Part II.

My wife was fatally injured in her Ph.D.
program. The OP outlines a lot of just
what happened to her. To have time to try
to help her, for a while I took a slot as
a B-school prof. It didn't work -- lost
her anyway.

I never for even a milli, micro, nano,
pico, femto second wanted to be a prof.
Instead, I wanted to be solving problems
in business, the money making kind.

(5) Non-Academic Career. Then I tried to
get my career going again, outside
academics. Bluntly, that didn't work very
well.

I made a mistake: I should have returned
to DC and gotten back into applied math
and computing for US national security. I
guessed that there would be opportunities
as an employee in business; I was wrong.

Bluntly, my view is that US business and
Ph.D. holders mix less well than oil and
water.

Part of why:

(A) Business is still a lot like Ford in
Henry's day: The manager knows more, and
the subordinate is there to add muscle to
the work of the manager. A manager has no
use for a subordinate who knows much and
resents or feels threatened by such a
person.

Supposedly lawyers have a solution: A
working level lawyer should work only for
a lawyer. Period.

Well, a working level Ph.D. should work
only for another Ph.D., and that criterion
would eliminate nearly all jobs for a
Ph.D. in business.

Not even a CEO wants a Ph.D. around except
maybe tucked away in some side
organization, out of the main work of the
business. E.g., the CEO is plenty sure
that he is the only really important
person in the company and, thus, certainly
doesn't need a Ph.D. or some academic
background he (the CEO) doesn't have!

(B) Business regards Ph.D. holders as blue
sky dreamers out in the ozone who refuse
to contribute to the business, who really
want to publish a lot of papers and get a
prof slot in academics.

(C) If a Ph.D. person does anything
original relevant to anything in business,
usually the business will regard this
person as a threat.

(D) Suppose a Ph.D. takes on a practical
business problem:

(i) If the Ph.D. successfully uses their
advanced knowledge to get a good solution,
e.g., one that makes a lot of money for
the business, then everyone else in the
business, even the CEO and the BoD, will
feel threatened and/or jealous.

(ii) If the Ph.D. fails to get a good
solution, then everyone else will take the
opportunity to denigrate both the person
and the Ph.D. degree -- "I always thought
that a Ph.D. was just a useless, hopeless,
worthless impractical dreamer out in the
ozone, and now we know for sure.".

(6) A Ph.D. in a business research
division. Yes, some businesses, say, ones
with some loose cash, might set up a
research division, hire a Ph.D. as the
director, and hope for something good. If
nothing good happens, well, the company
could afford the wasted money.

Generally, connections about the actual
business between the research division and
the rest of the company are more awkward
than a skunk at a Victorian garden party.
The rest of the company doesn't want to be
bothered, sees various threats, etc.

Here are some of the reasons for such a
research division:

(A) Luster. Use the research division to
impress the public, for good PR, to
impress customers, to cover the rear
exhaust port of both the CEO and the BoD,
etc.

(B) As a patent shop. So, the research
division can develop a patent portfolio,
maybe dozens, hundreds, thousands of
patents. Then some specialized lawyers
can use that patent portfolio as a, call
it, battering ram against any would be
competitors. There can be cross licensing
deals, revenue, etc.

(7) Career direction. It's your career.
In this career, there will necessarily be
some directions you will be pursuing.
Some directions are good; most are not.
It's up to you, and maybe your family,
closest, trusted friends, etc. to pick, at
least try to pick, a good direction(s).

If you just look for a job, get some
offers, and take the best offer, then
likely you will be following the direction
of your employer, especially your
immediate supervisor. That direction was
not picked by you; likely it is not a very
good direction for you or anyone; likely
in that job you will have quite limited
opportunities to change the direction to
be something good for you.

Bluntly, you will want income enough to
provide for food, clothing, shelter,
transportation, medical care, insurance
against risk, recreation, a house you own,
a family, education and other needs for
your kids, and retirement, with some
security, i.e., low risk, and at least a
comfortable life style. That obvious goal
is surprisingly difficult to achieve,
especially if you are working just for a
salary for a manager in a company, small,
medium, or large.

(8) Blunt US Fact of Life. IMHO, nearly
all the people in the US doing well
supporting a family get their money from
owning part or all of a business that
makes the money needed to pay the bills
for that family.

For this, can use some strategy: E.g.,
run the most popular Italian restaurant in
a radius of 50 miles. Then you have:

(A) A strong geographical barrier to
entry, that is, a restaurant more than 50
miles away will be little or no
competition for you. You have a better
"Buffett moat" than any of IBM, Cisco,
Intel, etc.

(B) Your business is unlikely to be killed
off by changes in technology.

(C) We can be sure lots of people will
still want a good Italian restaurant 10,
50, 100 years from now. You have a
business more stable than any of IBM,
Cisco, Microsoft, Facebook, Google, Intel,
etc. Good economy or poor, people will
still want to go for a dinner at an
Italian restaurant -- you are relatively
immune from changes in the economy. You
have a very wide variety of customers,
i.e., are not vulnerable to some one or
few customers going broke, leaving town,
etc.

(D) Your family, spouse, children, can
help in the restaurant and learn the
business and continue running it as you
grow old.

(E) Working as an employee, you can be
fired by a manager who, for whatever
reason, doesn't like you. If you are the
owner, then you can't be fired.

(F) No one can please all the people all
the time, and some managers can never be
pleased. But in a good Italian
restaurant, one unhappy customer
occasionally can usually be mollified by
an apology, a free glass of wine, just
tearing up the check, etc. You DO have to
do good work and please nearly everyone
nearly all the time, but you can't be run
out of business by just one unhappy
customer.

All or nearly all of (A)-(F) apply with no
more than small modifications to a huge
range of Main Street US family
businesses. In your career, you should
aim to do at least that well.

(9) Ph.D. Entrepreneur. Okay, you have a
STEM field Ph.D. and want to own your own
business. If you work hard and smart,
find that your Ph.D. is a great
technological advantage (e.g., you can
stir up powerful, valuable, new secret
sauce), have some good luck, avoid too
much bad luck, get well informed, consider
strategy, ..., etc. then you might do
really well. Your Ph.D. could be a
terrific advantage.

(10) Warning. Generally, if want to use
your Ph.D. to help you be an entrepreneur
in something relatively new, i.e., not an
Italian restaurant, then likely you need
to be darned careful and insightful.

In this sense, I will say:

(A) I believe strongly in the potential of
some original applied math based on some
powerful pure math prerequisites.

(B) I regard current work in artificial
intelligence (AI) and machine learning
(ML) as not very promising. Some people
may yet have good careers there, or
quickly get rich from some stock, invest
the money in an index fund, and
essentially retire, but generally my view
is that the math is not powerful enough to
be very promising and 90+% of what is
being done in those fields now is based on
wild, blue sky dreams with little real
hope and a lot of hype, PR, maybe patent
games, etc.

Why: So far too much of the AI/ML work is
too close to empirical curve fitting.

(i) For small amounts of data, we've been
able to do, and often have done, such
curve fitting going back decades to the
first transistor computers. At one point
in my career, inside GE I did a lot of
consulting for that work. So there was,
and still are, SPSS, SAS, Matlab, R, etc.
I never saw such people in yacht clubs.

(ii) What appears to be new is curve
fitting for large amounts of data. Well,
we don't expect to have a lot of such data
collections and promising corresponding
problems.

For more, I'd guess that self-driving cars
are not very promising: For now, for
current traffic on current roads, driving
occasionally, and too often, needs real
human intelligence. E.g., chimpanzee
intelligence is not enough, and AI/ML are
a long way short of chimpanzee
intelligence. There is a chance for
self-driving cars on roads that have a lot
of new engineering, but that will be very
expensive, IMHO, for a long time, too
expensive. Self driving might work on
some large farms, in a big open pit copper
mine, some military tasks, and some other
situations much less challenging than
Manhattan traffic, I-95, etc.

The general lesson: One of the keys to
success is good initial problem selection.
Most of the problems people have selected
are not good. So, we have to try quite
hard to select a good problem.

Your mileage will likely vary widely.