I don't think any serious practitioners were out there thinking in this manner. But there is a gold rush right now, and any gold rush will attract its share of charlatans.
I don't think any serious practitioners were out there thinking in this manner. But there is a gold rush right now, and any gold rush will attract its share of charlatans.
It’s a dynamic that sadly burns out overly optimistic, but smart data scientists and sadly leaves a negative impression on existing practitioners on the promise of ML. Those practitioners stick their head back in a hole instead of innovating.
All to say with more explainable ML (and more humility on everyone’s part) more progress would be made.
I consider it the responsibility of computer scientists and engineers to make the tools better and easier. But unfortunately, it's that one has to become a good computer scientist first then a domain expert.
We are not doing enough on innovations of tooling.
But a lot of thought pieces / YouTubers are pushing it, which is a problem.