Can't agree more. In my undergraduate research in the Cognitive Neuroscience labs at Berkeley, it was disappointing to see how much effort was wasted because people avoided technology instead of embracing it (in neuroscience!).
The work done there was incredible, but as I was passed around to researchers in the lab, programming the experiments they had designed (have to pay your dues to get into research), I got a chance to see the methods they used before they were able to get competent programmers. Manually marking spikes and anomalies in EEG data when there was an api for the program to allow access to recorded data for just such a purpose, dealing with timing issues because few understood the difficulties of achieving high-precision event timing, etc.
It was depressing to think of how much further it could have gone. When I left to pursue my startup, I was working on some automated techniques to remove noise from fMRI data. That type of work will speed up research and allow researchers to spend time on meaningful things.
The work done there was incredible, but as I was passed around to researchers in the lab, programming the experiments they had designed (have to pay your dues to get into research), I got a chance to see the methods they used before they were able to get competent programmers. Manually marking spikes and anomalies in EEG data when there was an api for the program to allow access to recorded data for just such a purpose, dealing with timing issues because few understood the difficulties of achieving high-precision event timing, etc.
It was depressing to think of how much further it could have gone. When I left to pursue my startup, I was working on some automated techniques to remove noise from fMRI data. That type of work will speed up research and allow researchers to spend time on meaningful things.