The Trail of Information
Walking on a trail the other day, I recognized a lot of problems with information.
The trail map looks good. It makes sense, but the actual trail is often a bit more ambiguous than the map.
The map is oversimplified and leaves out much detail. The actual trail is more complicated and it may not be as well marked as you would think.
Admittedly, part of the fun of being on the trail is figuring it out as you go. Trying to interpret the limited information available to stay on the right path may produce anxiety, but it is also very satisfying when you get it right.
Personally, I am fascinated by the markings. A painted red dot on a tree here, a small symbol there and sometimes even a sign with a pointed arrow that is hard to follow. I wonder if that was the best way to mark the trail. Did a marker get lost? A lot of information is left up to interpretation.
How much extra would it cost and how much longer would it take to make the trail unambiguous?
And that is the case when the information being presented is clear like a physical trail.
The same can be said of other information that is even less clear. How do you mark information that is potentially ambiguous so that others can navigate it.
A big part of information theory is encoding information in the least amount of space. To the extent that information is clear, that is an awesome strategy. However, this gets more complicated as the information becomes less definitive.
Even something seemingly easy like the address of a building can be ambiguous.
But how much information can you add to make it less ambiguous and for how does that information remain valid. In the physical world physical things change, and that change is not usually synced up with all the areas in the information system. Street names change, or a new numbering scheme is deployed or landmarks disappear. All these pieces are moving.
Throughout time, having out of date data is something humans are used to . But in the age of always-on information systems, it is strange to see how often data is out of date or incorrect.