(T)he iPad (and its little brothers, the iPhone and iPod touch) abstract much of the computer away. Apple watcher and former Spark guest John Gruber says it’s a bit like the automatic transmission in a car:
Used to be that to drive a car, you, the driver, needed to operate a clutch pedal and gear shifter and manually change gears for the transmission as you accelerated and decelerated. Then came the automatic transmission. With an automatic, the transmission is entirely abstracted away. The clutch is gone. To go faster, you just press harder on the gas pedal.
That’s where Apple is taking computing. A car with an automatic transmission still shifts gears; the driver just doesn’t need to know about it. A computer running iPhone OS still has a hierarchical file system; the user just never sees it.
And from the standpoint of the vast majority of computer users, this abstraction can be a good thing. It makes computing simpler, easier, friendlier. Why should I need to understand what’s going on under the hood of my computer if all I want to do is send email to my friends?...
But I wonder, is the same attitude towards computers dangerous? Does oversimplifying technology –removing necessary complexity — have a downside? By making technology simple, easy, and convenient, do we risk a generation of people who can’t tell the difference between this blog post and the Facebook login page?
As I ponder this, I’m a bit torn. The technology populist in me wants to say, “Of course, make computers easy! What’s wrong with making computers as simple and friendly as possible?”
But another (geekier, snobbier) part of me wants to say, “Yes, computers are hard, and that can be a good thing. I don’t want to use technology designed for the lowest common denominator.”
The question this Spark show hopes to tackle is this:
If I don’t understand how to use my computer, whose fault is it? Is it my fault for not wanting to read manuals or spend time learning a new technology? Or is it the fault of the designers and engineers who build the technology we use?
You can weigh in on the discussion at the Spark blog, then listen in live or or download the podcast of the show; information on broadcast times and podcast download is available here.
Here's my take on this issue, which I've also posted as a comment on the Spark blog:
This is a thorny issue, because easier interfaces help to drop the barriers to participation, but on the other hand this shift means we give up some degree of empowerment to make decisions about which sorts of interfaces, and by extension which sorts of technologies, work best for our specific needs. Indeed, the crafting and marketing of products like the iPad is deeply, deeply political, and the embedded politics that lead to the tools we use is not readily evident to those without a degree of computational literacy. And enormous swaths of the computer-using public are lacking in this area.
On the other hand, computational literacy is very much like other forms of literacy: reading, writing, mathematical literacy, and so on. We don't blame the math-illiterate learner who has never been exposed to mathematics education, or whose math education was lacking in significant ways. This is the exact case with computational literacy education: It's nearly nonexistent in formal classrooms, and has become the nearly exclusive domain of those with the luxury of access to computational technologies outside of school. In some ways, then, perhaps we get the technologies we deserve.