 Causality describes a relationship between two or more things where a change in one thing causes a change in another. The essence of causality is a phenomena being dependent on some other effect. As such, causality is a connection or linkage between states or events through which one thing, the cause, under certain conditions, gives rise to or causes something else, what we call the effect. Causality forms a fundamental and pervasive part of our perception and interpretation of the world around us. Equally, our ability to act in the world depends upon our grasp of causal relationships between things, that is to say the way things act and interact. In everyday life, humans and other animals rely on the assumptions of causality, literally every waking second. And in academia, much of science is a study of systematic cause and effect relations. Perceived causality involves the process of inductive inference. The basic process of induction is one of inference from a set of things that have something in common to generalizing what we observe about them as being true for all instances of that kind. We generalize from a sample of previous experiences to a whole population. We project past uniformities in our experience onto future events through expectations. We've seen a ball move off in the opposite direction every time that it was hit with a bat in the past, so we assume it will be the same in the future and this assumption through inductive inference creates the perception of there being a causal relationship between things. Thus although cause and effect appear a central characteristic of our world, they are in fact simply associations that we make between events. The philosopher David Hume illustrated how there are no necessary connections between events in the world. In his words, all events seem entirely loose and separate. One event follows another but we can never observe any tie between them. They seem conjoined but never connected. We perceive cause and effect and then extrapolate from that to infer cause and effect relations about things that we cannot see such as black holes, subatomic particles or events in the future. Of course when we generalize we're going beyond the evidence by the definition of generalizing. Our conclusion covers things that we have not or cannot know. The rising and setting of the sun in the past cannot guarantee it will rise and set tomorrow. Conceptions of causality can be roughly divided into linear and non-linear. Linear causality is the idea that cause and effect follow a single direction between events. From A the cause to B the effect and that for every effect there is a single or limited number of causes. Non-linear causality is the idea that causality may follow a bidirectional path from A to B or from B to A or even both at the same time and that there may be an unlimited number of causes for a given effect. With linear causality there is seem to be a direct link between cause and effect. Cause precedes effect in a sequential pattern. Linear causality has a clear beginning and a clear end. There is one or a limited number of causes for any given effect. Additional linkages of causes or effects create a line or a sequential domino pattern of causality. The central ideas behind linear causality are captured in what is called the axiom of causality. The axiom of causality is the proposition that everything in the universe has a cause and is thus an effect of that cause. This means that if a given event occurs then it is the result of a previous related event. If an object is in a particular state then it is in that state as a consequence of another object interacting with it previously. The philosopher Plato stated this when he wrote in addition everything that becomes or changes must do so owing to some cause for nothing can come to be without a cause. The three criteria for establishing linear cause and effect are correspondence, time precedence and non spuriousness. The first step in establishing linear causality is in demonstrating correspondence or association. This means asking the question is there a relationship between the independent variable and the dependent variable. Correspondence or correlation means that the cause and effect occur within the same unit of analysis. For example, if being exposed to the cold is more likely to make you sick then people who are exposed to the cold should be more often ill. Time precedence means that the cause must occur before the effect. If one wants to say that being well educated causes one to earn a higher salary then the cause of being educated must precede the effect of earning a higher salary. A spurious or false relationship exists when what appears to be associations between the two variables is actually caused by a third extraneous variable. This is captured in the saying correlation does not imply causation a phrase used to emphasise that a correlation between two variables does not mean that one causes the other. For example, a false correlation might be drawn between the amount of ice cream sold and the sale of sunglasses. There is a hidden variable of temperature that is causing both to change together without there being a direct cause and effect relation between them. This linear causality is a keystone of the analytical reductionist approach and searching for these linear cause and effects has formed a central part of modern science. This process of inquiry is conducted by defining a closed system and then isolating it from its environment to control variables. Cause and effect interactions are searched for as an explanation for how elements in the system behave. Within this paradigm cause and effect relations are seen to move in one direction that is from the bottom up and not the reverse direction. Lower level phenomena are seen to cause higher level events. For example, in asking why the body functions as it does we would refer to the internal constituent parts of the organs and tissues to derive an upward causal relation instead of looking for a cause within the system's environment which would be a form of downward causation. Linear causality equally leads to the conception of determinism in that it defines a closed system and reduces the number of causes to a limited set acting in a single direction. Reductionism and linear causality try to reduce the cause of an effect to a single or limited number of determinants and the fewer the number of component determinants that we identify the greater the determinism will be. Nonlinear causality sees causation as flowing in a bidirectional or multidirectional pattern. Nonlinear causality involves cyclical processes where one thing impacts another which in turn impacts the first. Although this chain of events leading to feedback may be mediated through several events or take place over a prolonged period of time. Nonlinear causality is part of the holistic synthetic paradigm that looks at systems within their context or environment as such it is much more focused on downward causation whether are many or even possibly an infinite number of interacting variables. The holistic paradigm posits that effects can be the product of a great many causes to gain a full understanding of the effect we need not drill down to find a single cause but instead look at multiple different factors and how they interact to give rise to the outcome as an emergent phenomenon. Whereas in the linear model the relationship between cause and effect is seen to derive from one of the components affecting another. Within the systems thinking approach it is the relationship between the parts that is seen to create the effect. For example from this perspective it is not that one chemical substance causes another to react in a particular way. It is in fact the type of relationship between them that generates the emergence of a particular outcome and thus there is no direct cause and effect. It is instead an emergent phenomena of a relationship of interdependence. With nonlinear causality cause and effect can flow in both directions through time. However this requires information and some kind of control system being involved. Purely physical processes result in a unidirectional flow to causality from the past to the future and not the other way around. But once there is a control system involved this can define some future desired state, the system's goal and then this can affect events in the present based upon information about the future. For example whether I spend lots of money now may be contingent upon whether or not I think I will get paid at the end of the week. Thus with nonlinear causality causes for events may be derived at least partially from the future. But this would only appear to be possible under the condition of goal orientated behavior where current events are conditioned and controlled by projections surrounding some goal in the future. In a coming video we'll dig further into nonlinear causality as we talk more about indeterminism, downward causation and equifinality.