From the Northeastern Section of the ACS, focusing on career management and development

July 2019
« Jun    
Future Trends in Technical Careers. 2. Meso-facts, interpreting information and Meta-materials
Filed under: Observ. Trends, Alternate Career Paths
Posted by: site admin @ 2:13 pm

The world, as we know it, is not as things were when we
were growing up, before adulthood.  A truism, if there
ever was, yet more than that.  Listened to Ray Kurzweil
interview talking about his latest book ‘How to create a
mind’ where he remarked that we fill our brain with facts
by about age 20.  The facts that we hold in them then
need to be realized for what they are then.  We need to
learn to forget some, because 1-they are no longer needed,
2-they have been subsumed by more recent facts or
3-they are too complex and not easily assimilated.

S. Arbesman speaks about three kinds of facts as: 
  - very slowly changing facts, these are close to what
we determine as “objective truth”.  The search in science
endeavors to get closer to this truth.
  - very fast changing facts that are descriptions of the
moment and will usually fall within a range but depending
on a number of factors change.
  - MESO-FACTS that shift slowly and are part of the
technological world in which we live.  They change more
slowly than the fast-changing facts and we notice them
and sometimes have trouble dealing with them, as they
represent a certain notion of our understanding of the
world.  Arbesman does a nice job of describing these
three patterns, which Kuraweil observes is what the
human brain does well.

In the world of Mesofacts there are interesting concepts
Arbesman points out: 
  long tail of discovery -  new discoveries are not as startling
in an established field as a newly emerging one.
  medium ties in social networks bear larger responsibility
for distributing mesofacts
  rule of hidden knowledge - non-experts collaborating
have a better chance of producing solutions to hard problems
than experts.
  careful analysis of data needs to use various predictor
tools and indeces like p-value (statistical power– especially
p<0.05), sample size, error range, conflicts of interest,
causation vs. correlations (need confirmation), and precision
of the question.  (See Wired Oct. 2012, p. 114)

So often innocent analyses of comparison data leads to
misleading conclusions as Cari Tuna pointed out in
an article about Simpson’s paradox on comparing average
of different items.  Her example of two baseball batting
averages brought it out clearly.  The article comments are
superb, as well.  Also see 2  . 

Science is continually opening new opportunities to
develop technologies to extend our human capabilities.
Photonics spectra highlighted innovations where
meta-materials created from layers of natural elements
and molecules have incredible properties that can
bend light backwards in some directions (negative
refraction).  Silver and germanium layers produce
photonic integrated circuits.  That same issue also
described spintronic circuits for quantum computing
using light.

So new opportunities are emerging on the horizon
that require us to adapt to new ways of thinking about
problems and how to solve them.  As we see proposals
offered we need to constantly apply critical thinking
skills and take the extra effort to confirm experimental
with replicate experiments.

Leave a Reply