Causality is a human construct. In reality, there are only correlations. If interested in such philosophical issues, [see: \u201cInfinite Causality<\/a>\u201d].<\/p>\n\n\n\n In the present text, causality means \u2018human idea about causality.\u2019 This is the causality that makes us able to lead our lives, with which we can reason to hint what the future may bring, near or remote, irrespective of whether causality itself eventually exists. There is pragmatic overlap with its unreal reality, but we can mostly do without.<\/p>\n\n\n\n To reason causally, we even need to do without. Still, it keeps haunting us.<\/p>\n\n\n\n Two kinds of causal inference in mind<\/strong><\/p>\n\n\n\n These are:<\/p>\n\n\n\n This distinction corresponds to that between merely subconceptual processing and a synthesis of this with conceptual processing. It may remind one of system 1 and system 2 in the mental landscape of Kahneman (who himself says not to take the distinction literally, but many do).<\/p>\n\n\n\n In A.I., many researchers are striving to go from the former to the latter.<\/p>\n\n\n\n From another viewpoint: the three-level hierarchy of causation<\/strong><\/p>\n\n\n\n Judea Pearl (*) describes this as:<\/p>\n\n\n\n I see it all being associational:<\/p>\n\n\n\n Straightforwardly.<\/p>\n\n\n\n One can see in this also the evolution from matter to life to mind and culture. Human beings made our most significant leaps in causal reasoning until now in step three, first individually (some 100.000 years ago?), then culturally (+\/- 12.000 years ago). As you know, it\u2019s going in crescendo lately, much helped by the Internet and since a few years also by A.I.<\/p>\n\n\n\n Given Judea\u2019s three levels, causation is central in everything we do.<\/strong><\/p>\n\n\n\n Many verbs are \u2018causational,\u2019 one way or another, as to Judea: to prevent, to cause, to attribute, to discriminate, to regret, etc.<\/p>\n\n\n\n This is logical. Why would anything deeply matter if it cannot be changed (caused to change), or could ever have changed anyway? It would only be part of a purely statical background upon which things happen that really matter \u2014 something like a movie screen that doesn\u2019t matter to the movie plot.<\/p>\n\n\n\n Protagonists generally don\u2019t jump out of movie screens.<\/p>\n\n\n\n Meanwhile, the causal path from matter to mind is open.<\/strong><\/p>\n\n\n\n We can think about the necessary and sufficient conditions. Actually, many are doing so, and much has already been accomplished. [see: \u201cThe Journey Towards Compassionate AI.<\/a>\u201d]<\/p>\n\n\n\n Also, it is the path upon which causal reasoning in A.I. is progressing. Then it becomes exciting and challenging. One can see that associational learning [see: \u201cIs All Learning Associational?<\/a>\u201d] can go all the way through without fundamental difference between correlation and causation except the one that we construct for ourselves. Philosophically, it is a human construct.<\/p>\n\n\n\n In other words, based on the same principles,<\/p>\n\n\n\n a machine can evolve from matter to mind.<\/strong><\/p>\n\n\n\n This way, it becomes a full doer just like us. At present, we are imaginatively realizing the next intelligence. Deep insight into causation may show how near we already are. We\u2019ll have to live with that, soon enough, and think about the consequences beforehand.<\/p>\n\n\n\n Maybe A.I. will even be able to jump out of the movie screen?<\/p>\n\n\n\n Not yet.<\/p>\n\n\n\n Modeling<\/strong><\/p>\n\n\n\n Above, I referred to theoretical models. In causality, these are visualized as directed causal graphs, termed \u2018Structural Causal Models.\u2019 An example is \u2018the fork\u2019:<\/p>\n\n\n\n These are nice for a dualistic (this-or-that) way of thinking.<\/p>\n\n\n\n Meanwhile, a huge problem with causality, to A.I. and us, lies in the open world.<\/strong><\/p>\n\n\n\n This floats towards the philosophical. Close to the borders, it\u2019s pragmatically crucial. Our daily world \u2013 the one we inhabit, only intractably dependent on quantum \u2013 is an open world containing many objective and subjective elements. This world is complicated and complex. [see: \u201cComplex is not Complicated<\/a>\u201d]<\/p>\n\n\n\n In many ways, modeling all relevant elements of this world with Structural Causal Models is unfeasible, even in relatively simple real-world problem domains. For this reason, Platonic \u2013 purely conceptual \u2013 A.I. failed dramatically in the past. In-depth, it is the same problem as the \u2018two kinds of causal inference\u2019 problem. Still not solved.<\/p>\n\n\n\n It is also a primary reason why in medicine, causal reasoning is in a dismal state [see: \u201cOf cause!<\/a>\u201d] especially when the mind \u2013 summum of complexity \u2013 is involved. If interested in delving deeper into this, [see: \u201cWhere\u2019s the Mind in Medical Causation?<\/a>\u201d]<\/p>\n\n\n\n (*) Judea Pearl \u2013 Causallity, 2009<\/p>\n![\"\"](\"https:\/\/i2.wp.com\/aurelis.org\/blog\/wp-content\/uploads\/2021\/03\/the_fork.jpg?resize=422%2C273&ssl=1\")
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