Is predictability equals to amelioration?

The suggestion by IXDA forum about basic user interaction design concepts gives us opportunity to make clear an intrinsic paradigm to complexity.

As in, if you can accurately predict what’s going to happen next in a System, it’s because the Action you’re taking is understandable, clear, logical and above all brings ameliorations to the main subject. If you can accurately predict what’s next, It means the System has high ameliorability.
If you can’t accurately predict what’s next, the System has low improvement perspectives.

Thus, Predictability derives from the Actions you’ve chosen to improve on going System and how many data you collected to draw it are relevant choices. However, collecting data and selecting Actions moments are going to be a background where develop tangible solutions, just before and after system visualizing process. Inside both, we might understand some emerging questions.

It’d be a right thesis, in fact according with Ben Fry (2008), the most important part of

“[…] understanding data is identifying the question that you want to answer. Rather than thinking about the data that was collected, think about how it will be used and work backward to what was collected. You collect data because you want to know something about it. I you don’t really know why you’re collecting it, you’re just hoarding it.”

In conclusion, predictability derives from past data still working in the form of governmental statistics, demographical reports, corporation quality manuals, etc. They’re getting us as information as possible to become new topical visualizations to builds ameliorations in order to the society.

So, let’s plan our future.

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