[ExI] intelligence and generalization

William Flynn Wallace foozler83 at gmail.com
Mon Jan 14 21:48:03 UTC 2019

To me, the whole point of college was learning how to learn.  I have had
people laugh at me when I could not answer a question.  I told them that I
did not want to make room for such as that in my head.  I can look it up
fast.  But the key is knowing what to do with it when you find it, and the
college courses should prepare you for that.  If a physical therapist does
not remember the name of a muscle, well, big deal - he/she knows what to do
with it if it is out of whack (just what does 'in whack' mean, anyhoo?).
'Get a feel for it' describes the process well.  Some students just don't
'get it' - they can memorize facts, which is a pretty worthless skill.

bill w

On Mon, Jan 14, 2019 at 2:07 PM Adrian Tymes <atymes at gmail.com> wrote:

> On Mon, Jan 14, 2019 at 11:35 AM Adrian Tymes <atymes at gmail.com> wrote:
> > such as learning basics of science
> > and critical thought that could be applied to any scientific field,
> > picking up details of biology/geology/physics/et cetera later on as
> > relevant to specific investigations, or more handwavium - in my work,
> > anyway - practices to study other fields broadly and quickly
> To clarify this bit: what are the components of mastery, and how might
> they be taught or automated?
> "I've seen this before." - database lookup from fragmentary
> information.  (One will most often not have the exact title of a work,
> so the emphasis is on multiple ways to find the information based on
> the limited data one will typically start with.)  Kind of like search
> engines, but learning the field includes learning how to use search
> engines specific to that field.  A database of scientific concepts is
> not the same thing as a database of musical riffs, in the same sense
> that a professor of science is not the same thing as an experienced
> composer of music (although the two could be aspects of the same human
> being).  The database would likely have to generate its own indexes
> (and analyze existing entries as new types of indexes are introduced),
> as humans who enter examples will most likely not think of every
> possible connection when providing an example; this is unlikely to be
> perfect, and learning to compensate for these imperfections (again:
> learning how to use the field's search engines) would be part of
> learning a field.
> "If you want to do this thing, here's what you need to worry about."
> or "Alright, I'm doing this?  Then to do it quickly, efficiently, and
> (a much higher chance of) correctly, I start with X, Y, and Z." -
> broadly applicable requirements planning for a field, augmented with
> details (which can be looked up on the fly) for a specific project.
> (Building a skyscraper is not the same as building a house, but many
> of the processes are similar or near-identical, and the differences
> could be well-documented if an expert construction manager cared to do
> so.)
> Specific motor functions and patterns of thought can be guided with
> appropriate AR software, though one would need to get familiar with
> that class of software (including being able to competently select
> said software).  The class would likely differ by field (formulating
> scientific experiments and composing music differing enough that their
> software would feel different).
> What other elements would be needed, to be said to truly master a
> topic?  (Some would suggest the appearance of confidence, but there
> are non-confident people who do quite well in a field, and there are
> confident but incompetent types.)
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