Autor: Melchin, R. Kenneth

Buch: History, Ethics and Emegent Probability

Titel: History, Ethics and Emegent Probability

Stichwort: Einsicht; Abstraktion, inverse Einsicht; Sein: systematische Interrelationen; Zufall: Mangel an hinreichenden Daten; statistisches Wissen

Kurzinhalt: ... the inverse insight grasps the absence of an intelligibility which previously was expected to be present; ... randomness ... is merely an illusory appearance resulting from insufficient data

Textausschnitt: 20/3 Before going on to consider some of the problems associated with inverse insights and with randomness that are treated by McShane in Randomness, Statistics and Emergence it might be helpful to note here that there is a kind of inverse intelligence corresponding to every direct insight. The term 'abstraction' is often taken to refer to an act of intellect whose performance results in a unified experiential manifold being wrenched apart or torn from its proper context for the purposes of empirical or analytic scrutiny. The image associated with the term might be that of a student of biology dissecting a frog without any regard for the wonder of life. Or perhaps the term might evoke the image of a 'scholar' making up his mind (usually the image is of a male) on what the world is like or on what it ought to do, in 'abstraction' from any real concrete, detailed knowledge of human experience. It is certain that far too many examples of either image can be found in our world of experience. But let us consider for a moment another, not so popular meaning for the term 'abstraction.' Here the image might be that of a mechanic troubleshooting a failure in the electrical system of a car. When the solution is found the diagnosis 'abstracts' from all the aspects of the car's operation which were not relevant to an understanding of the malfunction. The abstraction, in this case, is an enrichment in understanding and not an impoverishment. And the enrichment involves both the fact that the relevant data on the car's malfunction were identified and correctly interrelated and the fact that the irrelevant data were rejected. Anyone who has needlessly paid seventy dollars for a new battery only to find that the problem was a defective starter motor is in a good position to appreciate this difference between relevant and irrelevant data (and thus this 'enriching' sense in which Lonergan uses the term abstraction).1 (68; Fs)

21/3 Corresponding to every direct insight there would seem to be a kind of inverse intelligence which rejects those elements in experience which are not relevant to the insight. And so the very possibility of any act of intelligence, in this analysis, would seem to rest upon the capacity of intellect to select and interrelate, on the one hand, and, on the other, to reject as irrelevant, at the same moment, data which do not constitute a part of the unity that is the insight. The distinctive feature of the inverse insight, then, would be not that it represents a departure from what usually occurs in a direct insight, but that it involves a focus upon something that is essentially but not obviously present with a direct insight.1 However this focus comes as a surprise in the case of the inverse insight because, unlike the inverse dimension to the direct insight, the inverse insight grasps the absence of an intelligibility which previously was expected to be present. (68; Fs)

22/3 The first chapters of Randomness, Statistics and Emergence are devoted to raising and answering questions about the objects of inverse insights, non-systematic or random relations in data. And this discussion inevitably leads into the distinctions between a naive realist and a critical realist cognitional theory.1 For the purposes of this introduction I will state here simply that Lonergan's cognitional theory affirms that knowing does, in fact, know reality but that knowing reality and experiencing reality are two different but inevitably interrelated ways of relating to reality. Thus the question that Lonergan poses is always the 'nature' of knowing and its relative correspondence with reality. It is never the question as to 'whether' knowledge ever 'knows reality.'2 (68f; Fs)

23/3 One of the prevailing theories on statistical knowledge discussed in Randomness affirms that there exists no objective correlate in being for an inverse insight. The whole of being is systematically interrelated. Knowledge is only of 'classical' laws (laws which express a unified set of direct insights). And thus randomness, or the absence of a systematic, intelligible unity to data or to a process is merely an illusory appearance resulting from insufficient data. Hence statistical knowledge, knowledge which paradoxically grasps a sort of 'intelligibility' in randomly occurring events, is merely an imprecise substitute for complete knowledge of systematic relations.1 (69; Fs) (notabene)