The Illustrated Guide to a PhD(matt.might.net) |
The Illustrated Guide to a PhD(matt.might.net) |
When you finish a Master's degree, you realize you know nothing.
When you finish a PhD, you realize nobody else knows anything, either.
But it is important to remember what you are doing. In a PhD you should be pushing the boundary of knowledge. As a programmer in a company, you should be solving problems to generate value for your customer and your company.
If you aren't doing these things, you are in the wrong place.
You don't need to get a phd to push the boundaries of knowledge, and often people who get phds aren't actually doing that. PhD is just a fake status indicator like an MBA.
A lot of work that generates real value is also pushing the boundaries of science. Good scientific work often has real world impact.
I noticed you used "programmer" to refer to the person working in a company, but programming is also an essential skill for pushing the boundaries in just about any field now. Many "scientists" are not capable of it and look upon it as grunt work, which says a lot about their true competence.
This is definitely true. But it is important to remember that writing code is a means to an end and not the goal in many PhDs. You do it to get results and to many bears no more importance than measuring chemicals or prepping an animal for examination. In the eyes of professional coders this will lead to poor practices (hard to maintain, little testing, etc.) but up to a certain degree this is fine, IMO, because you don't need production-quality code to get results.
> You don't need to get a phd to push the boundaries of knowledge > A lot of work that generates real value is also pushing the boundaries of computer science.
I agree with both of these. A lot of cool stuff pushing the boundary of knowledge is happening outside of academia. But a lot of cool stuff is also happening within academia.
> Good scientific work often has real world impact. I agree, whether it is within or outside of academia. As I think that this is the goal of academia, I remain with my stance that if you aren't trying to do that you are in the wrong place.
A PhD works as a status indicator is valid in the sense that a Github account with lots of accepted PRs into major OSS is a status indicator: that you have done the work and it has been found by academics in that field / the code maintainers for that OSS to be of high enough quality to be accepted. The work (thesis / PRs) and the credentials of the academics and academic institution / the code maintainer and the OSS project are probably public information that can be verified if there is doubt as to the worth of the credential.
Pick any field. Find some measure of who pushes the boundaries the most in that field. Check after picking the metric, not before, what percent of those making the advances had a PhD, compared to the field overall.
For example, in computer science a the top advances sometimes get a Turing Award. Turing Awards winners need not have a PhD. Most people working in computer science don't have PhDs, yet among Turing Award winners, 59 have one and 13 don't (and most of those have masters degrees).
The same happens in chemistry, physics, biology, engineering, history, geology, psychology, and on and on.
Maybe a PhD is more than a "fake status indicator"? Maybe those most driven to push boundaries very often get a PhD along the way to become more skilled in their field.
Care to present a field and a metric of who has pushed the boundaries the most for which we can asses the impact of PhD and non-PhDs where PhDs are not the most impactful?
That's not what you wrote, though.
And, all else equal, I suspect a PhD is a good indicator of skill.
With no info, hiring for someone to solve math problems, which do you think will be better: math PhD or not math PhD?
Again, please provide some empirical evidence for your claims; not anecdotal feelings.
There's a reason starting salaries for PhDs are much higher than non for almost all positions, and it's not because hiring people are ignorant.
>no substitute for good evidence of ability
It's pretty hard to impossible to get one from a decent school without well above average ability.
>This is why things like basic leetcode interviews are so important, "phds" will often fail these.
Do they fail them more than non-phds? By how much? Again, please provide evidence. I'd suspect non-phds do much worse on average than phds.
I know for a fact PhDs score far higher on Kaggle competitions, for example. PhDs are over-represented in the winners, and if you look into the winners, a lot more without PhDs are PhD students. Go ahead an look there to check for yourself.
Heck, Kaggle even has a data mining degree vs pay dataset, and guess what? Check for yourself https://www.kaggle.com/salmanq/do-phds-earn-more
I'm pretty sure you're running on selection bias, not quantified measurements.
And it's well known that if you are smart and start working out of undergrad instead of getting a phd you usually end up significantly ahead in terms of earnings and on the corporate ladder.
Yet you claim a PhD is not a signal. Weird. I'd have suspected you would have some empirical, not anecdotal or selection bias, evidence that was demonstrable....
>And it's well known that if you are smart and start working out of undergrad instead of getting a phd you usually end up significantly ahead in terms of earnings and on the corporate ladder.
Citation? Also now you're moving the goalposts. It's especially funny since you didn't like that I pointed out how many Turing Awardees had PhDs, to which you complained. Now you see fit to sub-select your original claims. :)
Well known? Then you should be able to provide evidence, since it must be so commonly demonstrated.
I claim it's not well known, because it's not true.
I've worked with lots of PhDs, and lots of non-PhDs, and the PhDs by earn more than the non, including owning the companies.
Also, look over the boards of companies, especially tech, and see again if PhDs are over or under represented. Hint: they're over-represented.
So you are simply incorrect in this. Demonstrably so.
You make a lot of popular claims but have provided no empirical evidence. I at least provided two demonstrable cases where you're wrong.
I noticed I've offered many times for you to provide actual evidence. None so far presented as expected.