Too Much Time on the Computer

At the outset of Sherry Turkle’s excerpt from The Second Self, she boldly claims that “Children use the computer in their process of world and identity construction”. As for assimilating them into this progressive, technological generation, it executes its job by familiarizing them with the processes of the computer, its programs, and by stimulating their minds on the plethora of educational and non-educational video games. However, Turkle fails to specify the amount of time spent on this computer apposed to other activities that can help children grow and mature. Turkle’s points are valid if the children are also using other mediums to discover themselves, and not relying on the computer as their sole source to “forge their sense of themselves” and use it as their only tool towards “development of their personalities and ways of looking at the world”.

The dilemma created by this sole, and I stress the term sole, reliance on computers to build ones personality, is the creation of an inward, intelligent person who spends all his or her time on video games like MMORPG’s and studying. In my past years of playing wow, I’ve conversed with, in the game and in real life, many players who fit into this mold, which has lead me to understand that completely shutting yourself off from the physical world can cause stunted social skills and a reluctance to step outside the now norm of staying on the computer.

I’m not saying that socializing does not happen on the internet, as I have clearly seen in wow, but there is a large distinction between typing from behind a computer screen and conversing with people in real life. For example, on the internet when something extremely awkward is said, it is most likely ignored and the conversation continues. However, in a face to face conversation when that same line is verbalized, it could result in public humiliation and the end of the conversation.

A possible solution to this issue is a balance between time spent on the computer and time spent participating in some sort of social activity, be it sports, band, clubs, etc. I don’t want to sound like I’m on some high horse preaching about nerds, I’ve always been a gamer and will continue to be one.

Chapter 5: The Second Self

“Machines impose their own rhythm, their rules, on the people who work with them, to the point where it is no longer clear who or what is being used. We work to the rhythms of machines – physical machines or the bureaucratic machinery of corporate structures” (Turkle 159).

Reading this quote it is not too difficult to ask: Do we use a computer or does a computer use us? In the simplest sense, the answer is simple: off course, we are the beings, we are in control – we use computers to accomplish tasks, as tools; however, let us reconsider this.

In chapter five of The Second Self, Turkle establishes the computer as a machine and as a tool – determined by the user and the manner of their usage. Taking this quote one step further, analyzing our society, isn’t the need for stronger, better and more efficient computers growing. Turkle points out that from the beginning “prominent literature and popular accounts of home computer use emphasized … how computers could teach French or help with financial planning and taxes” (Turkle 157), what she considers the ‘utilitarian rhetoric’. I think it is interesting to note that our physical infrastructure along with social manners have dramatically changed to make the rise of computers – the machine from the past for the future – occur. In this sense, I do not think that it is too difficult to ascertain that we can be looked upon as being used by computers – for their continued improvement and our greater dependence on them.

Changes in culture have dramatically re-shaped work distribution between man and machine with the computerization of society. Social mechanisms from dating, to establishing solidarity and independence have all dramatically changed – from what they were not too far in the past. New social mechanisms have been added to our collective culture, as email and web chatting replace letter writing and telegrams. Rituals which did not require computers now begin and end with computers and computerized technology. Not only has our pre-existing culture changed, Turkle writes: new groups which “share a unity of place, lifestyle, and passion … have [their] own rituals, language, myths, even its own literature” (Turkle 181) have emerged built on computers. With the advent of computers, it seems that a silent movement started which takes ‘work’ from human beings and instead gives it to the computers with the simple advantage that with these machines humans can do more. As a byproduct of this movement our dependence on computers is continually increasing.

If the ultimate biological purpose of an organism is too reproduce then computers are extremely successful their and are thriving in their expanding niche. But how can view a computer as an organism? Generically there are (among many) six characteristics of life: cells, organization, energy use, homeostasis, growth and reproduction – in one way or another a computer comes really closely to fulfilling these prerequisites. If generic hardware components be considered cells, homeostasis by the use of sensors and fans, growth through downloads and uploads, and reproduction through computer managed computer manufacturing facilities – computers come really close to living especially as research continues into using Deoxyribonucleic Acid instead of traditional silicon chips for information storage. Doesn’t a simple prokaryotic bacterium with plasmid DNA, a simple phospholipids membranes and polysaccharide coatings seem less complex than the world’s largest supercomputer? It is easy to say that it is humans which have caused the rise in computers – but I ask you, is it that different to consider that perhaps it is due to the computers that human beings are becoming more and more depended on them and because of computers that mechanisms and forces continue to push humans to develop the next more advanced computer.

I would also like to say that I do not how much I agree with the central argument of this post – but I do believe it is an interesting concept and one which certainly will become more interesting with time.

Jaskaran Saggu

Artificial Intelligence: Neural Networks and Genetic Algorithms

Artificial intelligence has advanced considerably since Alan Turing's article "Computing Machinery and Intelligence", published in 1950. Turing speculated that one day computer programs emulating a learning behaviour and heuristic could become possible with sufficient computing power, and he gave certain principles regarding the components such programs would require. From the day the article was published, some of these principles have been gradually developed into sophisticated algorithms, and new algorithms independent on Turing's research have been researched. Many of Turings propositions became fundamental components in advanced artificial intelligence today; others became technologically obsolete because of the lack of sophisticated computing at the time of publishing.

One such computer science field, only suggestively touched in Turing's article, is an fascinating and, quite frankly, mysterious type of algorithm called Artificial Neural Networks. Neural networks are analogous to the processes which occur in our own human brains. More specifically, the algorithm consists of an abstract "brain" in which there are "neurons" connected to eachother in an intricate network pattern. Neurons may send and transmit signals according to pre-designed rules, and by using defined "input" and "output" neurons it is possible to train the network to perform tasks in similar ways as humans do, and more importantly, learn.

Neural networks are so fascinating and ground-breaking because of their very hard-grasped inner workings. To explain with an analogy, consider seeing a team of construction workers, and their end result, a tall skyscraper, in which the intermediary process was hidden. The individual components, the construction workers, tools and material are simple, but the end result is highly complex. Because you do not know how the building was constructed by these simple parts, you are naturally fascinated. This applies for neural networks too. We still only understand their intermediary process on a very shallow level, yet they have showed amazing results, especially when combined with genetic algorithms. By evolving the networks, allowing artificial selection to select the well-suited and eliminate the badly-suited networks, one can "teach" networks to perform complex tasks using complex tools to do so. One can also make the neural network teach itself by implementing a "reward and punishment"-system described by Turing, but compared to networks evolved by genetic algorithms, these networks usually do not adapt as radical and scientifically interesting behaviours as do the genetic algorithm networks.

Some may think that a learning machine, especially after seeing films like The Terminator, is a frightening offspring of science gone wrong. I oppose this view - it is easy to contain an artificial intelligence by providing no physical tools it can use. Comparing this drawback to the scientific interest of neural networks demonstrates that we should accelerate research within this field. Some of the results of neural networks, however, are unexpected and perhaps not really useful. I have researched neural networks myself, as I contributed once in making a computer game in which the opponents (in the shape of tanks) were controlled by neural networks. The opponent was rewarded points for shooting opposing tanks and collecting powerups. I watched the neural networks evolve, and curiously, the tanks did not learn to shoot each other; instead, they chose a pacifistic approach and instead only drove around the track collecting powerups. This actually, in total, gave more points than shooting at the enemy tanks, thus explaining the strange result. Another amusing example comes from military research in the 60's in which  neural networks were trained to recognize hidden tanks in pictures. All went well: Eventually the computer could seem to tell the difference between pictures in which there were tanks and pictures in which there were not. However, when presented with a new set of pictures of hidden tanks, the neural network failed; this obviously puzzled the researchers. They eventually found the problem; the pictures of the hidden tanks were taken on cloudy days, and the pictures without tanks were taken on sunny days. Thus, the military now had a multi-million-dollar computer which could tell if it was sunny or not.

Week 3: More History of Computing and Artificial Intelligence

Post comments to this thread for week three's readings/viewings: the Engelbart "Mother of All Demos" and Sherry Turkle.

Personally, I don’t think Turing answered the question “Can Machines think?”
even when he shifts the question to “Are there imaginable digital computers
that would do well in the imitation game?” Instead, he writes about how a
machine might be thought of as intelligent. This would be done, he writes,
by having a computer convince a person that the computer was really a
different person of a specific gender. By implication, Turing is equating
thinking with the ability to pose as a human. However, the ability for
a computer to fool someone is relatively easy, given
the fact that more than 55% of communication is nonverbal.
This means that it is easy to trick a human when only text is involved.

It would be both very interesting and frightening if scientists were
to go about producing artificial intelligence in the way that Turing
proposes. In a sense, computers (or their software, at any rate) would
be bred to be more intelligent. In his paper, Turing is absolutely
convinced that Artificial intelligence is what is needed. In his conclusion,
Turing wants to teach a computer to “understand and speak English”.
Yet in all of his paper, Turing never says why he wants to do that. This
might have something to do with the fact that Turing thought of his
brain as being a hyper-advanced form of the digital
computer he defined.

artificial intellegence. can machines think

“Can machines think?” Alan Turing had arguments on whether the machines that man has built can think. He uses an example of the mimic game, where an interrogator is to distinguish who is a man and who is a computer. Computers are programmed to do what we want them to do. They understand the words that are coming from us, but it sometimes does what you want, but what you didn’t want at the same time. For example, if I wanted to draw and elephant and I want the computer to do the work I would give it instructions to do so. Let’s say, I tell it to draw a circle for the body. Instead, the computer draws a tiny circle instead of the size I originally wanted. But it is in fact a circle. Therefore one questions if computers do think on their own if not in a different way in which they are programmed.

One distinctive characteristic of the “artificial intelligence” is that it cannot make mistakes. Humans programmed it to do work in a sufficient manner for algorithms and calculation for us. So in a sense to my first point, it’s not wrong in doing to what you are saying, it’s just your fault for not describing it correctly. However, for this reason it is considered errors, errors of functioning and errors of conclusion. However humans wants to feel superior and always in control.But one thing that became interesting was that he stated what if vice versa a computer can become a man, or even better a child for it can have the ability to develop in knowledge. And it will progressively learn and when it does something right, it will have more possibly cause repetition and if it is wrong, it will adjust. And what if, it can develop speech and had eyes and legs to walk? For now it is unimportant, but if so, the world of the “Terminator” can one day be true. Maybe one day we can have one to act as guides for us, such as finding Alenda’s room in Moffit.

I'm lost... help, please!

A thread for questions, clarifications, confusions, frustrations, and general mind-boggling. Are you confused about terminology we've encountered in our reading? Puzzled by something Alenda mentioned in class? Don't be afraid to ask for help here and we can all exercise what Pierre Levy calls collective intelligence.

From last week: HCI, GUI, avant-garde
From this week: cybernetics

Guess who sang these apropos lyrics?

Help, I need somebody,
Help, not just anybody,
Help, you know I need someone, help!

When I was younger, so much younger than today,
I never needed anybody's help in any way.
But now these days are gone, I'm not so self assured,
Now I find I've changed my mind and opened up the doors.