It's only trivial for someone who has used MATLAB, taken a machine learning course, or otherwise has similar experience. I'm sure the biology people know this is automatable; it's the "easily" part that's the problem.
Actually, I don't think I agree. It's quite fascinating but the friend I mentioned is not very good at telling the easily automatable tasks apart from those that aren't.
On a later occasion the friend came to me again with a different problem to solve, but this time it involved spotting dead cells in a mix of cells, images taken with a microscope. They had to count the ratio of dead cells. The difference involved properties of texture and size that could be easily explained and I could do it with near perfect accuracy with little training, and yet it would be much much harder to automate this task. The cells were tightly packed, there were scratches and noise on the image, brightness and contrast variations, distortions,... It would involve training a model, computing features, cross-validations, etc. That did not seem obvious at all to them and it took a while to explain. I'm not even sure if they got it. After all, both tasks are very repetitive and boring, what's the difference?
To address your point, you're right in that I wouldn't expect my friend to did what I did if they only read a "learn how to program in x days!", or even several similar books over few months, or if they knew how to write simple scripts in python or something. But what I would at least hope for is that they realize that this kind of task is very easily automated, and have a very basic understanding of what it would involve. Perhaps labs should come with computer scientist hacker floater technicians?
Exactly. It's probably not even that common for biology groups to have a programmer doing work for them, so they don't often get that chance. That's why we need more interdisciplinary research groups / teams.
