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Considering being an employee such
as in the OP, I have two reactions: (1) Take statistics, machine learning,
neural nets,
artificial intelligence (AI), big data,
Python, R, SPSS, SAS, SQL Server,
Hadoop,
etc., set them aside, and ask
the organization looking to hire:
"What is the real world problem
or collection of problems you want
solved or progress on?" Or, look at the desired ends, not
just the means. (2) Does the hiring organization
really know what they want done
that is at all doable with
current technical tools or only modest
extensions of them? Or, since artificial intelligence
is such a broad field, really, so
far of mostly unanswered research
questions, and the list of topics
I mentioned is still more broad,
I question if many organizations
know in useful terms just what
those topics would do for their
organization. So, for anyone with a lot of technical
knowledge in, say, the AI, etc.,
topics, it is important for them
to be able
to evaluate the career opportunity.
I.e., is there a real career
opportunity there, say, one
good to put
on a resume and worth
moving across country,
buying a house, supporting
a family, getting kids through
college, meeting unusual
expenses, e.g., special schooling
for an ADHD child,
providing for retirement,
making technical and financial
progress in the career, etc.? So, some concerns: (A) If an
organization is to pay the big
bucks for very long, e.g., for
longer than some fashion fad,
then they will likely need some
valuable results on their real
problems for their real bottom
line. So, to evaluate the
opportunity, should hear about the
real problems and not just
a list of technical topics. (B) For the opportunity for the
big bucks to be
realistic, really should know
where the money is coming from
and why. That is, to evaluate
the opportunity, need to know more
about the money aspects than
a $10/hour fast food guy. (C) As just an employee,
can get replaced, laid off,
fired, etc. So, to evaluate
the opportunity, need to
evaluate how stable the job
will be, and for that need
to know about the real business
and not just a list of technical
topics. (D) For success in projects,
problem selection and description
and tool selection are part of
what is crucial. Is the hiring
organization really able to do
such work for AI, etc. topics? Or, mostly organizations are still
stuck in the model of a factory
100+ years ago where the
supervisor knew more and the
subordinate was there to add
muscle to the work of the
supervisor. But in the case of
AI, etc., what supervisors
really know more or much
of anything; what hiring managers
know enough to do good problem
and tool selection? Or, if the supervisors don't
know much about the technical
topics, then usually the subordinate
is in a very bad career position.
This is an old problem: One of the
more effective solutions is some
high, well respected professionalism.
E.g., generally a working lawyer
is supposed to report only to a lawyer,
not a generalist manager. Or
there might be professional licensing,
peer review, legal liability, etc.
Or, being just an AI technical expert
working for a generalist business
manager promises in a year or
so to smell like week old dead fish. (E) If some of the AI, etc.,
topics do have a lot of business
value, then maybe someone with
such expertise really should be
a founder of a company, harvest
most of the value, and not be
an employee. So, what are the
real problems to be solved.
That is, is there a startup
opportunity there? Really, my take is that the
OP is, net, talking about
a short term fad
in some topics long
surrounded with a lot of
hype. Not good, not a
good direction for a career. AI and hype? Just why might
someone see a connection there? |