Can we jumpstart new tech usage?

It’s a well-known phenomena that new technologies get used in the same ways as old technologies until their new capabilities emerge.  And this is understandable, if a little disappointing.  The question is, can we do better?  I’d certainly like to believe so!  And a conversation on twitter led me to try to make the case.

So, to start with, you have to understand the concept of affordances, at least at a simple level.  The notion is that objects in the world support certain action owing to the innate characteristics of the object (flat horizontal surfaces support placing things on them, levers afford pushing and pulling, etc).  Similarly, interface objects can imply their capabilities (buttons for clicking, sliders for sliding). They can be conveyed by visual similarity to familiar real-world objects, or be completely new (e.g. a cursor).

One of the important concepts is whether the affordance is ‘hidden’ or not.  So, for instance, on iOS you can have meaningful differences between one, two, three, and even four-fingered swipes.  Unless someone tells you about it, however, or you discover it randomly (unlikely), you’re not likely to know it.  And there’re now so many that they’re hard to remember.  There are many deep arguments about affordances, and they’re likely important but they can seem like ‘angels dancing on the head of a pin’ arguments, so I’ll leave it at this.

The point here being that technologies have affordances.  So, for example, email allows you to transmit text communications asynchronously to a set group of recipients.  And the question is, can we anticipate and leverage the properties and skip (or minimize) the stumbling beginnings.

Let me use an example. Remember the Virtual Worlds bubble?  Around 2003, immersive learning environments were emerging (one of my former bosses went to work for a company). And around 2006-2009 they were quite the coming thing, and there was a lot of excitement that they were going to be the solution.  Everyone would be using them to conduct business, and folks would work from desktops connecting to everyone else.  Let me ask: where are they now?

The Gartner Hype Cycle talks about the ‘Peak of Inflated Expectations’ and then the ‘Trough of Disillusionment’, followed by the ‘Slope of Enlightenment’ until you reach the ‘Plateau of Productivity’ (such  vibrant language!).  And what I want to suggest is that the slope up is where we realize the real meaningful affordances that the technology provides.

So I tried to  document  the affordances and figure out what the core capabilities were.  It seemed that Virtual Worlds really supported two main points: being inherently 3D and being social.  Which are important components, no argument. On the other hand, they had two types of overhead, the cognitive load of learning them, and the technological load of supporting them. Which means that their natural niche would be where 3D would be inherently valuable (e.g. spatial models or settings, such as refineries where you wanted track flows), and where social would also be critical (e.g. mentoring).  Otherwise there were lower-cost ways to do either one alone.

Thus, my prediction would be that those would be the types of applications that’d be seen after the bubble burst and we’d traversed the trough.  And, as far as I know, I got it right.  Similarly, with mobile, I tried to find the core opportunities.  And this led to the models in the Designing mLearning book.

Of course, there’s a catch.  I note that my understanding of the capabilities of tablets has evolved, for instance. Heck, if I could accurately predict all the capabilities and uses of a technology, I would be running venture capital.  That said, I think that I can, and more importantly,  we can, make a good initial stab.  Sure, we’ll miss some things (I’m not sure I could’ve predicted the boon that Twitter has become), but I think we can do better than we have.  That’s my claim, and I’m sticking to it (until proved wrong, at least ;).