@Systems Innovation In truth then we can always trace back the Linear End Effect to a multitude of Non Linear Cause & Effect Cycles which ultimately lead us back to our original Linear Beginning Cause. To illustrate this statement we may simply imagine a person throwing a pebble into a body of water: *[Beginning: Cause]* Person throws rock into water. | | | *[Middle: Non Linear Cause and Effect Cycles]* Ripples form, Fish scatter, splashing sound created, etc. | | | *[End: Effect]* Thrown rock makes contact with water. So then what appears to be a string of unrelated alternating cause and effect chains by analysis, are actually, in sum, a single effect traceable to a single cause through synthesis.
It could be that our nonlinear biological, social processes of perception and analysis sometimes align with certain other nonlinear processes in such a way that it produces a linear process.
Systems with feedback can be modeled using Dynamic Bayesian Networks. In the example of the plane in flight, all the reasons given both in 'linear' and 'nonlinear' causality are causes, which can be represented as parent nodes of the 'plane in flight' node in a Bayesian Network. Criticisms: 'Emergence' in this video seems like a synonym for an effect that has more than one cause. But since most, if not all, effects have more than a single cause, why call them emergent? The distinction between 'top down' or 'bottom up' causation seems like a distinction between the literal size of causal entities (small DNA vs large biosphere, small atoms vs large stars), and the usefulness of that distinction isn't clear. Also, why would interaction between large and small entities give rise to indeterminism? The biggest problem with this video is the false equivalence between "events in the future" and "past beliefs about the future". The beliefs people hold about the future causally influence a system, but the actual events in the future do not. Events in the future do not reach back in time and cause events in the past, which is what this video implies with "reverse causation".
It depends on if they are being produced by a system that is aware of there being goals. My goals are real enough; they exist as a belief in my head. Though you could reductively argue that goals don’t exist “out there,” it is hard to see how they do not exist as motivating factors in my mind.
I agree. It seems to be more like linear with non-linear place holders, such as memory, a model, or some non-data factor that modifies a system as it progresses forward in time. Otherwise non-linear seems to be a claim of actual time travel, rather than the practical time travel that memory and imagination affords.
4:30 - Either this is a terrible example or non-linear causality is a bad joke. Just take a reductionist approach and simply SPECIFY the question being asked. Now look at that! All these other possible causes have been reduced, since we ceased asking too broad a question. Though we also note that in finding every possible explanation as to why the plane is flying, we reduced this sytem of flight to its components anyway (in the form of different qualitative causes).
I think the flight example is misleading, depending on how you approach it. If you ask the question, why does an Emirate A380 fly from LA to Sydney ? yes there are several reasons that enable it besides aerodynamics, which i think is the point of systems thinking/ holism. But if you ask the question, Why does flight occur ? The reductionist approach yields the primary reason for flight which is found in aerodynamics. In this case, none of the other factors matter.
@@jasim3839 No. No matter how much you try to simplify the question, the amount of answers or contributing factors are essentially limited only by your understanding of reality and physics.
Jasim Ahamed you seem to be suggesting that the range of the question we choose to ask determines the limits of causation. Shouldn’t we be considering all possible causal chains at least on some level? I mean, I think I see what you mean. The other causal chains do not directly relate together abstractly but only in a practical way: they all pertain to a specific plain. However, it seems clear that practical considerations are important and this is a model for dealing with that.
@Systems Innovation In truth then we can always trace back the Linear End Effect to a multitude of Non Linear Cause & Effect Cycles which ultimately lead us back to our original Linear Beginning Cause. To illustrate this statement we may simply imagine a person throwing a pebble into a body of water:
*[Beginning: Cause]*
Person throws rock into water.
|
|
|
*[Middle: Non Linear Cause and Effect Cycles]*
Ripples form, Fish scatter, splashing sound created, etc.
|
|
|
*[End: Effect]*
Thrown rock makes contact with water.
So then what appears to be a string of unrelated alternating cause and effect chains by analysis, are actually, in sum, a single effect traceable to a single cause through synthesis.
i wonder if, on a deeper scale; everything is nonlinear, and we only perceive some things as linear because we cant grasp the total concept.
My money is on a nonlinear universe, and linear causation as just a human cognitive lens
It could be that our nonlinear biological, social processes of perception and analysis sometimes align with certain other nonlinear processes in such a way that it produces a linear process.
Good material as usual.
I wish our high schools and colleges taught a lot of the ideas in these videos.
This should be mandatory learning in 9th grade
Systems with feedback can be modeled using Dynamic Bayesian Networks. In the example of the plane in flight, all the reasons given both in 'linear' and 'nonlinear' causality are causes, which can be represented as parent nodes of the 'plane in flight' node in a Bayesian Network.
Criticisms:
'Emergence' in this video seems like a synonym for an effect that has more than one cause. But since most, if not all, effects have more than a single cause, why call them emergent?
The distinction between 'top down' or 'bottom up' causation seems like a distinction between the literal size of causal entities (small DNA vs large biosphere, small atoms vs large stars), and the usefulness of that distinction isn't clear. Also, why would interaction between large and small entities give rise to indeterminism?
The biggest problem with this video is the false equivalence between "events in the future" and "past beliefs about the future". The beliefs people hold about the future causally influence a system, but the actual events in the future do not. Events in the future do not reach back in time and cause events in the past, which is what this video implies with "reverse causation".
thanks for all the systems videos. i learn every day
Thank you. Clear, Simple, Interesting. Although, just like how causality is vague and emergent, "goals" are probably not real things either!
It depends on if they are being produced by a system that is aware of there being goals. My goals are real enough; they exist as a belief in my head. Though you could reductively argue that goals don’t exist “out there,” it is hard to see how they do not exist as motivating factors in my mind.
Nonlinear seems a misnomer. Seems to me it would more apt called multi linear effect
I agree. It seems to be more like linear with non-linear place holders, such as memory, a model, or some non-data factor that modifies a system as it progresses forward in time. Otherwise non-linear seems to be a claim of actual time travel, rather than the practical time travel that memory and imagination affords.
The future is dynamic in the present
I think correlation is for reductionism and causation for system thinking
chicken and the egg on expert mode
4:30 - Either this is a terrible example or non-linear causality is a bad joke. Just take a reductionist approach and simply SPECIFY the question being asked. Now look at that! All these other possible causes have been reduced, since we ceased asking too broad a question. Though we also note that in finding every possible explanation as to why the plane is flying, we reduced this sytem of flight to its components anyway (in the form of different qualitative causes).
Is the question too broad because there were many causes? Or were there many causes because the question was too broad?
I think the flight example is misleading, depending on how you approach it. If you ask the question, why does an Emirate A380 fly from LA to Sydney ? yes there are several reasons that enable it besides aerodynamics, which i think is the point of systems thinking/ holism. But if you ask the question, Why does flight occur ? The reductionist approach yields the primary reason for flight which is found in aerodynamics. In this case, none of the other factors matter.
@@jasim3839 No. No matter how much you try to simplify the question, the amount of answers or contributing factors are essentially limited only by your understanding of reality and physics.
Jasim Ahamed you seem to be suggesting that the range of the question we choose to ask determines the limits of causation. Shouldn’t we be considering all possible causal chains at least on some level? I mean, I think I see what you mean. The other causal chains do not directly relate together abstractly but only in a practical way: they all pertain to a specific plain. However, it seems clear that practical considerations are important and this is a model for dealing with that.
Linear causation is a misconception