I've been doing Quantified Intuitions' Estimation Game every month. I really enjoy it. A big thing I've learned from it is the instinct to think in terms of orders of magnitude.

Well, not necessarily orders of magnitude, but something similar. For example, a friend just asked me about building a little web app calculator to provide better handicaps in golf scrambles. In the past I'd get a little overwhelmed thinking about how much time such a project would take and default to saying no. But this time I noticed myself approaching it differently.

Will it take minutes? Eh, probably not. Hours? Possibly, but seems a little optimistic. Days? Yeah, seems about right. Weeks? Eh, possibly, but even with the planning fallacy, I'd be surprised. Months? No, it won't take that long. Years. No way.

With this approach I can figure out the right ballpark very quickly. It's helpful.

Many years after having read it, I'm finding that the "Perils of Interacting With Acquaintances" section in The Great Perils of Social Interaction has really stuck with me. It is probably one of the more useful pieces of practical advice I've come across in my life. I think it's illustrated really well in this barber story:

But that assumes that you can only be normal around someone you know well, which is not true. I started using a new barber last year, and I was pleasantly surprised when instead of making small talk or asking me questions about my life, he just started talking to me like I was his friend or involving me in his conversations with the other barber. By doing so, he spared both of us the massive inauthenticity of a typical barber-customer relationship and I actually enjoy going there now.

I make it a point to "be normal" around people and it's become something of a habit. One I'm glad that I've formed.

I get the sense that autism is particularly unclear, but I haven't looked closely enough at other conditions to be confident in that.

Something I've always wondered about is what I'll call sub-threshold successes. Some examples:

• A stand up comedian is performing. Their jokes are funny enough to make you smile, but not funny enough to pass the threshold of getting you to laugh. The result is that the comedian bombs.
• Posts or comments on an internet forum are appreciated but not appreciated enough to get people to upvote.
• A restaurant or product is good, but not good enough to motivate people to leave ratings or write reviews.

It feels to me like there is an inefficiency occurring in these sorts of situations. To get an accurate view of how successful something is you'd want to incorporate all of the data, not just data that passes whatever (positive or negative) threshold is in play. But I think the inefficiencies are usually not easy to improve on.

In A Sketch of Good Communication -- or really, in the Share Models, Not Beliefs sequence, which A Sketch of Good Communication is part of -- the author proposes that, hm, I'm not sure exactly how to phrase it.

I think the author (Ben Pace) is proposing that in some contexts, it is good to spend a lot of effort building up and improving your models of things. And that in those contexts, if you just adopt the belief of others without improving your model, well, that won't be good.

I think the big thing here is research. In the context of research, Ben proposes that it's important to build up and improve your model. And for you to share with the community what beliefs your model outputs.

This seems correct to me. But I'm pretty sure that it isn't true in other contexts.

For example, I wanted to buy a new thermometer recently. Infrared ones are convenient, so I wanted to know if they're comparably accurate to oral ones. I googled it and Cleveland Clinic says they are. Boom. Good enough for me. In this context, I don't think it was worth spending the effort updating my model of thermometer accuracy. In this context, I just need the output.

I think it'd be interesting to hear people's thoughts on when it is and isn't important to improve your models. In what contexts?

I think it'd also be interesting to hear more about why exactly it is harmful in the context of intellectual progress to stray away from building and improving your models. There's probably a lot to say. I think I remember the book Superforecasters talk about this, but I forget. 

Hm. On the one hand, I agree that there are distinct things at play here and share the instinct that it'd be appropriate to have different words for these different things. But on the other hand, I'm not sure if the different words should fall under the umbrella of solitude, like "romantic solitude" and "seeing human faces solitude".

I dunno, maybe it should. After all, it seems that in different conceptualizations of solitude, it's about being isolated from something (others' minds, others' physical presence).

Ultimately, I'm trusting Newport here. I think highly of him and know that he's read a lot of relevant literature. At the same time, I still wouldn't argue too confidently that his preferred definition is the most useful one.

That makes sense. I didn't mean to imply that such an extreme degree of isolation is a net positive. I don't think it is.

That makes sense. Although I think the larger point I was making still stands: that in reading the book you're primarily consuming someone else's thoughts, just like you would be if the author sat there on the bench lecturing you (it'd be different if it were more of a two-way conversation; I should have clarified that in the post).

I suppose "primarily" isn't true for all readers, for all books. Perhaps some readers go slowly enough where they actually spend more of their time contemplating than they do reading, but I get the sense that that is pretty rare.

Cool! I have a feeling you'd like a lot of Cal Newport's work like Digital Minimalism and Deep Work.

When I'm walking around or riding the train, I want to be able to hear what's going on around me.

That makes sense about walking around, but why do you want to hear what's going on around you when you're riding the train?