This is offered by me under the category of ‘hmmmmm, I dunno….‘
I heard Sanford on the always-excellent Amiel Handelsman podcast:
No More Feedback With Carol Sanford (Episode 103)
Instinctively, I think there’s a lot to what she’s saying, but I’m not sure about the narrative, which I think might be wrong or confused. The historical timeline she sketches is that ‘feedback’, as in giving and receiving feedback, or 360 degree feedback, is a misunderstanding of the cybernetic governor, applied extrinsically rather than intrinsically. She draws a line through early behavioural analysis ‘in the rat-filled labs of John Watson at Princeton University and B. F. Skinner at Stanford’, to the Macy conferences where allegedly the concept was misinterpreted by the nascent science of psychology.
And then has a schema of closed systems – cybernetic systems – complex adaptive systems (NB Bateson gets swept up into this side of things) – developmental systems – evolutionary systems. She draws a lot on Charles Krone.
So I think there’s a lot of interesting stuff here, but some arguments and a strong developmental/teleological world view which I’m not comfortable with. Would value comments of others!
Providing feedback to peers, subordinates, and even superiors—particularly the 360 Degree view of performance appraisal—became popular as scientists and engineers began to understand how cybernetic systems work in computer applications. The creators of these artificial intelligence systems discovered that feedback loops are critical for correcting and adjusting the performance of control mechanisms, such as thermostats […]
Source: Why Feedback Is Irresponsible and What To Do Instead: Part One of Six – Carol Sanford
Forth and Fifth Levels of Systems Thinking: Different Capabilities Are Required, Different Potential Offered By Carol Sanford Originally published at Wharton School, International Conference on Systems Thinking and Management 2004, As a manager in DuPont who finally came face to face with the Freon nightmare, I can tell you that thinking too small about a […]
Source: Forth and Fifth Levels of Systems Thinking: Different Capabilities Are Required, Different Potential Offered – Regenerative Business Summit2
Source: Architecting for Wicked Messes (OCADU 2018/03/07-09) – Coevolving Innovations
Each year, my lecture in the “Understanding Systems & Systemic Design” course — in the program for the Master of Design in Strategic Foresight and Innovation at OCAD University — reflects where my research is, at that point in time. For 2018, the scheduling of my visit was towards the end of a busy winter. Firstly, I had just finished teaching a Systems Methods course at the UToronto iSchool. Then, the Open Innovation Learning book was officially launched. Less than 6 months earlier, I had conducted a workshop at the Purplsoc 2017 meeting, and at the PLoP 2017 meeting. This shaped an agenda for the prepared slides as:
Science and complexity.Warren WeaverPublished in American scientist 1948
Source for reference: Science and complexity. – Semantic Scholar
Classic paper (pdf) https://fernandonogueiracosta.files.wordpress.com/2015/08/warren-weaver-science-and-complexity-1948.pdf
The above includes this 2004 introduction: https://journal.emergentpublications.com/article/science-and-complexity/
Science and complexity
Originally published as Weaver, W. (1948). “Science and complexity,” in American Scientist, 36: 536-544. Reproduced with permission. The Editors would also like to express their sincere thanks to Mia Smith of American
Scientist for providing a high quality digital scan of the original publication.
t is easy to get caught up in the excitement surrounding the study of complexity and how our
new learning might be applied to the problems we
face today. We often feel like pioneers in a new land,
making new discoveries. For those involved in charting such a course, it is easy to lose historical perspective and the path already taken by others. It is to these
earlier pioneers that the Classical Papers Section is
dedicated. Such a side trip to the archives can quickly
bring the reader a dose of reality, that some “new” ideas
are really only “rediscovered.” Similarly, our view of
the future can gain some perspective when reading
about earlier predictions of the future, what we now
call the present.
Reaching back almost 60 years, E:CO readers
are invited to read a classic article by Warren Weaver
(1894-1978). For historical setting, this article was pubOLVKHGVKRUWO\DIWHU:RUOG:DU,,DQGLVLQíXHQFHGE\
for the war effort. During the war, Weaver headed the
Applied Mathematics Panel (AAAS, 2004), a position
that led to familiarity with many of the top scientists of
the era. It was a time of great advances in science and
optimism for more growth in the future. This article
was also written at the time Weaver was formulating
ideas that would later be published with Claude Shannon in The mathematical theory of communication,
which laid the foundation for information theory.
Weaver’s thoughts during this time on how computers
might be employed in machine translation were later
collected in his famous memorandum on the topic that
“formulated goals and methods before most people
had any idea of what computers might be capable of”
The optimistic attitude of the power of science
tion that separates simple, few-variable problems from
the “disorganized complexity” of numerous-variable
problems suitable for probability analysis. The problems in the middle are “organized complexity” with a
moderate number of variables and interrelationships
that cannot be fully captured in probability statistics
The second part of the article addresses
how the study of organized complexity might be
approached. The answer is through harnessing the
power of computers and cross-discipline collaboration.
“Some scientists will seek and develop for themselves
new kinds of collaborative arrangements; that these
groups will have members drawn from essentially all
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contribute greatly to the advance which the next half
sciences.” (Weaver, 1948)
When reading this, there is a bit of déjà vu in
what we sometimes hear today of our study of complexity. So too in the statement that “science has, to
date, succeeded in solving a bewildering number of
relatively easy problems, whereas the hard problems,
and the ones which perhaps promise most for man’s
future, lie ahead” (Weaver, 1948). In the end the reader
not further along in our understanding of complexity
given Weaver’s ideas nearly 60 years ago, while also
still being optimistic in our success for the same reasons
Weaver was optimistic.
As with every Sam Harris podcast, you might want to skip the first five minutes, and turn up the speed – but though this is positied as a conversation about AI, there is lots her (especially in the first interviews) about the origins of systems thinking / complexity / cybernetics.
Source: Making Sense Podcast #153 – Possible Minds | Sam Harris
April 15, 2019
In this episode of the Making Sense podcast, Sam Harris introduces John Brockman’s new anthology, “Possible Minds: 25 Ways of Looking at AI,” in conversation with three of its authors: George Dyson, Alison Gopnik, and Stuart Russell.
George Dyson is a historian of technology. He is also the author of Darwin Among the Machines and Turing’s Cathedral.
Alison Gopnik is a developmental psychologist at UC Berkeley and a leader in the field of children’s learning and development. Her books include The Philosophical Baby.
Stuart Russell is a Professor of Computer Science and Engineering at UC Berkeley. He is the author of (with Peter Norvig) of Artificial Intelligence: A Modern Approach, the most widely used textbook on AI.