Computing thinking
Amusing ad from october 1998: this made me smile.
This powerhouse was configured with a Pentium II 266MHz MMX processor, 128 MB of RAM, 24xCD ROM drive, 6.4 GB hard disk, 56Kbps USR modem, built in Zip 100MB drive, Matrox Millennium II graphics card and Altec Lansing's ACS90 multimedia speaker system. It is still a great performer.
Currently in New York on the couch of Lauren's (OLPC) apartment. The traffic noise of Brooklyn is drifting through the window, which has a stained-glass plate of a robot hanging in front of it with fishing line. This post is my online indulgence before I return to the Massive Block Of Tasks awaiting me on the OLPC wiki... it's definitely a working trip. (And as I write this, there are at least three simultaneous conversations on the #olpc-content IRC channel, where Nikki and I - among others - have become regulars. You can join us if you'd like; ask one of us if you don't know how.)
Today's train of thought comes from a conversation I had with Eric Munsing on the notion of "computing thinking" (during which I went on a long spiel about the use of computers as thinking tools - this was several months before I read Papert's book Mindstorms, which words it much more eloquently).
The following is taken almost verbatim from notes on the conversation and some scattered emails - side conversations on other topics have been clipped for clarity, and some sentence fragments have been filled in to add context, but otherwise they're untouched.
Eric: I'd hazard a theory that computers are naturally conservative analytical tools - they only process existing data reflecting the current structure/beliefs and don't introduce new concepts or frames for analysis.
Mel: Interesting exercise - take your four lines of text above and replace the word "computers" with the word "languages."
I see computing thinking partially as a different type of language. Mathematics as well, for that matter. There's a grammar, a vocabulary, and a set of structures you can build both mentally and electronically. In and of themselves, they don't mean anything, but they can be used to build spectacular things that do have meaning, and as tools to help people express and create meaning. It's the "Guns don't kill people, people with guns kill people" philosophy, except the non-depressing version with computers and innovation instead of guns and death.
From one perspective, computers are very powerful tools for manipulating information in ways that enable humans to see new concepts and come up with different paradigms for viewing the world. The plots that facilitated the development of chaos theory, prototyping houses in SketchUp, sorting columns in Excel, or Hans Rosling's first Gapminder presentation on TEDtalks are all new worlds of creativity we couldn't have explored before. There's more. The entirety of Eyebeam's R&D lab output. The communications capabilities of the internet; croudsourcinig, open-sourcing. The ability to provide statistical, historical, analytical proof to back up a glimmering hypothesis you came up with in the shower.
They're powerful tools. But tools need to be learned, mastered, understood, and appreciated. There's a craftsmanship behind the black boxes that I feel that many people don't even try to understand.
If computers become the dominant tools we use for gathering information, they will be stagnant and silent (and we won't realize it, trapped inside that box). My lack of fluency in non-English languages restricts my thinking to English structures. My lack of fluency in non-engineering disciplines restricts my thinking to technical structures. (I'm finding this a difficult thing to cope with in my sociology class.)
Eric: I'm of the belief that most technology is like this. I'd say that funding a new computer science program is not very likely to give new insight into major societal problems like environmental injustices or the eradication of slavery.
Mel: But it can help you track and understand, however imperfectly, how you're doing in working towards those goals.