[sdenton4]

The author did fine in another field, but might have picked biology instead if they had gotten the switch flipped earlier in life. That some people get through bad classes isn't a proof that those classes are good; you get those few who would survive no matter what, and those whose brain-wiring is conducive to the way the bad classes are structured. This has a tendency to reduce diversity of thought over time, and contributes to academic ossification.

Secondly, fields really do need cross-discipline collaboration. Finding passionate CS people is fantastic because they bring a different skill set. I have often found that when we get diverse experts together, we can have everyone do the "easy part" and get results which would be otherwise unobtainable.

Yes, some people have 'engineers disease' and fail to appreciate the depth of knowledge and skills of folks who have spent their life in another domain... But the author doesn't seem to be one of these. Many of their favorite stories appreciate the combination of insight and hard work in the history of the field.

It does, indeed, suck that people working in biology get paid less than computer engineers. Blame capitalism...

[ramraj07]

As a biologist with a tech background (but actual biotechnology majors) - please we have enough tech bros who think they're biology's saviors. They'll just come in fascinated by some technological problem, call it the only blocker to solving aids and cancer and take away a billion dollars in funding over decades and show nothing of actual consequence. Like the entire protein folding field. It's a tool. Not the solution. Even today there was this hyperbolic piece on NBC about how this Harvard scientist working on microscopy image processing is being deported and now we are not going to cure cancer.

I feel bad for them, but I can assure you, as someone who did the research in the exact same field, they're curing nothing and are more likely to make cures slower by sucking away funding from more pertinent projects.

Also relevant xkcd https://xkcd.com/1831/

[__MatrixMan__]

I've been working my way towards a biololgy degree very slowly (can only really fit one-class-at-a-time alongside working full time). I'm maybe 70% to a bachelor's degree in it. Been writing code for ages, but I've saved enough to accept a lower salary if it means I get to work on a real problem for once in my life. So I guess I'm one of those people you're frustrated with.

Do you have any advice for how to not be that kind of problem? For now I'm just focusing on my coursework, but at some point I'll be biologist-enough to help out with research. How do I approach it without being that guy?

[ramraj07]

In my (possibly not the best) opinion the most important quality will be to not delude oneself with the idea that their method or field is the most important field in all of science. Unfortunately academic structures force you to think and believe that and then proselytize that way. But if you stay above it at least in my books you're above most folks. But then I'm a lowly guy in a corner lol.

Practically what this means is that you should decide what you truly want to change (not necessarily what you can change with your current expertise) and pursue it across whatever fields necessary. If it's curing a disease, you have to decide what is the most important thing that's stopping us from curing that disease and pursue that exact topic. More often than not it's not anything software related. You have to grab a pipette at some point and guillotine a few mice at another lol.

[__MatrixMan__]

I once met a scientist who spent a week traveling to where there was a powerful x-ray laser. He used it to blast a thin film of something or other that was floating on the surface of some water. He left with a flash drive full of data and some FORTRAN titled LSQREFL, which allegedly could decode the laser results. He then spent the next 6 months trying to make it actually do that. Turns out you had to have a folder with today's date on it on your desktop, otherwise the program would crash. This was documented nowhere, he just eventually puzzled it out from the code.

I offered to put it on github for him, so that at least he didn't have to be the sole caretaker for this endangered bit of software, but he was afraid of running afoul of the original author's rights, so endangered it will stay.

This was maybe an unlikely occurrence, falling neatly in the not part of your:

> More often than not it's not anything software related

But it makes me think that there is still some juice left to squeeze out there. I mean, I'm having a good time with my one-class-per-semester, I'd just prefer to not have to do it for another decade before I'm enough of a biologist to get my hands dirty.

[ramraj07]

Sounds like he was doing an xray diffraction experiment? The last time (in my opinion) XRay diffraction based structure results meaningfully changed scientific discourse that affects human life was probably in the 80s or 90s. While it's important work it's no more important for Healthcare than some physics guy doing things with a random metal alloy. The point is there are interesting things but one shouldn't delude that this is the thing that's keeping us from unleashing human health prosperity.

[sdenton4]

There's two kinds of ignorance which come into contact when people work across disciplines.

In my own work helping ecologists, I see plenty of CS/ML folks who think they'll change the world by throwing a transformer at the problem. (which problem? you think we haven't tried that?) It takes some time and exposure to figure out what kinds of problems you can meaningfully contribute on.

On the other hand, I've met lots (most?) of ecologists who underestimate the impact of looking at their work through CS/ML lenses. Effective automation can greatly improve iteration speed, which ultimately leads to better outcomes than a slow but 'perfect' process. (and, indeed, the 'slow-but-perfect' process may not be sufficiently benchmarked, and not be perfect at all...)

You can do a lot of good by working closely with a practitioner, and identifying the places where they are spending a lot of time doing 'boring' stuff, and finding ways to automate or approximate the outcomes of that boring work. As you work with more people, you'll be able to identify boring stuff that everyone in the field is stuck doing.

So, in short, an excellent goal is to find ways to save people time through bottleneck analysis. Improve iteration speed and you improve the speed at which we can accumulate knowledge / make discoveries / etc. When you're done, it's "just a tool", but beforehand it's a problem holding back discovery.

[__MatrixMan__]

There were https://en.wikipedia.org/wiki/Galectin proteins embedded in a thin lipid layer on the surface of the water. The goal was to understand what conditions triggered various conformational changes. I'm under the impression that such details end up in databases and get selected for further inquiry by drug design processes, particularly those targeting autoimmune diseases. Or at least, that's what I got from his talk on it. I'm still working my way up to the biochemistry classes.

But yeah I get your point about avoiding that delusion. Honestly I'd be happy enough to be doing something that I suspect is not actively harmful (this should be easy but SaaS tends to converge on products that control their users and not the other way around). I don't need to be humanity's savior. More helpful than harmful will be enough.