The Image of the World We See
The tools we use to record the present are abstract representations, symbols, if you like, of things that exist which we then understand conceptually to be what they are. Writing enables me to sign an email with "David" which the person receiving it understand it's from me: a person, who has some interests, lives in a particular space and time on planet Earth and has some expertise on specific subjects. CH4 is the chemical formula for methane, a flammable gas that is found as a byproduct of certain biochemical processes and which has the potential to damage the environment through its interaction with chemical elements in the biosphere.
A name and a chemical formula are classifiers, they stand for an entire collection of other names and other chemical formulas which themselves represent an ontology which can be further structured into sexes, ethnicities, nationalities (for names) and inert, volatile and reactive (for gases).
The point is that neither methane nor "David" would be subject to that kind of analysis had it not been for chemistry and handwriting. Similarly, photography, represents an abstraction. We photograph people and things but we also photograph moments and capture memories. We encode on paper (and now in digital) a collection of entities, frozen in time and space that signify something greater than what they are because of what they represent.
The value of such analysis in the age of Big Data and Machine Learning is that we can crunch through masses of data sets to find overlapping points and points of differentiation which show just how the means we use to communicate changes how we communicate by slightly altering our perception of things.
Just like now I did not need to start this post with the 19th century journalistic staple of "Dear reader," we also, when photographing or being photographed no longer have to guess at the context of the photograph we are taking part in or how it will be consumed or what it is intended to do.
This affects everything from the postures we adopt when being photographed to our willingness to smile (that was heavily promoted by Kodak as the way to capture "happy memories"). Check out this machine learning algorithm used in a study that went through a century of school yearbook photos, and this revealed. Dive in: http://goo.gl/XP7EZt
and .... happy Wednesday!