Mind, Body, World- Foundations of Cognitive Science, 2013a

perspectives could be taken? To accomplish this, the framework of cybernetics was
exclusively mathematical. Cyberneticists investigated the input-output mappings of
machines by making general statements or deriving proofs that were expressed in
some logical or mathematical formalism.
By the late 1950s, research in cybernetics proper had begun to wane (Conway
& Siegelman, 2005); at this time cybernetics began to evolve into the modern field of
cognitive science (Boden, 2006; Gardner, 1984; Miller, 2003). Inspired by advances
in digital computers, cognitive science was not interested in generic “machines” as
such, but instead focused upon particular devices that could be described as information
processors or symbol manipulators.
Given this interest in symbol manipulation, one goal of cognitive science is to
describe a device of interest in terms of the specific information processing problem
that it is solving. Such a description is the result of performing an analysis at the
computational level (Dawson, 1998; Marr, 1982; Pylyshyn, 1984).
A computational analysis is strongly related to the formal investigations
carried out by a cyberneticist. At the computational level of analysis, cognitive
scientists use formal methods to prove what information processing problems a
system can—and cannot—solve. The formal nature of computational analyses lend
them particular authority: “The power of this type of analysis resides in the fact
that the discovery of valid, sufficiently universal constraints leads to conclusions
. . . that have the same permanence as conclusions in other branches of science”
(Marr, 1982, p. 331).
However, computational accounts do not capture all aspects of information
processing. A proof that a device is solving a particular information processing
problem is only a proof concerning the device’s input-output mapping. It does not
say what algorithm is being used to compute the mapping or what physical aspects
of the device are responsible for bringing the algorithm to life. These missing details
must be supplied by using very different methods and vocabularies.
2.8 Behaviour by Design and by Artifact
What vocabulary is best suited to answer questions about the how a particular inputoutput
mapping is calculated? To explore this question, let us consider an example
calculating device, a Turing machine (Turing, 1936). This calculator processes symbols
that are written on a ticker-tape memory divided into cells, where each cell can hold a
single symbol. To use a Turing machine to add (Weizenbaum, 1976), a user would write
a question on the tape, that is, the two numbers to be added together. They would be
written in the format that could be understood by the machine. The Turing machine
would answer the input question by reading and rewriting the tape. Eventually, it
would write the sum of the two numbers on the tape—its answer—and then halt.
Multiple Levels of Investigation 41