A Show About Nothing... and Racism

*The following video contains obscene racist comments which are not shared by this author. The use of this video is strictly to benefit the following article. Viewer discretion is strongly advised.*



The video above shows the very recent comments of Michael Richards, better known as Cosmo Kramer on the hit sitcom "Seinfeld", where he openly insults some Afro-Americans in the audience who were heckling him. His comments are absolutely unacceptable and irreversable, but just blindly watching the footage does not give enough information to judge from.

First, watch the very start of the video again: Kramer's outburst comment is said, and is arguably the most racist statement he ever gives. What is the audience's reaction? The audience does not boo or fall silent, but they actually applaud and cheer! How could this possibly be? Aren't these people sick? No, of course not. What these people are is in a state of comic readiness. No matter what Richards said next, they were going to laugh and react in a similar fashion. People really are sheep like this.

This may seem like an overly bleak image of us. Considering the applause, you cannot really accuse Richards of racism without accusing the majority of the audience of racism as well. The fact is that a stand-up act is one of the most effective ways to form crowd mentality. Take a minute to consider how this comedy works. One man is allowed to think while everyone else stays quiet and absorbs these thoughts. Comedians are also especially trained to make people adopt their point of views, perhaps moreso than politicians. Comedians just make people laugh, but first they have to make everyone adopt their point of view. While most comics stick to the mundane "airline peanuts" style of jokes that do not require the audience to change their mentality very much or at all, some comics can convince their audience of points of view that are more important and serious.

Consider Comedy Central's amazing hit: "The Daily Show with Jon Stewart". The show was originally hosted by Craig Ferguson, instead of Jon Stewart, and was another late night show like "Late Night with Letterman", and "The Tonight Show with Jay Jay Leno". When Jon Stewart took the reins to the show, he slowly reaimed it towards politics, and the show is no longer thought of as a late-night show, but rather as a fake news show. Jon Stewart takes current headlines and comments on them as his daily comedic bit, usually taking a very cynical view. This is where it gets serious. Through comedy, the Daily Show delivers an opinion on current affairs, and unlike a debate show or a known partisan show like right-winged "The O'Reilly Factor", the viewers take this in as fact, not opinion. Studies have found that viewers who watch The Daily Show are more cynical about politicians than those who watch a typical news program.

The bottom line is that comedy is one of the greatest ways to convince someone of your argument. By correctly using comedy, not only does your side seem inarguably correct, but the opposing side seems laughable. Therefore a stand-up comedy location is an especially volatile place for crowds to form. This is exactly what happened to Michael Richards too. He was obviously upset about some people of African descent talking during his set, and so he "flipped out" and said that first unforgivable comment. As the crowd has already developed some crowd behaviour with Richards as the crowd leader, they immediately applauded this, even though it would not reflect their own regular opinions. Richards then took the applause as acceptance, and, since he too was a part of the crowd, he continued into what became a fiery and lengthy hate speech.



Above is a video of Michael Richards' apology aired on the "Late Night with Letterman". There are a few things to mention here. First off, Richards really does appear to, not only be sorry, but rattled and confused about what happened. Richards would have to be a very good actor to be able to portray such emotions as just an act. This fits in to the crowd behaviour idea, where the ideas and actions when the crowd is in formation no longer make sense after the fact. The individuals involved in the crowd regain control of their own minds and are highly regretful and confused about the prior actions.

Secondly, we begin to see crowd formation once more. Many people said after the fact that "Late Night with Letterman" was not the right place to deliver the apology, and they would most likely be right. The people in the audience are expecting comedy; and are ready to interpret anything as a joke. At 1:30 into the video, Jerry Seinfeld has to tell the audience to "stop laughing; it's not funny". Richards later remarks similarily on the laughter. Certainly if the apology had been made on CNN or a more news-related source, the same audience would not have laughed at all, but since they had already been brought in to that state of mind by the whole show, they were ready to laugh at any reasonable chance they got.

On a quick sidenote, this explains why laugh tracks are so effective. As I've mentioned before, the opinions we hold for many movies are based strongly on what kind of viewing audience we saw it with. Watching a show like Family Guy alone, I will not laugh once, even when jokes strike me as funny, but in a crowd, everything gets loosened, and laughter comes easier. A laugh track is a program's way of simulating this viewing environment so that people who are alone will have a higher opinion of the show. Contrary to popular belief, the laugh track is not an insulting tool made by the networks to tell its dumb audience when to laugh; it merely enhances this laughing experience.

Back to the original stand-up of Michael Richards, there is still one unanswered question. Even if Richards was just very frustrated at the people who were talking in the crowd, and that was what started the whole hate speech, why is it then that he attacked them with a racist comment if he himself is not a racist. Easy answer: he is a racist. Not that there's anything wrong with that!

As Adler and Rodman have no doubt observed, people are constantly monitoring other people and making patterns to more easily classify others in the future. If someone never knew an Italian person, but saw "The Sopranos" as well as all the "Godfather" movies, they might have a skewed image of what an Italian person is really like. In reality, not every Italian person is in the mafia, in fact, very very few are. However, even if this person was well-educated to know that this is just a stereotype and in no way reflects the Italian community, they will still have some bias in them from their viewing experience, a bias they would not even be aware of.

Today's society tries to make great strides towards "political correctness", that is, we will not ever judge anything about a person based on the race, gender, class, or background. The problem with this is that these judgments cannot be turned off so easily, since they are an internal process. They are our brain's way of making the connections mentioned earlier, and these connections are not just to classify people based on physical attributes, but for practically anything.

Consider a red button in front of you. When you press it, it delivers a shock. If you see a similar button in the future, you will probably be cautious around it. This is a stereotyping of the button, since, while similar, may not do the same thing. However, we could still agree that the reaction is understandable and smart. People, of course, are not buttons, and can differ greatly despite physical attributes. This, however, is a higher-level way of thinking, while first impressions based on physical appearance is more instinctual. With proper education on the matter, we can make it so that these opinions do not too flagrantly affect us, but they will always be present in us to some small degree.

"I'm not a racist. That's what's so insane about all of this!" said Michael Richards. Of course, it is clear that he did have some racial profiling during his standup. The best way to describe what happened is that Richards, like all of us, developed some opinion based on race, and when he got angry at the group, this opinion became temporarily enlarged, and the rest is history.

This is not meant to completely absolve Michael Richards of all responsibility. The initial words he used are still stronger than they should have been for someone of minimal racist tendencies, so there were some roots of racism there that are larger than they are in most of us. However, the majority of the night was just a crash and burn disaster that one can not strictly accuse Richards of being responsible for.

On a final sidenote, I disagree with the political correctness attempt that today's society has. It is the wrong way to set the equality of race and sex since it applies rules. People are truly afraid to be racist now, and so they become racist in the other direction, by bending over backwards for other races. Now, it is nearly impossible to carry on regular relationships with other races since everyone is too afraid of offending each other. There are now walls between all of us. So, contrary to political correctness, the best way to break these walls is actually to be more honest, even by insulting other races. For instance, I was down in the study room learning Algebra with other engineers, and there were several different races present. There were some "racist" comments made in pure fun (nothing serious), and both sides were fine with it. For instance, an Indian person did an impression of how an Indian person talks. This is hard to explain how it works, but it does, and it is the only way racial equality can work, as well. You can't be friends with someone if you are constantly walking on eggshells around them.

Anthony Tsikouras
#0655775
Alex Sévigny
CMST 1A03
Rita Tourkova
Due Date: November 20, 2006

A Critical Examination of Alan Turing’s Concept of Artificial Intelligence

“The machines will rise.”

- Tagline from “Terminator 3: Rise of the Machines”

Artificial intelligence has long been a popular subject in science fiction. The most popular of these stories feature machines that, once they become self-aware, rebel against the human race, and ultimately take control. While an admittedly terrifying plot, many critics believe the entire idea of artificial intelligence to be a pure impossibility. Alan Turing, however, argues that if a machine is indistinguishable from a human being in a controlled study, it has achieved a level of intelligence (p. 77). It is a study Turing refers to as the imitation game. The game consists of an interviewer communicating through text conversations with another person and a machine. The interviewer then has to identify which personality was a real person and which was a machine.

While the imitation game does provide a good starting ground for which artificial intelligence can be measured, there are two serious flaws. Turing never explains how the machine would understand language as well as being able to respond in language. The only way the imitation game would be possible then would be if the same questions were always asked, so the machine could keep set answers stored in its memory. This would actually not be a form of artificial intelligence, since all the answers are predictable and not learned. It is the equivalent of a well-trained parrot. The second flaw threatens to destroy Turing’s basis of what consists of artificial intelligence: the machine has no life to protect or genes to pass on. Because of this, its conversation would be different, sometimes drastically, from that of a human. This is not to say that the theory is lost, and that artificial intelligence is impossible, but it certainly does require a tweaking.

Before elaborating on how to fix this definition, it is important to realize that man is a machine, in the most literal sense. To understand this, consider a squirrel. If one were to watch a squirrel’s movements throughout a day, they would find them to be very repetitive and predictable. A squirrel is one of the most definitive examples of an animal being controlled by its instincts. It is not a stretch of the imagination to consider programming a robot that would behave exactly like a squirrel. Next, consider a bird: while its behaviour is somewhat less predictable, it still follows its instincts for the most part. The idea is that as we advance to species of higher and higher intellect, the programming code associated with them becomes harder and harder, until we reach human, the species of highest intellect on the planet. Though the coding does get harder as we advance up to humans, there is no one point where we can draw the line, where one animal was predictable enough to code and another was not. It is simply that the animals become so complex that we can not understand their processes well enough to code them. Therefore, if one considers a squirrel to be a machine, then a human must be a machine as well.

It is now possible to define the problem correctly. If we cannot base artificial intelligence on the result of the imitation game, then what qualities do we look for in artificial intelligence. What would seem simplest is that a thinking machine must be capable of producing thought. This may seem too vague and improvable to be the definition, but by combining Turing’s theory with some ideas of Steven Pinker, the definition becomes suitable. We must also specify that the machine is man-made, since otherwise a human being could still qualify.

Pinker’s main theory involves man’s ability to learn language naturally (p. 44). He claims that language is not an invention of man, but rather it is instinctual, with the proof being that language has developed in every human tribe on Earth. His idea is that every human mind has some basis of grammar that transcends all languages, referred to as the Universal Grammar. In other words, every language is formed of the same sub-components, for instance: nouns, verbs and adjectives. A child is able to learn a language from the people speaking around him by using the Universal Grammar, along with the situational context of the sentences.

At first glance, this process appears to already be installed in every word processor: the feature of Spell Check has become a standard. Spell Check is now able to correct text according to grammar and syntax for nearly any language. It is also able to add new words to its repertoire if the user so wishes, and find synonyms and antonyms for words. Despite all of this, it still does not understand language. It has a basic Universal Grammar, being able to recognize sentence fragments, and it can therefore verify that flawless sentences are written, but it is far from comprehending what it is reading. To understand language, words must exist as more than letters; they must represent something to the computer as well. Consider that the dictionary in a computer has the word “apple”, and its definition is “a kind of fruit”. The computer still has no idea what an “apple” is since it does not know what a “fruit” is.

The only way for a machine to learn a language is for it to have senses like humans have. How would you describe an apple to me if you could not make reference to what it looks like, what if feels like, what it tastes like, or what it smells like? It is technically impossible. Therefore, for a computer to learn a language, it must have sensors that can deduce the sensory qualities of a given object. If a computer was set up with the proper sensors and its basic universal grammar, and it was immersed in a language, given a suitable situation with references to objects, it would be able to quite literally learn words, with the correct associated meanings as well. Up to now, this has only gone to explain how to define objects for machines. Verbs can be learnt in a similar way, but adjectives cannot be learnt until after nouns and verbs are learnt, since their meanings are based on the characteristics of nouns and verbs.

This may seem like a very long process ensuing before the machine could respond in the language of its surroundings, and that is absolutely true. It would take years of near constant immersion in language before the machine would know enough to be able to use it. However, far from being a problem with the learning process, it could be seen as a great success. Human children take two years of constant immersion before they say their first word. Considering that humans are machines, it is likely that the process designed for the machine accurately matches the organic equivalent inside every human.

Despite this major accomplishment, there is still a large flaw that will prevent the computer
from ever being able to communicate like a human being. Consider the stereotypical example of artificial intelligence: the on-board computer “HAL”, from “2001: A Space Odyssey”. After HAL incorrectly detects a malfunction on the ship, the astronauts on board see HAL is a danger to their safety and try to disconnect him. HAL, however, wants to survive, and so does everything he can to prevent the astronauts from shutting him down. This is unrealistic since the machine should not be interested in its own survival. This is the great error when one theorizes on artificial intelligence. Just because a machine is conscious does not mean that its life has meaning. The machine will do what it was programmed for with the same kind of perseverance as animals try to stay alive.

If we return to the idea that humans are machines, then one might expect them to have a main driving goal as well, and correctly. Humans, along with every other animal are built to survive and procreate, which is the survival of genes. This may seem like a bleak oversimplification, but in the end, that is what we all have in common, and any activities we take part in are all different means to the same end. A human’s goal is survival, just like antivirus software’s goal is to scan for viruses, and the lives of both do not extend past these respective goals. Proof of this is clear everywhere in society: the urge for offspring to get good jobs and the immense focus on sex in the media are examples of survival and procreation respectively.

Besides the many ways our primary objective affects our lives overall, there are many ways it affects our communication. Adler and Rodman catalog many observations of human tendencies in communication: we cling to first impressions, we tend to believe the worst in people, and we are more likely to interpret comments as insults when we are already in a bad mood (p. 37). These are mechanisms for survival that have been proven to work. At a glance, it is not hard to decipher why they are effective. First impressions are usually correct since the other person is dressed in a way that represents himself. The other two mechanisms are based on the “better safe than sorry” approach, where our survival is more assured by taking the cautious, or worst case scenario, route.

These are just a very select few of the survival mechanisms that constantly play a role in our interpersonal communication. Aside from the more complex mechanisms observed by Adler and Rodman, there are the more basic ones: emotions. These are all based on human survival method, so they will not be apparent in a machine’s side of a conversation.

Combining the methods discussed for creating an artificially intelligent machine, we have a machine that can learn language through sensory recognition of objects. It would actually be intelligent in the terms Turing presented, and yet it would still fail his test. This is because, while it would actually be more accurately intelligent, since intelligence demands the creation of your own sentences, it would be clear that the artificial intelligence displays no emotion, none of the
qualities we take for granted in people.

If a machine could talk, what would it say? Like us, it would depend on its goal.


Works Cited:

Adler, Ronald B. and George Rodman. Understanding Human Communication, 9th ed. New York: Oxford University Press, 2006.

Pinker, Steven. "An Instinct to Acquire an Art". Communications Studies 1A03 Custom Courseware. Ed. Alex Sévigny. Dubuque, Iowa: Kendall/Hunt Publishing Company, 2006, 41-45.

Terminator 3: Rise of the Machines. Dir. Jonathan Mostow. Perf. Arnold Schwarzenegger, Kate Nick Stahl and Claire Danes. Warner Bros., 2003.

Turing, A.M. "Computing Machinery and Intelligence". Communications Studies 1A03 Custom Courseware. Ed. Alex Sévigny. Dubuque, Iowa: Kendall/Hunt Publishing Company, 2006, 77-85.

And That's All I've Gotta Say About Hat

In grade 12, my high school introduced the hat rule: no student could wear a hat inside the building. The rule was very unpopular, especially with me, so much so that I wrote my French opinion speech on it.

The English version of the speech can be found here: http://atsikouras.spaces.live.com/blog/cns!F93F3721AF1BE8!270.entry

In the speech, I addressed every possible reason I could think of for the ban of hats: gang activity, respect, distraction, etc. Later in the year, I met with the vice principal to discuss the rule, and he claimed that the reason for the rule was to be able to easier identify students. This answer was so unexpected to me that I couldn't really reply to it, but looking back it made even less sense. The basis of his argument is that people are easier to identify with their hats off. This itself is seriously flawed.

In "Cool Bodies: TV Ad Talk", Gillespie says "clothes are an important manifestation, often a conscious public statement, of one's cultural affinities". In other words, people where things that represent them.

Consider me, for an example. Since grade 6, I've always worn a Blue Jays cap. When I meet new people, the first thing they probably remember me as is "the guy with the Jays cap". This is the truth, and it is not insulting. Of course it is not my full personality, but any form of fashion is really you trying to portray yourself to the world without directly communicating. This way, it is easier to meet people who have common interests because you know from afar whether or not you have anything in common.

Style does not stop at caps either, though, but is represented in everything you wear. In the end, you can find that most people have a small section of their personality that is actually visible to the public. I might wear my Jays cap, a Van Halen t-shirt and running shoes, and someone might guess (correctly) that I like baseball, classic rock music and playing sports.

The idea that hats make us harder to identify is very flawed. Of course, our faces aren't as visible, but caps are a much stronger identifier than the face. This is why commercial products work so well: their logos are based on catching the eye. Our faces may produce some identification traits, but it is much more limited than a large multi-coloured object on top of the head. Think about "Where's Waldo?"; wouldn't he be a little easier to find if no one else on the page had that red and white shirt and toque?

In fact, it is more than having a marketable icon on you: it is about marketing yourself. This is what we do from high school through university. We are attempting to sell ourselves to people, and what we wear is the box the product comes in. Once someone picks up the box, then you can have a chance at showing them what's inside, but before that, you need an attractive box to catch their attention. To prevent teenagers and young adults from displaying this could technically be considered a crime against nature.

Finally, I close with this image I made last year as my display pic for MSN. While it is not a photo of me, is there any doubt who it represents?

Explaining the "How" with the "Y"

The chart above displays height frequency in males (dotted line) and females (continuous line). This, simply put, shows the range of how tall a male and female with typically be. The first thing anyone can note, and seems obvious when considered, is that both sets of data form bellcurves, with a very tall center and exponentially smaller fringes. This makes sense, since there are a lot of people around average height, and few people wildly removed from average height. However, when we compare the two functions on the graph, we see that the male bellcurve is not as tall as the female one. This suggests that there is a smaller density of males at average height. Correspondingly, the fringe zones on either side of the curve do not fall as fast as the females, and extend longer before hitting the x-axis.

This tells us that males are more deviational. Again, this makes sense when you consider your daily observations. Some men are fairly short, others fairly tall; and while there is variance for women too, the difference in height is generally less pronounced. This extends far beyond height: if you took a graph comparing almost anything between the two genders, you will get the same bellcurves. Consider grades: I bet that the award for highest overall mark at your high school graduation went to a male. This is not being sexist, and it isn't a wild guess. Men are just more likely too finish with 100% because that is a fringe mark. Men are also more likely too finish with a 25% average. Women will probably have exactly the same overall average, but with less of a range of marks.

All of this in itself is valuable, but the value does not really begin to unfold before we consider why (soon, we'll get to the pun in the title).

Completely changing gears, let's consider nature, that is, evolution. It's all well and obvious why evolution happens at all: it is a way of ensuring that each succeeding generation gets the traits of the successful prior generation. In the end, through many generations, only the successful traits remain, and all unsuccessful traits are lost.

This is a bit oversimplified though. The fact is, the world and our society are always changing. Successful genes one generation might not be as successful the next. Sometimes drastic changes are made to our environment and the successful genes are now a nuisance. Consider body hair: initially this would be a large advantage, keeping us warm in a colder climate. Now, it is looked at unfavourably: men shave their faces, women shave their legs, and naturally hairless people now have the advantage.

The question is, how can our genes bring back an attribute that has been exterminated through generations of opposite thinking? The dodo isn't suddenly going to walk out again, so how can technically extinct genes do this? As we all covered in grade 9 sex ed class, a new human life forms from a half of the genes of the mother and half the genes of the father combining. Aside from this faithful combination of the two parents, there are slight random mutations for the next generation, that are uncommon to both parents. This is how extinct genes can be brought back for another chance.

We now have a seemingly working model for evolution. Every generation of people have a set of genes, and if they are successful for survival, then they will be passed along to the next generations and perhaps someday become commonplace. So, if this were the case, why do we have two genders? Surely, the best way to combine genes would be to have every person's genes open every other person, instead of just half the population. This is absolutely true mathematically, but obviously nature has some purpose for two sexes.

Continuing on grade 9 knowledge, while the mother always contributes an X chromosome, the father may contribute and X or a Y chromosome, resulting in the offspring being either a girl (XX) or a boy (XY). It is my opinion that, while there may be slight mutation on the part of the X chromosome(s), the main mutation is caused by the Y chromosome. That would make it so that, looking at the below graphic, that while a daughter is a faithful representation of her parents, a son can noticeably deviate from the genes that created him. So, the old saying "the apple doesn't far fall from the tree" doesn't always apply.

This theory goes a long way to explaining why there are two sexes. Females of the species can be considered the final products. They are the combination of two successful beings (their parents), so, considering her environment is relatively similar to her parents', she should be successful too. Females are the anchors of the species, making sure we hold on to our successful roots. Males, on the other hand, are the opposite. They are the prototypes: still based off a successful model, but the lab wants to try something new and see if it works out. Sometimes the changes are effective (Cherry Coke), and sometimes they are not (Vanilla Coke). The result of this final product-prototype relationship is that the entire species is constantly in a state of controlled flux, making sure that the bellcurve shifts to respond to external changes.

This is all just a theory, but it does go a long way to explaining a few things about us:

- Men are the suitors. While on rare occasions, women ask men out, usually the man asks the the woman out, and the woman gets to make the decision. Also, contrary to almost every episode of Seinfeld, women are usually those who terminate the relationship, as well (http://www.sandstorming.com/2006/02/men-are-more-romantic-than-women/). It is an evaluation of the prototype.

- Men are the guides in relationships. Men are the ones expected to pick the girl up for the dinner, plan the little surprises... in short, whisk the girl off her feet. This isn't just a male perspective; what is a Harlequin romance besides this? The fact is, the women are taking the prototypes out for a test drive, and noting his performance. Does this man's genes deserve to survive for the next generation?

- We are all attracted to someone who is different from us. Our goal is to keep passing on our genes through to the next generations, and if you are on one side of the bellcurve, it is fitting to find someone on the other side of the bellcurve so that your offspring (especially your daughters) will be closer to the center.

With this important rider, the model of nature seems to make perfect sense. Nature within a species (and in the longterm, across species) is the constant evolution of the successful model. Deviational models are created to make sure that the majority of our species stays centered around the most successful model corresponding to the natural and societal environment. Two genders are used to support this system: one to try new things that might be beneficial, and one to anchor down what works, making the beneficial more standard for the species.

And that is how the "Y" can explain the "how".