[HN Gopher] Actual Causality (2016)
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Actual Causality (2016)
Author : Tomte
Score : 43 points
Date : 2020-03-16 18:32 UTC (4 hours ago)
(HTM) web link (www.cs.cornell.edu)
(TXT) w3m dump (www.cs.cornell.edu)
| xtacy wrote:
| I think this is a very important area with applications to legal
| issues; in the computer systems domain, a close application I can
| think of is troubleshooting / root-cause analysis.
|
| In legal situations and troubleshooting alike, one is often
| interested not in the "general" causes of why things happen
| (e.g., an increase in load will contribute an increase in
| latency), but causes that explain specific cases (e.g., the
| increase in latency on this incident was because of an increase
| in file system latency at the backend.)
|
| These concepts are quite interesting; one linked article
| discusses many variations and refinements in detail:
| https://plato.stanford.edu/entries/causation-law/. I found these
| useful mental models to organize my thoughts when troubleshooting
| systems and doing root-cause analysis:
|
| - But-for cause: We can say that A is the actual cause of B when
| the following holds: If not for A, not B. To avoid pathologies
| like "If not for _big bang_ , this B wouldn't have happened", we
| have ...
|
| - Proximal cause: In the causal chain of explanations: If not for
| A1, not A2; if not for A2, not A3, ..., the proximal cause of
| A(k) is the closest, i.e., A(k-1).
|
| - Necessary element of a sufficient set (NESS criterion): Things
| get interesting here if we need a conjunction of many events to
| happen simultaneously for a desired effect. For simplicity,
| assume that events are boolean, and causal relationships can be
| defined using boolean formulae. Here, A is a cause of B in the
| NESS sense, when B = (A and C1) OR (C2 and C3) OR ... A here is
| "necessary" in the sufficient set {A, C1} for B to happen.
| juskrey wrote:
| A book on casualty with no any single hint on mutual
| information.. hm
| jpt4 wrote:
| Intermittently 404.
| dropalltables wrote:
| Thanks for sharing. I'm a sucker for anything advancing causal
| reasoning amongst technical folks :)
| adaszko wrote:
| Me too! Any other resources you can share?
| alexhutcheson wrote:
| Marc Bellemare's Metrics Mondays posts are pretty good:
| http://marcfbellemare.com/wordpress/metrics-mondays
|
| Lots of practical tips for causal inference on real data.
| [deleted]
| dwheeler wrote:
| Thanks for the link, I've started reading it.
|
| The complexity of defining and determining "actual causality" is
| a good justification for mathematicians' avoiding the whole thing
| and using material implication instead. As most of you already
| know, material implication A -> B ("A implies B") is a boolean
| operation, which is the same as ((not A) OR B), see
| https://en.wikipedia.org/wiki/Material_implication_(rule_of_... .
| Material implication avoids all this complexity.. but because
| it's simpler, it _cannot_ by itself represent our notions of
| causality. Material implication even has some "weird" surprises,
| e.g., "All Martians are green" and "All Martians are not green"
| are both true when defined using material implication. I created
| an "allsome" quantifier to deal with this problem:
| https://dwheeler.com/essays/allsome.html . But it'd be nice to
| learn about other alternatives, so I started reading this.
|
| I've only started reading this book, but the approach does seem a
| little odd. Its definition of causality embeds a model, which has
| embedded causality in it. In section 2.1
| https://www.cs.cornell.edu/home/halpern/papers/causalitybook...
| it notes this issue: "It may seem somewhat circular to use causal
| models, which clearly already encode causal relationships, to
| define causality. There is some validity to this concern...
| Nevertheless, I would claim that this definition is useful."
|
| I don't have a better idea, and I can see the value in making the
| use of models clear. But it does seem to weaken the idea of
| defining causality. Is this considered reasonable? Is there a
| possibly better approach?
| [deleted]
| 6gvONxR4sf7o wrote:
| I'm familiar with the usual potential outcomes framework, and
| some of the high level machinery of Pearl's version too, but this
| 'type causality' vs 'actual causality' mentioned in the intro
| seems like a very unnecessary complication that just confuses
| things.
|
| They use "smoking causes lung cancer" as an example of type
| causality. A counterpart in actual causality would be "Dave's
| smoking caused him to get lung cancer." Then they go on to talk
| about how these are such different kinds of causality.
|
| They're no more different than "Dave has $35 in his pocket" and
| "the average american has $21 in their wallet."
|
| Seems totally unnecessary. Am I missing something?
| xtacy wrote:
| The distinction serves a real and practical purpose, as
| mentioned in the introduction: responsibility/blame assignment.
|
| In legal situations, this blame assignment is critical as it
| helps identify who is actually responsible for some bad
| outcome.
|
| Would you agree?
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