# All of X No-Archive's Comments + Replies

Limiting Causality by Complexity Class

Maybe I'm confused or misinterpreting. The first sentence of your first paragraph appears to contradict the first sentence of your second paragraph.  The two claims seem incommensurable.

The first sentence of your first paragraph appears to appeal to experiment, while the first sentence of your second paragraph seems to boil down to "Classically, X causes Y if there is a significant statistical connection twixt X and Y."

Several problems with this view of causality as deriving from stats. First, the nature of the statistical distribution makes a ... (read more)

3Bunthut1y
No. "Dependence" in that second sentence does not mean causation. It just means statistical dependence. The definition of dependence is important because an intervention must be statistically independent from things "before" the intervention. These are methods of causal inference. I'm talking about what causality is. As in, what is the difference between a mere correlation, and causation? The difference is that the second is robust to intervention: if X causes Y, then if I decide to do X, even in circumstances different from those where I've observed it before, Y will happen. If X only correlates with Y, it might not.
Unpopularity of efficiency

A thoughtful discussion of efficiency. Points for metacognition: "If efficiency has really earned its poor reputation, I wonder if I should be more worried about this."

This discussion seems (to me) to conflate a number of issues that it seems to me should be separated, in the manner of a scalar getting substituted for a vector, or, even better, a dynamic vector field (i.e., tensor).

Issues conflated seem to me (I could be wrong) to include:

[1] Substitution of mathematical optimization for human values -- the difference twixt quantity and quality. Is this an... (read more)