Austin's salary is public data, and I have a really good sample of what people like him make in industry.

Try 5x. Before RSU appreciation.

Maybe 3x. But 3x would imply a VERY chill industry position. "Name your interest space and we'll let you work on that" type of gig. Probably way more chill than academia.

> The freedom and unstructured time to explore fuzzy problems is unmatched.

Industry also provides this. Actually, I find much more freedom in industry than in academia. And, if we're honest, my industry position is probably at least as secure as a faculty position at a public university in a red state.

> I don't know any other job that gives you 6-figure salary and lets you basically do whatever you want for 42% of the year.

In industry research, you can't do whatever you want. But you can usually do what you want.

In fact, the caveat of "prove your worth" is a huge tell. In industry, you REALLY CAN do what you want! Real freedom; just be useful. In academia you have "freedom". By which we mean "raise money".

But even if not... look at it like this: an industry position that pays 5x allows you to work for a year and then take the next 4 off. 2/5 is bigger than 1/5. And that is time you can actually take off. To do whatever. Not "off" in the "better be writing grant proposals!" sense. Actually off.

> Is a 2x salary increase worth giving up that kind of time?

Probably not. But if you can land an R1 CS position in SE, you should be making closer to 5x.

But... perhaps this is because after you've made $industry_money for 10 years and hit your late 30s, you realize you'd rather spend all of your time training your biological AGI agents and don't really give a shit about the kinda unpleasant industry rat race, much less the totally brutal higher ed rat race.

Or skiing. Lots of multi-millionaire ski bums in my grad cohort. No idea what they do in the summers. Not my cup of tea, but probably better than writing papers no one will read.

In early retirement, there's time for research. And time to share that research. Just... no incentive to do the rat race thing that's necessary to convince an academic you're "accomplished something". But who cares? You finished the race. You don't have to get paper awards or NSF grants. You just have to do work that matters. Or ski. Or change diapers.

So, I guess, to be even more fair: yes. CS PhDs work through their 30s and then retire. Totally. All the time.

Partly I'm posting this to support 'lapsedacademic's assertion, you can do good research in industry. It takes a certain element of luck to land a spot, but it also helps to be very passionate about the research itself.

I'm now writing a paper on an exciting GPU algorithm, but it's pure love, funding doesn't depend on it, it just makes a nice point on my list of accomplishments during perf time.

I'll also add, I looked into academia and talked to some people about steps in that direction, for example seriously considering taking on teaching a class at UC Berkeley. But I decided that the daily grind of academia was not for me. I think I get to spend a larger fraction of my time actually working on my problems at Google than I would at a university.

CS is nice in that you don't (initially) need access to a lot of resources. I think this would be much harder to do in a wet-lab field, which is one of the reasons I'm still here.

exactly. high-level ICs at FAANG set their own schedules/roadmaps and salaries as long as they pushing expanding the forefront of an area that brings value. the truth is academia is a shelter for a lot of people who can't do useful things.

And that's a good thing, because often times it's not obvious immediately how a particular thing is useful or brings value. Sometimes a particular area of inquiry doesn't appear promising until a subsequent invention many years later.

For example, driverless cars were incubated in academia. Now corporations are using those same techniques. A lot of researchers crashed a lot of cars before a winning combo was discovered. You don't get positive results without a ton of failures and not-useful ideas. It's worth noting that industry was not the one footing the bill here to get all of these negative results. There were no high-level ICs at Google doing this research when it was being done at CMU. Google only started doing it only once the the techniques were proven at the DARPA grand challenges.

this could be the tagline of every single application to NSF. i'm not sure if you're in academia but there are hordes of projects that are funded that are clearly useless.

>For example, driverless cars were incubated in academia.

are you really claiming that driverless cars weren't immediately obvious as valuable? just because CMU got to it first doesn't mean industry wouldn't have gotten to it.

I don't understand what your point is. It's not like industry is immune to funding ideas that are clearly useless (Juicero) or even fraudulent (Theranos). If you have a way to fund only good ideas, I think that would be quite a breakthrough. I mean, look around you: this community is set up around a good-idea selection engine that itself struggles to consistently identify good ideas. Bad ideas are a part of getting to good ideas. If you really had a 100% fool-proof way if identifying bad/good ideas at the pre-funding stage you wouldn't be here talking about it -- you'd be using it to make a ton of money.

Also, I would challenge you to point to a NSF funded idea that is 100% clearly, objectively useless. Something so clearly has no plausible utility whatsoever. I think this would be very hard to do.

> are you really claiming that driverless cars weren't immediately obvious as valuable?

It's true that industry could have but they didn't, and that's the point. It only became attractive to industry after the public sector dumped a massive amount of R&D into it and basically proved how to do it to industry, and that's not a coincidence. Before the the DARPA grand challenges it was absolutely a question as to how viable the idea of driverless cars were. This story is not an uncommon thing.

No it's I that don't understand your implicit point that we should let academics fiddle. Is it just because there's some grand narrative around science being objectively and absolutely for the betterment of mankind? The ideological devotion to science as some kind of monastic pursuit blinds you to the very real facts (on the ground) about how much funding is wasted on one off papers, one off projects, whole conferences devoted to areas that will never improve anyone's life or generate absolutely any return on investment.

>Also, I would challenge you to point to a NSF funded idea that is 100% clearly, objectively useless

It's very easy: pick any nsf grant going back as far as you'd like (such that there's enough lead time) and look at the number of citations on the papers generated from the grant. I don't even have to do this because everyone knows that probably 50% of all papers get absolutely zero citations (https://www.science.org/content/blog-post/not-so-many-uncite...).

>It's true that industry could have but they didn't, and that's the point

Again I have no clue what you're claiming here. You're trying to make some kind of case for academic science shouldering the burden of some fraction of fundamental (pie in the sky) research by citing self-driving cars which is positively laughable as an example of such research.

Do you see the contradiction here? I don't think bibliometrics are useful for measuring utility.

> I don't understand your implicit point that we should let academics fiddle

I'm actually totally okay with letting academics fiddle. They are super cheap and you're mostly just paying them for small amounts of their time.

But, it should be the faculty who are allowed to fiddle. They shouldn't be given resources to direct other people's fiddling time. In particular, I think we should massively reform the graduate student system to invert the power relationship between faculty and students on any highly exploratory projects.

Specifically, for any grant whose purpose is "fundamental science" and/or training (e.g., ALL NSF money as a starter):

1. the agency funds students instead of faculty. So 100% of the money that goes to graduate students on NSF grants should be redirected to a GRFP-like funding model. This means that NSF grants to faculty should only fund PI summer salaries & shared department resources. Never students. Want a student? Recruit them to collaborate with you.

2. NSF should put a hard upper bound on the number of funded teaching hours permissible or required and funded through any sort of stipend.

NB: students can still teach more hours! But then they will be normal W2 employees who are paid prevailing rates, are included in faculty+staff retirement/pension/benefits, get FICA benefits, etc. The point: if your uni takes a single dollar from NSF, then student stipends can only be actual stipends, not back doors for tax-advantaged ad junct labor that excludes universities from paying FICA taxes on behalf of their teaching staff (who happen to be grad students).

Tippy-top programs in any particular field already operate in a way that treats grad students more like students than itinerant labor.

It's the other 99% of institutions that are gutting scientific human capital in the name of empowering incompetent middle management. (Professors are middle management. Most of them are incompetent at that job.)

that's not a contradiction that's like just your opinion man. it's also the no true scotsman fallacy on your part.

>we should massively

>NSF grants should be redirected to a GRFP-like funding model

>NSF should put a hard upper bound

cool when you replace panchanathan you can institute all of the policies and only then will academia be more egalitarian and possibly more useful to society as a whole. until then you're just playing bait and switch wrt the current state of things.

I don't follow.

Useless work gets cited all the time. I'm not suggesting that there should be less accountability to be useful to society. I'm just pointing out that bibliometrics is a particularly bad way of measuring utility.

> until then you're just playing bait and switch wrt the current state of things.

Again, I don't follow. How am I playing bait and switch? I don't work in academia.

> replace panchanathan

Fortunately, that's not necessary. You don't put pressure on agencies like NSF by joining the civil service. Even high-ranking civil servants are... well, servants. You put pressure on federal agencies by having tons of money and free time. Which many lapsed academics in CS have in spades ;-)

Also when you work as an academic you are underpaid and working the equivalent of three jobs, 1) research and begging for grant money, 2) teaching, 3) bureaucratic nonsense, committees, student advising, etc. So I think 42% to do your research is a very generous estimate.

I left academia after my PhD and wish I would've left sooner. It's a house of cards built on the illusion "prestige" and indentured servant wages.

A tenure-track professor, in particular, isn't going to be taking 42% of the year off. They're going to be crushing it, attempting to turn out quality work and secure enduring funding.

The reason to pursue a Ph.D. is love. Perhaps the reason to pursue a professorship: if you look at the combined tasks of committee-work, grant-applications, teaching, and research and think, "hell yes, I'm in!", it might be for you.

As I worked through my undergraduate, graduate, and post-doc careers, I consistently noted that faculty were not, on average, all that happy. The work can have real purpose, but the sacrifices one (and their families) must make toward that purpose are substantial.

A major reason that I left academia was that we were under-resourced, especially in institutional support, to do our jobs, despite being extremely well-funded by academic standards. The IT-onboarding my first day in industry was a huge breath of fresh air -- it would have taken 1-4 weeks to do in academia what was accomplished in 4 hr; industry values time.

Henry Ford once said "A customer can have any color they want, as long as it is black".

You can do whatever you want as long as you want to do exactly what you've been told you have to do. You have to do something extremely specialized - publish your work in good outlets (whatever that means, depending on the field). The truth is that you can work on any topic you want, as long as you can publish in the right place. You have to deal with reviewers. You have to follow the norms of the profession. Don't like the way things are done? Tough. You do it the way the reviewers and editors want you to do it.

I'm writing this more for anyone that's considering going into academia. It's not at all what you think when you hear people talking about your "freedom". There's a long list of rules you have to follow, not unlike any profession.

3x-5x is more reasonable.

But those numbers are before RSU appreciation, which I suspect you're massively underestimating.

FB granted 5 years ago went from 128 to 326. AMZN 800 to 3200. AAPL 29 to 171. GOOG 800 to 2700. MSFT 62 to 311. (Netflix excluded for the obvious reason.)

So if your total comp is 500K and half or more of that is long-dated stock (or you just didn't sell) then over the last 4-5 years you could very well have been making million a year or so. And 500K is doable for an asst prof.

Not guaranteed, of course. But cash is comp is risky as well. How many professors got a 7% raise to adjust for inflation last year?

10x pre-appreciation is certainly possible after 5-10 years in industry, though. Probably not the norm, but not some crazy impossible out-of-reach number.

Regarding IP: Yup. It's true. If you're willing and able to do the work to make millions in ARR from your IP then academia can break even. (beware tech transfer... universities can be more predatory than the slimiest of VC firms!)

Even at tippy top R1s that's a tiny fraction of faculty and requires a ton of extra work. But, yeah, it's a good case where academia can make sense.