Let Traits Accrete
How can it be that complex, dynamic objects can be described by short and simple strings and words? We often seek:1
Selectivity – Our images are often falsely clear. We may think of an object’s “personality” in terms of that which we can easily describe. We may set aside the rest for now as though it simply weren’t there.
Style – To avoid making decisions we consider unimportant for now, we may develop policies that become systematic traits.
Predictability – It’s hard to maintain fruitful exchange without trust, so we may try to conform to expectations. To the extent we frame our images of producer/consumer systems in terms of traits, we teach our data to behave in accordance with those same traits.
Self-Reliance – Imagined traits can, over time, make themselves actual because we must be able to predict outcomes of the use of our own data. This prediction becomes easier the more we simplify our models.
We need to be able to trust our own data, logic, and presentation resources. One way to accomplish this is to think of these resources in terms of traits, and then proceed to train those dynamic resources to behave according to those immediate images.
Still, like a personality is merely the surface of a person, a schema is merely the surface of a dynamic digital object. What we call traits, properties, etc. are only the regularities we manage to perceive and deem worthy of systematizing at present.
We may not be able to “pin down” the traits of our digital resources because there are many processes and policies that don’t yet show themselves directly in elicited behavior but that work behind the scenes and that may only become important to name and systematize later.