,


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[Assistant] And often in response, people who want to foster more positive views will often try to, will often put in representatives from other groups in unusual ways to make that point. Anybody here ever see the television show Battle Star Galactica? Okay. Who's that? He's the star of Battle Star Galactica. You don't know because you're too young.


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[Assistant] And, and I, I, I hate you. And in the original, in the original Battle Star Galactica, this was the star, uhm, this was the main character known as Starbuck, who got transformed into a woman in the more recent one.


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[Assistant] A sort of example of how portrayals are shifting in interesting ways. There's also of course, uhm, moral problems.


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[Assistant] I think this is perfectly fair because young people like you get into a lot more accidents with your reefer and your alcohol.


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[Assistant] On the other hand, what if insurance companies, uh, determine that people from Asia got into more accidents than people from Europe?


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[Assistant] Would people be equally comfortable charging people from Asia higher rates of insurance? Almost certainly not.


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[Assistant] So, the issues are complicated as to what sort of generalizations are reasonable to make and what aren't. There's also a second problem.


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[Assistant] Stereotypes have all sorts of effects. Now some of them are obvious effects. Uhm, you know, if people, for instance, if people pull you over while you're driving, because you're black,


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[Assistant] Uhm, this could have a huge effect on how you feel welcome in the society, on race relations and so on. But some of the effects are more subtle and more interesting.


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[Assistant] And you might not expect this. And this is some work done by the psychologist Claude Steele and his colleagues at Stanford. And the issue is called Stereotype Threat.


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[Assistant] Black people do worse on this math test. It's very simple.


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[Assistant] The finding is that if your race or your group has a negative stereotype associated with it in any particular domain, being reminded of it serves as a stereotype threat.


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[Assistant] And hence damages your performance in all sorts of domains. If the stereotype is your group doesn't do good in this, if I remind you that you're a member of that group immediately before doing it, your performance will drop. Uhm, now you know how to make women do worse on math tests too. Like that. And this has a demonstrative effect.


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[Assistant] They often make certain distinctions between three levels of stereotypes.


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[Assistant] One of the, one of the people running for the Democratic nominee for president is black. Another one is female. Uhm, if I ask people to raise their hands for uhm, who thinks that because being black, because being female, they should be automatically disqualified for being president? Few of you would raise your hands.


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[Assistant] For somebody, because he or she is black. But they won't tell you. But they know it to be true.


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[Assistant] That's common sense. What's more interesting is, below even that, there may be unconscious associations that work that people don't actually know about, but affects their thoughts about race, gender, and other social groups.


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[Assistant] So here's some data about what people publicly say. Uhm, this is a proportion of people who say they will vote, they would vote for an African American president. Uhm,


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[Assistant] What's interesting is around when I was born, the answer to the United States was about half.


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[Assistant] Uhm, now it is as close to 100% as you can get it.


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[Assistant] Here's another one, this is also public stereotypes of blacks, proportional white respondents endorsing each trait. Now, it's infinitesimal.


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[Assistant] But what about implicit views? This gets more complicated.


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[Assistant] Here's a simple study. This is the sort of study that you might do here at Yale.


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[Assistant] Uhm, what you might do, for instance, is be sitting in a computer screen.


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[Assistant] What you don't know is that pictures of black faces or pictures of white faces are being flashed on the screen. But they're being flashed on the screen subliminally.


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[Assistant] So fast you don't even know you're seeing them. Still, this has an effect.


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[Assistant] When you see black faces, subjects are more likely to feel this before it's like, hostile.


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[Assistant] And uhm, and, and it's called the implicit attitude test. It's the biggest psychology experiment ever done in terms of people. I don't know, like a million people have participated in this. And you can just go online, implicit.harvard.edu


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[Assistant] Uh, and then you could do it yourself. But we'll do it now as a group. If you did it in the lab,


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[Assistant] Are on your computer screen. You do it by pushing buttons. We'll do it by speaking. And it's very simple. You're gonna see things over here. And they're either gonna be words, or they're gonna be pictures.


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[Assistant] If it's an African American, or a bad word, a negative word, I want you to shout out, right.


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[Assistant] This side, right. If it's a white American or a good word, I want you to shout out left.


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[Assistant] People ready. Try to do it as fast as possible without making any mistakes.


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[Assistant] Uhm, have biases to favor white Americans over African Americans.


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[Assistant] If it's an African American, or a good word, say left.


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[Assistant] And you could do it yourself on the computer screen. And this is one way of doing it, but I'll alternate and I'll give you different ones to shift around and everything. And it turns out that this version people are slower at than the other version.


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[Assistant] Uh, attitudes towards, uh, people who are obese versus people who are thin. Attitudes towards people who are straight versus people who are gay.


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[Assistant] Well, there's two answers to this. One answer is, uhm, there are times in your life where half a second can matter a lot. Uhm, so studies with police officers using reaction time and split second choices on who to shoot.


[User] Please transcribe this text

[Assistant] Find that your stereotypical attitudes, uhm, play a huge role in who you're likely to shoot when you're holding an object in your hand that's unclear. Also, more generally, it could be


[User] Please transcribe this text

[Assistant] You know you're not racist. You have no explicit racist attitudes. Honestly, you really don't. But the argument is that these stereotypes can affect your behavior in all sorts of subtle ways. Here's one example. Uhm, what they do is they do an experiment where somebody is in trouble. You hear a scream from outside. Either from a black person or a white person.


[User] Please transcribe this text

[Assistant] In one condition, you're the only person around. In another condition, there's other people around you.


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[Assistant] Now we know from work in the bystander effect that in general


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[Assistant] When it's the only person, just about everybody helps. Regardless of the color of the person in trouble.


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[Assistant] Now again, this isn't, these studies are not done with members of the KKK. They're done with, they're done with standard university undergraduates like you. Uhm, and these are, and if you were in this group,


[User] Please transcribe this text

[Assistant] You wouldn't say, oh, I didn't want to help because the person's black.


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[Assistant] Rather what you would say is, uhm, well, I didn't think it was worth helping or other people around, someone else would help, but we know by looking at it that this difference makes a real difference. A final study


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[Assistant] Uhm, and this was done by my colleague who just got hired here, Jack DeVideo, who's done some wonderful work. Uhm, looked at how people


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[Assistant] Judge to hire somebody based on their recommendations. Uhm, this is a little bit of a confusing thing. The green bars are to African Americans, the blue bars are to white Americans. And in some cases, these people have strong recommendations. When they have strong recommendations in 1989, you're willing to hire everybody.


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[Assistant] And, uh, this is not a difference at all. But when the recommendations are so-so, when it's a judgment call, the subjects are significantly more likely to hire the white American than the African American. 1989 was a long time ago, but the same results showed up in 1999. The same results also showed up about a year and a half ago.


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[Assistant] Is in, uh, in Trish Devine's automaticity theory, which goes something like this. The idea is that everybody holds stereotypes.


[User] Please transcribe this text

[Assistant] We have to consciously push them down. We have to consciously override them


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[Assistant] And that's possible, but it takes work. It takes work both at the individual level and it takes work at the group level. Any questions or thoughts about this?


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[Assistant] It's a good question. These results, these results are surprising.


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[Assistant] What we do now in the psychology department is we make a special point of trying to get names from disadvantaged groups. Not with an eye towards an affirmative action policy, but rather because there's a lot of evidence suggesting that people who are just as qualified don't come to mind.


[User] Please transcribe this text

[Assistant] Unless you make some sorta procedure to do it. Here's another example. A lot of journals do blind reviewing now.


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[Assistant] Because of the evidence I talked about before regarding sexual stereotypes, that whether it has a male name or a female name makes a difference.


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[Assistant] At an individual level, your question's a harder one, and I'm not exactly sure what we could do, but I think what we should do is be conscious of these things, and


[User] Please transcribe this text

[Assistant] So, I'll give everybody a fair shake, but to recognize we might have biases, and to work hard to overcome them. Not by over-correcting in some, in some random way, but trying to, if you're interested, for instance, in qualifications, setting up some system that these qualifications can be observed absent knowledge of race or sex. Yeah, in fact,


[User] Please transcribe this text

[Assistant] Showing it doesn't reduce to group favoritism, though that probably plays a big role.


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[Assistant] How many people here, on average, from the beginning of the semester till now, get on average more than 8 hours of sleep a night? Good, good.


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[Assistant] Who here has been making it since the beginning of the semester on under six hours a night?


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[Assistant] Okay. There's big individual differences in how much sleep people need.


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[Assistant] And we didn't use to know much of it because you can't ask people what's happening during it because they're sleeping. So you need


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[Assistant] And you see what these, what sort of electrical activities you get in the brain.


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[Assistant] Some of you are awake, but non-attentive, and your brain's giving these large, regular alpha waves. Some of you are sound asleep, deep in delta. Uhm, when you sleep, you get the following stages.


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[Assistant] Uh, you start off with a transition period when you're falling asleep. We call that stage one. Then you get successively deeper. Two through four. Uh, slow, irregular, high amplitude delta waves.


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[Assistant] Then REM sleep emerges, rapid eye movement sleep. REM sleep is neat because your brain looks like it's wide awake.


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[Assistant] But, and I'm gonna go talk a little bit more in detail about this later, you're relaxed, your rapid eye movements occur, that's where your name comes from, and dreams occur.


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[Assistant] And then on a good night's sleep you've got four to five sleep cycles and it looks like this.


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[Assistant] Then there's REM sleep. Your brain is active as if you were awake. Your EEGs are similar to waking. Paralyzed, except for the eyes.


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[Assistant] Oh, men get erections, and you have dreams.


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[Assistant] Why do we sleep? And why aren't we always awake?


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[Assistant] There's a couple of answers to this. Uhm, probably the best answer is


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[Assistant] Uhm, our body's worn out during the day and sleep is necessary to put it back into shape.


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[Assistant] And the answer is not, is not one discovered in the laboratory, but it's been reported in different cases. If you stop sleeping, you die. You don't die in some dramatic way, you get sick. And then you die.


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[Assistant] When you bring your car for repairs, when you're repairing your car, the first thing you do is you stop it and shut off the engine.


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[Assistant] Is that sleep, it, uh, emerged to preserve energy and keep you out of trouble at night.


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[Assistant] And these views are of course not incompatible. Uhm, this explains why we sleep at all, and this probably explains why we sleep at night.


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[Assistant] There are sleep disorders, uhm, I won't go through them, I just list a few of them here. There's sort of bad things that can happen to you in your sleep. Uhm, one particularly trendy sleep disorder that's been discovered recently are side effects of sleeping pills such as Ambien.


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[Assistant] And so he made up two lists. The list of reasons to kill himself were the slings and arrows of outrageous fortune, a sea of troubles,


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[Assistant] He only had one argument not to kill himself. Nightmares. To sleep or chance to dream.


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[Assistant] For in that sleep of death what dreams may come when we have shuffled off this mortal coil might give us pause. Uhm, he was worried about nightmares.


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[Assistant] And can you be immoral in a dream? We do all sorts of things in dreams that are bad.


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[Assistant] Are these sins? And the great theologians and philosophers like Augustine wondered about this. Can you sin in a dream? I will answer both questions.


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[Assistant] If you want to remember your dream, by the way, keep your dreams, keep a dream diary. Very useful. But everybody dreams. Three to four times a night, that depends on how much sleep you get. But dreams leave fragile memories. They fade quickly.


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[Assistant] This is why a dream diary or writing up, writing your dreams as soon as you wake up turns out to be useful.


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[Assistant] What do people dream about? Well, basically the way to find that out is you ask people. And people have, psychologists and sociologists have collected dream reports. Uhm, if you go to dreambank.net, uhm, a guy named Hill collected 50,000 dream reports. You can make some generalizations. Most dreams are bad.


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[Assistant] Uhm, women want to dream about romance and adventure. Men want to dream about sex with strangers.


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[Assistant] Turns out that once you get past the hormonal blast of adolescence, uhm, about 10% of dreams have explicit sexual content.


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[Assistant] Rebuilds itself while you're sleeping. But also what happens while you're sleeping is your memories get played over and over again to consolidate them in the different parts of the brain. Almost the best analogy here is backing up a computer. Your brain backs itself up.


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[Assistant] And this is a true mystery. I am, I got interested in this, well,


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[Assistant] I got interested as a developmental psychologist watching my own children laugh and, and trying to figure out what it is that made them laugh. This is my son Zachary, pretty young.


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[Assistant] Sex and food and drink and sleep are not these huge mysteries, our abilities to understand language and


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[Assistant] Psychologists have failed to explain this puzzle. So here's something, uhm, here's a first guess I read in a neuroscience textbook.


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[Assistant] Consisted of staccato stegmas of one fifteenth of a second each, separated by a fifth of a second. It doesn't explain why we make that loud noise when dealing with incongruity.


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[Assistant] It's not the case that incongruity, uhm, causes laughter. If there was, uhm,


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[Assistant] A lot of laughter isn't caused by incongruity.


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[Assistant] So, a lot of times we laugh, there's nothing incongruous in any deep sense about it.


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[Assistant] By Robert Proven, who summarizes this in his excellent book, Laughter. And Proven decided to do something that nobody in the history of the world has done. He decided to send himself and his students


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[Assistant] To different places, including shopping malls, and observe when people left.


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[Assistant] Or the question of humor. Most of what people, what made people laugh wasn't in any sense a joke or humorous. So he had over a thousand laughter initiated


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[Assistant] Laughter could be viewed as a form of involuntary, uh, noise making. And it's contagious.


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[Assistant] After a comic remark is an attempt to simulate a sort of a pre-technological attempt to simulate the sound of laughter. Children are particularly influenced by


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[Assistant] When monkeys get together to kill and eat somebody, they make a kind of a laughing noise.


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[Assistant] And ehm, let's see. And what's tickling? Well, a fair definition of tickling is touching parts of the body in a mock attack.


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[Assistant] So, one theory is, is a signal of mock aggression and collective aggression. It's basically a, an,


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[Assistant] It's like a sound of some sort of mob attack. Uhm.


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[Assistant] It's mock aggression, in a sense that when people laugh, they're often teasing, kidding around.


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[Assistant] Uh, it, most laughter is inspired by some degree of aggression, but it's attenuated and it's not real. And a laughter is a signal, this isn't real. And collective aggression.


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[Assistant] Uhm, a lot of mob assaults, executions, lynchings, rapes are accompanied by the sound of laughter.


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[Assistant] When you're in a group doing something terribly aggressive and you are not, you don't feel like you're at risk, you might laugh. And laughter is a signal to other members of your group as a signal of solidarity and what you're doing together.


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[Assistant] Who view laughter as a form of bonding against a common enemy.


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[Assistant] It's a sound, it's a sound of group cohesion against a common enemy.


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[Assistant] The most important humor, truth of all, is that to really see the humor in a situation, you have to have perspective. Perspective is derived from two ancient Greek words. Perse meaning something bad that happens to someone else, and active meaning, ideally, somebody like Donald Trump. And the idea is that it's something bad happening, but not to you or to somebody you love.


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[Assistant] Mel Brooks puts it in somewhat sharper terms, distinguishing between comedy and tragedy. Tragedy is when I cut my finger. Comedy is when you fall into an open sewer and die.


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[Assistant] To sum up, ingredients of humor is there has to be a target who experiences some harm. It could be an enemy, it could be a friend, it could be yourself.


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[Assistant] The harm shouldn't be so serious that it elicits strong negative emotions like fear, grief or pity.


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[Assistant] So, if a stranger, you know, slips on a banana peel and lands on his butt, I might laugh, because I'm not overcome by compassion. You know, if he splits his head open, there's blood everywhere, I'm less likely to laugh unless I don't like him or something.


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[Assistant] The humor for that baby comes in. Which is, you couldn't predict when the sound was coming.


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[Assistant] The final question for anybody interested in laughter is, why can't we tickle ourselves? Now, I've talked about laughter on two separate occasions, and on each of the occasions when I talk in front of a large group like this, somebody came up to me afterwards and said,


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[Assistant] It's a fascinating question why some people can. The general story of why we can't in general is because there's no surprise. Uhm, there's no mock aggression and also there may be a general deadening of self-stimulation. Uhm, I'm going to end with the final reading response. Uhm,


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[Assistant] Think of an interesting testable idea about either dreams or laughter.


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[Assistant] I will ask the teaching fellows to each send me their one or two most interesting remarks. I will then judge and then the winner will win some small prize, either of a literary or a food nature. Okay. I'll see you all on Wednesday.


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[Assistant] Well, uh, thanks very much for your help, and again, I'm very, very sorry.


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[Assistant] What would you like me to make him say next?


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[Assistant] God look here. God look here. God look here. Stop it. Nice touch this, the pool, where little Carl dies. I stopped him


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[Assistant] I can stop John Watson too. Stop his heart. Who are you?


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[Assistant] Oh, maybe I should. Okay. Okay.


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[Assistant] Cock-a-shaman-tino. Wolf bitch. Next to the ducks.


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[Assistant] What? Where's luxury condo? Where's sports car? Where's Barbara with big titties and Stephanie who sucks like a vacuum? What are you talking about? In your letters to my mother, in your letters to me, all I hear about is Mr. Big, Mr. Roman, living the American dream.


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[Assistant] Sports cars, condos, women, money, the beach, opportunity.


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[Assistant] I come here and the only thing big about your life is the cockroaches.


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[Assistant] No. What do you mean no? No, I never tell you anything. Another time.


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[Assistant] Roman? ROMAN! Are you sleeping, you f-


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[Assistant] Doing some home improvements, Roman? You're going to build this mansion you tell me about?


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[Assistant] Get it? I seriously hope your cards are better than your nicknames.


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[Assistant] You and your debts, Roman.


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[Assistant] It's so quiet out here, Roman. You winning? Molintere cida.


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[Assistant] Cousin, two guys are going in the store. I think they are the loan sharks you speak of.


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[Assistant] Alright cousin, I lose them. Just like the old days, eh?


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[Assistant] I remember. What's up, Michelle?


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[Assistant] All your stuff is new. Some even still have tags on.


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[Assistant] I can see that, but uh, everything is new.


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[Assistant] I don't know. I'm new here. I thought maybe we could go to the, uh...


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[Assistant] I thought you were doing me a favor by going out with me. You're the local.


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[Assistant] So you don't know many people here in Liberty City? No boyfriends or husbands or anything?


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[Assistant] What's anybody doing here? I don't know.


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[Assistant] Yeah, that would be good. I'll give you a call.


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[Assistant] Thanks for coming! Can you take me over to Masterson Street? Masterson Street it is, Jermaine.


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[Assistant] I had a feeling you sounded too good to be true. The question is, are you willing to get your hands dirty? My hands haven't been cleaned for a long time. Being here in Liberty City is just making them dirtier. Okay, okay.


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[Assistant] I gotta pick up some hot parts for my locker. You down? I ain't got no problem with that. Just don't tell me if you stole this shit from a hospital or a school for sick kids. My conscience is troubled enough already.


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[Assistant] Jacob, where you wanted to go? Driving for you ain't as boring as I thought it would be.


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[Assistant] Sure, I was looking to branch out a bit anyway. I'll see you soon.


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[Assistant] I'm sorry, it's an ugly city. Orders are sometimes hard. You must be sure you agree before you follow. I have made that mistake myself a long time ago.


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[Assistant] I had to smash the shopper pretty good, but he paid.


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[Assistant] Thank you, cousin. That could be very useful in this city.


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[Assistant] Huh. Want some? Good. We walked all the way over here so you could snort coke?


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[Assistant] No, it's mom, who ask it? You that fat Russians bitch? Just try and take.


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[Assistant] Hey, I could fuck this car up worse than a little dirt.


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[Assistant] Hey Mickey. What do you have? Glass of water.


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[Assistant] So, why is Ivan going to rob my cousin?


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[Assistant] There ain't nowhere left for you to run.


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[Assistant] Once you're dead, you can't be all bad. Stay out of whole beach.


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[Assistant] You won't be seeing your boyfriend Ivan no more. Oh, are you going to miss him?


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[Assistant] Hey, what's wrong? Eh, cousin. Bullshit. What's bullshit? Mallory. Oh, what about her? I like her.


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[Assistant] You knew? I had suspicions.


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[Assistant] I'm not going to stand here, and have you call me disloyal.


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[Assistant] You might let some Russian asswipe bang your woman, but I won't.


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[Assistant] Duff Beer is proud to make a corporate commitment to gouging.


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[Assistant] He was a friend of your sergeant, when we were in Vladivostok. He's an imbecile.


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[Assistant] Lay off that stuff! Why?


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[Assistant] Let me guess. In a prison camp in Siberia, or selling hash to tourists in Red Square or still in the Navy. Which is it today?


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[Assistant] Yes, but you've angered the wrong people. Too many bodies, too much attention will be dealt with if we don't start playing by the rules.


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[Assistant] You're getting delusional. Look, we have to go.


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[Assistant] I'm not saying don't run things your way. I'm saying become!


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[Assistant] Here. Take a couple of these.


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[Assistant] Where's your boss? What do you mean? He's, uh... In the back!


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[Assistant] I didn't kill Joseph. We will make more money because he's alive.


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[Assistant] Kill me. Thank you for your help, Nico!


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[Assistant] Come to see us at the club soon, Mikhail will be cool by then.


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[Assistant] He's my cousin's boyfriend, it's not him. Yes, he's a moron, yes, but he's okay. I don't trust him.


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[Assistant] Michael, please calm down. We're already in a lot of trouble. I don't know if I can smooth things over with Petrovic. Fuck it.


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[Assistant] Wherever you go, people will find you if they want to battle enough. And for this they want blood.


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[Assistant] I told them you are a hired gun. And they said as long as you were the one to kill him, you'd be spared.


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[Assistant] He'll be leaving his house in a little while and heading for the club. Do what you have to do.


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[Assistant] You know, if there's one thing I've learned, it's that we must obey the rules of the game. We can pick the game, Nico Bellic, but we cannot change the rules.


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[Assistant] But I just wanted to say how grateful me and my bosses are for what you did. Good. Yes. And I just wanted to check something with you.


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[Assistant] You are... Nico Bellic, correct?


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[Assistant] Yo, I'm all out of product, dropping in to pick some up. Be ready.


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[Assistant] Hey, one day you'll have kids of your own. I do. Really? Then this is much creepier than I thought. Much!


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[Assistant] We've talked about this, Marge. The hammock is a chore-free zone.


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[Assistant] Okay, she moved in with her boyfriend. Well, he's not a boy. He's immature. But fat and old.


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[Assistant] Ah, fuck you. You're a bunch of pussies and fags. Nice. I'm going back to the meeting. Good. I'm going to be somebody! Yeah, yeah. See you later, Mel. You always were an asshole, Mickey. Hey, watch where you're going. Hey! Hey!


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[Assistant] And although I love being Dean, I do miss, uh, teaching introductory psychology. Uh, the feeling of exposing people to, uh, uh, ideas that maybe you hadn't heard before.


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[Assistant] Well, I suspect some of the ideas in this talk you'll have not heard before, uh, and for a variety of reasons.


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[Assistant] Uh, andro-centric and heterosexual quality to much of the social psychological research, uh, on romantic love. Uh, you'll see that in the experiments, usually the participants are men and usually the targets are, uh, women.


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[Assistant] Uh, relationships, uh, and that's a question that I think you can, eh, you can ask throughout this lecture.


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[Assistant] Who is now the Dean, uh, at, uh, Tufts University, but was here on our faculty at Yale for nearly, uh, 30 years or so.


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[Assistant] And he has a theory of love that argues that it's made up of three components. Intimacy, passion,


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[Assistant] And commitment, or what is sometimes called decision commitment.


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[Assistant] That's really what intimacy is. The bond that comes from sharing information that isn't shared with other, with many other people.


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[Assistant] Second, uh, element, uh, is passion. Passion is what you think, uh, it, it is. Uh, passion is, uh, uh, the dr-, we, we would say the drive that leads to romance, you can think of it as physical attraction or sex. And, uhm,


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[Assistant] Stormberg argues that this is a required component of a love relationship. It is not, however, a required component of taking a shower in Calhoun College. The third


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[Assistant] These are, what's interesting about this kind of theorizing is it gives rise to many different permutations that when you break them down and start to look at them carefully


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[Assistant] Uh, Sternberg calls this non-love. That's the technical term. And uhm, uh, essentially what he's saying is, uh, the relationship you now have to the person sitting next to you, presuming that you're sitting next to a random person that you didn't know from, uh, your college, uh, is probably non-love.


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[Assistant] If it's something else, we can talk about it at the end of the lecture, uh, or perhaps when I get to it in a moment. Now let's start to add elements.


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[Assistant] And liking is really, uh, uh, what is happening in most typical friendships. Not your closest friendship, but friendships, uh, of a casual kind.


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[Assistant] But you're not physically attractive, and there's no particular commitment to maintaining this, uh, for a long period of time. Now what if you're not intimate, you're not committed, but you're passionate. You feel that sexual arousal.


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[Assistant] This, uh, is what, uh, Sturmbrig would call infatuation, and that term probably works for you too. Infatuated love. And, uh, this is love at first sight. I don't know you.


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[Assistant] But we better stay together for the kids. Right? Or we better stay together for appearances sake.


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[Assistant] Is in societies where marriages are arranged, this is often the first stage of a love relationship.


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[Assistant] What's interesting of course is that such relationships don't seem to have any greater chance of ending in divorce than people who marry for love. But there's a big confound, there's a big problem.


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[Assistant] What might be the problem in the statement I just made that these kind of relationships are just as likely to survive as people who marry for love? Yes.


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[Assistant] But there's no particular physical attraction, but we are really committed to this relationship.


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[Assistant] Maybe the Greek ideal, uh, in, uh, relationships of some kind.


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[Assistant] Alright, what if we have passion, I'm sexually attracted to you, but no intimacy, I don't want to really know that much about you, I don't really want to share anything of me with you.


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[Assistant] But it, it's very hard to make those relationships last a long time because we might not have anything in common, we might not share anything with each other, we might not trust each other, we're not particularly bonded.


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[Assistant] Is it has focused on seven variables. And I've divided these into two groups. The big three and the more interesting four. And I call them the big three are three variables that the effects are so powerful


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[Assistant] That they almost don't need to be discussed in much detail. The more interesting four are the ones I'm going to focus on in this lecture because they're a bit more subtle and, uh, they may be, uh, things that you've never heard of before.


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[Assistant] Seems kind of obvious, right? Uh, this even works on college campuses. We can measure in feet.


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[Assistant] But if we could statistically control for every other variable, all I'd need to do is measure the distance from your door to everybody else's door on campus and I could chart out who's gonna fall in love with whom, uh, on the Yale, uh, campus.


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[Assistant] Uh, I don't know. Maybe it's a little counterintuitive. There's a kind of cultural myth around the, uh, the stranger, the person you don't know who you, uh, will, uh, uh, who you fall in love with. And that is not likely to be the case if it's the person who's nearby.


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[Assistant] Isn't it interesting we have all of these common sayings that contradict each other, and then empirically some of them turn out to have more evidence supporting them than others. So, opposites attract, not much evidence. Similarity breeds contempt, not much evidence. Birds of a feather flock together, yeaah, there's some evidence for that idea. Finally, familiarity.


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[Assistant] You suddenly find attraction, attractive and a relationship forms. Okay?


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[Assistant] So, uh, the big three, people who are similar to you, people who are already familiar to you, people who are nearby in space, these are the people, all things being equal, that you will find attractive.


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[Assistant] And I can later repeat some of those words and mix in some new ones that you've never seen before.


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[Assistant] But people who are super competent, people who seem competent on all dimensions, they're kind of threatening to us. They don't make us feel so good about ourselves.


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[Assistant] You can see this with public figures. Public figures who are viewed as competent.


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[Assistant] Bill Clinton, when he was president, his popularity at the end of his term, despite what everyone would agree, whether you liked Bill Clinton or not, was a big mistake with Monica Lewinsky. His popularity didn't suffer very much. A lot of people


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[Assistant] In the media would describe him, well he's just, it just shows he's human. He makes mistakes like the rest of us. Even though that was a pretty big mistake.


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[Assistant] And you can see this even with smaller pratfalls, sometimes public figures are liked even more after their pratfall.


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[Assistant] You're in this experiment, you're brought to the lab, and you're listening to a tape recording of interviews with people who are described as possible representatives from your college to appear on a quiz show.


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[Assistant] The quiz show is called College Bowl, which I don't think is on anymore, but was on when I was in college. And you're listening to interviews with possible contestants from Yale who are going to be on College Bowl. You have to decide how much, what you're told is you have to decide who should be chosen to be on College Bowl.


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[Assistant] Admitted modestly to being a member of the Campus Honor Society, was the editor of the yearbook and ran varsity track. That's the nearly perfect person.


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[Assistant] Uh, and myths that he has only average grades. He worked on the yearbook as a proofreader, and he tried out for the track team, but didn't make it.


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[Assistant] So you see they're keeping a lot of the elements consistent, but in one case he's kind of an average performer, and the other case nearly perfect.


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[Assistant] Now which of these two people do you find more attractive in listening to the tape? So when they ask you questions about which person should be on the quiz show, people say the more competent person, but they also ask questions like, how attractive do you find this person? Now you're only listening to an audio tape. How attractive do you find this person?


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[Assistant] And the, uh, results are pretty obvious. The competent person


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[Assistant] Now what happens is half of the participants in the experiment who have listened to each of these tapes


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[Assistant] You only get to listen to one tape. Half of them are assigned to the blunder condition. And what happens in the blunder condition is the tape continues and what you hear is the clattering of dishes, uh, uh, uh, a person saying, the person saying,


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[Assistant] Oh my goodness, I've spilled coffee all over my new suit. Okay, that's the blunder, that's the platform.


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[Assistant] Your rating of the attractiveness of the competent person grows even higher.


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[Assistant] This is the sad irony in these experiments. The effect works both ways. So the mediocre become even more lowered in your esteem, in your regard.


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[Assistant] So, so, uh, and it was done by Elliot Aaronson who has retired now but for many years taught at the University of California Santa Cruz. Name is not one that you need to know.


[User] Please transcribe this text

[Assistant] And I was looking for an advisor and I was kind of interviewing with a faculty member at Yale, uh, at the time named Judy Rodin. Some of you may know that name because she went on later to become the president of the University of Pennsylvania and now is the president of the Rockefeller Foundation.


[User] Please transcribe this text

[Assistant] But I was interviewing with, uh, uh, her, and I set up a meeting, and what I was trying to persuade her in this meeting was to take me on as one of her students, to let, to be my advisor.


[User] Please transcribe this text

[Assistant] And it's about my third or fourth week of graduate school and I'm pretty nervous about this and, uh, you know, she could be intimidating to a first year graduate student. And I remember I was holding this mug of coffee and I was


[User] Please transcribe this text

[Assistant] And I'm, I'm gonna move a little bit quickly through all of this because I wanna leave time, uh, for a few questions, uh, at the end of the lecture. Uh, let's talk about physical attractiveness as number two of the more interesting four.


[User] Please transcribe this text

[Assistant] Now physical attractiveness is one that really bothers us.


[User] Please transcribe this text

[Assistant] Except at the margins, there isn't much we can do about physical attractiveness.


[User] Please transcribe this text

[Assistant] So we don't like to believe that physical attractiveness matters. And the interesting thing is if you do surveys of college students and you say to them, rate how important different characteristics are in


[User] Please transcribe this text

[Assistant] All of those things. Let's do it in a different order. If you send everybody out on a blind date,


[User] Please transcribe this text

[Assistant] And then you look at after the blind date, how many of those people who are matched up blindly actually go on a second date? Actually get together again. What predicts who gets together again? Was it the rating of warmth?


[User] Please transcribe this text

[Assistant] And it's one of those classic dissociations between what we think is unimportant and what empirically turns out to be


[User] Please transcribe this text

[Assistant] Uh, the randomly assigned partner, they were more likely to continue the relationship.


[User] Please transcribe this text

[Assistant] Now it's interesting to ask why, and we have to start to look at other experiments to try to get at what is it about physical attractiveness that, uhm, uh, makes people want to pursue the relationship.


[User] Please transcribe this text

[Assistant] And in one, one experiment, which many people know as the Frizzy Wig experiment, he did the following.