TITLE: Learning to Learn to Automate Work
AUTHOR: Eugene Wallingford
DATE: August 31, 2011  8:52 PM
DESC: 
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BODY:
Jon Udell recently wrote about
<A HREF="http://blog.jonudell.net/2011/08/25/learning-to-automate-work/">
   the real problem with automating work</A>:
most of us don't know how.  The problem isn't with using
particular tools, which come and go, but with recognizing
the power of information networks and putting data into
a form from which it can be leveraged.

I want to apply his advice more often than I do.  I have
found that for me it is not enough simply to learn the
principles.

The first challenge is fighting an uphill battle against
institutional inertia.  The university provides too much
of its data in dead-tree form, and what data comes to us
in digital form comes unstructured.  Despite a desire to
increase efficiency and decrease costs, a university is
a big, slow organization.  It takes a long time for its
many bureaucracies to re-make themselves.  It also takes
a persistent, pervasive effort to change on the parts of
many people.  Too many administrators and faculty thrive
in a papered society, which makes change even harder.
This is the broad base of people who need to learn Udell's
core principles of information networks.

The second challenge is my own habits.  I may not be of
my students' generation, but I've been in computer
science for a long time, and I think I get the value of
data.  Even still, it's easy -- especially as department
head -- to be sucked into institutional habits.  My
secretary and I are combating this by trying to convert
as much data entering our office as possible into live,
structured data.  In the process, I am trying to teach
her, a non-computer scientist, a bit about the principles
of data and structured representation.  We aren't worrying
yet about networks and pub/sub, simply getting data into
a named, structured form that supports computational
processing.

Yet I need to change some of my own habits, too.  When
under time pressure, it's easy for me to, say, whip up
assignments of graduate assistants to tasks and lab
hours on a legal pad.  Once the assignments are made, I
can communicate a subset of the information in a couple
of e-mail messages.  The result is a lot of information
and not a byte of structured data.  Oh, and a lot of lost
opportunities for using code to check consistency, make
changes, publish the assignments in multiple forms, or
reuse the data in adapted form next semester.

My next big opportunity to practice better what I preach
is scheduling courses for spring semester.  Instead of
using spreadsheets as we have in the past, perhaps I
should open up Dr. Racket and use it to record all the
data we collect and create about the schedule.  Scheme's
reliance on the simple list as its primary data structure
usually puts me in the mindset of grammars and
syntax-driven programming.  Sometimes, the best way to
break a bad old habit is to create a good new one.

So, yes, we need to teach the principles of data networks
in a systematic way to information technologists and
everyone else.  We also need to practice applying them
and look for ways to help individuals and institutions
alike change their habits.
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