Caring Selectively

Caring Selectively
Photo by Glenn Carstens-Peters / Unsplash

Learning not to care is not easy. I have been so bombarded all my life about how I should learn and care about everything, caring and paying attention to everything has been a big default.
The onslaught of recommendation algorithms makes it easy to get lost in the world's suffocating information flow. It is hard to stop... and breathe and draw my own lines and boundaries. This selectiveness is important for my mental health and my professional life. I need to be able to focus to do deep work.
To find my way around this mess, I need to know how not to care about certain things. A suffocating feeling of missing out and not doing enough gripped me until I chose to care selectively. Choosing not to care is about protecting myself against overwhelming anxiety and making sure I leave enough time for the things that matter to me.
That brings me to my point, what do I actually care about? The question itself sounds complicated so I believe it is better to have a straightforward answer. You align it with what you're trying to achieve.
Richard Feynman famously had 12 Questions written somewhere. Those 12 Questions reminded him of all the open problems that he was curious about. So whenever he came across anything about those questions, he would collect and analyse them.
I believe that there is a simplicity here that is just amazing. Just have the list of open questions, go after them and feel free to ignore everything else. Don't feel compelled about those.

How do you select the questions?

My questions direct me to collect about what I am trying to achieve.
At the time of writing this piece, I am trying to understand how to efficiently finetune large language models (LLMs). So that is literally my question:
"How can I efficiently fine-tune an LLM?"
Another example; I've recently started to do cross-fit in a local gym, and my energy has been in flux ever since. I think it is because of my eating and sleeping habits but I am not sure so this is another question:
"How can I keep myself energised and ready for the rest of the day even with heavy exercising?"
Any source, tweet, newsletter, or blog post that seems credible goes in my buckets, at least to skim. If not, even if the topic seems very interesting, I am sure I can run into a similar post at later or I can search for it when I need it.
But I need to keep things off my mind and focus on my problems NOW. This is a reminder about what to care about and if I can stop myself from going down a rabbit hole about the things that are not on this list.

When do they change?

I try to keep these questions relevant. I review my open projects both personal and professional, I think about any big news about my field and keep my eye out for any new developments that I might need to learn about, if someone tells me an interesting thing that sticks with me for a while, I might even add that to my list to know more about.
A curious thing that happens is that, once I start to look for a piece of information, I just start noticing it all around and after a bit of an osmosis, I find myself where I need to be. This type of selective caring helps me to clear my attention.

What about when we don't know where to go?

If the topic I want to delve into is very large, the question can be appropriately large. While researching a field that I have no clue what I am looking for, I'll keep the question very high level and just diverge as much as I can. It is important to remember that I am in control of what I need to do and can stop at any moment. Learning and researching go through divergence and convergence stages.

Conclusion

To simplify all of this, the philosophy behind this can be reduced to:

  • Have a list of active items to care about
  • Clear the attention by trying not to care about the rest

And I also try to remind myself all the time, any information that I'm filtering out can be found out later, when and IF I need them. We are living in an information-abundant era, and most of the old advice doesn't work any more.