Terry Jones

I’m often surprised at how confident people are about their knowledge of the world. Looking at the history of thought and of science, you quickly see that it’s strewn with discredited and totally incorrect theories about almost everything. So I don’t understand why it’s not more commonplace to look at history and to arrive immediately at the most likely conclusion: that we too have almost everything wrong.

I don’t mean that literally everything we think is completely wrong. Some things are certainly partly right, or even mainly or fully right. But to have a high degree of confidence, or to assume we’re right just because we know so much more about the world than our ancestors did, or simply because we think we’re right, is just inviting ridicule. Considering our record, and our continual attendant misguided arrogance and confidence along the way, you’d be nuts to think that we know much today or that our confidence adds any weight at all. Many thousands of years of history argue strongly against that conclusion.

Thinking that almost everything is probably wrong in some important fundamental way is a useful default. That attitude stands you in good stead for digging into things, for reconsidering them, for asking questions at a low level. In mathematics when you know for sure that something is wrong (or right) it helps enormously in proving it. It’s a psychological thing. In my dissertation I proved a statistical result that I knew must be true from running simulations. It took me a week or two to nail the proof, and I would never have gotten there if I hadn’t known in advance that the equality I was trying to prove analytically was certainly true (pp 201-207 here in case you’re interested).

As an example of something that I think will be overturned, I think we’ll come to regard our decades of designing computational systems according to the Von Neumann Architecture as extremely primitive. Maybe that will involve some form of analog or quantum computation. I think we’ll take more and more from nature, for instance in solving optimization problems.

On a less grandiose note but still important, I think we’ll look back on our current information architecture and also see it as being extremely primitive. Or, as I’ve said before, we’re living in the shadow of information architecture decisions that were made decades ago. I think that’s all hopelessly wrong. In the real world, information processing simply doesn’t look much like a hierarchical file system.

Hence Fluidinfo.

And so ends another semi-cryptic and ultimately unsatisfying post. I do, as always, plan to eventually say more. And I will.

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