36 Informational environments
notion of signals that are transmitted from sender to receiver through information
channels, as in computing and telecommunications, serves as the paradigm of
semantic information. In fact, Floridi identifies the source disciplines of his GDI
to lie in those fields which treat data and information as reified entities – almost
literally: information is composed of bits and pieces (or bits and more bits for that
matter) that are processed by an appropriate assembly of hardware and software
so as to produce a certain output. No such reified entities can be found in theories
of natural information, where information is a probabilistically described (but, in
Dretske’s case, nomologically governed) relation between world affairs that does
not add anything, ontologically, to a natural environment and that assumes its
status as information long before and perhaps without ever becoming processable
by some appropriate, organic or other, machinery.
With respect to the use of information for perception by organisms, the processing view of information presumes that, in order for an organism to produce a
structured response to some external stimulus, that stimulus, which taken by itself
is insufficient to structure that response, has first to be encoded in perception and
then modified through a series of processing stages, which are likely to include
the addition of other information, coming from different sources and through different channels, so as to arrive at a fully image-like or propositionally structured
representation that finally serves to inform the organisms’s response. The information relevant to the organism is constructed in the process of perception. Marr
was the advocate of such an explicitly computation- and AI-based view of visual
perception and is aptly considered the founder of computational neuroscience. He
not only was a leading opponent of the Gibsonian view in the field of the psychology of perception but also closely worked with leading figures in classical AI such
as Seymour Papert and Marvin Minsky. In Marr (2010), which was first published
in 1982, he conceived of vision as the process of constructing, on different levels
of perceptual processing, descriptions, via internal representations, of the information derived from an input image. “Representation” and “description” are to be
understood as technical terms in this context:
A representation is a formal system for making explicit certain entities or
types of information, together with a specification of how the system does
this. And I shall call the result of using a representation to describe a given
entity a description of the entity in that representation.
(Marr 2010, 20, emphasis in original)
In Marr’s own example, the Arabic or binary numeral system would be the representation that provides the elements and the rules by which to generate any string of
elements (33, 42, 999, etc.) as the descriptions of the individual numbers (rather than
the numbers themselves). Hence, a representation is not a mental image or a sentence that is supposed to refer to some world affair, and that would be generated in
the perceptual process, but a formal method of generating symbolic descriptions of
that world affair or the intermediate staged of the perceptual process. The perceptual
process generated by representations, so understood, and resulting in descriptions,
notion of signals that are transmitted from sender to receiver through information
channels, as in computing and telecommunications, serves as the paradigm of
semantic information. In fact, Floridi identifies the source disciplines of his GDI
to lie in those fields which treat data and information as reified entities – almost
literally: information is composed of bits and pieces (or bits and more bits for that
matter) that are processed by an appropriate assembly of hardware and software
so as to produce a certain output. No such reified entities can be found in theories
of natural information, where information is a probabilistically described (but, in
Dretske’s case, nomologically governed) relation between world affairs that does
not add anything, ontologically, to a natural environment and that assumes its
status as information long before and perhaps without ever becoming processable
by some appropriate, organic or other, machinery.
With respect to the use of information for perception by organisms, the processing view of information presumes that, in order for an organism to produce a
structured response to some external stimulus, that stimulus, which taken by itself
is insufficient to structure that response, has first to be encoded in perception and
then modified through a series of processing stages, which are likely to include
the addition of other information, coming from different sources and through different channels, so as to arrive at a fully image-like or propositionally structured
representation that finally serves to inform the organisms’s response. The information relevant to the organism is constructed in the process of perception. Marr
was the advocate of such an explicitly computation- and AI-based view of visual
perception and is aptly considered the founder of computational neuroscience. He
not only was a leading opponent of the Gibsonian view in the field of the psychology of perception but also closely worked with leading figures in classical AI such
as Seymour Papert and Marvin Minsky. In Marr (2010), which was first published
in 1982, he conceived of vision as the process of constructing, on different levels
of perceptual processing, descriptions, via internal representations, of the information derived from an input image. “Representation” and “description” are to be
understood as technical terms in this context:
A representation is a formal system for making explicit certain entities or
types of information, together with a specification of how the system does
this. And I shall call the result of using a representation to describe a given
entity a description of the entity in that representation.
(Marr 2010, 20, emphasis in original)
In Marr’s own example, the Arabic or binary numeral system would be the representation that provides the elements and the rules by which to generate any string of
elements (33, 42, 999, etc.) as the descriptions of the individual numbers (rather than
the numbers themselves). Hence, a representation is not a mental image or a sentence that is supposed to refer to some world affair, and that would be generated in
the perceptual process, but a formal method of generating symbolic descriptions of
that world affair or the intermediate staged of the perceptual process. The perceptual
process generated by representations, so understood, and resulting in descriptions,