A lot of science deals with explanations. Predictive power comes as a spin effect from this goal. As expectations of forward precision increase social scientists are confronted with questions of accuracy. Minimizing error propagation in practical venues often requires a human touch. As Kauffman states (2008, pp 149);
Our incapacity to predict Darwinian preadaptations, when their analogues arise in our everyday life, demands of us that we rethink the role of reason itself, for reason cannot be a sufficient guide to live our lives forward, unkowning.The new scientist recently ran a major article discussing the limitations of conventional reason. It makes a good read for those who may just be getting into some of the standard arguments in this realm. However, I don't think any of the arguments are as strong as Kauffman's. They tend to be more about the application of reason more than fundamental limitations.
Kauffman's position in relation to reason , or at least conventional reductionist approaches to knowing, focusses on forward knowledge. His frequently restated position basically sums up to this:
- There is no lowest-level basement language of simple functionalities from which all possible higher future functionalities can be logically derived (pp. 153)
- We can not prestate all the variables required for prediction.
- Evidence points to emergence as a significant organizing characteristic.
- We live in a critical chaotic universe.
- Natural laws can not fully describe this reality.
- Reductionist approaches are incomplete.
- If we truly can't predict, then "the way a CEO lives his life and guides his company is a combination of rationality, judgment, intuition, understanding, and invention that goes far beyond the purview of normal science, and far beyond the normal purview of rationality and “knowing", (pp. 176).
- "We must come to see reason as part of a still mysterious entirety of our lives, when we often radically cannot know what will occur but must act anyway," (pp. 149).
This is a fairly significant proposal. At what point during investigation do we break the Galilean spell of conventional rationality? The arguments are really over practicality. The Dawkins and Dennetts contend that science is the best thing we have. It has features that resist corruption, enable common semiotics, and filter intuition. Its application, while containing some self-correcting features, is, however, susceptible to abuse. So, the debate really centers on maximization. How do you balance the viral corruptive capacity of our predictive powers with the errors of a rationally modeled universe?
I think the answer to that injunction is an unstable equilibrium. One needs to leverage the deity of inspiration and group-dynamics while cycling back to the reliability of science. However, our evolutionary history lead us to one valley or another. The cycling point is the power position. However such locations are unstable and highly susceptible to abuse. So, is it worthwhile? Again, I think insights from new religious movements are essential for informed opinion. The dynamics seem fairly analogous - controlling reality as experienced.
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Another way of looking at the science-religion debate and its prediction maximization is to frame some of the issues in terms of emergence. At what level are we forced to deal with the emergence of a phenomenon? Instead of reducing things beyond their predictive power, one could argue phenomenon should be dealt with as real, whole, entities.
For instance, leadership would be an emergent entity. We can certainly backwards state much of what it is, but forward leveraging is non-trivial. As Kauffman would argue, can you prestate all the variables associated with leadership?
Thus forward prediction should operate with leadership as an entity while backward explanations can operate with it reductively.
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