This document discusses the connections between classical economics, Austrian economics, and complexity theory. It argues that (1) models in modern economics oversimplify human behavior and interactions, which are actually very complex, (2) Austrian economists like Hayek recognized economics as a complex, adaptive system and anticipated ideas from complexity theory, and (3) complexity theory provides a useful framework for understanding spontaneous order and economic change over time in a way that acknowledges our limited knowledge.
The relationship between 'modernity' and 'capitalism' and its implication in the context of South East Asia including Thailand, especially in the recent contemporary political context (Thailand deep polarizing and political struggle : 2006 - 2014 and going on...)
Muhammad Saud Kharal
PhD in Social Science, Department of Sociology Faculty of Social and Political Sciences, Universitas Airlangga, Surabaya Indonesia
The relationship between 'modernity' and 'capitalism' and its implication in the context of South East Asia including Thailand, especially in the recent contemporary political context (Thailand deep polarizing and political struggle : 2006 - 2014 and going on...)
Muhammad Saud Kharal
PhD in Social Science, Department of Sociology Faculty of Social and Political Sciences, Universitas Airlangga, Surabaya Indonesia
The post modernity as ideology of neoliberalism and globalizationFernando Alcoforado
The failure of the Enlightenment and Modernity in the realization of human progress and of happiness achievement for humans paved the way for the advent of Post-Modernity that is a cultural reaction to the loss of confidence in the universal potential of the Enlightenment project and Modernity. The Postmodernism means, therefore, a reaction to what is modern. Some schools of thought are located its origin in the alleged exhaustion of the modernity project by the end of the twentieth century.
Max Weber's modernisation theory and applications, including the case of capoeira in Rio de Janeiro and Salvador, containerisation, and consumer capitalism. (Note: part 1 given by a colleague, so I won't be posting it.)
The post modernity as ideology of neoliberalism and globalizationFernando Alcoforado
The failure of the Enlightenment and Modernity in the realization of human progress and of happiness achievement for humans paved the way for the advent of Post-Modernity that is a cultural reaction to the loss of confidence in the universal potential of the Enlightenment project and Modernity. The Postmodernism means, therefore, a reaction to what is modern. Some schools of thought are located its origin in the alleged exhaustion of the modernity project by the end of the twentieth century.
Max Weber's modernisation theory and applications, including the case of capoeira in Rio de Janeiro and Salvador, containerisation, and consumer capitalism. (Note: part 1 given by a colleague, so I won't be posting it.)
PPT presentation developed and implemented while at the Alabama Organ Center to educate clinicians regarding the necessity of collaboration with respect to maximizing opportunities for eye, organ, and tissue donation emphasizing the hospital clinician\'s role in the organ donation and recovery process.
R. Rosicki, The Crisis of the Formula of Liberal Democracy, w: Ł. Jureńczyk, N. Shukuralieva, W. Trempała (red.), Kryzys w stosunkach międzynarodowych, KPSW, Bydgoszcz 2012, pp. 19 - 37.
Twenty Years of European Business Ethics– Past Development.docxmarilucorr
Twenty Years of European Business Ethics
– Past Developments and Future Concerns
Luc van Liedekerke
Wim Dubbink
ABSTRACT. Over the past 20 years business ethics in
Europe witnessed a remarkable growth. Today business
ethics is faced with two challenges. The first comes from
the social sciences and consultants who have both
reclaimed the topics of business ethics, regretfully often at
the loss of the proper ethical perspective. The second
comes from the remarkable rise of corporate social
responsibility which has pushed aside the mainstream
business ethics methodology with its emphasis on moral
deliberation by the individual. These challenges can be
tackled by an institutional transformation in business
ethics that links up to the long-standing European tradi-
tion of institutional analysis of the market. The second
remedy is an enlargement of the research agenda in
business ethics by coming closer to other parts of applied
ethics where the business ethics view is at this moment
grossly neglected.
KEY WORDS: business ethics, corporate social respon-
sibility, Europe
From Europe to America and back:
the invention of business ethics
Both the greatest critics and the greatest advocates of
the free market often point out that the ‘‘moral
viewpoint in business’’ is an oxymoron. Morality does
not, should not or cannot have any business in busi-
ness because man is greedy beyond redeem or because
systemic pressure is relentless. Only strong (govern-
ment) regulation can and should curtail business in
order to safeguard our fundamental rights. Any
business ethicist, who was confronted with this type
of remarks, knows how to rebut these comments as a
mantra learned by heart. Even if man has fundamental
rights, these rights do not overrule morality, but
presuppose it. And if the last 50 years have given us
any macro-sociological truth, it is that ‘the state’ or
‘the system’ is not going to save us – at least not
without humans helping them and helping them-
selves. What is more, systemic power is not com-
pletely beyond societal control and not so relentless
that the actor perspective becomes completely trivial,
as man cannot be reduced to greediness, even if self-
interest can become at times quite dominant.
As much as business can never do without ethics,
‘‘business ethics’’ as an academic discipline is a rare
breed. It is in a sense surprising that it could develop
in Europe at all (van Luijk, 2006, p. 7). In the 60s and
70s many people were quite critical of ‘‘the corporate
interest’’ and the ‘‘profit motive’’ as such. Societal
problems such as pollution, structural poverty and
over-consumption were squarely blamed on business
but ‘‘business ethics’’ was not seen as part of the
solution by these critics. On the contrary, it was
perceived as a cover up meant to lure the public into
believing that the market and the businessman could
add something positive to society. Conversely,
business peopl ...
How the Culture of Economics Stops Economists from Studying Group Behavior an...hacyard
'Today, wealthy individuals and well-organized business and financial groups exercise their power by means of costly public relations, advertising, and lobbying activities.
By “investing” in the promotion of their interests, private financial interests have largely captured the major political parties in most democratic countries as well as the news media that communicate political events and debates to the public.
When the news media seek economists to provide commentary and insight into economic issues, more often than not they interview economists who work for business or financial firms, not independent universities or impartial
research organizations...'
Article Link:
http://wer.worldeconomicsassociation.org/papers/how-the-culture-of-economics-stops-economists-from-studying-group-behavior-and-the-development-of-social-cultures/
The Invention of Capitalism - Michael Perelmanberat celik
The Invention of Capitalism is novel in four major respects. First, it
addresses the question of what determines the social division of labor, the
division of society into independent firms and industries from the per-
spective of classical political economy. It also develops the theoretical
implications of primitive accumulation. Third, this book offers a signifi-
cantly different interpretation of classical political economy, demonstrat-
ing that this school of thought supported the process of primitive ac-
cumulation. Finally, it analyzes the role of primitive accumulation in the
work of Marx. All of these threads come together in helping us to under-
stand how modern capitalism developed and the role of classical political
economy in furthering this process.
Constructivist Political EconomyRawi Abdelal, Mark Blyth, .docxmaxinesmith73660
Constructivist Political Economy
Rawi Abdelal, Mark Blyth, and Craig Parsons
January 14, 2005
13,330 words, including footnotes
Chapter One: The Case for a Constructivist International Political Economy
Introduction: Constructivism – Where to Find it, and Where Not
Social constructivism focuses on the social facts of the world. These social facts
exist only because everyone agrees that they exist. Social facts are very real, and they are
the product of intersubjectively (that is, collectively) held beliefs that cannot be reduced
to a series or summation of subjective, individual beliefs. Social facts differ
fundamentally from material facts, the reality that exists irrespective of collective beliefs
about its existence, but they nonetheless have causal properties.. As John Ruggie
observes, “collectivities of individuals within states hold intersubjective understandings
that affect their behavior,” just as do “collectivities of states.”
Although what we think of as “the world economy” is composed of both material
and social facts, the field of international political economy (IPE) within political science
has tended until recently to focus almost exclusively on the material facts of the
economy. Materialist scholars have attempted to map individual, firm, and government
preferences over outcomes onto these material facts, thereby privileging the rational,
goal-oriented pursuit of policies as the central causal mechanism in accounts of economic
policy making. In IPE, the combination of materialism and rationalism has become the
dominant, even orthodox, view of the world economy.
IPE has been remarkably impervious to inroads from sociological approaches to
economic policy making. The intersubjective beliefs that give the world meaning are
absent in almost all IPE scholarship. Indeed, IPE is increasingly the last bastion for the
materialists and rationalists, who have had increasingly to share the intellectual terrain
with the constructivists on virtually all other topics. Constructivists have made
contributions that are recognized as fundamentally important to economics and sociology,
as well as to every other sub-field in political science. Similarly, economic sociology has
produced a vibrant research program that has influenced policy and management
scholarship as well. As Frank Dobbin observes,
“Sociologists began to explain economic behavior in terms of the same four social
mechanisms they had observed shaping all of social behavior. These mechanisms entered
the common lexicon under the terms institution, network, power, and cognition.
Sociology’s core insight is that individuals behave according to scripts that are tied to
social roles. Those scripts are called conventions at the collective level and cognitive
schemas at the individual level.”
Similarly, cultural, ideational, and institutionalist theorists have made similar
claims in comparative politics for .
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Securing your Kubernetes cluster_ a step-by-step guide to success !
Economics And The Complexity
1. Pratt 1
Economics and the Complexity Vision
2009 Summer Project
Greg Pratt
Mesa Community College
The static neo classical model of economics typically found in the economics
classroom (and professional journals) belies the reality of human interaction. While
models demand a set of simplifying assumptions, the quantitative approach that swept
economics in the post WW II era to dominate the profession does as great a disservice to
society as a service. However, looking back to classical economics as well as the
Austrian school a small group of scholars have begun to examine what has been called
economic behavior from another perspective. While these scholars are a tiny part of the
profession, their view has more than passing importance. David Colander in The
Complexity Vision and the Teaching of Economics observes: “. . . the field of economics
displayed many of the characterize a complex system. It had a self-organized quality to
it, and it dealt with interdependent agents. Indeed it has along history of explanations
involving the invisible hand and spontaneous order. “(1).
So the examination of the emerging work in complexity, (2) centered at the Santa
Fe Institute (SFI), is an appropriate and compelling allocation of time. The Santa Fe
Institute is a private, not-for-profit, independent research and education center founded in
1984, for multidisciplinary collaborations in the physical, biological, computational, and
social sciences. Understanding of complex adaptive systems is critical to addressing key
environmental, technological, biological, economic, and political challenges. Complexity
itself is centre-stage, rather than an emergent property of research in particular
disciplines, at the Santa Fe Institute. (http://www.santafe.edu/about/ ) At SFI, set up in
2. Pratt 2
1984 as an independent research centre, scientists (some of them eminent) from a range
of disciplines – physics, biology, psychology, mathematics, immunology and more - have
engaged with computing expertise to conduct interdisciplinary work on the behaviour of
complex adaptive systems. They have built models which can be interpreted as
representing biological, ecological and economic phenomena. (Rosenhead )Colander’s
edited work in The Complexity Vision and the Teaching of Economics, the inspiration
for this summer project, is based upon the work of SFI scholars and covers a series of
topics ranging from bioeconomics to the Austrian school of economics.
This complexity work is tied to two of the giants in Austrian thought – Ludwig
von Mises and F. A. Hayek as well as Adam Smith. Hayek underscored the importance
of complexity to his body of work in his 1974 Nobel Prize Lecture: “This brings me to
the crucial issue. Unlike the position that exists in the physical sciences, in economics
and other disciplines that deal with essentially complex phenomena, the aspects of the
events to be accounted for about which we can get quantitative data are necessarily
limited and may not include the important ones. . . ., in the study of such complex
phenomena as the market, which depend on the actions of many individuals, all the
circumstances which will determine the outcome of a process, for reasons which I shall
explain later, will hardly ever be fully known or measurable.” The major problem for
any economy Hayek argued is how people’s actions are coordinated. He noticed, as
Adam Smith had, that the price system—free markets—did a remarkable job of
coordinating people’s actions, even though that coordination was not part of anyone’s
intent. The market, said Hayek, was a spontaneous order. By spontaneous Hayek meant
3. Pratt 3
unplanned—the market was not designed by anyone but evolved slowly as the result of
human actions. Roger Koppl writes of the connection between Austrian and complexity:
Austrian economists (of the Hayekian variety at least) share
common elements and a common past with complexity theory.
Complexity theorists trace their origins in part to Ludwig von
Bertalanffy’s work on systems theory and Norbert Wiener, creator of the
related field of cybernetics. Hayek had a series knowledge of and interest
in systems theory and cybernetics. . . . The most characteristic feature of
Hayek’s system of thought is probably his notion of ‘spontaneous order. . .
A spontaneous order is a complex adaptive system. It is Adam Smith’s
idea of the ‘invisible hand’. (Colander 139-140)
The tie then between classical economics, modern Austrian thought and complexity
theory can be found both in the work the SFI as well as the sources of classical and
modern economic thought.
This tie between complexity theory and the Hayekian notion of spontaneous order
(3) is not widely communicated in social sciences and is arguably one of the most
important contributions that is lacking in contemporary social sciences education. The
connection between the two is both clear and compelling. Koppl goes on to clarify this
connection when he points out: “. . . they are complex; for spontaneous orders, the
‘degree of complexity is not limited to what a human mind can master. Second, they are
abstract . . . Third, they have no purpose, ‘not having been made’ by any designing
minds,” (140). This final point is critical, complexity is adaptive, emergent and
evolutionary and the work of the Austrians builds on the insight of Adam Smith to
indicate the implications of these set of conditions which seem to inform behavior. (2)
Harvard economist and former Harvard University President Lawrence Summers
explains Hayek's place in modern economics this way: quot;What's the single most important
thing to learn from an economics course today? What I tried to leave my students with is
4. Pratt 4
the view that the invisible hand is more powerful than the [un]hidden hand. Things will
happen in well-organized efforts without direction, controls, and plans. That's the
consensus among economists. That's the Hayek legacy.quot;(quoted in The Commanding
Heights: The Battle Between Government and the Marketplace that Is Remaking the
Modern World pp. 150-151.)
While Hayek is neglected or often unknown in current economic education, Adam
Smith remains a central, if misunderstood, element of both instructor generated
instruction and textbook analysis of the markets. His invisible hand (mentioned only 3
times in his collected works) is frequently emphasized although misinterpreted. Vernon
Smith, an advocate of the constructivist or complex vision points to Smith’s contributions
to his work in experimental economics. He writes that this vision is:
an undesigned ecological system that emerges out of cultural and
biological evolutionary processes: home grown principles of action,
norms, traditions, and morality. Thus, quot;the rules of morality are not the
conclusions of our reason.quot; According to Hume, who was concerned with
the limits of reason and the boundedness of human understanding,
rationality was a phenomena that reason discovers in emergent
institutions. Adam Smith expressed the idea of emergent order in both The
Wealth of Nations and The Theory of Moral Sentiments. According to this
concept of rationality, truth is discovered in the form of the intelligence
embodied in rules and traditions that have formed, inscrutably, out of the
ancient history of human social interactions. (Vernon Smith)
Vernon Smith argues for the view that Adam Smith in both the well known Wealth of
Nations and virtually unknown Theory of Moral Sentiments finds the emergent and
evolutionary view of human activity persuasive. Thus, the invisible hand metaphor
acquires a deeper meaning as a symbol for what Hayek would call spontaneous order that
is emergent, in the words of Vernon Smith, over the extended period of the “ancient
History of human social interactions. These interactions are the informal institutions –
5. Pratt 5
norms and conventions that Douglass North sees shaping formal institutions and
incentive structures that impact behavior. This process is one that is complex in nature,
has not been fully understood or modeled, in spite of the impression given by
introductory texts in economics that see markets and outcomes as fait accompliat. North
writes: Informal constraints (norms, conventions and codes of conduct) favorable to
growth can sometimes produce economic growth even with unstable or adverse political
rules. So North agrees with Vernon Smith and writes: “It is necessary to dismantle the
rationality assumption underlying economic theory in order to approach constructively
the nature of human learning. History demonstrates that ideas, ideologies, myths,
dogmas, and prejudices matter; and an understanding of the way they evolve are
necessary for further progress in developing a framework to understand societal
change.”(Nobel Lecture)
As Douglass North reminds us, the complicating factor in our study and
instruction of economics is change. In works ranging from Structure and Change in
Economic History to Understanding the Process of Economic Change North reiterates the
centrality challenge of understanding the forces that lead to change. In his 1993 Nobel
lecture North explicates what he calls the non ergodic nature of change. “increasing our
understanding of the historical evolution of economies” can “contribute to our
understanding of the complex interplay between institutions, technology, and
demography in the overall process of economic change.” He concludes much of his
recent work with the twin observations that it is “adaptive rather than allocative
efficiency that is key to our understanding of complex economic process and path
dependence, one of the remarkable regularities of history. . . . Pioneering work on this
6. Pratt 6
subject is beginning to give us insights into the sources of path dependence (Arthur, 1989
and David, 1985). But there is much that we still do not know.” (Nobel) In a subsequent
Nobel ceremony, Vernon Smith recognized this limitation in his banquet toast. (4)
So the line of thought from Smith to Hayek to North is clear – there is much we
do not know, the modern models used in economics mask or ignore this ignorance and
complexity theory is a vision or prism that can allow a more realized view of human
behavior. All three provide a rationale for their vision; the economic growth or change
has allowed humanity to dramatically increase the standard of living in the 21st century.
While an understanding of the limitation of contemporary quantitative economic
modeling, institutions such as the Santa Fe Institute seem to argue for a Hayekian
recognition of the limits to understanding of spontaneous orders or complex systems.
Complexity theory views behavior over time as informed by a series of certain
kinds of complex systems. The systems of interest are dynamic systems – systems
capable of changing over time and economics is concerned with change. Hayek points
out that: “It is, perhaps, worth stressing that economic problems arise always and only in
consequence of change.”(Use of Knowledge). So the underlying vision of complexity
theory is well positioned to examine the processes that shape and motivate behavior.
Chris Lucas points that that once goal of theory is to view complexity in a self-organizing
context. (5) The key to this goal is the realization that, as Hayek titled his Nobel Lecture,
knowledge is a pretense.
7. Pratt 7
Notes
(1) Because it is undesigned and not the product of conscious reflection, the
spontaneous order that emerges of itself in social life can cope with the radical
ignorance we all share of the countless facts on knowledge of which society
depends. This is to say, to begin with, that a spontaneous social order can utilize
fragmented knowledge, knowledge dispersed among millions of people, in a way
a holistically planned order (if such there could be) cannot. “This structure of
human activities” as Hayek puts it “consistently adapts itself, and functions
through adapting itself, to millions of facts which in their entirety are not known
to everybody. The significance of this process is most obvious and was at first
stressed in the economic field.”34 It is to say, also, that a spontaneous social
order can use the practical knowledge preserved in men's habits and dispositions
and that society always depends on such practical knowledge and cannot do
without it.
http://oll.libertyfund.org/?option=com_staticxt&staticfile=show.php
%3Ftitle=1305&chapter=100481&layout=html&Itemid=27
(2) Complexity and chaos theory have already generated an impressive literature, and
a specialised vocabulary to match. This introduction can, at most, sketch in the
general area of intellectual activity, and hope to draw the sting of the
terminology. The works cited above are possible starting points for those wishing
to pursue the subject in more depth.
The more general name for the field is complexity theory (within which ‘chaos’ is
a particular mode of behaviour). It is concerned with the behaviour over time of
certain kinds of complex systems. Over the last 30 years and more, aspects of this
behaviour became the focus of attention in a number of scientific disciplines.
These range as widely as astronomy, chemistry, evolutionary biology, geology
and meteorology. Indeed there is no unified field of complexity theory, but rather
a number of different fields with intriguing points of resemblance, overlap or
complementarity. While some authors refer to the field as ‘the science of
complexity’, others more modestly and appropriately use the phrase in the plural.
The systems of interest to complexity theory, under certain conditions, perform in
regular, predictable ways; under other conditions they exhibit behaviour in which
regularity and predictability is lost. Almost undetectable differences in initial
conditions lead to gradually diverging system reactions until eventually the
evolution of behaviour is quite dissimilar. The most graphic example of this is the
8. Pratt 8
oft-quoted assertion that the flapping of a butterfly’s wing can in due course
decisively affect weather on a global scale.
The systems of interest are dynamic systems – systems capable of changing over
time – and the concern is with the predictability of their behaviour. Some systems,
though they are constantly changing, do so in a completely regular manner. For
definiteness, think of the solar system, or a clock pendulum. Other systems lack
this stability: for example, the universe (if we are to believe the ‘big bang’
theory), or a bicyclist on an icy road. Unstable systems move further and further
away from their starting conditions until/unless brought up short by some over-
riding constraint – in the case of the bicyclist, impact with the road surface.
Stable and unstable behaviour as concepts are part of the traditional repertoire of
physical science. What is novel is the concept of something in between – chaotic
behaviour. For chaos here is used in a subtly different sense from its common
language usage as ‘a state of utter confusion and disorder’. It refers to systems
which display behaviour which, though it has certain regularities, defies
prediction. Think of the weather as we have known it. (That is, I will leave
possible future global climate change out of the picture.) Despite immense efforts,
success in predicting the weather has been quite limited, and forecasts get worse
the further ahead they are pitched. And this is despite vast data banks available on
previous experience. Every weather pattern, every cold front is different from all
its predecessors. And yet…the Nile doesn’t freeze, and London is not subject to
the monsoon.
Systems behaviour, then, may be divided into two zones, plus the boundary
between them. There is the stable zone, where if it is disturbed the system returns
to its initial state; and there is the zone of instability, where a small disturbance
leads to movement away from the starting point, which in turn generates further
divergence. Which type of behaviour is exhibited depends on the conditions
which hold: the laws governing behaviour, the relative strengths of positive and
negative feedback mechanisms. Under appropriate conditions, systems may
operate at the boundary between these zones, sometimes called a phase transition,
or the ‘edge of chaos’. It is here that they exhibit the sort of bounded instability
which we have been describing – unpredictability of specific behaviour within a
predictable general structure of behaviour.
http://www.human-nature.com/science-as-culture/rosenhead.html
(3) One idea propounded by Hayek is central for the understanding of the Social
Sciences: the notion of complex phenomena. This notion was originally
introduced in his paper “The theory of the complex phenomena” published in
Studies in 1967. He proposes that the degree of complexity of a phenomenon
depends upon “the minimum number of elements of which an instance of the
11. Pratt 11
thinking, that of defining just what complexity is, why one system of, say, 100
components differs from another of the same size.
To approach such questions we need to look for patterns as well as the statistics of
quantity. It is clear that an arrangement of 50 white then 50 black balls is less complex
than 5 black, 17 white, 3 black, 33 white, 42 black, yet the significance of such a pattern
is unclear - is it random or meaningful ? When we expand this sort of analysis to 3
dimensional solids, and include more than one property of each part (e.g. adding size,
density, shape), we get a combinatorial explosion of possible complexity that strains the
analytical (pattern recognition) ability of current mathematics, even for relatively trivial
systems. We have concentrated so far on just visual modalities, and views at a single
magnification, yet we should be aware also that in nature multiple levels of structure exist
in all systems, and this added fractal complication (e.g. complexity of molecule, plus cell,
plus organism, plus ecosystem, plus planet etc.) makes even this static simplification
mathematically difficult to quantify.
Dynamic Complexity (Type 2)
Adding the fourth dimension, that of time, both improves and worsens the situation. On
the positive side, we can perhaps recognise function in temporal patterns more easily than
in spatial ones (e.g. seasons, heartbeat), but conversely by allowing components to
change we can lose those spatial patterns we originally identified, categories and
classifications alter with time (e.g. leaves are green - except in autumn when they are
yellow, and winter when they don't exist !). Function is one of the main modes of
analysis we utilise in science, we ask the question 'what does the system do?', followed
by 'how does it do it?', and both these presuppose actions in time (cyclic processes), an
intrinsic meaning to the structures encountered.
Given our obsession with experimental repeatability in science, it is interesting to note
that the property of being either static or cyclic is at the heart of our classification of
phenomena as either being scientific or not. Science relies heavily on testing or
confirmation, and this presupposes that we have multiple samples (either spatially or
temporally). The forms of mathematical description that we employ will therefore have to
be such that we obtain the same answers each time, and this has major implications for
complexity theory. We are forced, currently, to artificially reduce the complexity of the
phenomena we study to meet this constraint. A person has many aspects, but we describe
them only by those that do not change with time (or do so predictably), e.g. name, skin
colour, nationality (or address, job, age, height). Complexity theory however requires that
we treat the system as a whole, and thus have a description that includes all aspects (as
far as practical). In this we go far beyond conventional scientific and mathematical
treatments, by including also one-off or variable aspects (e.g. actions, moods).
Evolving Complexity (Type 3)
Going beyond repetitive thinking takes us to a class of phenomena usually described as
organic. The best known examples of this relate to the neo-Darwinian theory of Natural
12. Pratt 12
Selection, where systems evolve through time into different systems (e.g. an aquatic form
becomes land dwelling). This open ended form of change proves to be far more extensive
than previously thought, and the same concept of non-cyclic change can be applied to
immune systems, learning, art and galaxies, as well as to species. Classification of
complexity thus takes another step into the dark, since if we cannot count on there being
more than one example of any form how can we even apply the term science to it ?
The answer to this question comes back to pattern. In any complex system many
combinations of the parts are possible, so many in fact that we can show that most
combinations have not yet occurred even once, during the entire history of the universe.
Yet not all systems are unique, there are symmetries present in the arrangements that
allow us to classify many systems in the same way. By examining a large number of
different systems we can recognise these similarities (patterns) and construct categories
to define them (this is, in essence, what the Linnean taxonomy scheme for living
organisms is based upon). These statistical techniques are fine, and give useful general
guidelines, but fail to provide one significant requirement for scientific work, and that is
predictability. In the application of science (in technology) we require to be able to build
or configure a system to give a specific function, something not usually regarded as
possible from an evolutionary viewpoint.
Self-Organizing Complexity (Type 4)
Our final form of complex system is that believed to comprise the most interesting type
and the one most relevant to complexity theory. Here we combine the internal constraints
of closed systems (like machines) with the creative evolution of open systems (like
people). In this viewpoint we regard a system as co-evolving with its environment, so
much so that classifications of the system alone, out of context, are no longer regarded as
adequate for a valid description. We must describe the system functions in terms of how
they relate to the wider outside world. From the previous categories of discrete and self-
contained systems we seem to have arrived at a complexity concept that cannot now even
qualify a separate system, let alone quantify it, yet this misses an important point.
Co-evolutionary systems, like ecologies and language, are extremely adept at providing
functionality, and if this is a requirement of science (the what question) we may be able
to side-step the how question and tackle the desired predictability in another way. This
methodology moves the design process from inside the system under consideration to
outside. We can design the environment (constraints) rather than the system itself, and let
the system evolve a solution to our needs, without trying to impose one. This is a very
new form of organic technology, yet one already beginning to show results in such fields
as genetic engineering, circuit design and multiobjective optimization. From the point of
view of complexity theory we wish to be able to predict which emergent solutions will
occur from differing configurations and constraints.
Quantification Preliminaries
13. Pratt 13
If we allow that traditional quantification in terms of static parameters or formulae is (at
best) inadequate to fully deal with complex systems, then what other options do we
have ? Specifically, how do we deal with variables and constants that swap places over a
system lifetime (the edge of chaos interplay of barriers and innovation) ? In essence we
need to allow that all the parameters in our system are variables (operating at differing
timescales perhaps), and also allow for the number of parameters to increase or reduce
dynamically (simulating birth or death). This again is a break from tradition in science,
and requires what Kuhn called a scientific revolution - a new paradigm or set of initial
axioms. This is what Complexity Theory provides.
Having set out the considerable problems we face in the analysis of complex systems, we
can now turn to more positive matters. Much work has already been done as a
preliminary to the quantification of complexity theory, and we can build on some 50
years of work in general systems theory or cybernetics, in linguistics, dynamics and
ecology, as well as in modern genetics, cognitive science and artificial intelligence. The
mistakes and successes of this inheritance can help steer our path towards more
productive assumptions, those relating to the common features we find across the subject
matter of all these disciplines, and related areas.
Assumptions and Objectives
In complexity thought we look for global measures that can apply in all fields. This
assumption, along with others related to unpredictability, non-equilibria, causal loops,
nonlinearity and openness means that our world view is in many ways the opposite of
traditional science. Yet all these assumptions are valid for the organic style systems being
considered here. A new type of quantification may well be needed in consequence.
Many objectives can be proposed for Complexity Theory itself, e.g. :
• Explain emergent structures (self-organization)
• Measure relative complexity (hierarchical multi-parameter)
• Provide control methods for complex systems (steering points)
• Generate effective models (abstractions)
• Give statistical predictors (constraints)
• Solve outstanding problems (breakthroughs)
• Demonstrate possible new applications (novelty)
• Quantify the laws of order and information (if any)
http://www.calresco.org/lucas/quantify.htm
14. Pratt 14
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http://www.calresco.org/lucas/quantify.htm
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PRACTICE
http://www.human-nature.com/science-as-culture/rosenhead.html
15. Pratt 15
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