The FOTA EduBeardStroke Parabola 2013

Most predictions are wrong. The small number that turn out to be right are largely luck, but we tend to remember them because they reinforce our naive belief that the future can be predicted.

Apophenia, they call it. The predilection of people to perceive patterns in meaningless noise.

Politics, ideology, is the battle for the narrative. The imposition of a pattern on the noise of life. I’ve talked about it in the past as a branch of storytelling – on reflection I might have been wrong. In storytelling there is a pattern, in politics only the ghostly perception of a pattern.

With enough events, enough data points, you can back up any narrative concerning the immediate past. The rise of “big data” makes this more, rather than less, of a problem. I have found myself, when confronted by a position ostensibly backed by a mass of data (be it university funding or climate change), to treat it the same as an unreferenced opinion. Given all the possible narratives you could construct with that data, why have you chosen this one?

People who play with big datasets (and increasingly, people who don’t) like to imagine the emergence of unassailable truth within them. A misunderstanding of the scientific method means that the idea of data as backing up a theory until either more data or a better theory comes along and changes everything has been lost.

So it would be unfair to dismiss something like the Gartner Technology Hype Cycle as being wrong because of an absence of hard data. It is wrong for far more interesting reasons than that.

(1) it presents the graph as an external, “natural”, process – seperate from human intervention. The cycle (and accompanying guidance) is sold as an investment aid. You “understand” the hype cycle, you don’t “use” it. It’s a map of the future. A future which cannot be changed.

(2) It reinforces our greatest secular myth – that “it will all turn out right in the end”. Technologies, no matter their idiocy, will eventually sail up onto the plateau of productivity. The difficulties – why, that’s just the trough of disillusionment. Soon the world will somehow see the light (without intervention, mind you) and the slope of enlightenment will be scaled. Our own experience tells us this is not true, but so desperate are we for it to be true we believe it anyway.

(3) It’s NOT A BLOODY CYCLE. there’s no iteration. there’s no improvements to old technology. Everything is a technology trigger – not an adaption based on findings out there in the real world.

So the hype cycle is just a model of an idealised closed system. It neatly illustrates the danger of too much data – so many technologies have been hyped, trashed, re-evaluated and used that we assume that they all must do.

Now I’m loath to do this, because I know the graphic will be used out of context and people will ask about the datapoints and complain even though I will tell you how it was prepared, but I present the FOTA EdubBeardStroke Parabola 2013:

[Methodology: This diagram was prepared by taking one person who thinks too much about learning technology, leaving them on a train for a stupid amount of time and then marinating in beer and nachos]

So, in terms of a prediction of what might happen this year it probably works as well as anything else I might do – it’s got most of the right things in most of the right places, it’s arguable enough to get clicks and comments and it slags off Clay Shirkey. Typical cynical blogging really.

If you want something more real – technology (and technology aided learning processes) only work when fun. As soon as they get boring, codified, standardised they stop working. They become a part of the “grind” of education that they initially promised to free us from. They stop being interesting – they stop being chosen and start being imposed.

Most technology is awful, it doesn’t work and it causes us endless pain trying to make it work. People will get renumerative careers in helping us to get within touching distance of the initial promise. Eventually they will write books and articles, run conferences and workshops, and the problem will be filed as completed.

It won’t be. We will never, never solve education with technology. It won’t work. We will solve education with education, and we will solve education with a way of educating that is closer to collaborative play than anything we currently do. Technology might help us start to understand education a bit better. That’s it.

(trouble is, I suspect we’ll need to solve capitalism before we get there… and I suspect that technology is only going to be a distraction there as well)