[A Deming and Theory-of-Constraints type systematic ten-step approach which is quite interesting]

THE DECALOGUE SHORT OVERVIEW – Intelligent Management –

HENRY FARRELL

APR 17, 2024

Cybernetics is the science of the polycrisisWhat Stafford Beer and Dan Davies say and why you need to read themHENRY FARRELLAPR 17, 2024

Cybernetics is the science of the polycrisis

https://www.programmablemutter.com/p/cybernetics-is-the-science-of-the

Presented at the 2018 Science and Nonduality convention.

Topics

THE WORLD IS A NETWORK
October 2018
In this discussion, Fritjof Capra discusses systems thinking, the cognitive dimension of life, nonlinear causality, emergence of novelty in (Text sourced from https://www.organism.earth/library/document/world-is-a-network) living systems, ethics, world problems and solutions, transformative learning, and the importance of community. He covers the systems view of life from his book and emphasizes relationships, interconnectedness, and sustainability.

Presented at the 2018 Science and Nonduality convention.

The World is a Network – Fritjof Capra

https://www.organism.earth/library/document/world-is-a-network

[This is an absolutely awesome opportunity – Sandra is fabled, and rightly so, and Michael is such a storied facilitator and a clear and deep thinker, as well as being engaging and just general a delight to be around. I see him as one of the people who is successfully picking up the torch from Sandra’s generation and taking deep, effective and proven thinking forward with respect and with awareness of the adaptation that’s needed. If I had the time I’d go myself.]

🍀 Come to Berlin this October to join our Trainings with Sandra Janoff and Michael Donnelly.
We are very happy to host Sandra and Michael this year. This is a very rare opportunity to meet the source of hashtag#FutureSearch and real role models for hashtag#facilitation of complex, multi-stakeholder questions that matter and learn together.

📣 We have a special rate until end of May:
🍀 Early bird 10% and another 15% if you book both trainings. Please Contact us with any questions.

📣 Managing a Future Search: 9-11 October 2024
A Learning Workshop with Sandra Janoff and Michael Donnelly
https://lnkd.in/eww7xBWC

📣 P10 Facilitation: Ten Principles for Leading Meetings that Matter 14/15 October 2024
A Learning Workshop with Sandra Janoff and Michael Donnelly
https://lnkd.in/eiYi-xGn

📣 Future Search Learning Exchange, 16/17 October 2024
https://lnkd.in/ewZWQbMm

(4) Post | LinkedIn

[Drawn to my attention by John Siegrist on this blog from Felix Hovespian https://www.linkedin.com/feed/update/urn%3Ali%3Aactivity%3A7193830352144977920/?commentUrn=urn%3Ali%3Acomment%3A%28activity%3A7193830352144977920%2C7193839932258353152%29&dashCommentUrn=urn%3Ali%3Afsd%5Fcomment%3A%287193839932258353152%2Curn%3Ali%3Aactivity%3A7193830352144977920%29&replyUrn=urn%3Ali%3Acomment%3A%28activity%3A7193830352144977920%2C7194207491482615809%29&dashReplyUrn=urn%3Ali%3Afsd%5Fcomment%3A%287194207491482615809%2Curn%3Ali%3Aactivity%3A7193830352144977920%29 ]

John McCarthy Tue Jun 13 03:06:03 PDT 2000
https://www-formal.stanford.edu/jmc/reviews/bloomfield/bloomfield.html
(From his interesting and very 90s website https://www-formal.stanford.edu/jmc/)

pdf of the same: http://jmc.stanford.edu/artificial-intelligence/reviews/bloomfield.pdf

A book review, in which he says

Schopman mentions many influences of earlier work on AI pioneers. I can report that many of them didn’t influence me except negatively, but in order to settle the matter of influences it would be necessary to actually ask (say) Minsky and Newell and Simon. As for myself, one of the reasons for inventing the term “artificial intelligence” was to escape association with “cybernetics”. Its concentration on analog feedback seemed misguided, and I wished to avoid having either to accept Norbert (not Robert) Wiener as a guru or having to argue with him. (By the way I assume that the “Walter Gibbs” Schopman refers to as having influenced Wiener is most likely the turn-of-the-century American physicist Josiah Willard Gibbs, though possibly McCulloch’s colleague Walter Pitts). Minsky tells me that neither Wiener nor von Neumann, with whom he had personal contact, influenced him, because he didn’t agree with their ideas. He does mention influence from Rashevsky, McCulloch and Pitts.

__
On his own thread, Felix Hovespian had responded:

“Most of what is called hashtag#artificialIntelligence today is based on 1st order hashtag#cybernetics, and therefore it’s very like hashtag#behaviorism.

It doesn’t take into account what the intelligence has to do in order to hashtag#observe, to construct, to hashtag#think … ”

[ Ernst von Glasersfeld and a History of Cybernetics,
https://youtu.be/pm5u68t6kPI ]

___
Various tweets on this point (turns out’Grok’ is an actually useful search engine for twitter – hurrah!) – all coming back to the same quote:

Apr 19 2022 Alex Dimakis

May 5 2023 Eryk Salvaggio

Jan 21 2024 Meredith Whittaker

_____________

A couple of useful-looking LLM summaries of the differences:

ChatGPT:
John McCarthy, a pivotal figure in the development of artificial intelligence, had several key differences with the field of cybernetics, particularly concerning the methods and goals of research in understanding and creating intelligent systems. Here are the main areas where McCarthy’s views diverged from those predominant in cybernetics:

### 1. **Focus on Symbolic Processing:**
– McCarthy was a strong proponent of symbolic AI, which emphasizes the manipulation of symbols to perform reasoning tasks. He believed that intelligence could be described as symbol manipulation and that machines could be made intelligent by programming them to manipulate symbols according to formal rules.
– Cybernetics, in contrast, focused more broadly on communication and control in animals and machines, often considering feedback mechanisms and homeostatic systems rather than specific computational models of intelligence.

### 2. **Theoretical Foundations:**
– McCarthy was instrumental in developing the theoretical foundations of computing and artificial intelligence, emphasizing formalisms such as recursion theory and the use of formal logic to model intelligent behavior. His approach was more mathematical and abstract, rooted in formal logic and computation theory.
– Cybernetics tended to be more interdisciplinary and system-oriented, involving fields like biology, engineering, and psychology, and often focused on practical applications rather than abstract computation.

### 3. **Methodological Differences:**
– McCarthy’s approach in AI research was to create an environment where artificial agents could perform tasks by thinking, using heuristic methods to solve problems. This approach was quite different from the cybernetic focus on systems dynamics, feedback loops, and regulatory mechanisms.

### 4. **AI vs. Cybernetics Communities:**
– During the 1950s and 1960s, as AI emerged as a distinct field, there was a notable division between the AI community and the cyberneticians. McCarthy, who coined the term “Artificial Intelligence” and organized the famous Dartmouth Conference in 1956, was part of shaping AI as a field that, in some ways, defined itself in opposition to cybernetics. AI was seen as focusing on creating intelligent machines, whereas cybernetics was seen as more concerned with understanding systems, including but not limited to intelligent behavior.

### 5. **Philosophical Disagreements:**
– McCarthy often expressed skepticism about some of the philosophical stances that were sometimes associated with cybernetics, such as overly broad interpretations of system theory or the applicability of cybernetic principles to all aspects of human knowledge and activity.

Despite these differences, both McCarthy’s work in AI and the broader field of cybernetics have contributed foundational concepts to the understanding of complex systems and intelligent behavior. The development of AI has since embraced many cybernetic principles, particularly in areas like neural networks and autonomous robots, showing that the fields have potential for convergence despite their initial distinctions.
_____________
Gemini:
John McCarthy, one of the founding fathers of Artificial Intelligence (AI), had several key differences with cybernetics:

1. **Focus on Symbol Manipulation:** McCarthy believed that the essence of intelligence lay in the manipulation of symbols and that creating intelligent machines required a way to represent and process abstract concepts. In contrast, cybernetics focused on feedback loops, control systems, and the study of communication within natural and artificial systems.

2. **Disinterest in Biological Models:** McCarthy was less interested in replicating biological processes as a route to intelligence. Cyberneticists like Norbert Wiener and Warren McCulloch were explicitly interested in understanding biological systems (like the brain) and applying those principles to engineering.

3. **Top-Down vs. Bottom-Up Approach:** McCarthy argued for a top-down approach to AI, focusing on developing high-level cognitive functions like reasoning and problem-solving. Cybernetics often took a more bottom-up approach, interested in understanding and building self-organizing systems that could adapt and learn.

4. **Artificial vs. Augmented Intelligence:** McCarthy aimed to build wholly artificial intelligent systems, independent of human control. Parts of cybernetics focused on augmenting human intelligence and the connection between humans and machines.

5. **Distinct Terminology:** McCarthy coined the term “Artificial Intelligence” in 1955, intentionally distinguishing his work from the existing field of cybernetics. This reflected his desire to create a new discipline focused on the specific goals of building intelligent machines.

**In Summary:**

While both fields shared a common interest in systems, information, and how machines process them, McCarthy’s work in AI aimed to break away from the more biologically focused cybernetics movement. He sought a more abstract, symbolic approach to create independent intelligent entities.
___

[I don’t expect to be in the habit of doing ‘AI’ summaries, but it seemed relevant here 😉 – and I didn’t easily find other quick sources summarising etc…]

[Email newsletter being discontinued in favour of LinkedIn]

The IFSR Quarterly informs you of the latest developments in the systems community.

(8) LinkedIn

https://www.linkedin.com/newsletters/7165311035111940096/?displayConfirmation=true

May 8, 2024

ONLINE ZOOM SEMINAR, THIRD OF FOUR SEMINARS IN THE SERIES ‘SOCIETY, TECHNOLOGY AND THE HUMAN-MACHINE INTERFACE’.

Reframing Technological Displacement of Labour: Insights from Social System Theory

Tuesday 14th May 2024, 13.00-15.00 London Time, online via Zoom

To attend and receive zoom access details, please sign up using the below link. Participation is free of charge.

Sign up for event

Abstract

Approaches to the technological displacement of labour have traditionally been oriented towards critical theory, often overemphasising the cultural or economic aspects of capitalism. These approaches frequently lead to moral judgments of the process. In contrast, this lecture explores the concept of technological displacement of labour through the lens of Social System Theory, particularly drawing on the work of Niklas Luhmann. It is argued that technology, while viewed as a self-sufficient system, operates within a complex web of social systems, influencing and being influenced by them. Luhmann’s theories of autopoiesis and operational closure serve as the foundation for understanding how organisations, as autopoietic systems, interact with technology. The paper emphasises that technological displacement is not a direct result of technological advancement or monopolised by the capitalist exploitation of labour, but rather the outcome of organizational decisions within the context of their internal and external environments, especially in contemporary organisations. It challenges traditional views by suggesting that change within organisations stems from their internal dynamics and decision-making processes, rather than from external technological pressures. It contributes to the discourse by highlighting the importance of organisational self-reflection and adaptation in navigating the challenges posed by technological advancements.

Speaker biography

Dr. Erik Brezovec is an Assistant Professor at the University of Zagreb, Faculty of Croatian Studies. Within the Department of Sociology, he is the head of the courses on Sociological Theory II, Contemporary Sociological Theory, Contemporary Social Theory, Phenomenological Sociology, and Sociology of Health and Illness. His main areas of interest are meta-sociology, sociological theory, and the sociology of knowledge. Utilising his approaches, he studies various areas of social reality; one of his main areas of focus is the social aspects of alcohol consumption in Croatia. He has published over 30 scientific articles and one monograph and has participated in more than 20 conferences.

Spin-off activity | Online seminar | Society, Technology and Luhmann – Luhmann Conference

[There’s a reason Kauffman is an OG in this field – and even though I have increasingly less patience/excitement for discussions of the origins of life, life in the galaxy etc, this goes from (before) autocatalytic sets*, where a network of molecules mutually catalyze each other’s formation, to broader questions about the conditions and processes that facilitate life, potentially applicable across the universe, and broader concepts of complexity and evolution, economics technology etc.

*Wasn’t there a group of cyberneticians who palled around calling themseles ‘The Autocatalytic Set’?]

Main show link, with transcript etc https://www.jimruttshow.com/stuart-kauffman-2

EP 227 Stuart Kauffman on the Emergence of Life – YouTube

30 April 2024

By Gerrit Van Wyk.

A Personal Journey Towards Understanding Human Social Complexity – The Complexity of Health Care

A Personal Journey Towards Understanding Human Social Complexity

[Claim to fame: I did first-year economics tutorials with Josh Ryan-Collins. At the time, we were both very frustrated by it and possibly very bad at it. He, unlike me, persisted… (while also rising to prominence in sociology)]

Authored by Lydia Marsden, Josh Ryan-Collins, Jesse Abrams and Timothy Lenton

25 April 2024

Download the report

UCL Institute for Innovation and Public Purpose (IIPP) policy report no. 2024/03

Authors: 

• Lydia Marsden | Research Fellow in Sustainable Finance | UCL Institute for Innovation and Public Purpose
• Josh-Ryan Collins | Associate Professor in Economics and Finance | UCL Institute for Innovation and Public Purpose
• Jesse Abrams | Senior Research Impact Fellow | Global Systems Institute, University of Exeter
• Timothy Lenton | Chair in Climate Change and Earth System Science | Global Systems Institute, University of Exeter

Summary:

Stable natural ecosystems underpin all economic activity. Ecosystems provide the natural resources needed for production; regulate climate change and global rainfall patters; and provide resilience against natural disasters and the extremes brought on by global warming. 
 
Pressures on nature from human activity – such as land use change and pollution, as well as climate change – are increasing the risk of terrestrial ‘ecosystem tipping points’ (ETPs): non-linear, self-amplifying and irreversible changes in ecosystem states that can occur rapidly and on a large scale. 
 
Losing these critical ecosystems will severely impact the economy through reduced food and energy security; damages to assets such as real estate; croplands and infrastructure; and health risks that impair household productivity. The direct impacts of ETPs can reverberate globally and extend far beyond the regions where these ecosystems are located, not least through the amplifying effect that ETPs would have on climate change. 

This means ETPs are highly relevant for central banks and financial supervisors’ understanding of how nature loss can affect the economy and financial system. The scale of environmental breakdown posed by ETPs necessitates a precautionary approach. This must focus on rapidly eliminating negative drivers to prevent thresholds being crossed ex ante, including exploring the role of the financial sector in facilitating these drivers (known as “double materiality”). Improved modelling can and should play a role, but the fundamental uncertainty associated with ETPs means these exercises are more suited for exploring risks rather than managing then. 

Ultimately, this approach will need to be led by governments, and requires central banks and financial supervisors to coordinate with policymakers in ministries of finance, industry and environment to fulfil their primary mandates of price and financial stability.

Reference:

This report can be referenced as follows:

Marsden, L., Ryan-Collins, J., Abrams, J., and Lenton, T. (2024). Ecosystem tipping points: Understanding risks to the economy and financial system. UCL Institute for Innovation and Public Purpose, Policy Report 2024/03. Available at: https://www.ucl.ac.uk/bartlett/public-purpose/2024/apr/ecosystem-tipping-points

Ecosystem tipping points: Understanding the risks to the economy and the financial systemAuthored by Lydia Marsden, Josh Ryan-Collins, Jesse Abrams and Timothy Lenton25 April 2024Download the reportUCL Institute for Innovation and Public Purpose (IIPP) policy report no. 2024/03Authors: Lydia Marsden | Research Fellow in Sustainable Finance | UCL Institute for Innovation and Public PurposeJosh-Ryan Collins | Associate Professor in Economics and Finance | UCL Institute for Innovation and Public PurposeJesse Abrams | Senior Research Impact Fellow | Global Systems Institute, University of ExeterTimothy Lenton | Chair in Climate Change and Earth System Science | Global Systems Institute, University of ExeterSummary:Stable natural ecosystems underpin all economic activity. Ecosystems provide the natural resources needed for production; regulate climate change and global rainfall patters; and provide resilience against natural disasters and the extremes brought on by global warming.  Pressures on nature from human activity – such as land use change and pollution, as well as climate change – are increasing the risk of terrestrial ‘ecosystem tipping points’ (ETPs): non-linear, self-amplifying and irreversible changes in ecosystem states that can occur rapidly and on a large scale.  Losing these critical ecosystems will severely impact the economy through reduced food and energy security; damages to assets such as real estate; croplands and infrastructure; and health risks that impair household productivity. The direct impacts of ETPs can reverberate globally and extend far beyond the regions where these ecosystems are located, not least through the amplifying effect that ETPs would have on climate change. This means ETPs are highly relevant for central banks and financial supervisors’ understanding of how nature loss can affect the economy and financial system. The scale of environmental breakdown posed by ETPs necessitates a precautionary approach. This must focus on rapidly eliminating negative drivers to prevent thresholds being crossed ex ante, including exploring the role of the financial sector in facilitating these drivers (known as “double materiality”). Improved modelling can and should play a role, but the fundamental uncertainty associated with ETPs means these exercises are more suited for exploring risks rather than managing then. Ultimately, this approach will need to be led by governments, and requires central banks and financial supervisors to coordinate with policymakers in ministries of finance, industry and environment to fulfil their primary mandates of price and financial stability.Reference:This report can be referenced as follows:Marsden, L., Ryan-Collins, J., Abrams, J., and Lenton, T. (2024). Ecosystem tipping points: Understanding risks to the economy and financial system. UCL Institute for Innovation and Public Purpose, Policy Report 2024/03. Available at: https://www.ucl.ac.uk/bartlett/public-purpose/2024/apr/ecosystem-tipping-points

Ecosystem tipping points: Understanding the risks to the economy and the financial system | UCL Institute for Innovation and Public Purpose – UCL – University College London

https://www.ucl.ac.uk/bartlett/public-purpose/publications/2024/apr/ecosystem-tipping-points-understanding-risks-economy-and-financial-system

Systems Thinking & Complexity Management to Support Community Development

• Book
• © 2023

Overview

Authors:

• Camilo Andrés Navarro Forero

• Describes possible combinations of processes and methodologies to address the complex problems
• Focuses on the value of systemic thinking and complexity management for decision makers
• Demonstrates methods of addressing complexities in private, public and mixed companies and vulnerable

Part of the book series: Synthesis Lectures on Engineers, Technology, & Society (SLETS, volume 29)

Untangling Complexity—Peace Building Engineering: Systems Thinking & Complexity Management to Support Community Development | SpringerLink

https://link.springer.com/book/10.1007/978-3-031-37038-0

Sveta Stoytcheva, Author

https://scalar.usc.edu/works/boundary-objects-guide/boundary-objects?path=index

[There seems to be precious little systems thinking in this, judging from the syllabus – ‘mapping the system’, ‘the iceberg model’, stakeholder interviewing, some visioning… and the old canard of ‘complexity’ and ‘root causes’… I dunno]

A holistic approach to problem solving starts with people

DOWNLOAD SYLLABUS

Course Outcomes

• Gain techniques for mapping complex systems and identifying the root causes of a problem.
• Establish a shared view of the system and reframe problems from different perspectives to uncover new solutions.
• Find the right problems to solve and pick the best solutions to experiment with.
• Deepen your understanding of your organizational systems by taking an iterative approach to testing solutions and gaining insights.

Part of Certificate Programs

• Change Leadership Certificate

Course themes

Decision Making Collaboration Systems Thinking

About the Course

People are at the heart of every complex human system–but they’re often the most overlooked. Effective problem solvers today know how to visualize the larger dynamics of the system while staying grounded in the needs of people. In this course, you’ll learn to combine the analytical tools of systems thinking with the creative mindsets of human-centered design to make sense of complex systems challenges. Explore mapping tools to identify the right places to focus, surface insights about your stakeholders, and pick the most impactful solutions to experiment with so you can go beyond the obvious and design lasting solutions.

Human-Centered Systems Thinking – New IDEO U Course