Edited
September 17, 2004
Anticipatory Web
5/11/2004
8:14 AM
Short PowerPoint
on Building Anticipatory Technology -> .
Anticipatory Technology Diagram: an introduction
The Anticipatory Technology Diagram
Definition of the phrase
“mutual-induction”
Anticipatory Technology Diagram: an introduction
The PowerPoint linked to the above hyperlink develops the initial material in this short paper in a slightly different fashion. We identify some but not all of the topics that are needed to understand anticipatory technology.
One of the topics not addressed, in the PowerPoint, are the role of self-image, or autopoeisis (Maturana and Varela’s term for image of self), and the interplay between ecological affordances (J. J. Gibson’s term) and the endophysics of memory assembly. These concepts need not be so difficult to learn and to place into the context of working with anticipatory technology.
All of this material needs to be developed within a K-12 plus college curriculum by the leading scholars, in ecological sciences, social science, psychological science, physics, chemistry, biology, computer science and mathematics.
The Anticipatory Technology Diagram (Figure 1) is based on work I have derived from my study of the biology of cognitive function, computer science and the foundations of mathematics. The primary application area is in the development of distance learning and many-to-many communication systems, such as envisioned as part of the Rural Safe Net, and the National Project to Establish the Knowledge Sciences.
The scholarly citations of my work are in the reference section of my on-line book.
The anticipatory technology diagram
Anticipatory Technology Diagram
The concepts illustrated by the diagram are written about extensively in pages gathered together in the bcngroup.org and ontologyStream Inc web sites. The task of developing this work into a curriculum is only starting, and I apologize for the incompleteness of the presentations. The existing literature is extensive and the task for synthesizing this literature into a simple curriculum has been only recently begun.
The machine architecture that is suggested by my work is called “Tri-level” because there is a separation of the machinery related to “memory” from the machinery related to “anticipation”. Each machine is quite different and work together to produce an evocation of awareness as the user interacts with these two machines in real time.
We use the notion of induction is a specific way, and contrast “induction” with “deduction”.
We suggest that deduction is not as natural to humans as our academic traditions indicate. Rationality and formal logics has been represented as the ideal for human thought, not only in some theoretical sense but also in the sense that a perfect human being has been portrayed as being perfectly rational. Rationality is defined in terms of what are viewed as consistency and completeness, and is best reflected in David Hilbert’s grand vision about the completion of mathematics. Hilbert’s grand vision still governs a great deal of the work in science and mathematics. However, Godel’s work on the foundations of mathematics and related literatures demonstrate limitations that are forced on rationalism expressed as formal models about natural systems.
The concepts expressed, by myself, are expressed to make statements of belief and to point into the literatures. The student may wish to study further, and the learned person may wish to reflect on the similarity between my formulation of the contrast between induction and deduction, and other scholars.
Two electrical motors will induct changes in state. The coupling between electrical systems is due to “holonomic” constraints related to the electromagnetic field. We use the term “holonomic” in the sense established by neuroscientist, Karl Pribram. Holonomic effects are not locally concentrated as in our notions of Newtonian action-reaction systems. The induction occurs non-locally, and thus the mechanism “causing” the state changes is not accounted within a discrete model. However, the state changes do occur and can be modeled using continuum field models. The mathematics is elegant but is often beyond the reader’s experience, so we will point to a longer introduction to this discussion between holonomic and non-holonomic causes.
Definition of the phrase “mutual-induction”
In the same way as two physical electrical motors induce state modifications in each other via a non-local interaction; we observe that symbol systems such as natural language or gestures will cause modification in the mental state of a human being. Because of the confusion about the nature of a computer program, we use the term “mutual-induction” to talk about and action-perception cycle that involves in each cycle the two mutually exclusive systems:
1) the computer program with some type of display or informational interface
2) the acting and perceiving human living in real time and experiencing, among other things, the information being computed by the computer.
The human can be involved in creating computer input as a result of the responses that the human has to old information states. These human inputs can result in new informational states in the computer.
Likewise, the computer can be computing informational states in the computer. Upon viewing an informational state, the human’s mental state is altered, or manipulated via cognitive priming, so that human cognitive acuity and tacit knowledge is primed by the computer informational state.
The human action-perception cycle is influenced by the series of states generated by the computer.
Why is this radically different from the current uses of a computer? Of course, humans are always involved in these action-perception cycles. So the primary difference is in the architecture of the computer’s data encoding and production rules. The Tri-level architecture matches the biological facts, as understood by many leading cognitive scientists, and separates the invariance of structure from the anticipation of function in environmental context in real time.