<p>It is frequent to find statistical studies observing some correlation between two events; this correlation is often interpreted by the medias as a causality relation (e.g. "blue-eyed people have more kids" or "obese people have more chronic diseases") although most often there is little scientific support in favor of one causality relation rather than the other. So the reasonable conclusion is that these studies can only observe "correlation" but not "causality". Now suppose that a correlation between two events $A$ and $B$ could be interpreted not as a binary causality (e.g. $A$ implies $B$) but as a ternary relation involving an unobservable "cause factor" trigerring an observable "correlation" (e.g. $K$ implies $A$ and $B$).</p>

<p>This leads to some basic questions that might have some connection with computer science / graph theory. First, even if we cannot detect the "cause factor", can we distinguish experimentally between the above two scenarii? Second, is it still possible to prove "causality" with a more fine-grained knowledge of reality, or do we have to abandon it completely? I guess this second question hinges on physics and philosophy, as it depends on the assumed model of physical reality -- for instance causality makes sense in a deterministic, sequential world but maybe not in some alternate models involving quantum theory and branes ??-</p>

<p>(NOTE ADDED: I expect that my answer will be labeled as "off-topic" but there might still be some cross-disciplinary people interested in it)</p>

CC BY-SA 3.0
2014-03-23T15:08:49.190Z
You might check out the foundational work of Judea Pearl on causality, but I don't know the right reference (maybe someone else will).
usul
CC BY-SA 3.0
2014-03-23T21:41:58.503Z
If you have a philosophy or physics question you can ask them on [philosophy.se] or [physics.se]. What is your TCS question?
Kaveh
CC BY-SA 4.0
2021-03-13T00:56:31.940Z
@Kaveh， could we be open-minded to this question, it is really relating to computability
XL _At_Here_There
<big-picture>
Observable correlation vs non-observable causality
NisaiVloot
# Observable correlation vs non-observable causality

(Asked by: username_0 on 2014-03-23)

It is frequent to find statistical studies observing some correlation between two events; this correlation is often interpreted by the medias as a causality relation (e.g. "blue-eyed people have more kids" or "obese people have more chronic diseases") although most often there is little scientific support in favor of one causality relation rather than the other. So the reasonable conclusion is that these studies can only observe "correlation" but not "causality". Now suppose that a correlation between two events $A$ and $B$ could be interpreted not as a binary causality (e.g. $A$ implies $B$) but as a ternary relation involving an unobservable "cause factor" trigerring an observable "correlation" (e.g. $K$ implies $A$ and $B$).

This leads to some basic questions that might have some connection with computer science / graph theory. First, even if we cannot detect the "cause factor", can we distinguish experimentally between the above two scenarii? Second, is it still possible to prove "causality" with a more fine-grained knowledge of reality, or do we have to abandon it completely? I guess this second question hinges on physics and philosophy, as it depends on the assumed model of physical reality -- for instance causality makes sense in a deterministic, sequential world but maybe not in some alternate models involving quantum theory and branes ??-

(NOTE ADDED: I expect that my answer will be labeled as "off-topic" but there might still be some cross-disciplinary people interested in it)

**Tags:** big-picture
> **Comments:**
> **username_1**: You might check out the foundational work of Judea Pearl on causality, but I don't know the right reference (maybe someone else will).  
> **username_2**: If you have a philosophy or physics question you can ask them on [philosophy.se] or [physics.se]. What is your TCS question?  
> **username_3**: @Kaveh， could we be open-minded to this question, it is really relating to computability  

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## 0 answers

