Causal Reductionism

Network Capital

Most outcomes are products of a complex arrangement of events. There is an interwoven thread of causality that leads to a given result. However, in most cases, our minds are not able to comprehend the complexity of a situation. This leads us to a singular and reductionist understanding of events.

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Popular perception is that the fourth Industrial Revolution will lead to scaled automation, rapid innovation and mass unemploy- ment. We have painted a gloomy picture for ourselves of tech- nological advancement at the cost of human replacement. This understanding is a typical case of causal reductionism. It reduces the complexity of the involved actors, events and outcomes of the fourth Industrial Revolution to the loss of existing jobs. By doing so, among other things, it ignores the possibility of creation of new industries and jobs.

Will AI lead to job losses?

Of course. Are the number of jobs in the world finite? Of course not. In the years to come, we will witness a reduction in the number of institutional jobs but a massive addition of jobs where people monetize their individual stories and skills.Similarly, in interpersonal relations and small groups, we are quick to presume that Y did X because Z happened. We superficially ascribe a ‘proximate’ cause. This form of thinking is most com- monplace in the aftermath of a tragedy or in explaining an unusual incident. It reduces a complex chain of events into narrow fallacy. Casual reductionism in such cases comes most prominently in the form of blame or arbitrary supposition.To avoid casual reductionism, we need to sharpen our ability to think objectively and rationally. As a rule of thumb, we should, (a) Never oversimply and (b) Always look at the conjoint possibilities.
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