Apart from getting my own research projects done, I have always been enthusiastic about learning new things, broadening and deepening my knowledge. So I've been reading rigorously on many different topics ranging from econometrics to cosmology. Understanding the theoretical aspects of machine learning, I think, is very important, but understanding its role in real-world applications is even more important.
Reading lots of papers, of course, already gives me a big picture of where machine learning is in scientific communities. However, it lacks social context. I would also like to know what other people think about it.
So I have recently set up a journal club called the Empirical Inference Journal Club with a strong hope that it will provide such a platform for students and postdocs in the department to share their knowledge on some particular topics related to empirical inference. In the department, people have actually been organizing the reading groups on different topics, but to my knowledge they had the reading for a short period of time and then stop.
I commit to keeping this journal club running. Of course, I have to do some extra works, but I think it's worthwhile. After three-week of the journal club, things seem to go smoothly. I hope more people will join and contribute to the journal club.
We always have two options: accepting things the way they are or having enough courage to change them.