Author J. Jones
Biography: Jed Jones
is president and chief data scientist at the advertising firm, MindEcology,
http://www.MindEcology.com. He has worked in the field of marketing for 20 years and possesses advanced knowledge in the areas of data science, market segmentation, and systems approaches to organizational management. He holds a Ph.D in organizational systems inquiry from Saybrook University, an M.B.A. in marketing from UC Irvine, and a B.A. in Japanese studies from UCLA.
Dyer G., Jones J., Rowland G. & Zweifel S. (2015) Authors’ Response: Conversation Never Ends. Constructivist Foundations 11(1): 60–64. https://cepa.info/2215
Dyer G., Jones J., Rowland G. & Zweifel S.
(
2015)
Authors’ Response: Conversation Never Ends.
Constructivist Foundations 11(1): 60–64.
Fulltext at https://cepa.info/2215
Upshot: Our five colleagues have offered what we consider to be complementary views and welcome suggestions. We extend the conversation with them by examining areas of agreement, responding to criticisms, and considering potential additions to the Banathy Conversation Methodology. We add a description of the mate tradition and further details on Las Conversaciones del Extremo Sur.
Dyer G., Jones J., Rowland G. & Zweifel S. (2015) The Banathy Conversation Methodology. Constructivist Foundations 11(1): 42–50. https://cepa.info/2209
Dyer G., Jones J., Rowland G. & Zweifel S.
(
2015)
The Banathy Conversation Methodology.
Constructivist Foundations 11(1): 42–50.
Fulltext at https://cepa.info/2209
Context: Thirty years ago, members of the systems science community discovered that at their conferences, more was being accomplished in the breaks than in the sessions. Led by Bela H. Banathy, they cancelled the sessions and created a conversation methodology that has proven far more effective. Dozens of conversations have now been held around the world. Problem: At a recent conversation in Linz, Austria, a team devoted its inquiry to the Banathy Conversation Methodology (BCM) itself, asking, in particular, how to develop and spread the methodology further, beyond the systems science community. Method: The team captured key features and benefits of BCM and developed new tools. Results: Described herein are the development of the methodology, its theoretical underpinnings, the methodology itself, heuristics for successful conversations, and an example of how the methodology is spreading. Implications: Ultimately, the hope is to develop the methodology in such ways that communities could apply it to meet significant challenges and co-create their futures.
Jones J. (2005) The Cybersemiotic Roots Of Computation: A Critique of the Computational Model of Cognition. Cybernetics & Human Knowing 12(3): 7–29.
Jones J.
(
2005)
The Cybersemiotic Roots Of Computation: A Critique of the Computational Model of Cognition.
Cybernetics & Human Knowing 12(3): 7–29.
This paper challenges the prevalent metaphor of human cognition as a von Neumanntype (1945) computational process. This computational model of cognition is flawed because it fails to recognize the crucial role of an embodied observer’s capacity for semiosis in any computational process. The paper argues against the computational model of cognition on epistemological, theoretical, practical, and ethical grounds. It affirms Brier’s (1996) cybersemiotic framework, which states that semiosis is the organism’s selection of environmental perturbations in the attempt to satisfy its own needs. The paper identifies the primary computational steps involved in the Turing (1936) machine and the von Neumann (1945) architecture, as well as those of three common applications of artificial intelligence. It then argues that each of these computational processes requires one or more of the human capacities for abstraction, purposive control of the physical environment, and judgment. It concludes that fully autonomous, self-adapting computers in some imagined utopian (or dystopian) future would diverge from human evolutionary relevance because they are incapable of semiosis.
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