
What You Need to Know Before Considering a PhD - hardmaru
http://www.fast.ai/2018/08/27/grad-school/
======
GlenTheMachine
I have a PhD in aerospace engineering.

I loved grad school. Loved loved loved it. I wouldn't give up the worst day I
had in grad school for almost anything. And I love having the skills it taught
me. I am a much better engineer and researcher than I could possibly have been
had I taken almost any other route. I was given freedom in grad school that
just would not have been present in most industry jobs. I was given a hardware
project - a submersible robot - that I was completely in charge of on day 1. I
had to teach myself machining, how to do electrical and electonicd works, how
to do embedded programming, how to tune a PID loop. How to work with other
students. How to give a persuasive presentation. How to come uo with my own
ideas, how to convince other people that they were worth pursuing, how to
quickly become an expert in a topic.

That being said, I am not under any illusions about the financial loss I
experienced. I spent ten years making a pauper's wage, when if I had chosen to
go into industry I would have been a software engineer... in the Valley... in
1993.

I also was in a remarkable lab in grad school. It made top-ten lists of
“coolest college lab”. And that wasn't hype. The caliber of student and of
professor was off the charts. And they were not only smart, the vast majority
of them were good people. A lot of places aren't like that. And as the srticle
correctly said: a toxic graduate school environment is worse than most toxic
work environments. In any practical sense, students don't have HR protections.
If you can't get your advisor to write you a recommendation, getting into a
different program is nearly impossible. You can be worked 100 hours a week.
You can be blackballed for getting sick, for taking vacations, for taking
maternity or paternity leave (even if it is - and it almost certainly will be
- unpaid).

The key is to find an advisor who is doing good work and who is sane and
moral. If you can find that you're golden. If you can't you may be completely
screwed.

~~~
majos
As a current PhD student in CS -- seconded. I'm fortunate to have a great
advisor, and my research career so far has been largely fun and productive as
a result. I have also seen equally (or more) talented and hard-working
students have worse experiences because of worse advisors. It's just hard to
become a good researcher without good mentorship.

As far as practical advice for finding good advisors, track records of
previous students can be a helpful first filter once you've made a list of
people who wrote papers you like. Probably the most helpful thing is talking
to current students at the admitted students day and listening to them. Bad
advisors usually have at least one notable case, and there will probably be at
least one person who'll take you aside and tell you about it. Listen to them
carefully. Even great advisors can have at least one unsuccessful and bitter
student through no fault of their own...but they usually don't show up to the
admitted student events unless there's a real cause for animus.

~~~
pyedpiper
recently minted Chemistry PhD here -- Thirded.

Grad school was one of my best decisions. I went to a great school that was
what I call the Goldilocks size, big enough to have a great faculty,
equipment, and decent funding but small enough so that collaboration was the
norm and the crazy horror stories of maniacal hours and/or cutthroat
competition were normally self induced. My PI was an incredibly good guy and
still a close friend. I met my business partner and co-founder while working
with him the lab and we're now building a company that expands on the work we
did in grad school.

That being said, I saw plenty of people not having the experience I did. This
was almost always because i) they didn't really like research and didn't know
it until they were there or ii) they picked a PI (PI = professor/boss) that
was a really bad match for their work style and personality. Finding a lab &
PI that matches your personal expectations about the PhD I would say is more
important than the research focus. Don't choose something you'll hate learning
about but ultimately the PhD can be more about learning how to teach yourself
than the skills you learn during research.

YMMV

~~~
wink
What would interest me much more is if y'all liked studying or university life
before that? Because for me.. I originally started to study CS because I
wanted to learn stuff (was already working as a programmer) and hadn't ruled
out pursuing a PhD afterwards per se. But the longer I was at university
(German Diploma, 13 semesters for me, 9 minimum) the more I couldn't wait to
leave - so even the thought of staying there went away quite quickly, although
I wasn't "in academia" per se. I'm still not sure if I'm just more on the
practical and pragmatic side of problem-solving and less in research.

~~~
GlenTheMachine
I didn’t mind being an undergrad. But that was largely because of my friends
and being an adult away from home for the first time. My friends and I built
robots in our dorm room with our own money because the university didn’t have
a program and wasn’t willing to accommodate us in any way. I enjoyed learning
in class but it was always so rushed and stressful - you were always working
up to an exam, then making it past and preparing for the next one. There was
never any time to breathe.

Grad school was far, far better. Completely different league.

------
sytelus
This is quite an unfortunate article. Author goes on to list several folks who
don’t have PhD but have “made it” and asserts that many people can do
fascinating and cutting-edge work without PhDs. There are always outliers in
stuff like this but ask yourself: How many people you know who don’t have PhD
and have freedom to explore at work full time what truely interests them?
Author has rather twisted view of the selection bias.

People should do PhD if they are genuinely interested in doing scientific
research. If you are doing PhD under pressure or in hope of getting better
paying jobs you will be dissopointed. It is an arduous process and taking up
your precious years but it gives you opportunity to have freedom to explore
and work on your interests for rest of your life. You won’t be coming to
office everyday doing assigned task on your backlog and reporting your status
in scrum meeting. Instead you will be reading about new creative work that was
literally published yesterday, mulling over that in lunch with colleagues and
apply your original ideas to actually get published under your name. The
downside could be lower pay and/or no stock bonuses for many outside of hot
areas like AI. But in general, you have much better chance of doing cutting
edge work that you are truely passionate about if you have PhD in that area.

~~~
icelancer
> How many people you know who don’t have PhD and have freedom to explore at
> work full time what truely interests them? Author has rather twisted view of
> the selection bias.

I don't have a degree and I have that. Also I know a lot of people with a PhD
who do not have anything remotely resembling freedom.

The author might be biased but it's good to hear it from that side once in
awhile, rather than be deluged with "you can't do science without a PhD" and
similar sentiments (I work parallel to academia and get plenty of shit from
their ivory towerism, hence my comment).

~~~
edanm
> The author might be biased but it's good to hear it from that side once in
> awhile,

In what way is the author "biased" exactly? She did this course, was in both a
PHD and tech, and tells people why she thinks it's worth considering not
getting a PHD, listing various (valid IMO) reasons.

Where does bias come in exactly?

~~~
icelancer
It's selection bias at the very least.

------
peterlk
I was once told by a professor who I respected very much how he gives advice
to prospective PhDs. When someone asks "should I get my PhD?" the answer is
always "no". Because the only people who will enjoy grad school are the ones
who will do it anyways.

I have found this to be good advice for people who are thinking of starting
companies too.

~~~
SamTheDev
I didn't get the logic behind this advice ! if they would enjoy it, shouldn't
the advice be to do it ?

~~~
oarfish
If they know they'll enjoy it, they'll do it and not ask for validation
before.

------
ibuildthings
First principles of doing a PhD and taking up an industrial jobs are quite
different, which this article sidesteps. I am talking from the perspective of
someone who did a PhD, postdoc and migrated to be a founder/CEO.

A PhD system trains you to think about unsolved problems in an given domain
deeply with a larger time runway. The end goal is not a tangible product that
reaches millions of people, but rather a set of ideas that can take a crack at
the unsolved problems in your field in a novel way. A good work should inspire
others in the field, and eventually a larger audience to pick them up and
expand and build on top of it. To give a small example, a majority of the
fundamentals of machine learning was charted out by many, many PhD works over
the last 40 years. Implementing a linear classifier is 2 lines of code in
2018, but many Bothans died to bring us this information :-) .

The goals of industry are more immediate. Expect for a privileged few research
labs in industry, your work is expected to be monetized, and rightly so. The
goal is for you, if you run the business, else your management team to first
figure out a problem of high relevance and monetary value. Build
products/solutions for that problem, that can be used by someone who is less
versed/ambivalent of your technical solutions. Efficacy of solving that
particular problem often defines the merit of your contribution.

The fundamental of choosing the PhD or industry should be taking stock of what
kind of contribution you want to make as an individual. If it is a few set of
ideas to science, which on a later date might become something fundamental in
our understanding of the world, then PhD is a good path. If it is a set of
contributions towards a product/solution that eases the pain of many users
then go into the industry first.

------
jedberg
This is total anecdata, but out of my closest college friends, five of them
went to get a PhD, while I went to industry. When they graduated, I was
already making more than of all of them, with five years of industry
experience. And I made more them them for the next thirteen years too. I never
hit any magical ceiling where a PhD was necessary.

In other words, don't do a PhD if you're in it for the money.

It _may_ open a few more interview doors for you, but honestly, at least in my
experience, I wasn't even aware of which of my coworkers had PhDs. When I
eventually found out, they were all just slightly older than me working at the
same pay grade.

~~~
GuiA
I was in a PhD program, I dropped out. I have been working in R&D at a large
company for a while now; many of my best colleagues have PhDs, many others do
not. As far as my personal experience is concerned, a PhD has no bearing
whatsoever on your capacity to do solid research.

That said, I am seriously considering going back on the PhD route, because I
think I’d like to spend more time teaching down the line. Kind of silly, but I
have only a master’s and it seems like most higher ed institutions do not
consider hiring you as a professor unless you have the magical piece of paper.

~~~
sytelus
> PhD has no bearing whatsoever on your capacity to do solid research

In my experience this is not true except unless you are super genius. Most
folks without PhD often keeps making same naive mistakes, for example, not
studying previous state of the art, not recording experiments properly,
heuristics instead of rigorous analysis and so on. PhD trains to avoid all
these. It allows you to build network, identity great researchers in the field
as role models and understand what scientific scrutiny entails. It is not
unusual to identify paper written by someone not experienced vs someone
experienced. For example, a person without PhD would often neglect to mention
scale in the graphs, compute variances in findings, describe figures properly
and so on. These might look minor cosmetic things but it often goes long way
in overall rigor.

~~~
gaius
_not studying previous state of the art, not recording experiments properly,
heuristics instead of rigorous analysis and so on_

??? They taught all of us that in undergrad.

 _a person without PhD would often neglect to mention scale in the graphs_

... and they taught us about the scale of a graph in secondary school ...

------
variational123
This is a rather narrow perspective focused on (and giving examples from) one
subfield (deep learning) at one point of time (year 2018). Have factors like
(i) commoditization of software + hardware, (ii) the limited mathematics
required, (iii) many open problems, and (iv) a lot of industry funding made a
PhD unnecessary for doing research in deep learning in year 2018?: Yes. But
does this mean that a PhD (with several advanced courses and a few years of
struggle solving hard research problems) won't be useful for doing Computer
Science research for the next 30 years? The answer is probably "No". If you
want a long-term, intellectually satisfying research career, whether in
academia or industry, a PhD is extremely useful.

~~~
yiyus
Also, this field is quite easy to get into without any external support. You
can become an expert in deep learning with a laptop and an internet
connection. Most research fields will require a well equipped lab. You can
usually find good labs in industry, but you won't have the same freedom to
play with all those toys as you will have when pursuing a PhD.

------
MikeTaylor
There is only one good reason to do a Ph.D, and that is because you really
really want to invest 10,000 hours of your life into researching a topic that
you love deeply for itself. I have a Ph.D in vertebrate palaeontology, which I
got because I loved the work; I know a lot of other palaeo Ph.Ds who did the
same. But in my experience, everyone who attempts a Ph.D for any other reason
-- for prestige, to improve job prospects, whatever -- either craps out of the
course (best case) or endures a miserable five years (or often much longer).

Bottom line: do a Ph.D if and only if you want to do the work. Don't do one in
order to get the qualification. Focus on the journey, not the destination.

------
bane
Something that I've found deeply troubling with the PhD education and training
and how it interfaces in industry, having worked with a very large number of
PhDs over the years, is the seeming inability for PhD-level staff to simply
edit their work and ship things on time.

I know this is a large generalization, but I could comfortably say this is a
predominant trait among maybe 70-80% of the folks I've worked with. On the
surface it seems like there's something in the training for PhD staff that
seems to kill the ability to self-regulate that's a very good thing when
pursuing the unknown, but an excruciating pattern to deal with in industry
where budgets and shipping times are primary importance.

Seeing this in action, and knowing I have no interest in working in academia,
has been the primary reason I haven't pursued one myself. I don't want to be
"broken" by training.

I get to pursue all of the R&D I can handle already working in an R&D lab --
with the usual publication, patent, ship to customers that it all entails. So
I'm not starving for interesting things to pursue.

------
azhenley
Don't do a PhD for the money (although it is more than adequate in STEM
fields).

Do a PhD for the jobs that it unlocks (professor or researcher, mostly) or the
type of freedom that it provides (it was 6 years of mostly unstructured time
that I got to explore things that interested me while being paid). If all else
fails, you can still go join a big tech company and make more than enough
money to live a good life.

I'm a professor now and love it! Couldn't have happened without a PhD first.

~~~
dopeboy
I'm envious of that. I went through a master's program and I sorely miss that
unstructured time to research and genuinely explore a topic. All of the
learning I do these days is by force of business. I'm OK with that but it
would be cool to get back to learning sometimes.

Could you talk about what life is like as a professor? I looked at your
research interests and they lean heavily on the applicable-to-industry side -
is that by purpose?

BTW - I think it's so cool that a professor is posting on HN. I think back to
my professors and I couldn't imagine anyone of them being nearly as hip.

~~~
azhenley
Thanks for the kind words! My research interests are definitely on the applied
side on purpose. Some of the major criticism of research is that it is too
theoretical or doesn't help people, so I wanted to do the opposite. I study
actual engineers and the problems they face while working. This was actually
my interest long before grad school. I wanted to make tools, plugins, and
languages that were easier for me to use. Being very applied has worked out
well for me so far since many people can relate to what I do!

I am a new professor but I can give you a short summary of what it is like. It
is very unstructured. No one tells me how to spend my time, but I have to
balance many different things: teaching a course, working on multiple research
projects, writing multiple papers, writing grant proposals, reviewing papers
for journals/conferences, traveling to conferences, recruiting and working
with student researchers, etc. Some people like to describe it like running a
startup.

~~~
dopeboy
As someone in startup life, that sounds exactly right.

------
nicodjimenez
A PhD is a license to do deep research. Deep research careers are very rare,
but for the right kind of person, they're great. However, deep research by
definition means it probably won't work, and there's just a lot more money in
doing things that will probably work vs things that probably won't. So it
helps to be extremely talented at deep research if you want to pursue the PhD.

Also, most engineering PhD's are bogus because most engineering "research" is
actually not deep research - it's building prototypes that aren't quite useful
but not quite that novel or interesting either. If you're in a PhD program and
you're not doing something really interesting and fundamental, you're
definitely in a tough spot.

~~~
tha12
What do you consider to be deep research? I agree that engineering research is
not actually deep, but once you eliminate that almost all of the current
(applied, and maybe theoretical too) Machine Learning work for instance is
also dismissed.

~~~
nl
I don't have a PhD, but I have run research programs.

The deeper into a field you get the more you realize that the parts which seem
deep research aren't, and the parts which seem incremental improvements are
actually very deep.

I can think of a number of things in machine learning which appear hard which
are easy, and vice versa.

Theoretical justification for GAN improvements (eg, the WGAN paper): elegant
but obvious, even though I'm not a mathematician.

Generative models for text including entities that remain coherent for longer
than a sentence? We barely know how to even start thinking about this problem.

------
account2
I have several questions regarding this:

1) Do FAANG companies hire non-PhDs for machine learning positions? Most seem
to require a MS or PhD

2) What are the interview questions like at FAANG companies for machine
learning positions? Is the interview different if you don't have a PhD?

3) For non-PhDs applying, what are the math requirements for the job?

4) For people that have a PhD working in ML at a FAANG, do you feel like you
use your PhD level skills day-to-day?

~~~
sdrothrock
I'd like to know a variation on this:

> 4) For people that have a PhD working in ML at a FAANG, do you feel like you
> use your PhD level skills day-to-day?

5) For people who work with a mix of PhDs and non-PhDs in the same field, do
you notice a difference in output quality?

~~~
david-gpu
5) No, but I am obviously biased due to not having a PhD. I doubt you are
going to get an unbiased answer from anybody; everybody wants to believe they
made the right choice.

~~~
sdrothrock
> I doubt you are going to get an unbiased answer from anybody; everybody
> wants to believe they made the right choice.

I'm not sure where choices come in here. I specifically mentioned a mixed
team; the choices have already been made, so the performance of the existing
team is what I'm asking about.

As far as not getting an unbiased answer, that's why I'm asking HN at large --
hopefully there are enough people in enough environments to give an
interesting and informative combination of answers. :)

------
asafira
I often get asked about what my views on doing a PhD are (I am more-or-less
finished with one now), and one of the ways I frame it is the following:

You know how you've take a course before where the professor was just
surprisingly _awful_ at teaching? These professors are often some of the most
knowledgeable people in a subfield of the subject you are taking, yet their
teaching ability is severely lacking and you have to scramble to learn the
material some other way (or just never learn it).

During a PhD, there is a decent chance that your adviser is similarly a bad
manager. Unfortunately, having a bad manager for 5-7 years of your life can be
a fairly awful experience. You will work with someone who you, on the one
hand, look up to, but on the other hand, who seems to not care at all about
your mental health, your possible career desires outside of academia, your
work/life balance, or the exact reason why this week was a rough week for
research in your (human) life.

I have a lot of other thoughts on the matter, but I thought I'd try to keep
this post more concise =).

~~~
Al-Khwarizmi
_not care at all about your mental health, your possible career desires
outside of academia, your work /life balance, or the exact reason why this
week was a rough week for research in your (human) life._

I wouldn't call that being a bad manager, but rather being an asshole.

As a professor, I often think that one of my biggest weaknesses is indeed
management skills. After all, we suddenly find ourselves having to manage
people without any training in the matter, and when our true call is typically
science, not management.

But at least I'm not an asshole.

------
apo
_I grossly underestimated how much I could learn by working in industry. I
believed the falsehood that the best way to always keep learning is to stay in
academia, and I didn’t have a good grasp on the opportunity costs of doing a
PhD. My undergraduate experience had been magical, and I had always both
excelled at and enjoyed being in school. The idea of getting paid to be in
school sounded like a sweet deal!_

Wholeheartedly agree. Aspiring PhDs discount what industry can teach them. The
problem is compounded by undergrads who have zero industry experience when
they graduate.

~~~
thebooktocome
It'd help if industry didn't treat undergrads as though their labor were
worthless.

~~~
apo
That's a pretty broad brush to be painting with. What were the specifics of
your situation?

~~~
thebooktocome
My situation is I'm in this conversation with a random online persona who
thinks that aspiring PhDs are ignorant of industry.

------
fulafel
Mind the survivorship bias when reading all the comments from grad students
and PhD's here. Drop outs are much less likely to open this comment section or
post a comment.

------
Scea91
It is even worse in Europe where you are often required to have Master's
degree before you can even start a PhD.

People in my country usually start PhD. at 25 and take at least 6 years to
finish, because the universities use them as cheap workforce and aren't
incentivised to allow students graduate quickly.

~~~
AlunAlun
This used to be the situation in Europe but it got out of hand, as a result
all new PhDs in Europe must be advertised as three year programs, and
completed in four at a maximum.

~~~
collyw
I have worked in a few academic institutes (and still know many friends in the
same places). 5 years seems to be the norm, with some people taking up to 7.

~~~
Al-Khwarizmi
I didn't know this was a Europe-wide rule, but as a professor in Spain I can
attest that the 3 years + 1 year extension rule is now enforced and met. If
your time elapses and you haven't completed your thesis, you're out.

~~~
collyw
I am in Spain. Maybe it has changed but a few years back it was the norm. The
institute I worked for had a 5 year rule and you got kicked out (if you were
doing research), but a few people managed to get extensions around that.

~~~
Al-Khwarizmi
It has changed, I think around 3 or 4 years ago.

------
fnrslvr
If your FAANG research team employs just as many PhDs as non-PhDs, and we
accept that there are a couple of orders of magnitude more non-PhDs in
software engineering than CS PhDs looking for work in industry, then I don't
rate my chances of getting recognized within the company for my robust
knowledge of theory of computation and abstract algebra later down the road if
I take that grad job I was offered by a tech giant. Also, it's not all that
likely that a job as an engineer is going to keep me my theory knowledge or
research skills fresh.

The article makes a few resonant points, but overall I think the "you can get
into research if you jump straight into industry" pitch it tries to make is
very weak. As someone who very much wants to do research (mostly hard-to-
monetize research about comparing exotic models of computation to one another,
but I'll listen to a pitch for applied research too), I'd very much like to
see someone lay out a highly plausible roadmap for getting into a research
position without a PhD. I don't think this article is that.

------
sparso
I was a PhD student in the UK, it was always something I wanted to do and even
had a publication during my undergraduate degree. I ultimately didn't complete
my PhD for two reasons. Firstly my supervisors were scarcely available and
neither focussed on my PhD subject, it was a bit of a side interest for them
both. As I look back at it now I should have possibly seen the warning signs
earlier. Secondly various delays on the project (including 6 months for a
piece of hardware to be repaired under warranty by the manufacturer) meant
that I had to find a job before I was able to complete the PhD. I did gather
enough data to complete my PhD in my spare time, but once in full time work it
was very hard to stay motivated to complete it in the evenings.

So having an incomplete PhD, would I do it again? Probably. I would be a bit
more cautious about the topic and ensure my supervisor(s) were focussed on the
area before beginning. With hindsight I would be more aware of the risks
associated with external sources (hardware) that could delay the project for
whatever reason. What I did learn though was the ability to manage my own time
and collate information from various data sources in order to back up my side
of a discussion. The ability to manage my own time I think is something that
separates me now from my peers who did not do a PhD, but I do find when
applying for jobs that I lack the necessary years of commercial experiences
for roles where the hiring manager does not understand the nature of working
on a PhD. So whilst it was definitely a great learning experience, I think it
has set back my career slightly.

Do I regret doing a PhD? Absolutely not. Sure it was stressful and frustrating
dealing with problems out of your control. But I learnt alot about myself and
how to manage my own time, as well as how to stay motivated when presented
with problems that are outside of your control.

------
throwawayaug28
Am I the only one that finds it questionable to write this kind of "career
advice", when the author clearly has a conflict of interest?

The author is running a business whose main purpose is to sell educational
content marketed towards people that want to learn Machine Learning (and
claiming you don't need a PhD to do it).

I only have a good impression of fast.ai, but perhaps the author is not in the
best position to give career advice on this topic? The author didn't even do a
PhD in ML/CS, but in mathematics which arguably less applied/practical.

~~~
elmozyz
There is an obvious conflict of interest but it doesnt make his views invalid.
Several other PhDs have said pretty much the same thing. Frankly, I dont see
much more utility for working in industry beyond a Masters. You really should
have the skills to learn anything else by the time you complete a thesis.

------
somberi
I am considering doing a Phd in a completely unrelated area when I turn 50 (45
now).

Is there anyone in this thread done a phd that late? Obviously my motivation
is different now to study - to really learn the subject. I am financially self
sufficient and will continue to be, and hence making a living out of my phd is
not a consideration.

Edit: I would like to be able to study in a university setup (not distance
education). Main reason is to soak in all the related conversations /
workshops and also I like being in a young environment.

~~~
otoburb
>> _I am financially self sufficient and will continue to be, and hence making
a living out of my phd is not a consideration._

I'm curious about this scenario from the advisor or departmental perspective:
If a PhD candidate is financially self-sufficient, does this mean that a
potential advisor has one less mouth to feed when competing for grants? How
does the power dynamic change between advisor and financially independent PhD
candidate? What if the PhD candidate is capable of funding a whole (or good
portion) of a lab themselves - is there a conflict of interest somewhere there
between donor vs. principal investigator vs. PhD-candidate roles? Do
financially independent PhD candidates have more, less, or no competitive
advantage during the selection and admissions process for an R1 institution?

So many questions...

------
dannykwells
A little disappointed with the one-sided point of view here - the author
states

"...I deeply admire everyone I’ve listed, and I am not arguing that a PhD is
never useful or never works out well" but never really gives examples of
skills that PhDs do provide.

And there are absolutely career paths where a PhD is not required, but since
many of the practitioners have one, can often be selected for (data science,
biotech, biostats, lots of engineering research etc.) So without a PhD you
might have a harder time rising as far as you would like in one of these
positions (again being realistic that it's not all about talent, it can often
be politics/perceived competence, which a PhD can augment).

It's just important to be honest about both pros and cons when writing advice
articles like this.

~~~
azhenley
Sadly, there is a weekly post on HN that hates on PhDs and grad school. I have
tried my best to comment on each one and try to give a different perspective:

In CS you can earn over 50k a year with your stipend plus summer internship,
you have a lot of unstructured time to explore your interests, and there are a
lot of tenure-track positions without doing a postdoc.

------
bitxbit
I am sure I am in the minority here but I believe there are way too many
people getting PhDs just to get a job. I am not blaming the
candidates/graduates because that's what the job market requires these days
but there is something seriously wrong with that picture. It takes a lot of
public capital and goodwill to support PhD programs and in many aspects PhDs
have become glorified professional degrees. I also see a lot of half-baked
thesis that would not have passed muster two decades ago but advisors are more
interested in building his/her brand within public and private domains.

------
arunmp
The Author is unfortunately right about the academic PhD program today, but
mixes up two different things. A PhD is meant to teach you about what I call
the "body of human knowledge" and to initiate you into it. Period. It does not
matter if you can make a learning out of it, nor it helps you earn loads of
money. All those hours of reviewing done by the DC members, journal reviewers
etc. are done without the expectation of a single penny. It is done to place
the PhD research in context among the world of human knowledge. Once you have
done a PhD, you are supposed to get more confident dealing with unknown
problems in general. Granted, other pressures like career, money and sometimes
mere survival! take precedence after PhD but those are beyond the scope of
your PhD.

Of course, you can work on cutting edge problems without a PhD but probably do
it better with PhD. A PhD teaches a lot of intangible things like being
comfortable with unknown problems , working patiently towards an end goal, get
over the fear of failure etc. One thing it does not teach is how to earn money
:).

In this context I would like to highlight unique cases where you do an
"Industrial PhD" where you are working in a company and chose a relevant
problem for a PhD. These have the "best of both worlds" and one is not bogged
down with typical pressures in a regular PhD like those pointed by the author.
That said, the final word is that a PhD is merely a conduit. Its more of what
you chose to do with it than what it is , which matters at the end.

------
SimplyUnknown
The focus I dislike most about this article is that a PhD is considered a
means to an end. The author compares that opportunity (financial, mental,
physical) is lost that is somehow to be compensated by having a PhD as opposed
to people that don't have one (big surprise, it isn't).

Also, the metric of success seems to be here how much you earn and how many
startups you have founded. If these are your success metrics then don't ever
even consider doing a PhD or moving out of Silicon Valley.

There is of course value in the critique that PhD programs can be oppressive
with a toxic culture and depression. One has to consider how big this risk is
within your program and if one is willing to take it. Thinking you can tackle
these issues within your department is beyond naive.

With regards to learning new stuff and finding and scoping interesting
problems of your own: People don't seem to realize that it is _your_ PhD
program. _You_ are in the lead of the direction your research is taking* .
Advisors are there to _advise_ you and not the other way around. If you are
just following orders when doing a PhD you are doing it wrong.

To conclude my tangent rambling, if you are going to do a PhD do it for the
right reasons. Money, fame, titles and number of startups founded are IMHO not
valid reasons to consider doing a PhD. If you _are_ doing a PhD you can shape
your research the way you want and be advised by your advisors, not the other
way around.

* Terms and conditions may apply. You are still (usually) working of course within a grant to solve one huge problem, but the way you solve it is mostly up to you.

------
the_rock_says
I'm in a similar boat thinking about getting a PhD in AI/ML. I have a masters
degree and in 2 years of my current job (research based) have already
published 2 conference papers one of which I'm a lead author. My work
colleagues who aren't research oriented suggested me to get a PhD instead
because of the effort I put in reading papers and spending hours on solving a
problem. It makes sense to me at times because not many people in my company
have a hardcore ML background and when I'm stuck reading a paper or solving a
ML problem, it's difficult to find someone to discuss it with. I end up
spending most time in figuring it out or eventually giving it up. This when I
miss academia the most. I'm on H1B visa and have money constraints so giving
up a 6 figure salary and living on stipend is something freaks me out.

I'd really appreciate if anyone reading this comment have something to
suggest. Thanks a lot HN community, you've been a great support.

~~~
Scea91
Is it possible for you to align PhD. and your current job?

I am in a similar position as you. My PhD. topic is focused on the same
research area as my job in tech company so I can do both together.

If it is not possible I would advise not pursuing PhD. and continue self-
learning. The opportunity cost of PhD. is not worth it in my opinion.

~~~
the_rock_says
Hey, thanks for your advice. I'm not sure if I can do that as my company's
focus is completely different to an ML research required for a PhD.

------
giardini
The first graph (titled "THIS IS YOUR EDUCATION, THIS IS YOUR SALARY") in the
following article will disabuse one of the misdirected desire to get a PhD:

"Career Guide for Engineers and Computer Scientists" by Philip Greenspun

[http://philip.greenspun.com/careers/](http://philip.greenspun.com/careers/)

------
YeGoblynQueenne
>> I think for many top students (my former self included), getting a PhD
feels like a “safe” option: it’s a well-defined path to doing something
considered prestigious.

A _safe_ option?

A (funded!) PhD is an opportunity to focus on a subject you are really
interested in, that you probably can't work on outside of academia and spend a
lot of time, three to four years, free of all other responsibilities but
producing a short book at the end describing your work.

It is the only three years in your life you can spend directing your own
research, choosing your own goals and creating new knowledge with nothing but
the power in your little hands and your little brain. "Safe"? There is nothing
scarier than staring at the darkness of a new path to knowledge, stumbling
around in the unknown trying to find your way where neither google, nor Stack
Overflow have gone before and there's noone to hold your hand while you make
it up as you go along.

A PhD is an opportunity to become a world-class expert in your field. Not
because you get an empty title at the end, but because _if you do it right_
there should be literally no-one else on this sweet earth who knows more than
you do about your chosen subject (well, except perhaps than your annoying
thesis advisor who's always been there and done that and can nip your best
ideas in the bud with but a couple of words. But I digress).

A PhD should be a time for your mind to open wide, like a blooming flower,
like the hippies of old thought LSD would do to them. It should be a time to
become a strong man or woman of knowledge, to drag yourself over and above the
mean and look at the stars and say "oh, sweet lord, I get it! I G E T I T !!".

Well of course if you try to take the safe path you'll be bored out of your
head and disappointed. What do you expect? "Safe"? "Prestigious"? It's not
public office, man! It's a PhD! Focus on the knowledge! That's what it's all
about.

Yes, of course you'll learn a ton if you stay in industry, too. But, in
industry, it's always someone else who chooses what you need to know. In a
PhD, it's your game. A PhD is knowledge, coupled with freedom.

------
andreyk
As I posted in response to the author on Twitter - while generally agreeable,
it would be nice if the post had a disclaimer that this is "What (bad stuff
about doing PhDs) You Need to Know Before Considering a PhD". There are plenty
of positives that one also needs to know when considering a PhD this article
does not list... see the ensuing discussion here
[https://twitter.com/andrey_kurenkov/status/10342151109678407...](https://twitter.com/andrey_kurenkov/status/1034215110967840768)

------
jccalhoun
I have a phd in a Communication-realted field. I like my job at a community
college but I am over-educated for it. However, I burned out on trying to get
published. My advice is if you have doubt about going to grad school then
don't. There are tons of people competing for every job. There is no guarantee
you will get a job and there are fewer and fewer tenure track jobs. I was
lucky to get out of adjuncting hell and I was lucky that I don't have a spouse
or kids so I could afford to live on 24k for a few years.

~~~
azhenley
If you don't have doubts about ANY major life choice, then you are the
exception.

My experience has been great. Straight out of grad school I got several
tenure-track offers from R1 universities. I'm not a super star and graduated
from an unranked department.

------
bobmarley1
I wonder how this applies to Part Time PhDs. They are exceedingly rare in the
US and it usually comes down to having a very supportive Job and an unusually
open minded Advisor, I've seen people at UNC and Duke doing part time CS PhDs.
It also seems much more common in the UK/EU. I know Oxford, ICL and others
offer part time programs.

Seems to have all the upside and none of the downside, you keep your industry
pay, continue racking up experience and after a few more years than normal get
a PhD to hang on your wall.

------
michaericalribo
This gets it right, I think. And I say that as someone who does not regret
taking five years to get a PhD.

A PhD is too long, narrow, and frustrating to do just to get a slightly fatter
paycheck.

For some reason, that deep dive clicked with me, and I’m grateful for all the
personal growth that came from that. But for the vast majority of people, I
think it could easily end as an exercise in frustration.

~~~
chrisseaton
Five years is a super long PhD. If you can get it done in two or three years
it makes more sense.

~~~
rntz
In computer science in the US, this is just false. Four years is the usual
"officially expected" length of a PhD straight out of a bachelors' (which is
the most common way to do a PhD in CS in the US). In practice it usually takes
longer, sometimes much longer (seven+ years is not unheard of).

In the UK and Europe, shorter PhDs are much more common, in part because
you're expected to do a master's before a PhD.

Even for two or three years, I don't think getting a computer science PhD is a
good bet if your primary goal is making more money.

~~~
azhenley
6.5 years is the average length in the US according to the NSF.

I tell students to expect 5-6 depending on whether you want to go to industry
or academia.

------
lbriner
This raises the significant issue again that colleges are attempting to do two
things, in most cases they only do one of them well: Academia and Industry
readiness.

At my university, I learned very little in my degree that was noticeably
useful in industry but then academia is not supposed to be about industry,
usually, but about increasing knowledge that may or may not have an
application.

In the college I attended before university, I learned an enormous amount of
information useful for Industry but it didn't give me much of a leg-up for the
work I was about to do at university.

Most industry work I have seen is not massively academic and does not require
academic qualifications. In certain jobs, however, they make a point of
requiring qualifications when they could probably run some tests instead to
demonstrate that you understand the basics of comp-sci or whatever else.

------
phyzome
I'm glad the article mentions how abusive grad programs can be. That doesn't
get a lot of airtime.

------
sandwall
PhD in Nuclear Engineering (Medical Physics) -- I wouldn't trade my years of
study (play) for anything. I was blessed with a wonderful committee chair (and
great committee members! beware! choose wisely, these people can make or break
you!) who allowed his students time and space to reach _Intellectual Maturity_
-- This is when a student should graduate, not after x publications or after y
objectives.

A Doctor of Philosophy should be an individual capable of critical thinking,
developing their own experimental process, and helping others do the same.
Unfortunately, many professors are just running a race chasing publications
and grants while their students are employees, not apprentices in the art and
practice of science.

------
harveywi
My personal grave warning to doughy-eyed youngsters wishing to get a PhD:

[https://news.ycombinator.com/item?id=8720640](https://news.ycombinator.com/item?id=8720640)

------
mendeza
I don't see how this article addresses the person's question that if you want
to work in machine learning, should you do a PhD? From my experience,
companies want a few years(3+) of software engineering experience and a
graduate degree of some sort, whether a masters or PhD. From my experience
after getting a masters, Ive gone through the hassle of interviewing and be
turned down bec they are looking for more experienced people for ML Eng and I
only had 1 year of professional eng experience.

------
pimmen
I have a colleague who is an ML PhD student part time and works as an engineer
part time, but his research (NLP with a focus on text classification) aligns
well with his job such that the company supports him writing on his thesis and
going on conferences on company time. He's doing a presentation in two weeks
about a paper he's written, on company time.

I have no idea how have managed to swing that, and if this arrangement will
last for long. He's only been employed here for about a year.

------
jokoon
There is a big difference between a degree and an education. To me, a degree
is worthless, it is just a piece of paperwork. It's difficult to view things
differently.

A solution would be to have a letter of recommendation and appreciation from a
school.

As long as you are pursuing any education, you should either get the degree
automatically, or just get some certificate that you went in some school.

It should be up to schools to select their students, merit in education
doesn't seem to work, as it doesn't anywhere anyway.

------
kalal
To me, this is whether you have good people around or not. PhD usually comes
with good advisers who help you think in different ways than you have done
before. However, such good advisers can be also at a company + you work on
practical an modern problems (usually). For that you don't need PhD. In any
case, once you ask whether you should do PhD or not it feels like you don't
want to be left out. In that case, just do it.

------
pbhat
PhD in Computational Biology here. Currently in industry and loving it.

Love the experiences shared here. I see a lot of them are centred around pay
(PhD vs. non-PhD). I think it is important to remind ourselves that seeing
earnings as a race against others and against time rules us out from doing
anything interesting in life.

------
logifail
I think it's completely and utterly wrong that one person (the advisor) should
ever have such absolute power over another (the student).

Just as the OP describes, if the advisor is great, it's fantastic. If they
aren't, you are in a world of pain.

I don't regret choosing to do a PhD, but I deeply regret choosing my advisor.

------
pvaldes
Your PhD will cost you the life of your firstborn:

[http://www.johnskylar.com/post/107416685924/a-career-in-
scie...](http://www.johnskylar.com/post/107416685924/a-career-in-science-will-
cost-you-your-firstborn)

Postdocs definitely deserve be paid (and treated) better.

------
emersion
When I asked one of my professors about doing a PhD he told me: "Doing a PhD
is like getting married: choose your advisor wisely". It seems that good
advisors are a key factor of a successful PhD.

------
keeptrying
Having seen what a PhD did to the mental health of a lot of my friends, I
would heavily advice people considering one to figure out how they’ll mentally
cope.

Have a plan and resources commited to how you’ll deal with the depression.
This means actually building out a support network and asking them if they’d
be available to talk during such a situation.

Not easy but yeah weigh the cognitive costs!

------
graycat
Part I.

I'll try to give an answer and a response more generally to the material in
the OP.

Background. I got a BS in pure math with nearly a second major in physics and
worked in computing and applied math for problems in US national security
around DC. Jobs were very easy to get; at one time my annual salary was 6
times what a new high end Camaro cost; much of the work was challenging for
both the computing and the applied math; I was learning a lot of both
computing, e.g., algorithms in Knuth, and applied math on the job and also
especially math in independent study on evenings and weekends. Soon I got a
call from a college friend to join FedEx. I used my background in computing,
with a little applied math, to write some software, in six weeks, to schedule
the fleet. The results pleased the BoD, enabled crucial funding, and saved the
company. Later the BoD wanted some revenue projections. I formulated and
solved

y'(t) = k y(t) (b - y(t))

for time t, revenue y(t) at time t, rate of growth y'(t) = d/dt y(t) at time
t, and full revenue potential b. The BoD was pleased, and ..., to make a long
story short, I saved the company again.

Then I got a Ph.D. in applied math from the engineering school of a famous,
high end research university.

Now I'm doing an Internet startup, a Web site, basically a new and very
different search engine -- for the, IMHO, very large part of search handled at
best poorly by the existing Web sites and well known techniques.

For the startup, my applied math background is crucial: The crucial, enabling
core of the startup is some original applied math I derived based on some
advanced pure math prerequisites I got both in grad school and in independent
study. I already knew enough computing except had to learn how to bring up a
Web site that has been easy for the user interface but due to the core math
somewhat tricky on the server side. I learned Microsoft's Visual Basic .NET
(for the programming language -- I like it), ADO.NET (for the Web pages), and
ASP.NET for the (relatively meager) use of SQL Server. The main difficulty was
working through 5000+ Web pages of documentation. The first code is the first
production code, 100,000 lines of typing, 24,000 programming language
statements, and lots of documentation. The code seems to run as intended, but
I need to add some data.

Some lessons:

(1) Math. IMHO, the key to powerful, valuable, new applications of computing
is applied math. That is, if we accept that the big opportunity is to exploit
and apply current computing, then we might notice that whatever we code to put
out data users will like, as information, entertainment, whatever, is
necessarily mathematically something, understood or not, powerful and valuable
or not. So, in some sense, from 100,000 feet up, it should help to proceed
mathematically, with possibly advanced prerequisites, some new results focused
on the application in mind, and complete with theorems and proofs. Just IMHO.
But I don't know anyone with a yacht over 100' long that did that; I suspect
that very few people agree with me. Maybe what I am saying is a hopeless wild
goose chase or a great green field opportunity -- you judge.

(2) Getting a Ph.D. In a nutshell, the three most important parts of getting a
Ph.D., in no particular order, are research, research, and research. Yes,
there can be courses, credits, grades, teaching assistant positions, weekly
research seminars, qualifying exams, etc., but at a research university what
can "cut through", dominate, and _trump_ all or nearly all of that is
research. The research should be publishable in a good peer-reviewed journal
of original research; if there is any question, then send it in.

The criterion for a Ph.D. dissertation may be something like "An original
contribution to knowledge worthy of publication." \-- so, in case of some
doubt, publish the thing.

The usual criteria for publication are that the work be (i) new, (ii) correct,
and (iii) significant.

Now for a non-standard observation and recommendation: Go for applied math in
an engineering school. Start with a real problem, hopefully a significant real
problem, likely from outside academics, hopefully identified before or early
in the Ph.D. program. Do some new math to get the first good or a much better
solution to the real problem. So, the math is "new" \-- got (i)! Since the
work is math, with theorems and proofs, it's easy enough to check for
"correct" \-- got (ii)! Since have the first good or much better solution for
the real problem which is hopefully significant, get "significant" \-- got
(iii). Note: The math may not, just as stand alone pure math, be seen as
significant -- so, likely have not proved the Riemann hypothesis, shown that P
= NP, etc. But compared with a lot of pure math, are already ahead by one
_point_ \-- have one real world application!

In my case, I started with a problem I had identified in industry before grad
school. I found an intuitive and rough solution on an airplane ride. In my
first year in grad school, one course I took let me make solid math out of my
intuitive solution; I did that independently in my first summer, walked out of
the library with an 80 page manuscript that had all the actual research for my
dissertation.

Then I encountered some of the nasty nonsense as in the OP: There was a prof
who didn't like me. He thought of rows, columns, and layers, lines, stay
within the lines, rules, etc. and resented that I'd basically written my
dissertation independently within 12 months of arriving on campus and before
taking the qualifying exams.

Well, a course had a question but no answer. I did a good enough literature
search and saw that likely there was no answer known -- since it was a very
narrow question, it was easy to do the literature search. I got a _reading
course_ approved to _address_ the question and write a paper, maybe just
expository and maybe without a solution. Just before getting the reading
course approved, in a few evenings I found a rough solution. So, got the
course approved -- shook hands with the prof. Then I cleaned up my first
solution, mostly sitting beside my wife on our bed while she watched TV and I
worked on the problem, and found a much better solution and a general result
that was surprising, even shocking, and settled some related questions. That
took two weeks into the reading course. I submitted my manuscript of about 20
pages, and I was done with the reading course. Fast course. The course also
had three credits and gave me the last credits I needed for an MS. News of my
work spread through the department; my favorite prof walked up to me in the
hall, "I heard about your result. It also says that ....". Yup, clearly it
did.

The result was clearly publishable; later I did publish it -- no problem,
accepted right away.

The biggie, practical result was that suddenly I had a halo and a coat of
Kevlar armor against any criticism; any of the faculty would have loved to
have done what I did. To defend against the abuse as in the OP, I recommend --
do some publishable RESEARCH.

(3) Handling Ph.D. Qualifying Exams. At least at one time, the Web page of the
math department at Princeton stated, IIRC (if I remember correctly):

"Students are expected to prepare for the qualifying exams on their own.
Graduate courses are introductions to research by experts in their fields. No
courses are given for preparation for the qualifying exams."

In part, the qualifying exams are like a foot race, but in this race you can
get a head start and be 1 foot from the finish line when the starting gun goes
off.

I consider that Princeton policy to be somewhat wise. So, prepare for the
qualifying exams on your own (to be able to do this in math, a good ugrad pure
math major should be sufficient to let you know how to study and learn, make
good progress, and not get stuck or lost). To do this preparation, get the
best, focused information you can on what will be asked. So, get recommended
texts, copies of old exams, maybe chat with some profs and some students who
have taken, hopefully passed, the exams, syllabi of any relevant courses,
etc., maybe all before applying to the Ph.D. program. Then study. Use some
judgment on how deep to cut and how many proofs to memorize -- cut deep enough
but not so deep you take too long or just quit.

Then show up as a first year Ph.D. student, do well in some courses, do well
on the qualifying exams, complete your research, listen to _Pomp and
Circumstance_ , get your degree, and LEAVE.

(4) Academic Career. If you want an academic career, then maybe don't leave
the grad program so soon. Instead, publish some papers, get some _streams_ of
promising research going, meet people at research seminars and conferences,
get known by the Editors in Chief of the journals or conferences where you
publish, if invited to give a talk at a conference, do so, do the usual meet
and greet and publicity, build your own professional network, etc., hopefully
some of your profs will help you get some job interviews, etc. Learn how the
academic games are played -- there are some really important academic games,
and you very much should learn how they are played. Then you will be in an
academic career.

One possible prof slot is in a B-school. Consider that. Someone with a good
applied math background has a heck of an advantage in a B-school. Papers that
make progress on practical problems are commonly considered good research in
B-schools. People who want to hire consultants tend to regard B-school profs
as more _practical_ , i.e., motivated by money, than more _pure_ profs.

~~~
graycat
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.

~~~
ddnb
TLDR: Not every boss appreciates an employee with a Ph.D. If you want to go
your own way, start your own business, otherwise you are expected to follow
the lead of your boss.

~~~
graycat
To be more clear and blunt, if your boss gets fired or leaves or if the whole
group is fired, you can be on the street, with an advanced education and some
recent, specialized experience (that likely didn't make big bucks for all
concerned), and 40+ and with a tough time ever again holding a job relevant to
your education, experience, interests, capabilities, or potential -- EVER.

My guess is that there are a lot of Ph.D. electronics engineers over 40 who
are essentially unemployable at anything close to their past who want an
electrician's license so they can install AC wiring in houses.

Maybe the best job they can get is to be a clerk in the electronics department
at Wal-Mart.

Imagine, two guys just out of high school. They both mowed lawns as teenagers.
Joe wants to continue that as a business, at first still living at home. Tom
goes to college, continues, gets an electronics Ph.D., and gets a job in an
electronics company.

Then they are both 35: Joe now has five lawn and garden crews, each with a
late model, crew cab truck, a $5000 trailer with 4 riding mowers each worth
$15,000. He has clients in upper class residential areas and small to medium
commercial lots. He does weeding, soil testing, fertilizer applications,
mowing, edging, shrubbery trimming, landscaping, etc. Tom's employer has a
policy: By age 35, promoted into management or fired. Tom gets fired.

Joe is now much better off than Tom. Tom would do well to look for a job with
Joe and rise to managing one of the crews, planning and marketing for higher
end parts of the business, etc.

This is not a joke. Besides, it's not funny.

