The point is that how “cool” something is is supposed to track the potential value there
Nope. How useful something is is supposed to track the potential value. If I were to go meta, I’d say that “cool” implies a particular kind of signaling to a specific social sub-group. There isn’t much “potential value” other than the value of the signal itself.
It seems like you see me as implicitly asking “why do you guys keep making pieces instead of going on an adventure!?!?!”
Still nope. Most people don’t want to go on a real adventure—it’s too risky, dangerous, uncomfortable. Most people—by far—prefer the predictable job of producing the pieces so that they can pay the mortgage on their suburban McMansion. In the case of academia, going for broke usually results in your being broke (and tenure-less) while a steady production of published papers gives you quite good chances of remaining in academia. Maybe not in the Ivies, but surely there is a college in South Dakota that wants you as a professor :-/
“you must produce the pieces”. Really?
If you want tenure, yes. If you don’t want tenure, you can do whatever you want.
then you should probably at least ask what your chance of winning the million is before settling for $500.
Sure. The answer is a shrug and if you want a verbalization, it will go along the lines of “Nobody knows”.
so they are going to end up stuck as pieceworkers even if there’s a way to have much much more”
There is no way for all of them to “have much much more”. Whether you think the trade-off is acceptable depends, among other things, on your risk tolerance, but in any case the mode—the most likely outcome—is still of you losing.
To be clear I do see the whole “intrepid explorers” thing pretty much exactly how you said it. I went that way myself and I’m super glad I did. It has been fun and had large payoff for me.
At the same time though, I realize that this is not how everyone sees it. I realize that a lot of the payoffs I’ve gotten can be interpreted other ways or not believed. I realize that other people want other things. I realize that I am in a sense lucky to not only get anything out of it, but to even be able to afford trying. And I realize why many people wouldn’t even consider the possibility.
Given that, it’d be pretty stupid to run around saying “drop what you’re doing and go on an adventure!” (or anything like it) as if it weren’t that from their perspective not only is “adventure” almost certainly going to lead nowhere, but they must make the pieces. As if “adventure” actually is a good idea for them—for most people, all things considered, it probably isn’t.
My point is entirely on the meta level. It’s not even about this topic in particular. I frequently see people rounding “this is impossible within my current models” to “this is impossible”. Pointing this out is rarely a “woah!” moment for people, because people generally realize that they could be wrong and at some point you have to act on your models. If you’ve looked and don’t see any errors it doesn’t mean none exist, but knowing that errors might exist doesn’t exactly tell you where to look or what to do differently.
What I think people don’t realize is how important it is to think through how you’re making that decision—and what actually determines whether they round something off to impossible or not. I don’t think people take seriously the idea that taking negligible in-model probabilities seriously will pay off on net—since they’ve never seen it happen and it seems like a negligible probability thing.
And who knows, maybe it won’t pay off for them. Maybe I’m an outlier here too and even if people went through the same mental motions as me it’d be a waste. Personally though, I’ve noticed that not always but often enough those things that feel “impossible” aren’t. I find that if I look hard enough, I often find holes in my “proof of impossibility” and occasionally I’ll even find a way to exploit those holes and pull it off. And I see them all the time in other people—people being wrong where they don’t even track the possibility that they’re wrong and therefore there is no direct path to pointing out their error because they’ll round my message to something that can exist in their worldview. I have other things to say about what’s going on here that makes me really doubt they’re right here, but I think this is sufficient for now.
Given that, I am very hesitant to round p=epsilon down to p=0, and if the stakes are potentially high I make damn sure that my low probability is stable upon more reflection and assumption questioning. I won’t always find any holes in my “proof”, nor will I always succeed if I do. Nor will I always try, of course. But the motions of consciously tracking the stakes involved and value of an accurate estimate has been very worthwhile for me.
The point I’m making is in the abstract, but one that I see as applying very strongly here. Given that this is one of the examples that seems to have paid off for me, it’d take something pretty interesting (and dare I say “cool”?) to convince me that it was never worth even taking the decision seriously :)
Yes, I agree that people sometimes construct a box for themselves and then become terribly fearful of stepping outside this box (=”this is impossible”). This does lead to them either not considering at all the out-of-the-box options or assigning, um, unreasonable probabilities to what might happen once you step out.
The problem, I feel, is that there is no generally-useful advice that can be given. Sometimes your box is genuinely constricting and you’d do much better by getting out. But sometimes the box is really the best place (at least at the moment) and getting out just means you become lunch. Or you wander in the desert hoping for a vision but getting a heatstroke instead.
You say
I don’t think people take seriously the idea that taking negligible in-model probabilities seriously will pay off on net
but, well, should they? My “in-model probabilities” tell me that I’m not going to become rich by playing the lottery. Should I take the lottery idea seriously? Negligible probabilities are often (but not always) negligible for a good reason.
Given that, I am very hesitant to round p=epsilon down to p=0
Sure. But things have costs. If the costs (in time, effort, money, opportunity) are high enough, you don’t care whether it’s epsilon or a true zero, the proposal fails the cost-benefit test anyway.
Yes. From the inside it can be very tough to tell, but from the outside they’re clearly they’re wrong about them all being low probability. They don’t check for potential problems with the model before trusting it without reservation, and that causes them to be wrong a lot. Even if your “might as well be 100%” is actually 97% - which is extremely generous, you’ll be wrong about these things on a regular basis. It’s a separate question of what—if anything—to do about it, but I’m not going to declare that I know there’s nothing for me to do about it until I’m equally sure of that.
I think one of the real big things that makes the answer feel like “no” is that even if you learn you’re wrong, if you can’t learn how you’re wrong and in which direction to update even after thinking about it, then there’s no real point in thinking about it. If you can’t figure it out (or figure out that you can trust that you’ve figured it out) even when it’s pointed out to you, then there’s less point in listening. I think “I don’t see what I can do here that would be helpful” often gets conflated with “it can’t happen”, and that’s a mistake. The proper way to handle those doesn’t involve actively calling them “zero”. It involves calling them “not worth thinking about” and the like. There is nothing to be gained by writing false confidences in mental stone and much to be lost.
My “in-model probabilities” tell me that I’m not going to become rich by playing the lottery. Should I take the lottery idea seriously? Negligible probabilities are often (but not always) negligible for a good reason.
Right. With the lottery, you have more than a vague intuitive “very low odds” of winning. You have a model that precisely describes the probability of winning and you have a vague intuitive but well backed “practically certain” odds of your model being correct. If I were to ask “how do you know that your odds are negligible?” you’d have an answer because you’ve already been there. If I were to ask you “well how do you know that your model of how the lottery works is right?” you could answer that too because you’ve been there too. You know how you know how the lottery works. Winning the lottery may be a very big win, but the expected value of thinking about it further is still very low because you have detailed models and metamodels that put firm bounds on things.
At the end of the day, I’m completely comfortable saying “it is possible that it would be a very costly mistake to not think harder about whether winning the lottery might be doable or how I’d go about doing it if it were AND I’m not going to think about it harder because I have better things to do”.
If I were gifted a lotto ticket and traded it for a burrito, I’d feel like it was a good trade. Even if the lottery ticket ended up winning the jackpot, I could stand there and say “I was right to trade that winning lotto ticket for a burrito” and not feel bad about it. It’d be a bit of a shock and I’d have to go back and make sure that I didn’t err, but ultimately I wouldn’t have any regrets.
If, say, it was given to me as a “lucky ticket” with a wink and a nod by some mob boss whose life I’d recently saved… and I traded it for a freaking burrito because “it’s probably 1 in 100 million, and 1 in 100 million isn’t worth taking seriously”… I’d be kicking myself real hard for not taking a moment to question the “probably” when I learned that I traded a winning ticket for a burrito.
And all those times the ticket from the mob boss didn’t win (or I didn’t realize it won because I traded it for a burrito) would still be tremendous mistakes. Just invisible mistakes if I don’t stop to think and it doesn’t happen to whack me in the head. The idea of making mistakes, not realizing, and then using that lack of realization as further evidence that I’m not overconfident is a trap I don’t want to fall into.
My brief attempt at “general advice” is to make sure you actually think it through and would be not just willing to but comfortable eating the loss if you’re wrong. If you’re not, there’s your little hint that maybe you’re ignoring something important.
When I point people to these considerations (“you say you’re sure, so you’d be comfortable eating that loss if it turns out not to be the case, the vast majority of the times when they stop deflecting and give a firm “yes” or “no”, the answer is “no”—and they rethink things. There are all sorts of caveats here, but the main point stands—when its important, most people conclude they’re sure without actually checking to their own standards.
That’s just not making bad decisions relative to your own best models/metamodels—you can still make bad decisions by more objective standards. This can’t save you from that but what it can do is make sure your errors stand out and don’t get dismissed prematurely. In the process of coming to say “yes, and I can eat the loss if I’m wrong” you end up figuring out what kinds of things you don’t expect to see and committing to the fact that your model predicts they shouldn’t happen. This makes it a lot easier to both notice the fact that your model is wrong and harder to let yourself get away with pretending it isn’t.
From the inside it can be very tough to tell, but from the outside they’re clearly they’re wrong about them all being low probability.
I don’t know about that. That clearly depends on the situation—and while you probably have something in mind where this is true, I am not sure this is true in the general case. I am also not sure of how would you recognize this type of situation without going circular or starting to mumble about Scotsmen.
if you learn you’re wrong, if you can’t learn how you’re wrong and in which direction to update even after thinking about it
What do you mean, can you give some examples? Normally, if people locked themselves in a box of their own making, they can learn that the box is not really there.
The idea of making mistakes, not realizing, and then using that lack of realization as further evidence that I’m not overconfident is a trap I don’t want to fall into.
That’s a good point—I agree that if you don’t realize what opportunity costs you are incurring, your cost-benefit analysis might be wildly out of whack. But again, the issue is how do you reliably distinguish ex ante where you need to examine things very carefully and where you do not have to do this. I expect this distinguishing to be difficult.
“Actually thinking it through” is all well and good, but it basically boils down to “don’t be stupid” and while that’s excellent advice, it’s not terribly specific. And “can you eat the loss?” is not helping much. For example, let’s say one option is me going to China and doing a start-up there. My “internal model” says this is a stupid idea and I will fail badly. But the “loss” is not becoming a multimillionaire—can I eat that? Well, on the one hand I can, of course, otherwise I wouldn’t have a choice. On the other hand, would I be comfortable not becoming a multimillionaire? Um, let’s say I would much prefer to become one :-) So should I spend sleepless nights contemplating moving to China?
I don’t know about that. That clearly depends on the situation—and while you probably have something in mind where this is true, I am not sure this is true in the general case. I am also not sure of how would you recognize this type of situation without going circular or starting to mumble about Scotsmen.
I mean about the whole group of things that any given person decides or would decide is “low probability”. I see plenty of “p=0″ cases being true, which is plenty to show that the group “p=0” as a whole is overconfident—I’m not trying to narrow it down to a group where they’re probably wrong, just overconfident.
What do you mean, can you give some examples? Normally, if people locked themselves in a box of their own making, they can learn that the box is not really there.
It’s not that they can’t learn that the box isn’t really there, it’s that even if they know it’s not there they don’t know how to climb out of it.
There are a lot of things I know I might be wrong about (and care about) that I don’t look into further. It’s not that I think it’s unlikely that there’s anything for me to find, but that it’s unlikely for me to find it in the next unit of effort. Even if someone is working with an obviously broken model with no attempts to better their model, it doesn’t necessarily mean they haven’t seriously considered the possibility that they’re wrong. It might just mean that they don’t know in which direction to update and are stuck working with a shitty model.
Some things are like saying “check your shoelaces”. Others are like saying “check your shoelaces” to a kid too young to know how to tie his own shoes.
“Actually thinking it through” is all well and good, but it basically boils down to “don’t be stupid” and while that’s excellent advice, it’s not terribly specific.
Heh. Yes, it is difficult and I expect that just comes with the territory. And yes, it kinda sorta just boils down to “don’t be stupid”. The funny thing is that when dealing with people who know me (and therefore get the affection and intent behind it) “don’t be stupid” is often advice I give, and it gets the intended results. The specificity of “you’re doing something stupid right now” is often enough.
And “can you eat the loss?” is not helping much. For example, let’s say one option is me going to China and doing a start-up there. My “internal model” says this is a stupid idea and I will fail badly. But the “loss” is not becoming a multimillionaire—can I eat that? Well, on the one hand I can, of course, otherwise I wouldn’t have a choice. On the other hand, would I be comfortable not becoming a multimillionaire? Um, let’s say I would much prefer to become one :-) So should I spend sleepless nights contemplating moving to China?
I’d much prefer to be a multimillionaire too, yet I’m comfortable with choosing not to pursue a startup in china because I am sufficiently confident that it is not the best thing for me to pursue right now—and I’m sufficiently confident that I wouldn’t change my mind if I looked into it a little further. It’s not that I don’t care about millions of dollars, its that when multiplied by the intuitive chance that thinking one step further will lead to me having it, it rounds down to an acceptable loss.
If, on the other hand, when you look at it you hear this little voice that says “Eek! Millions of dollars is a lot! How do I know that I shouldn’t be pursuing a china startup!?”, then yes, I’d say you should think about it (or how you make those kinds of decisions) until you’re comfortable eating that potential loss instead of living your life by pushing it away.
You say “don’t be stupid” as if it’s something that we’re beyond as a general rule. I see it as something that takes a whole lot of thought to figure out how not to be stupid this way. Once I started paying attention to these signs of incongruity, I started to recognizing it everywhere. Even in places that used to be or still are outside my “box”.
Nope. How useful something is is supposed to track the potential value. If I were to go meta, I’d say that “cool” implies a particular kind of signaling to a specific social sub-group. There isn’t much “potential value” other than the value of the signal itself.
Still nope. Most people don’t want to go on a real adventure—it’s too risky, dangerous, uncomfortable. Most people—by far—prefer the predictable job of producing the pieces so that they can pay the mortgage on their suburban McMansion. In the case of academia, going for broke usually results in your being broke (and tenure-less) while a steady production of published papers gives you quite good chances of remaining in academia. Maybe not in the Ivies, but surely there is a college in South Dakota that wants you as a professor :-/
If you want tenure, yes. If you don’t want tenure, you can do whatever you want.
Sure. The answer is a shrug and if you want a verbalization, it will go along the lines of “Nobody knows”.
There is no way for all of them to “have much much more”. Whether you think the trade-off is acceptable depends, among other things, on your risk tolerance, but in any case the mode—the most likely outcome—is still of you losing.
From here it looks like you aren’t addressing what I’m actually saying and instead are responding to arguments you think I must be trying to get at.
Are you sure you’re being sufficiently careful and charitable in your reading of my comments?
Sufficiently? X-D Clearly not.
Heh, okay. I’ll try again from another angle.
To be clear I do see the whole “intrepid explorers” thing pretty much exactly how you said it. I went that way myself and I’m super glad I did. It has been fun and had large payoff for me.
At the same time though, I realize that this is not how everyone sees it. I realize that a lot of the payoffs I’ve gotten can be interpreted other ways or not believed. I realize that other people want other things. I realize that I am in a sense lucky to not only get anything out of it, but to even be able to afford trying. And I realize why many people wouldn’t even consider the possibility.
Given that, it’d be pretty stupid to run around saying “drop what you’re doing and go on an adventure!” (or anything like it) as if it weren’t that from their perspective not only is “adventure” almost certainly going to lead nowhere, but they must make the pieces. As if “adventure” actually is a good idea for them—for most people, all things considered, it probably isn’t.
My point is entirely on the meta level. It’s not even about this topic in particular. I frequently see people rounding “this is impossible within my current models” to “this is impossible”. Pointing this out is rarely a “woah!” moment for people, because people generally realize that they could be wrong and at some point you have to act on your models. If you’ve looked and don’t see any errors it doesn’t mean none exist, but knowing that errors might exist doesn’t exactly tell you where to look or what to do differently.
What I think people don’t realize is how important it is to think through how you’re making that decision—and what actually determines whether they round something off to impossible or not. I don’t think people take seriously the idea that taking negligible in-model probabilities seriously will pay off on net—since they’ve never seen it happen and it seems like a negligible probability thing.
And who knows, maybe it won’t pay off for them. Maybe I’m an outlier here too and even if people went through the same mental motions as me it’d be a waste. Personally though, I’ve noticed that not always but often enough those things that feel “impossible” aren’t. I find that if I look hard enough, I often find holes in my “proof of impossibility” and occasionally I’ll even find a way to exploit those holes and pull it off. And I see them all the time in other people—people being wrong where they don’t even track the possibility that they’re wrong and therefore there is no direct path to pointing out their error because they’ll round my message to something that can exist in their worldview. I have other things to say about what’s going on here that makes me really doubt they’re right here, but I think this is sufficient for now.
Given that, I am very hesitant to round p=epsilon down to p=0, and if the stakes are potentially high I make damn sure that my low probability is stable upon more reflection and assumption questioning. I won’t always find any holes in my “proof”, nor will I always succeed if I do. Nor will I always try, of course. But the motions of consciously tracking the stakes involved and value of an accurate estimate has been very worthwhile for me.
The point I’m making is in the abstract, but one that I see as applying very strongly here. Given that this is one of the examples that seems to have paid off for me, it’d take something pretty interesting (and dare I say “cool”?) to convince me that it was never worth even taking the decision seriously :)
Yes, I agree that people sometimes construct a box for themselves and then become terribly fearful of stepping outside this box (=”this is impossible”). This does lead to them either not considering at all the out-of-the-box options or assigning, um, unreasonable probabilities to what might happen once you step out.
The problem, I feel, is that there is no generally-useful advice that can be given. Sometimes your box is genuinely constricting and you’d do much better by getting out. But sometimes the box is really the best place (at least at the moment) and getting out just means you become lunch. Or you wander in the desert hoping for a vision but getting a heatstroke instead.
You say
but, well, should they? My “in-model probabilities” tell me that I’m not going to become rich by playing the lottery. Should I take the lottery idea seriously? Negligible probabilities are often (but not always) negligible for a good reason.
Sure. But things have costs. If the costs (in time, effort, money, opportunity) are high enough, you don’t care whether it’s epsilon or a true zero, the proposal fails the cost-benefit test anyway.
Yes. From the inside it can be very tough to tell, but from the outside they’re clearly they’re wrong about them all being low probability. They don’t check for potential problems with the model before trusting it without reservation, and that causes them to be wrong a lot. Even if your “might as well be 100%” is actually 97% - which is extremely generous, you’ll be wrong about these things on a regular basis. It’s a separate question of what—if anything—to do about it, but I’m not going to declare that I know there’s nothing for me to do about it until I’m equally sure of that.
I think one of the real big things that makes the answer feel like “no” is that even if you learn you’re wrong, if you can’t learn how you’re wrong and in which direction to update even after thinking about it, then there’s no real point in thinking about it. If you can’t figure it out (or figure out that you can trust that you’ve figured it out) even when it’s pointed out to you, then there’s less point in listening. I think “I don’t see what I can do here that would be helpful” often gets conflated with “it can’t happen”, and that’s a mistake. The proper way to handle those doesn’t involve actively calling them “zero”. It involves calling them “not worth thinking about” and the like. There is nothing to be gained by writing false confidences in mental stone and much to be lost.
Right. With the lottery, you have more than a vague intuitive “very low odds” of winning. You have a model that precisely describes the probability of winning and you have a vague intuitive but well backed “practically certain” odds of your model being correct. If I were to ask “how do you know that your odds are negligible?” you’d have an answer because you’ve already been there. If I were to ask you “well how do you know that your model of how the lottery works is right?” you could answer that too because you’ve been there too. You know how you know how the lottery works. Winning the lottery may be a very big win, but the expected value of thinking about it further is still very low because you have detailed models and metamodels that put firm bounds on things.
At the end of the day, I’m completely comfortable saying “it is possible that it would be a very costly mistake to not think harder about whether winning the lottery might be doable or how I’d go about doing it if it were AND I’m not going to think about it harder because I have better things to do”.
If I were gifted a lotto ticket and traded it for a burrito, I’d feel like it was a good trade. Even if the lottery ticket ended up winning the jackpot, I could stand there and say “I was right to trade that winning lotto ticket for a burrito” and not feel bad about it. It’d be a bit of a shock and I’d have to go back and make sure that I didn’t err, but ultimately I wouldn’t have any regrets.
If, say, it was given to me as a “lucky ticket” with a wink and a nod by some mob boss whose life I’d recently saved… and I traded it for a freaking burrito because “it’s probably 1 in 100 million, and 1 in 100 million isn’t worth taking seriously”… I’d be kicking myself real hard for not taking a moment to question the “probably” when I learned that I traded a winning ticket for a burrito.
And all those times the ticket from the mob boss didn’t win (or I didn’t realize it won because I traded it for a burrito) would still be tremendous mistakes. Just invisible mistakes if I don’t stop to think and it doesn’t happen to whack me in the head. The idea of making mistakes, not realizing, and then using that lack of realization as further evidence that I’m not overconfident is a trap I don’t want to fall into.
My brief attempt at “general advice” is to make sure you actually think it through and would be not just willing to but comfortable eating the loss if you’re wrong. If you’re not, there’s your little hint that maybe you’re ignoring something important.
When I point people to these considerations (“you say you’re sure, so you’d be comfortable eating that loss if it turns out not to be the case, the vast majority of the times when they stop deflecting and give a firm “yes” or “no”, the answer is “no”—and they rethink things. There are all sorts of caveats here, but the main point stands—when its important, most people conclude they’re sure without actually checking to their own standards.
That’s just not making bad decisions relative to your own best models/metamodels—you can still make bad decisions by more objective standards. This can’t save you from that but what it can do is make sure your errors stand out and don’t get dismissed prematurely. In the process of coming to say “yes, and I can eat the loss if I’m wrong” you end up figuring out what kinds of things you don’t expect to see and committing to the fact that your model predicts they shouldn’t happen. This makes it a lot easier to both notice the fact that your model is wrong and harder to let yourself get away with pretending it isn’t.
I don’t know about that. That clearly depends on the situation—and while you probably have something in mind where this is true, I am not sure this is true in the general case. I am also not sure of how would you recognize this type of situation without going circular or starting to mumble about Scotsmen.
What do you mean, can you give some examples? Normally, if people locked themselves in a box of their own making, they can learn that the box is not really there.
That’s a good point—I agree that if you don’t realize what opportunity costs you are incurring, your cost-benefit analysis might be wildly out of whack. But again, the issue is how do you reliably distinguish ex ante where you need to examine things very carefully and where you do not have to do this. I expect this distinguishing to be difficult.
“Actually thinking it through” is all well and good, but it basically boils down to “don’t be stupid” and while that’s excellent advice, it’s not terribly specific. And “can you eat the loss?” is not helping much. For example, let’s say one option is me going to China and doing a start-up there. My “internal model” says this is a stupid idea and I will fail badly. But the “loss” is not becoming a multimillionaire—can I eat that? Well, on the one hand I can, of course, otherwise I wouldn’t have a choice. On the other hand, would I be comfortable not becoming a multimillionaire? Um, let’s say I would much prefer to become one :-) So should I spend sleepless nights contemplating moving to China?
I mean about the whole group of things that any given person decides or would decide is “low probability”. I see plenty of “p=0″ cases being true, which is plenty to show that the group “p=0” as a whole is overconfident—I’m not trying to narrow it down to a group where they’re probably wrong, just overconfident.
It’s not that they can’t learn that the box isn’t really there, it’s that even if they know it’s not there they don’t know how to climb out of it.
There are a lot of things I know I might be wrong about (and care about) that I don’t look into further. It’s not that I think it’s unlikely that there’s anything for me to find, but that it’s unlikely for me to find it in the next unit of effort. Even if someone is working with an obviously broken model with no attempts to better their model, it doesn’t necessarily mean they haven’t seriously considered the possibility that they’re wrong. It might just mean that they don’t know in which direction to update and are stuck working with a shitty model.
Some things are like saying “check your shoelaces”. Others are like saying “check your shoelaces” to a kid too young to know how to tie his own shoes.
Heh. Yes, it is difficult and I expect that just comes with the territory. And yes, it kinda sorta just boils down to “don’t be stupid”. The funny thing is that when dealing with people who know me (and therefore get the affection and intent behind it) “don’t be stupid” is often advice I give, and it gets the intended results. The specificity of “you’re doing something stupid right now” is often enough.
I’d much prefer to be a multimillionaire too, yet I’m comfortable with choosing not to pursue a startup in china because I am sufficiently confident that it is not the best thing for me to pursue right now—and I’m sufficiently confident that I wouldn’t change my mind if I looked into it a little further. It’s not that I don’t care about millions of dollars, its that when multiplied by the intuitive chance that thinking one step further will lead to me having it, it rounds down to an acceptable loss.
If, on the other hand, when you look at it you hear this little voice that says “Eek! Millions of dollars is a lot! How do I know that I shouldn’t be pursuing a china startup!?”, then yes, I’d say you should think about it (or how you make those kinds of decisions) until you’re comfortable eating that potential loss instead of living your life by pushing it away.
You say “don’t be stupid” as if it’s something that we’re beyond as a general rule. I see it as something that takes a whole lot of thought to figure out how not to be stupid this way. Once I started paying attention to these signs of incongruity, I started to recognizing it everywhere. Even in places that used to be or still are outside my “box”.