It seems like a good way to actually determine productivity would be to make it competitive.
Have marathon and long-term coding competitions between 100% human coding, AI assisted, and 100% AI. Rate them on total time worked, mistakes, coverage, maintainability, extensibility, etc. and test the programmers for knowledge of their own code.
It’s been clear that the best use of AI in a professional environment is as an assistant.
I don’t want something doing my job for me. I just want it to help me find something or to point out possible issues.
Of course, AI isn’t there yet. It doesn’t like reading through multiple large files. It doesn’t “learn” from you and what you’re doing, only what it’s “learned” before. It can’t pick up on your patterns over time. It doesn’t remember what your various responsibilities are. If I work in a file today, it’s not going to remember in a month when I work on it again.
And it might never get there. We’ve been rapidly approaching the limits of AI with two major problems. First, scaling is becoming exponential. Doubling the training data and computing resources won’t produce a model that’s twice as good. Second, overtraining is now a concern. We’re discovering that models can produce worse results if they receive too much training data.
And, obviously, it’s terrible for the environment and a waste of resources and electricity.
Zigbee and Z-Wave, too!
It means you’re gonna be the major break for some psychologist.