Friday, April 30, 2010

Why Predications Fail.

You can't talk about the future of Tertiary education without making predictions. If you are not prepared to put your neck on the block and say what you think is going to happen, it's a pointless exercise. Predicting puts you in harm way - almost all forecasts about the future are wrong.
Before I make too many predictions, It's worth reviewing why predictions fail.
1. Failure to account for economics as a key driver, rather than technology. 
Flying cars are a great example here. People think because a thing can be done, it will. We don't go to work in flying cars because they are impossible - they're not. They're just to expensive, and it's cheaper to go by road.

2. Failure to consider human factors and rates of change. 
A thing can be done a better way, but you have to wait for the old ones who do it the old way to die off first. This is especially important in Universities, where the great old ones live long.The paperless office comes to mind as an example. I've worked in one, it was great. There weren't any old people there who liked to print things off and scribble on them.

3. Predicting out of area of expertise
People who are experts in one field assume expertise in others. Artists imagining space travel is a nice example. There are nice paintings, but I'm not flying in that, thanks. A lot of people fail on technology driven predictions here, often the devil is in the details. Another reason we don't have many paperless offices is that until recently, the screens just weren't good enough, and the software tools for easy annotation weren't either. Generalists sweeping past miss those kinds of details.
4. Failure to account for changes out of area of expertise
This is really the converse of the above reason. There is a tendency to assume that changes you know about will dominate, and changes you do not know about are unimportant. For comparison, consider Ray Kurzwiel Singularity work - focused on technology with George Friedman's 'The Next 100 years' book - focused on geopolitics. Both are fine pieces of work by experts in their field, well argued and, like all predictions, probably wrong. Both focus heavily on developments in the authors own area of expertise, and miss, or err, on key topics outside the field.
5. Wishful thinking. 
Confusing 'We Can' 'We Should' and 'We aught" with what will probably occur. A prediction is not a wish, or a hope, it is a cold, rational analysis of what is likely to occur, whether we like it or not.
6. Predicting the Weather, not the Climate
When people think of predicting, they think of predicting earthquakes, or the stock market, or the weather. You can't predict these in any detail. They are essentially random noise in a pattern. You can predict where earthquakes are likely, that stock markets will exist and be useful, and that there will be weather. Very specific predications often fail not (just) because they are more specific bets on a random future, but because they are attempting to predict things on too fine a scale. Big trends have a mass, an inertia to them that is often the elephant in the room, too big to see. How the big trends collide and play out is important, but as humans we get lost in the human scale details. It's said no one predicted the First World War (and yet, every general staff in Europe had a plan for it for decades). It's true we couldn't predict the details of it, but history tells us that Great Power wars happen a lot, and technology and economics could tell us they would get bigger, and meaner. In the big scale of things, who fought, who won and who lost, the "Battles and Kings" school of history, don't matter so much. What was important to predict was that there would be battles and kings.

Number 5, Wishful thinking, is about the only one I'm confident of avoiding. Point 2 (rates of change) and point 6 (scale of prediction) are always going to be tricky, and the others all rely on having the right spread and depth of expertise - knowing enough about enough things to get the big picture right but not miss sneaky details.

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