New is old news (day 50)

Have we always been obsessed with the new?  Before there were stores, what was new?  Before there were peer reviewed journals, what was new?  Before there were internet rankings, what was new?  Before patents?  It seems that new is relative but we use the word as if it's absolute.  For me, new has been a sore spot for many years because it often drives a wedge between creativity and responsibility.  I see it in my students too.  If what you are passionate about is not new in the absolute sense, where do you go from there?  To graduate you need something original but yet you need to go through some well trodden steps before coming close to new.  I often tell the story of being stuck during my doctoral research and my supervisor telling me that if everything seems grey, go toward the thing that is a a little less grey.   If you lose the thread of interest, you have to take little steps out.   It's important that personal interest remains a priority and is honoured as unique in the individual.    In fact, the relationship between unique and new is perhaps worth a second look.   In reality, journals and patents are rewarding something in between unique and new.   Same with degrees.   In digital media the new has been especially problematic because technology changes so quickly.   If an artist is using old technology, are they behind or somehow not worthy of being called a digital media artist?  Clearly not, but often there is an impulse to use the latest even as the old has not been explored to its fullest.  I think it's better to view the available tech as mere ingredients.  My winning recipe will not be the same as my neighbour's even if our ingredients are the same.  The unique fusion of ingredients is what should be celebrated.  In computing science, we also talk about the difference between the model and the view.   The model is the underlying structure of the data and processes.  The view is how we choose to represent the model to the senses.   Two data artists with the same dataset (model) will not produce the same visualization (view).   Is it new to re-represent a data set?  I would argue that it is.

Our relationship to new is based on immediate needs and interest.  Something may linger for decades before being dug up as new, interesting, and useful.  Traditionally we've trusted our gatekeepers to tell us what is new but I'm seeing a trend where the crowd is perfectly able to suss that out for itself.   And what's neat about that is that the definition of new is implicit and much more fluid.  My students still need to defend their thesis but the real feedback on the work happens in the frenzy of the crowd.

A song for this post.