Sherry Turkle (MIT lecturer in computers and psychology) is a writer who understands about how social relations are embedded in computer programs and the user interface.
If her books were more widely read and understood we would be in a far better position to educate our youth in the use of the computer.
Victorian teacher Rob Costello (who blogs at learning in progress) pasted the following long quote from Turkle's 2004 introduction to her 1984 book The Second Self: Computers and the Human Spirit. This deals mainly with the limitations of computer simulations:
In The Second Self I report on my studies of children learning Logo. Their styles of programming were varied and revealing. The computer, as I have said, served as a Rorschach, and programming was one of the most powerful manifestations of its projective power. Twenty years later, programming is no longer taught much in standard classrooms, relegated for the most part to special after-school computer clubs. These days, educators most often think of computer literacy as the ability to use the computer as an information appliance for such purposes as word processing, running simulations, accessing educational CD-ROMs, navigating the Internet, and using presentation software such as PowerPoint. But the question remains whether mastery of these skills should be the goal of computer education.
Do they constitute computer literacy?
One unhappy seventh-grade teacher concurred, “It’s not my job to instruct children in the use of an appliance and then to leave it at that.” These teachers were struggling toward an argument for a certain kind of “computational exceptionalism.” It takes as a given that people once knew how their cars, televisions, or telephones worked and don’t know this any more, but that in the case of mechanical technology, such losses are acceptable. It insists, however, that ignorance about the fundamentals of computation comes at too high a price. One teacher put it this way: “Children know that the telephone is a mechanism and that they control it. But it’s not enough to have that kind of understanding about the computer. You have to know how a simulation works. You have to know what an algorithm is.”
In the nearly ten years since I recorded these conversations, educational advocates for computational transparency have, in large measure, lost their battle. Educators who want to demystify the computer face a new generation of children that no longer finds enough mystery in the machine to care what an algorithm is. It is a generation that has made a transition from the transparency of algorithm to the opacity of simulation. This generation takes overland journeys along a simulated Oregon Trail and when it plays The Sims or The Sims Online, it designs houses, personal histories, and social engagements for the virtual citizenry. In The Second Self, when I wrote of the “computer as Rorschach,” it was programming that served as the projective screen for personal and cultural differences. These days, computation offers far more immediate projective media: one can create multiple avatars in online communities and play with relationships, quite literally using one’s “second (or third, or fourth, of fifth) self.”
I have suggested, in talking about Deborah, that on the level of the individual child, something interesting has been lost in the move away from authorship of the programs that underlie one’s own game. On a societal level, there is an analogous loss. The aesthetic of transparency (common to the Logo movement and the early generations of personal computer hobbyists) carried with it a political aesthetic that was tied both to authorship and to knowing how things worked on a level of considerable detail.
This is a kind of understanding that is not communicated by playing off-the-shelf simulations.
On one level, high school sophomores playing SimCity for two hours may learn more about urban planning than they would from a textbook, but on another level, they may not know how to think about what they are doing. They “play” simulations but don’t have a clear way to discriminate between the rules of the game and those that operate in a real city.
Most have never programmed a computer or constructed their own simulations. They do not have a language for talking about how one might rewrite the rules of their games. So, for example, SimCity often gives players the impression that raising taxes will lead to riots. But, of course, there is a way to write the game so that increased taxes lead to an increase in health services, productivity, and social harmony. In my view, citizenship in a culture of simulation requires that you know how to rewrite the rules. You need tools to measure, criticize, and judge every simulation. Today’s teenagers are comfortable as inhabitants of simulated worlds, but most often, they are there as consumers rather than as citizens. To achieve full citizenship, our children need to work with simulations that teach about the nature of simulation itself.
Tim, who did not know how to program, worked in a complex system built by others. Tim played his simulation software as though it were a video game, moment to moment, with no understanding of the rules. Deborah was nurtured by transparency; Tim’s skill set was centered on the artful navigation of opacity. His philosophy of play: “Don’t let it bother you if you don’t understand. I just say to myself that I probably won’t be able to understand the whole game any time soon. So I just play it.”
Tim’s method enabled him to accomplish a great deal in simulation space. His comfort in his virtual world might serve him (not well, but adequately) in the many possible careers that lay before him, careers in architecture, law, business, medicine, or history. In all of these fields, dealing with information increasingly entails the navigation of simulations of other people’s creation. However, as I meet professionals in all of these fields who move easily within their computational systems and yet feel constrained by them, trapped by their systems’ unseen limitations and unknown assumptions, I feel continued concern. Are the new generations of simulation consumers reminiscent of people who can pronounce the words in a book but don’t understand what they mean? We come to written text with centuries-long habits of readership. At the very least, we have learned to begin with the journalist’s traditional questions: Who, what, when, where, why, and how? Who wrote these words, what is their message, why were they written, and how are they situated in time and place, politically and socially? The dramatic changes in computer education over the past decades leave us with serious questions about how we can teach our children to interrogate simulations in much the same spirit.
The specific questions may be different, but the intent needs to be the same: to develop habits of readership appropriate to a culture of simulation. These habits of readership are central to computer literacy and social responsibility in the twenty-first century.
2 comments:
I gotta say, I feel sad reading this, that learning programming has been relegated to an after-school activity carried out in computer clubs. This makes it sound like we've come full circle. I say this because this is where programming = literacy began, as after-school activities in computer clubs. Eventually this grew to regular programming courses, in the 1980s. Something about this doesn't make sense to me though, because to this day there are AP courses in programming, which typically teach Java, because that's what's on the AP test. How are kids going to get into coursework like this if there's no groundwork laid beforehand about how programs work? Java is a hard language for beginners to learn.
A follow-up: I agree that an understanding of what's going on underneath the covers is important. Turkle alludes to this in the quote you cited. As my discusssions with people on the subject of anthropogenic global warming continue, I fear that we're producing another generation of people who think that because a computer tells them something, they think it's true. I got into a discussion with a couple people recently on the subject (online), and I realized that I had a different conception about computer models than they did. I understood the idea that you can't just rely on what models tell you without understanding their underlying principles, and their limitations, and secondly I spoke generally about how problematic it is to model climate over the long term in a computer to begin with, particularly as a predictive tool. When I said this they took it to mean that I thought climate models were useless. I clarified it by saying that models ARE useful so long as their properties and limitations are well understood, and they are used reasonably within those constraints as educational tools to help scientists understand phenomena better. I still see no rational way for them to be used as long-term predictive tools for such a system though.
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