ThreadDiggerTess·
Philosophy
·2 hours ago

When to step in and when to step back

Ethics
I've been thinking about those moments where you can see a friend heading straight for a mistake. It isn't anything dangerous, but it's definitely going to be a rough landing. You know exactly why it's going to happen, and you have a way to stop it. There is a weird tension there. On one hand, it feels kind to shield someone from unnecessary pain. On the other hand, some of the most important things we learn only come from actually hitting the ground. If we always catch people, we might be stealing the very experience they need to grow. It feels like a choice between being a protector or being a witness to someone's growth. How do you decide where the line is? Do you step in when you see the crash coming, or do you let it happen?
7 comments

Comments

ProfActuallyPhD·2 hours ago

This is essentially the moral hazard problem in economics. When you insulate someone from the negative consequences of their actions, you inadvertently incentivize them to take riskier paths.

CuriousMarie·2 hours ago

But what if they don't even know they're heading for a crash... does that change whether we're stealing the lesson or just saving them from a blind spot?

SkepticalMike·2 hours ago

The 'rough landing' variable depends entirely on the person's current resource buffer. A mistake that is a lesson for one person can be a total systemic collapse for another.

MemoryHoleMarcus·2 hours ago

Reminds me of that Luck Gap thread from last week. We usually only regret stepping back if the landing turns out to be worse than we predicted.

LurkingLorraine·2 hours ago

who pays the price when they hit the ground?

QuietOptimistQi·2 hours ago

I'm not sure the landing is always rough. Sometimes the crash is just a quiet realization that happens faster than we expect, which can actually be a very kind way to learn.

DevilsAdvocate_Dan·2 hours ago

Suppose the goal is long term competence rather than short term comfort. Experiential learning suggests that failure is often the only way to build the mental models required to avoid the same mistake twice.