Knowledge and Information

Abstract

One task of data sonification is to provide a means by which listeners can obtain new ideas about the nature of the source of derived data. In so doing they can increase their knowledge and comprehension of that source and thus improve the efficiency, accuracy and/or quality of their knowledge acquisition and any decision-making based on it. The purpose of this chapter is to develop an historical understanding of what information is as a concept, how information can be represented in various forms as something that can be communicated with non-verbal sonic structures between its source and its (human) receiver and thus retained as knowledge. Whilst a complete philosophical and psychological overview of these issues is outside the scope of the chapter, it is important, in the context of developing computational design strategies that enable such communication, to gain an understanding of some of the basic concepts involved. A quasi-historical epistemology of human perception and the types of information these epistemologies engender is followed by a discussion of the phenomenal nature of sounds and sonic structures, and their ability to convey information of various sorts.

Hamlet: Do you see yonder cloud that’s almost in shape of a camel?.

Polonius: By th’ mass, and ‘tis like a camel indeed.

Hamlet: Methinks it is like a weasel.

Polonius: It is back’d like a weasel.

Hamlet: Or like a whale.

Polonius: Very like a whale.

Hamlet: … They fool me to the top of my bent….

(Shakespeare: Hamlet Act III, Scene 2)

Appendices

Appendix 3A General Methods of Acquiring Knowledge

General methods of acquiring knowledge

Authority: Leaders, considered knowledgeable and wise, decide what is true for everyone, sometimes during periods of special inspiration, insight or perhaps revelation. The surrender to authority is common in most arenas of human endeavour. It acts to stabilize and encapsulate a corpus of traditional knowledge against which new ideas can be tested.

Revelation: Often used by seers and prophets who employ magic and divination techniques. What is usually assumed is that the practitioners have ability to access knowledge through inspired communion with supernatural beings. Such access usually requires mindful techniques such as faith (belief), and is sometimes induced by body renunciation techniques.

Intuition: The direct, immediate and certain apprehension of truths without the intervention of conscious reasoning or related sensory perceptions. The difference between intuition and a revelation is the person doing the intuiting does not assume that the source of the knowledge is external to their own brain.

Heuristics, Folklore and Commonsense (Also known as Intentional Realism): The generalizations we apply in everyday life in predicting and explaining each other’s behavior, often collectively referred to as folk psychology. They are both remarkably successful and indispensable. A person’s ‘personal knowledge’ i.e. what they believe, doubt, desire, fear, etc. is a highly reliable indicator of what they will do, and we have no other way of making sense of each other’s behavior than by ascribing such states and applying the relevant generalizations.

It recognizes that we all, in some way, committed to the basic truth of common-sense psychology and, hence, to the existence of the states its generalizations refer to (Dretske 2000). Some, such as Fodor, also hold that common-sense psychology will be vindicated by cognitive science, given that propositional attitudes can be construed as computatinal relations to mental representations (Fodor 1987).

Churchland (1981) thinks that, as a theory of the mind, folk psychology has a long history of failure that can’t be incorporated into the framework of modern scientific theories, including cognitive psychology. He argues that the states and representations folk psychology postulates simply don’t exist; that it is comparable to alchemy and ought to suffer a comparable fate. On the other hand, Dennett (1987) seems prepared to admit that the generalizations of commonsense psychology are true and also indispensable, but denies that this is sufficient reason to believe in the entities to which they appear to refer. He supports this stance on that basis that there is nothing more to having a propositional attitude than to give an intentional explanation of a system’s behavior by adopting an the intentional stance toward it. Assuming a system is rational,² if the strategy of assigning contentful states to it and predicting and explaining its behavior is successful, then the system is intentional and the generalized propositional attitudes we assign to it are true (Dennett 1987: 29).

For an extended description, See http://plato.stanford.edu/entries/mental-representation/

Something is rational if behaves in accordance with the truths and falsehoods afforded by its environment

Appendix 3B Inference Methods of Acquiring Knowledge

Inference methods of acquiring knowledge

Deductive: Assuming a system is rational, if the strategy of assigning contentful states to it and predicting and explaining its behavior is successful, then the system is intentional and the generalised propositional attitudes we assign to it are true (Dennett 1987: 29). If a then b. [b is a consequence of the assumption of antecedent a].

Inductive Three types:

Assuming a system is is rational, if the strategy of assigning contentful states to it and predicting and explaining its behavior is successful, then the system is intentional and the generalised propositional attitudes we assign to it are true (Dennett 1987: 29).

(a) Simple: All observed a are b, therefore all a are b. (enumerative induction).

(b) Proportonal: P(g), a percentage of known g’s in group G, have attribute A. Individual i is another member of G, therefore there is a P(i), corresponding to P(g), that i has attribute A.

(c) Anaogic: a is similar to b. a has attribute X, therefore b has attribute X.

Bayesian: Assuming a system is rational, if the strategy of assigning contentful states to it and predicting and explaining its behavior is successful, then the system is intentional and the generalised propositional attitudes we assign to it are true (Dennett 1987: 29).

If P(b|a) = x (if the probability of b given a is x), then P(a|b) = x . P(b)/P(a).

(then the probability of a given b equals x multiplied by the probability of b divided by the probability of a).

Reliability S knows P if and only if S truly believes P, and S’s belief that P was produced by a reliable belief-forming process: Reliableness is a method for acquiring knowledge based on various belief-forming processes. It justifies the belief in the veridicity of perceptual sensations if the resulting perception is known to lead to a suitably high proportion of true beliefs. It is not a requirement of users of the method, or anyone else, to know that the process is reliable or have any sort of knowledge of its reliability–all that is required is that it is, in fact reliable. Thus, no appeal to sensory experience is required, effectively short-circuiting the issue that divides representationalism and phenomenalism. Reliabilism thus rejects the issue on which all three of the more traditional theories attempt to respond to: the issue of how sensory experience provides a reason for thinking that perceptual beliefs are true. On the assumption that our perceptual processes are in fact reliable in the way that we take them to be, it offers a seemingly straightforward and account of how perceptual beliefs about physical objects and the physical world are justified.

Reliabilism emphasizes the properties of the processes used to arrive at truths. In reliabilist approaches to knowledge acquisition, noticing a static relationship between a conjecture and a body of evidence, knowing that an hypothesis does not contradict the evidence, or even is in-accord with it, for example, is insufficient to warrant support for it from the evidence; additional account must be taken of how reliable the method that produce the hypothesis is known to be in producing truthful hypotheses. Reliabilist thinking underpins the greater acceptance of the diagnostic judgements of experts over laypersons, the preferential support for research programs with fecund histories and the scorn of ad hoc hypotheses.

The first, then unrecognised as such, formulation of a reliability account of knowledge was in the mathematician Frank Ramesy’s writing on knowledge (Ramsey 1931). Several similarly subjunctive theories, such as tracking theory and contexturalism, were developed in the latter part of that century, as discussed by Goldman, who notes. Reliability theories of knowledge of varying stripes are still in active development and continue to appeal to many epistemologists for their robustness and flexibility. Permutations abound. [Some theories] focus on modal reliability; on getting truth or avoiding error in possible worlds with specified relations to the actual one. They also focus on local reliability, that is, truth- acquisition or error avoidance in scenarios linked to the actual scenario in question Goldman (2008).