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Dear Academia, I loved you, but I’m leaving you (2014)

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31–40 of 92 posts

Re: Dear Academia, I loved you, but I’m leaving you (2014)

#31

Earlier quoted context omitted.

Wow, that's hard to read. I thought people who went into Literature had it bad. It sometimes seems like the education sector is an experiment in how to create a society with almost unlimited power to do things, and almost total ignorance about what's a good idea.

Academia lives in a world where people are willing to spend hundreds of thousands to make themselves more knowledgeable in subjects which might have no economic value in the world. Just look at how much of our undergrad education consists "general education" type courses. While these courses are interesting, most of them are pretty useless. I took Chinese history, Asian american film, music history, art history and s…

> I took Chinese history, Asian american film, music history, art history and so on. All of these courses were pretty much usless to me from an economic stand point.

I majored in Math and CS and took a smattering of other courses (one course away from a minor in each of Religion, Philosophy, and Economics).

The CS courses were by far the most useless. Perhaps 50% of the material I had taught myself before started undergraduate: everything up to and including data-structures as well as the pragmatic aspects of databases, OOP, and Networking courses. Another 40% I could've taught myself without much guidance (non-theoretical PL, non-optimizing compilers, and a non-proof-based algorithms course). The other 10% was project-based or independent study where the forcing function to work with people who were both above and below my skill level was the most valuable aspect of the coursework. (pre-college internships and freelancing gave me lots of experience working with others, but almost all of them were far above my skill level or else were completely non-technical).

The Mathematics coursework was by far the most useful. The lower-level content courses (Calculus and Linear Algebra) are essential for accessing most of the interesting parts of the software industry (self-driving, robotics, research software engineer, etc.). Also, the proof-based coursework is full of useful thought patterns. Most of the difficult/economically important problems I've solved in my life were all relatively trivial extensions of proof techniques or theorems from my undergraduate Analysis, Algebra, and Logic coursework.

The humanities courses sit right in-between CS and Mathematics in terms of usefulness. The value of regular practice writing and communicating, with a professional feedback mechanism, was extremely valuable. I don't often use the content knowledge at work, but the writing skills are extremely useful. Learning to write well without regular professional feedback is difficult.

The content knowledge from my humanities courses was not immediately useful in an economic sense. However, that well-roundedness did get me an amazing spouse and extremely interesting friend group, though. I'm not sure how to put a dollar value on either of those things.

So economically, Math > humanities > CS. CS is more economically valuable but the CS education isn't more valuable because the core content knowledge that's necessary to get a well-paying job doesn't require formal course-work. Basic programming, SQL, and web frameworks are definitely accessible to passionate middle schoolers.

In career dimensions beyond net worth (i.e., interesting work), Math > CS > humanities.

In non-career dimensions, humanities >= Math > CS. My marriage and friends are mostly a product of the humanities aspect of my education and are each easily worth the $20k I paid for undergraduate.

YMMV.

> I think we need to create two tiers of higher-education

FWIW there are at least 4 tiers:

1. Vocational: Community College and most for-profit universities/educational programs (including bootcamps)

2. Advanced Vocational BA/BS: "industry-tracked" degrees at traditional universities. E.g., many universities have both a CS degree and an SE degree. The physics/engineering split is comparable. Theoretical technical courses are replaced with pragmatic technical courses and the more pure humanities courses are replaced with business/econ/industry-specific communications coursework.

3. Traditional BA/BS

4. Traditional BA/BS at elite academic institutions (e.g., top 10 CS programs tend to have bachelors degrees that are different in kind from small branch campuses of most state university systems)

Re: Dear Academia, I loved you, but I’m leaving you (2014)

#32
post #7

Looks like this poster was in STEM. The situation's even more bleak in the humanities--see for instance this Reddit thread[1]: > The humanities PhD is still a vocational degree to prepare students for a career teaching in academia, and there are no jobs. Do not get a PhD in history. [1]: https://www.reddit.com/r/AskHistorians/comments/96yf9h/monda...

It truly is a shame. I was seriously considering pursuing a PhD in history and one of my professors warned me against it. I ended up geting a degree in accounting and have not regretted anything.

Re: Dear Academia, I loved you, but I’m leaving you (2014)

#33

Can anyone speak to what it's like doing a post doc in CS?

you should be more specific-what part of CS? all the CS postdocs I know see a) pretty happy b) have a really easy back up of a high paying industry gig that they can pivot to because of currently insanely inflated demand for academics to make deep learning on the blockchain on the cloud on embedded devices doing quantum backprop -these are ML/theory postdocs

I am primarily interested in the experience of ML post-docs that forgo going into industry. Can you elaborate a bit more about their experience? Salaries look a bit lower for post docs vs industry work. Some I've seen start in the mid-40k to 70k range. Could be different based on geography.

Re: Dear Academia, I loved you, but I’m leaving you (2014)

#34
post #3

Regarding "literally everyone does it" (fishing for results, removing negative ones, and so on): it's very true, and much more prevalent than what people think. Even at top-level universities with big shots. Especially at top-level universities with big shots. I know someone, upon entering a lab to do electronic microscopy, who found out that the image data her lab had written multiple papers on very high-impact jour…

Related story:

When I was in grad school I was doing graph theoretic analysis of human metabolic networks. I had some really interesting and promising preliminary results about the structure of various metabolic pathways and had been invited to present my unpublished work in a multi-departmental lecture. I was making some new visualizations for my talk and spotted something odd, which led me to a bug in my source code that had reversed the direction of several steps in many of the pathways. I was mortified . . . I ran some preliminary tests on the corrected code and saw that many of my results were completely in error. I wouldn't know for sure until I could get several days of cluster time, but I had proof that my last year of work was completely bogus.

I stayed up all night confirming the new code and the extent of my invalidated results and brought this to my advisor the morning before the lecture. He told me to shut up and present it anyways. Being a young idealist I argued with him about the nature of science and the search for truth . . . I refused to go along with it and present something I knew was false. He made one of the research scientists present on their topic at the last second so our lab wouldn't "lose face" and I was pretty much in the dog house forever after.

Re: Dear Academia, I loved you, but I’m leaving you (2014)

#35

Earlier quoted context omitted.

Science is not when you publish something. Science is when at least two independent labs can reproduce your published result.

Why two and not three or one?

If two independent labs can reproduce the result it is extremely unlikely to be the result of false positives. The difference between having two versus three independent verifications is minuscule. A standard has to be set and 2 is a good enough standard.

Re: Dear Academia, I loved you, but I’m leaving you (2014)

#36
post #3

Regarding "literally everyone does it" (fishing for results, removing negative ones, and so on): it's very true, and much more prevalent than what people think. Even at top-level universities with big shots. Especially at top-level universities with big shots. I know someone, upon entering a lab to do electronic microscopy, who found out that the image data her lab had written multiple papers on very high-impact jour…

I had a similar experience. I worked in a neuroimaging lab during grad school. I found a mistake in our code that basically meant we had being overestimating the p-value from MRI data. It potentially invalidated many of the previous papers (and there were a lot, this was a "paper mill").

Being naive, I just assumed they'd be retracting them, but my labmates explained there was no way our PI would let that happen. It was never boiled up to the PI, so he never even knew. A year later (due to this as well as other issues), I quit the PhD and joined a company doing something "real".

Re: Dear Academia, I loved you, but I’m leaving you (2014)

#37

Earlier quoted context omitted.

you should be more specific-what part of CS? all the CS postdocs I know see a) pretty happy b) have a really easy back up of a high paying industry gig that they can pivot to because of currently insanely inflated demand for academics to make deep learning on the blockchain on the cloud on embedded devices doing quantum backprop -these are ML/theory postdocs

I am primarily interested in the experience of ML post-docs that forgo going into industry. Can you elaborate a bit more about their experience? Salaries look a bit lower for post docs vs industry work. Some I've seen start in the mid-40k to 70k range. Could be different based on geography.

are you already a grad student or are you considering it?

in my department [we are an outlier probably] post doc wages are actually pretty comparable to industry i.e. >= 100k. 40k to 70k seems low to me.

I would expect the range to be more like 60-100k.

I haven't been on the real job market yet-but the key to getting a TT or postdoc position seems to be a) collaborators who want to hire you b) people who have heard you give a talk in person and are familiar with your research.

Re: Dear Academia, I loved you, but I’m leaving you (2014)

#38
post #3

Regarding "literally everyone does it" (fishing for results, removing negative ones, and so on): it's very true, and much more prevalent than what people think. Even at top-level universities with big shots. Especially at top-level universities with big shots. I know someone, upon entering a lab to do electronic microscopy, who found out that the image data her lab had written multiple papers on very high-impact jour…

I had a similar experience. I worked in a neuroimaging lab during grad school. I found a mistake in our code that basically meant we had being overestimating the p-value from MRI data. It potentially invalidated many of the previous papers (and there were a lot, this was a "paper mill"). Being naive, I just assumed they'd be retracting them, but my labmates explained there was no way our PI would let that happen. It…

Coming from neuroscience also, I can really relate to this. I'm just glad that people like Neuroskeptic are casting light on the problem. I was really surprised at the degree to which neuroscience is proof by brain graph with lit up blobs :/.

Re: Dear Academia, I loved you, but I’m leaving you (2014)

#39

Earlier quoted context omitted.

Science is not when you publish something. Science is when at least two independent labs can reproduce your published result.

Why two and not three or one?

The more the better. You'd really need a statistically significant number of labs repeating it to be sure. If the underlying study is scientifically sound then a single repeat is good, two repeats is better. 20 repeats is even better. Good luck getting 1 or 2, unless the study is an important work that introduces a useful new technique or is the basis for additional studies. Also good luck knowing whether 2 labs failed for every 1 published. Science is hard. Reporting needs to be improved and there should be grants available to fund repeat studies.

Re: Dear Academia, I loved you, but I’m leaving you (2014)

#40
post #26

This is a recurring topic on HN. My (European) experience is that academia provides a great work environment. If you have tenure, you're free to work on whatever you want, you have very low pressure (beside the pressure you decide to inflict on yourself), you're basically paid to learn new things and teach them to others. You can easily visit other institutes abroad. You get to meet interesting people. Age discrimina…

Yes, I believe we have it easier in Europe. I realize my other post sounds rantish but the reason I'm still in academia, beyond the very valid points you've mentioned, is that I don't believe the nepotism and dishonesty issues are specific to academia. >You get to meet interesting people. I want to stress that part because I don't feel it does the environment justice. You get to meet fantastic and very intelligent pe…

being around really smart people doing interesting things is pretty great.
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