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Methodological Naturalism, Methodological Theism, and Regularism
No full textScientists typically justify methodological naturalism on grounds that the supernatural (or extra-natural) is not testable, that admitting the supernatural (or extra-natural) into science would undermine scientific methodology and reasoning processes, and that methodological naturalism has been demonstrated to be effective. These admitted virtues of methodological naturalism are strongly associated, however, with unscientific metaphysical assumptions which tend to dominate scientific thinking even if they do not follow necessarily from methodological naturalism's assumptions. For that reason a metaphysically neutral alternative is called for, one that retains methodological naturalism's virtues while discarding its associated unscientific assumptions. Regularism, defined merely (and intentionally quite simply) as "the methodological expectation of reliable regularity of cause and effect in nature," fits these criteria, and is recommended as a superior alternative to methodological naturalism
Other Non-Naturalistic Methodologies in Modern Practice
No full textSome fields already incorporate alternatives to methodological naturalism. However, few people outside the field are familiar with these alternatives or how they are used. Sometimes these non-naturalistic methodologies are being used without the participants' cognizance that the methodology is not methodologically naturalistic. Here, we show a smattering of fields that we are aware of that have touched upon methodologies that don't depend on naturalism
The Relationship of Bacon, Teleology, and Analogy to the Doctrine of Methodological Naturalism
No full textFrancis Bacon divided natural science into physics and metaphysics. He claimed that of Aristotle’s four causes, only material and efficient causes belong to the realm of physics, and that final causes, or teleological claims, belong to the realm of metaphysics. Bacon objected to including teleology in physics because in his experience teleological claims tended to discourage the search for efficient causes for natural phenomena. Because Bacon relegated teleology to metaphysics science largely followed his lead, evolving over the next four hundred years a growing distaste for including any teleological implications in scientific explanations. Bacon claimed that human nature, ``will yet invent parallels and conjugates and relatives, where no such thing is.''
Yet, as the material and efficient causal discoveries by science have progressed since Bacon’s time, they have in turn revealed more legitimate parallels and conjugates and relatives than perhaps he could have ever imagined. Stated succinctly, the process of exploring material and efficient causes in nature has also given breathtaking justification for also inferring final causes as well. As such, inferences to teleology in science should be allowed where they are warranted by the empirical evidence.
The tool for determining whether a teleological inference is warranted is analogy. Bacon could have helped science avoid its gradual but inexorable drift into methodological naturalism if he had emphasized how analogy, used as an analytical tool in the process of induction, legitimately leads to reasonable inferences of teleology in nature
Linguistics
No full textHuman language can be studied bottom-up (corpus linguistics, neurolinguistics) and top-down (via conscious data creation and introspection as to grammaticality). Creativity in language hinges on both law and liberty, on the freedom of the will and constraints thereof. This paper focuses on the role of agency in language, and how our ability to learn and understand language is based not primarily on shared mechanics but rather agency-oriented concepts that we cannot not know
Introduction
No full textThis chapter discusses the recent history of questions about naturalism and its role in science, the motivations for the volume, and a preview of where the volume is headed
Problems with Non-Naturalistic Theories of Science
No full textNon-naturalistic theories of science are often criticized. The critics usually do not criticize the theory itself, but either misrepresent it or criticize the implications they consider wrong. What these theories need is internal criticism. A well-known and well-defined non-naturalistic theory is Intelligent Design (ID). There are currently no criticisms of ID theory from ID proponents. However, there are numerous legitimate issues with the theory such as difficulty in testing the theory and the theory requires fundamental revisions in our view of reality. It is important that these problems are explored in order to improve the usefulness of the theory. The criticisms will focus on ID, but similar criticisms apply to all non-naturalistic theories
Computer Science
No full textMachine Learning, despite its name, can incorporate an oracle. One common form of oracle interaction is known as active learning. Active learning samples ({x,y}) from an oracle for f (the function to be learned). Imagination sampling is the converse of active learning. Imagination sampling asks an oracle for hypotheses h from H (hypothesis space). In this paper imagination sampling is compared with a purely algorithmic approach to determine if oracle interaction outperforms a purely algorithmic approach. The theoretical basis for imagination sampling is developed and illustrated by simulating an oracle
Biology
No full textThe 2015 Nobel Prize winner in chemistry, Aziz Sancar, may have unwittingly given life to Paley's watch argument when he used the phrase ``Rube Goldbergesque designs'' to describe the nano-molecular clocks that provide timing to various processes in the human body. Other Rube Goldbergesque designs have been elucidated by National Institutes of Health (NIH) research initiatives such as the ENCODE and RoadmapEpigenomics projects, which represent approximately a half-billion dollar total investment.
The success of NIH initiatives and various other projects has drawn a bizarre reaction from some methodological naturalists such as evolutionary biologist Dan Graur who said in 2012 ``"If ENCODE is right, evolution is wrong." Graur's comment is reminiscent of Haeckel who said in 1876, ``"If we do not accept the hypothesis of spontaneous generation, then at this one point in the history of evolution we must have recourse to the miracle of a supernatural creation."
An unconventional approach called "``gambler's epistemology" is introduced as a perspective to clarify why naturalism should not be equated with science. Gambler’s epistemology, with its reliance on the notion of mathematical expectation, shows that the intuitive perception that "``life is a miracle" is not rooted in after-the-fact, ad-hoc probabilities, but is consistent with standard practice in science. Thus without formally settling the question of whether God or supernatural entities actually exist, Haeckel’s unwitting assertion that the emergence of life must be of miraculous origin is at least closer to the truth, statistically speaking.
Gambler's epistemology also shows that applying reward-to-risk analyses such as that seen in the professional investment and gambling world might be a better practical guide in committing financial and human resources to scientific exploration than the enforcement of unspoken creeds of impractical naturalism that may actually be detrimental to scientific discovery
Describable but not Predictable
No full textOur notions of causation in science are often unintentionally constrained by the mathematics we use. Typically, scientific investigations use algebraic or calculus-based mathematics to model causes and effects. In these types of models, there is a predictive relationship between the cause and the effect. This predictive pattern is what most people use to classify events as materialistic, leaving events that are not so classified as non-materialistic. Mathematics over the last century has introduced new formalisms that cover functions that do not conform to the materialistic pattern. While these functions cannot always predict outcomes for typical cases, they can be studied and analyzed in other ways, and therefore can be used for knowledge-building. Therefore, by expanding the mathematical toolset, investigators can better identify and model non-materialistic causes
Introduction
No full textThis presents and introduction and overview of the motivations, content, concerns, and direction of the volume as a whole