The Ontology of Randomness

The Ontology of Randomness

Jeremy Horne (The International Institute of Informatics and Systemics, USA)
Copyright: © 2018 |Pages: 11
DOI: 10.4018/978-1-5225-2255-3.ch161
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The Ontology of Randomness in this Encyclopedia of Information Science and Technology, focuses more on the thinking underpinning science, more specifically, whether randomness even exists, i.e., its ontology (Feibleman, 1951). Tests for randomness appear to assume what is trying to be shown, i.e., there is indeed randomness, begging the question of whether there is innate structure, or order, in the universe.

Because of very limited space, extended tutorials and discussions about ontology (the nature of existence), epistemology (how we know), the problems of induction (Hume, 1888; Mill, 1843; Russell, 1919; Ramsey, 1929; Keynes, 1921, pp. 305-314; p. 24 et seq.), stochastic analysis (series of random variables), and the problems of representation (Plato's cave allegory as the philosophical foundations of statistics) have been omitted. Also omitted is a discussion of the role of randomness in logical scientific exploration (Popper, 1934; hypothetico-deductive, 2015; Copi, 1979; Rosser, 1953; Mendelson, 1997; Whewell, 1847; Feyerabend, 1975), as well as discussions of Abraham de Moivre (bell curve), Pierre-Simon Laplace (calculus of probabilities), and martingales (Birnbaum and Lukas, 1980). There are many other conversations about the differences between probability, chance (Keynes, 1921; Eagle, 2010), and randomness that would enrich a more complete treatment of the subject. This says nothing of the hundreds of mainstream works of probability theorists and their views on randomness. Instead, given here is somewhat analogous to a brief literature search, with a focus on summarizing several main views of what people think randomness is and considering the implication of its existence status. If such can get the reader to think beyond technology, focusing more on the “why”, then this chapter will have accomplished its goal.

Key Terms in this Chapter

Cartesianism: Repeated subdivision; reductionism.

Chance: Unexpected happening without regard to any other phenomenon or explanation.

Compressibility: Ability to produce the same essence of content in a reduced or compacted manner.

Entropy: Either a dispersal of energy (Clausius) or loss of information integrity (Shannon).

Deduction: In logic, if the premises are true, the conclusion is guaranteed. Closed systems.

Scientific Method: Extrapolating from the past to project to the future.

Complexity: Amount and detail of intricacy, often expressed in the most reduced or abbreviated form.

Induction: In logic, the degree of probability that a conclusion will follow from the premises. Open systems.

Statistics: A form of computable induction, deciding the degree of certainty of future events.

Ontology: The study of what exists.

Random: Uncertain; unpredictable; not having any method or algorithm to produce a phenomenon.

Epistemology: A study of what exists.

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