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*[[What Are Things?]]
 
*[[What Are Things?]]
 
*[http://www.richardcarrier.info/archives/12390 All Godless Universes Are Mathematical]
 
*[http://www.richardcarrier.info/archives/12390 All Godless Universes Are Mathematical]
  +
*contrary to "lawless science", [https://www.chemguide.co.uk/physical/energetics/definitions.html look at how much context] is described for scientific laws
 
*treatise by Judea Pearl, ''Causality: Models, Reasoning, and Inference'' (Cambridge University Press, 2000):
 
*treatise by Judea Pearl, ''Causality: Models, Reasoning, and Inference'' (Cambridge University Press, 2000):
 
*: "a comprehensive exposition of modern analysis of causation. It shows how causality has grown from a nebulous concept into a mathematical theory with significant applications in the fields of statistics, artificial intelligence, philosophy, cognitive science, and the health and social sciences [including business, epidemiology and economics]. Pearl presents a unified account of the probabilistic, manipulative, counterfactual and structural approaches to causation, and devises simple mathematical tools for analyzing the relationships between causal connections, statistical associations, actions and observations. This book will be of interest to professionals and students in a wide variety of fields. Anyone who wishes to elucidate meaningful relationships from data, predict effects of actions and policies, assess explanations of reported events, or form theories of causal understanding and causal speech will find this book stimulating and invaluable."
 
*: "a comprehensive exposition of modern analysis of causation. It shows how causality has grown from a nebulous concept into a mathematical theory with significant applications in the fields of statistics, artificial intelligence, philosophy, cognitive science, and the health and social sciences [including business, epidemiology and economics]. Pearl presents a unified account of the probabilistic, manipulative, counterfactual and structural approaches to causation, and devises simple mathematical tools for analyzing the relationships between causal connections, statistical associations, actions and observations. This book will be of interest to professionals and students in a wide variety of fields. Anyone who wishes to elucidate meaningful relationships from data, predict effects of actions and policies, assess explanations of reported events, or form theories of causal understanding and causal speech will find this book stimulating and invaluable."

Latest revision as of 23:50, 4 October 2018

Aside from the obvious ("they happen due to the laws of physics!").  Right now this is one of my most scatterbrained pages...

Full-system causality

Basically: one moment of the universe causes the next moment.

All the variables have to be within certain parameters for the future to be a certain way.

All the variables, an example

A person getting a basketball into a net.

The variables most people will think of are about the person's skill and throwing.

But let's look at all the variables (we don't have time or room to list literally all the variables, but we can look at many of them):

  • the air (is there a sudden gust of wind? is the path to the net blocked by a wall? does the air pressure change and crush or explode the ball?)
  • concentration (does the person suddenly get a pang of headache, distracting their throw?  Is there a sudden distracting noise?  Is their mind just wandering?)
  • the net (does it move? how big is it? does it change size?)
  • gravity (does the force of gravity acting on the ball change and deflect the flight?)
  • birds (do birds come and collide with the ball?)
  • other people (do other people block the shot? with their hands, or by throwing objects at the ball?)
  • the ground (does the ground give away and thus move the net?)
  • history (does this person have a history of injury?  of skilled training? is the net damaged and too weak to stand for much longer?)

You could imagine these things causing the player to miss the net.  But they could also technically interfere in a way to make a shot succeed that would have otherwise missed.

Thus all of these variables, and others, come together into one event.  The whole produces the result.

The conceptual split between individual and context

The same hand motion has different result depending on whether it is holding a gun or not.  The human (the individual) could literally be doing the same muscle movements, but have a different result depending on where in space a gun is positioned (the context surrounding the movements). And different results if it is pointing through mere air to a person, than if it is pointing through a bulletproof wall to the same person.

Conceptually and semantically, many times when we talk about someone doing a certain action (for example, shooting a gun) that one action is composed of both the individual (their body) and the context around the individual (the gun in their hand). And both are required as causes for the result.

Responsibility

"Who is responsible?"

Arguments about who is responsible

Often there are disputes where one side sticks to one extreme ("the individual is responsible") while the other side clings to the other extreme ("the context is responsible").  But both the individual and the context must work together to cause any outcome.  So, talk of "responsability" isn't merely about how something was caused.  Things are always caused by both the individual and the context.  What must be determined in such arguments is much more about which of the variables we should change to get a correct result, and in what ways.  Notice that we could change any of the variables in order to change the result.  But which of them should change to get a correct result, and in what ways?

Different ways to achieve "the same outcome"

An earthquake could cause something on my desk to fall off.  Or a cat could push it off.  Or I could push it off.  Etc.

See also:  Rube Goldberg Machines.

I visualize a spectrum (or multidimensional space). Seems that any point on the spectrum can result in the same outcome.  Though not with equal real-world probability, nor will all the outcomes be completely the same.

As an example of a "spectrum", think of the earthquake and accidentally nudging a desk, with the outcome being a cup falling off the desk. One end of the spectrum is when only the earthquake occurs, I don't nudge the desk, and the cup falls off. The other end of the spectrum is where no earthquake occurs, but I bump the desk severely enough for the cup to fall off. In the middle of the spectrum, my nudge moves the cup halfway (50%), moments later an earthquake moves the cup the rest of the way (50%), and then as the cup falls the earthquake coincidentally ceases. Any less earthquake (or any less nudge) and the cup would have been spared. But at all points on this spectrum, the end result is that the cup falls off the desk. Perhaps even landing on the exact same spot on the floor.

Different outcomes from "the same action"

See "the conceptual split between individual and context" above. The same finger motion has a different result depending on whether or not it is beside the trigger of a gun.

Or, back to the cup on the desk example, you could have all the same nudges of the desk from me and from the earthquake as before (all the "same" actions), but the cup would never fall if it was further away from the edge of the desk (different outcome).

In reality, no two things that we say are the same are ever actually identical.  There are always tiny shifts in variables here and there, or even vast shifts in some variables that are just not mentioned by our description.

Control Systems Theory

Both Feed-Forward ("ballistic") and Feedback control systems.

Positive feedback loop

for example:  "more of A produces more of B, which in turn produces more of A".

Movies that give some philosophy of causality

The Matrix, specifically the things that The Oracle causes.  Would you still have knocked over that plant if I hadn't said anything?  By saying something about the future, she changed/caused the future.

Kung-Fu Panda:  the Dragon Warrior realizes something about causality (belief can cause results which then cause the belief to seem true), and is able to always cause a favorable outcome in battle despite unfavorable contexts in battle.  In real life, I'm pretty sure this kind of thing gets used as an excuse by woo peddlers so that they don't feel like they are lying when, really, they are lying.

Mr. Magorium's Wonder Emporium:  more "believe in yourself" type stuff, similar to Kung-Fu Panda.

The song "There Must Be Something More" in Charlotte's Web basically points out that relationships/friendships are a kind of emergent phenomenon ("more than the sum of the parts").

Sort of related: the final episode of Star Trek The Next Generation featured a reference to the question "which came first, the chicken or the egg", and seemed to feature causality backwards in time. The epilogue of the episode features Picard joining a social event (poker), commenting "I should have done this years ago", and being told "you were always welcome to". This isn't directly about causality, rather it's a point about social causality (see also, feedback loops).

See also

  • What Are Things?
  • All Godless Universes Are Mathematical
  • contrary to "lawless science", look at how much context is described for scientific laws
  • treatise by Judea Pearl, Causality: Models, Reasoning, and Inference (Cambridge University Press, 2000):
    "a comprehensive exposition of modern analysis of causation. It shows how causality has grown from a nebulous concept into a mathematical theory with significant applications in the fields of statistics, artificial intelligence, philosophy, cognitive science, and the health and social sciences [including business, epidemiology and economics]. Pearl presents a unified account of the probabilistic, manipulative, counterfactual and structural approaches to causation, and devises simple mathematical tools for analyzing the relationships between causal connections, statistical associations, actions and observations. This book will be of interest to professionals and students in a wide variety of fields. Anyone who wishes to elucidate meaningful relationships from data, predict effects of actions and policies, assess explanations of reported events, or form theories of causal understanding and causal speech will find this book stimulating and invaluable."