theory of science - mdh · theory of science research, technology, ... transformative hermeneutics...

CDT403 Research Methodology in Natural Sciences and Engineering

Theory of ScienceRESEARCH, TECHNOLOGY, SOCIETY,

COMPLEXITY AND INTERDISCIPLINARITY

Gordana Dodig-Crnkovic

1School of Innovation, Design and Engineering

Mälardalen University

SCIENCE RESEARCH TECHNOLOGY SOCIETYSCIENCE, RESEARCH, TECHNOLOGY, SOCIETY, COMPLEXITY

SCIENCES ON DIFFERENT LEVELS OF ORGANIZATION

SCIENCE, RESEARCH, TECHNOLOGY

SCIENCE, SOCIETY, PRODUCTION – TRIPLE HELIX, ,

SCIENCE, RESEARCH, TECHNOLOGY, PROGRESS

SCIENCE WARS AND COLLABORATION:TRANSDISCIPLINARY, INTERDISCIPLINARY ANDCROSSDISCIPLINARY RESEARCH

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SCIENCE IN MICRO AND MACROCOSMOSLevels of abstraction/Levels of organizationLevels of abstraction/Levels of organization

Sciences, Objects and Methods

http://www.youtube.com/watch?v=akbilxS1dGc&feature=related zoom in – zoom out

SCIENCE OBJECTS DOMINATING METHODSCIENCE OBJECTS DOMINATING METHOD

Simple Reductionism (analysis)

Logic & Abstract objects: D d tiLogic &Mathematics

Abstract objects:propositions, numbers, ... Deduction

Natural SciencesNatural objects: physical bodies,

fields and interactions, living organisms

Hypothetico-deductive methodorganisms ...

Social SciencesSocial objects:

human individuals, groups, society, ..

Hypothetico-deductive method + Hermeneutics

C lt l bj t h idHumanities

Cultural objects: human ideas, actions and relationships, language,

artefacts…Hermeneutics

Complex Holism (synthesis)

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p ( y )

SCIENCE RESEARCH TECHNOLOGYSCIENCE, RESEARCH, TECHNOLOGYAristotle's Distinctions between Science and Technology

Science Technology

Object unchangeable changeable

Principle of motion inside outside

End knowing the general knowing the concrete

Activity theoria: end in itself poiesis: end external

Method abstraction modeling complexityg p y

Process conceptualizing optimizing

Innovation form discovery invention

Type of result law-like statements rule-like statements

Time perspective long-term short-term

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SCIENCE, RESEARCH, DEVELOPMENT AND TECHNOLOGY

ResearchResearch

Science

Development

Technology

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CLASSICAL SCIENCES LANGUAGE BASED SCHEME

Culture

Logic &

MathematicsCulture(Religion, Art, …)

Natural Sciences(Physics,

Chemistry,Biology )Biology, …)

Social SciencesSocial Sciences(Economics,

Sociology,Anthropology, …)

Computing

The Humanities(Philosophy, History,

Li i ti )

Computing

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Linguistics …)

SCIENCES BASED ON SEVERAL RESEARCH FIELDS – CROSS DISCIPLINARY RESEARCH

Our basic scheme represents classical sciences. Many modern sciences however are stretching over severalMany modern sciences however are stretching over several research fields of our scheme. Computer science e.g. includes the field of AI that has its roots in mathematical logic and mathematics but uses physics, chemistryand biology and even has parts where medicine and psychologyare very important.Software Engineering include both formal methods and project management. HCI human computer interaction combines knowledge from “hard”HCI, human-computer interaction combines knowledge from hard and “soft” sciences.Computer games border with arts.

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TECHNOLOGY EXPANDS OUR WAYS OF THINKING ABOUT THINGS EXPANDSTHINKING ABOUT THINGS, EXPANDS OUR WAYS OF DOING THINGS.

Herbert A SimonHerbert A. Simon

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SCIENCE AND SOCIETYTHE “TRIPLE HELIX” MODEL

SOCIETY

Knowledge society based on ICT

CULTURE The triple helix model: – ACADEMIA

SCIENCES & HUMANITIES

ACADEMIA– PRODUCTION

(ECONOMY)– GOVERMENT

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SOCIETAL ASPECTS OF SCIENCE

Science has undoubtedly several important facets:

- insights in foundational issues (understanding of the world)- applications (practical use)

societal aspects (impact on the society)- societal aspects (impact on the society)

Sciences are promoting rational and analytical discussions of the fcentral issues of concern to scientists and other scholars, and to

the public at large, both in terms of knowledge production and in practical applications.

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SOCIETAL ASPECTS OF SCIENCERESEARCH COMMUNITY AS INFORMATIONAL NETWORK

“ if we consider Galileo alone in .. if we consider Galileo alone in his cell muttering, ‘and yet it moves,’ with the recent meeting t K t h h d fat Kyoto – where heads of

states, lobbyists, and scientists were assembled together in the same place to discuss the Earth – we measure the difference ..”

Bruno LatourBruno Latour

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SOCIETAL ASPECTS OF SCIENCE

Further reading on current topics:http://www sciencemag orghttp://www.sciencemag.org

Essays on Science and Society Science magazine

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POSTMODERNISM AND THE NATURE OF SCIENCE

Modernism may be seen as the height of the Enlightenment's quest for an rational aesthetics, ethics, and knowledge.

Postmodernism is a cultural and philosophical movement which formed in reaction to modernismformed in reaction to modernism.

Postmodernism is concerned with how the authority of those ideals sometimes called meta narratives are undermined throughideals, sometimes called meta-narratives, are undermined through fragmentation and deconstruction.

Meta-narratives - "grand narratives“, form of ‘universal truth'

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POSTMODERNISM

Postmodernism attacks the primacy of ideas of universals andPostmodernism attacks the primacy of ideas of universals and encourages fractured, fluid and multiple perspectives and is marked by an increasing importance in the ideas from the Sociology of knowledgeSociology of knowledge.

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POSTMODERNISM

All knowledge, scientific knowledge included, is found to be socially constructed. Being “socially constructed” implies not absolute, but relative to the humans and humanity. No (absolute) objectivity exists.

From that correct observation, postmodernism draws a very far-reaching conclusion: “Science is merely one story among others.”

The world we know is one that is constructed by human discourses. From the point of view of knowledge (epistemologically ), a

i tifi t t i d t d b i ith lit t tscientific text is understood as being on a par with a literary text.

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SCIENCE WARS (1)

In early 1996 the physicist Alan Sokal who was provoked by postmodernist derogatory attitude to science caused a controversypostmodernist derogatory attitude to science caused a controversy by publishing two controversial journal articles.

The first article, Transgressing the Boundaries: Toward a Transformative Hermeneutics of Quantum Gravity appeared in the journal Social Text.

It pretended to be a serious article on the implications of developments in the field of cultural studies for developments indevelopments in the field of cultural studies for developments in modern physics, and vice-versa.

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SCIENCE WARS (2)

The second article, A Physicist Experiments with Cultural Studies, appeared in the journal Lingua Franca just as issue of Social Textappeared in the journal Lingua Franca just as issue of Social Textcontaining the first article came out. It revealed that the first article was in fact a hoax.

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SCIENCE WARS (3)

But why did he do it?

“And I'm a stodgy old scientist who believes, naively, that there exists an external world, that there exist objective truths about that world and that my job is to discover some of them “world, and that my job is to discover some of them.

Allan Sokal

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SCIENCE WARS (4)

“To test the prevailing intellectual standards, I decided to try a modest (though admittedly uncontrolled) experiment:modest (though admittedly uncontrolled) experiment:

Would a leading North American journal of cultural studies (..) publish an article liberally salted with nonsense if (a) it sounded good and (b) it flattered the editors' ideological preconceptions? “

Allan Sokal

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SCIENCE WARS (5)

The post modern ideas were known as Deconstructionism and Social Constructivism.

The branch of sociology, Sociology of Scientific Knowledge (SSK) and Science and Technology Studies (STS) were influences by postmodern gy ( ) y pmovements and had the objective of showing that the results of scientific findings did not represent objective reality, but were basically instruments of the ideology of dominant groups within societyinstruments of the ideology of dominant groups within society.

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POSTMODERNIST ANTI-SCIENTISMPOSTMODERNIST ANTI-SCIENTISM

Post-modernism was a radical critique against science, contemporary philosophy and current understanding of rationality.

The view of science as a search for truths (or approximate truths) about the world was rejectedabout the world was rejected.

According to postmodernism, the natural world has a subordinated role in the construction of scientific knowledgerole in the construction of scientific knowledge.

Science was just another social practice, producing ``narrations'' and ``myths'' with basically no more validity than any other myths.

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IS THERE ANYTHING NEW UNDER THE SUN?IS THERE ANYTHING NEW UNDER THE SUN? ANY PROGRESS?

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AN EXAMPLE OF PROGRESS - TRANSPORTATIONAN EXAMPLE OF PROGRESS TRANSPORTATION

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AN EXAMPLE OF PROGRESS - TRANSPORTSAN EXAMPLE OF PROGRESS - TRANSPORTS

24Beam me up Scotty next?

SCIENCE WARS (6)SCIENCE WARS (6)

Sources for further reading:Sources for further reading:

http://www.physics.nyu.edu/faculty/sokal

http://www.math.gatech.edu/~harrell/cult.html

http://skepdic.com/sokal.html

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WHAT HAVE WE LEARNED FROM POSTMODERNISM?

Humans always produce theories that are context-dependent andHumans always produce theories that are context dependent and based on our (human) perspective. It is good to be aware of that context in which science operates.

Society is an important factor when it comes to politics, including policies in science which provides resources for science.

In a given context, by scientific methods we can reach our best knowledge, which is constantly improving

If not seen as absolute, but our best common knowledge about the world, science has a very distinct position among different

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y p gpossible descriptions of the world.

END OF SCIENCE WARS AND NEW EMERGING ALLIANCES

At present, a lot of activity in cross-disciplinary, multi-disciplinaryand inter-disciplinary collaborations.and inter disciplinary collaborations.

Examples: Computing and Philosophy http://ia-cap.organdInterdisciplines (Topics: Adaptation and Representation, Art and Cognition Causality Enaction (Action and perception intertwined)Cognition, Causality, Enaction (Action and perception intertwined), Issues in Coevolution of Language and Theory of Mind.)http://www.interdisciplines.org

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RESEARCH, COMMUNICATION AND ICT

New development of collaborationsNew development of collaborations between different research disciplines is enabled by the

f t h lprogress of technology.However, there is a problem of communication: Different knowledge fields traditionally have different languages.

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RESEARCH, COMMUNICATION AND ICT

Sciences cover well defined domains (physics, mathematics, biology, sociology, economy…) where knowledge is produced by specific scientific communities through intense communication within a group and with not much communication with the rest of the world.o e o d

However, access to knowledge have b d i tibecome easy and communication between sciences, arts and humanities more and more common.

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Cybernetics as a Language forCybernetics as a Language for Interdisciplinary Communication

Stuart A. UmplebyThe George Washington UniversityThe George Washington University

Washington, DCwww.gwu.edu/~umpleby

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How is interdisciplinary communication possible?

[Cybernetics is the interdisciplinary study of the structure of regulatory systems. Cybernetics is closely related to control theory and systems theory. Both in its

i i d i it l ti i th d h lf f th 20th t b ti iorigins and in its evolution in the second-half of the 20th century, cybernetics is equally applicable to physical and social (that is, language-based) systems. (Wikipedia)]

• We need to share a common language

• Perhaps there is a common “deep structure” which is hidden by our more specialized discipline-oriented terms and theories

31After Stuart A. Umpleby

Common processes in the external world

James G. Miller’s suggests that living systems exist at seven levels: - cell- cell, - organ, - organism,

group- group, - organization, - nation, - supranational organization


Basic concepts

In cybernetics there are three fundamental concepts:

Regulation

Self-organization

fReflexivity


Regulation

Regulation is based on two elements – regulator and system being regulated

Engineering examples – thermostat and heater, automatic pilot and airplaneand airplane

Biological examples – feeling of hunger and food in stomach, light in eye and iris openinglight in eye and iris opening

Social system examples – manager and organization, therapist and patient


The law of requisite variety

Information and selection“The amount of selection that can be performed is limited byThe amount of selection that can be performed is limited by

the amount of information available”

Regulator and regulated“The variety in a regulator must be equal to or greater than the

variety in the system being regulated”variety in the system being regulatedW. Ross Ashby


Coping with complexity

When faced with a complex situation, there are two choices

1. Increase the variety in the regulator: hire staff or subcontract

2. Reduce the variety in the system being regulated: reduce the variety one chooses to controlthe variety one chooses to control


The management of complexity

• There has been a lot of discussion of complexity, as if it exists in the world

• Cyberneticians prefer to speak about “the management of complexity”complexity

• Their view is that complexity is observer dependent, that the system to be regulated is defined by the observersystem to be regulated is defined by the observer


Self-organization

• Every isolated, determinate, dynamic system obeying unchanging laws will develop organisms adapted to their environments. W. Ross Ashby

• Many elements within the system• Boundary conditionsBoundary conditions– open to energy (hence dynamic), – closed to information (interaction rules do not change during the

period of observation)period of observation)

http://www-lih.univ-lehavre fr/ bertelle/cossombook/cossombook html

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lehavre.fr/~bertelle/cossombook/cossombook.htmlComplex Systems and Self-organization Modelling After Stuart A. Umpleby

Examples of self-organization

• Physical example – chemical reactions; iron ore, coke, and oxygen heated in a blast furnace will change into steel, carbon dioxide, water vapor and slagcarbon dioxide, water vapor and slag

• Biological examples – food in the h i f d i blstomach is transformed into usable

energy and materials, species compete to yield animals adapted to their environments, insect swarms


SELF ORGANIZATION IN ARTIFACTSSELF-ORGANIZATION IN ARTIFACTS

http://www.youtube.com/watch?v=SkvpEfAPXn4

http://groups.csail.mit.edu/mac/projects/amorphous/Robust/

http://www.calresco.org/links.htm Self-organization resources

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DIGITAL VIDEO FEEDBACK AND MORPHOGENESIS

Video Feedback systems tend toward either stability or chaos. While the stable attractor offers some interest in the subtleties of its decay, the unstable attractor offers an unlimited supply of endless evolving motifs and an emergent behaviour.

The system can be get into chaotic emergence via camera movement (rotation and positioning). The important thing was to catch the movement of ‘catching a shape’ in a particular temporal phase to feed back i h d i h l iinto the system advancing the complexity and initiating lifelike morphogenesis.

http://www.transphormetic.com/Talysis01.htm

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COMPLEX SYSTEMS

http://www.youtube.com/watch?v=QmrWfRX42ZM&feature=related

Four Important Characteristics of Complexity:

• Self-Organization

• Non-Linearity

• Order/Chaos Dynamic

• Emergent Properties

42http://www.calresco.org/links.htm

COMPLEX SYSTEMS

Computer Programming approaches used for demonstrating, simulating, g g g gand analyzing Complex Systems:

• Artificial Life

G ti Al ith• Genetic Algorithms

• Neural Networks

• Cellular Automata• Cellular Automata

• Boolean Networks

43http://www.calresco.org/links.htm

SELF REFERENCESELF-REFERENCE

44http://www.lsd.ic.unicamp.br/~oliva/guarana/docs/design-html/node2.htmlComputational Reflection

DOUGLAS HOFSTADTER ON SELF-REFERENCE

“ Self-reference is ubiquitous. It happens every time any one says “I” or “me” or “word” or “speak” or “mouth”. It happens every time a newspaper prints a story about

t ti it b k b treporters, every time someone writes a book about writing, designs a book about book design, makes a movie about movies, or writes an article about self-reference Many systems have the capability toreference. Many systems have the capability to represent or refer to themselves somehow, to designate themselves (or elements of themselves) within the system of their own symbolism Wheneverwithin the system of their own symbolism. Whenever this happens, it is an instance of self-reference.”

“My proposal [ ] is to see the “I” as a hallucinationMy proposal [...] is to see the I as a hallucination perceived by a hallucination, which sounds pretty strange, or perhaps even stranger: the “I” as a h ll i ti h ll i t d b h ll i ti ”

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hallucination hallucinated by a hallucination.”(I Am a Strange Loop, p. 293 )

Self-reference (Reflexivity)

• This model has traditionally been avoided and is logicallybeen avoided and is logically difficult

• Inherent in social systems where observers are also participants, in individual living

iorganisms

• Every statement reveals an yobserver as much as what is observed


EXAMPLES OF SELF-REFERENCE:RECURSIVE ALGORITHMS

This graph is based on a simple recursive algorithm. Recursion is a popular technique used toa popular technique used to describe trees and the like, because of the self-referentialnature of a tree.nature of a tree.

Self-reference can lead toSelf-reference can lead to undecidability (and paradoxes like set of all sets that are not members of themselves)

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Self-reference (Reflexivity)

Observation

48Self-awareness

After Stuart A. Umpleby

Reflexivity in a social system

49Stuart A. Umpleby

A pragmatic view ofA biological view ofA realist viewThe view of

Social CyberneticsBiological CyberneticsEngineering Cybernetics

A pragmatic view of epistemology: knowledge is constructed to achieve human purposes

A biological view of epistemology: how the brain functions

A realist view of epistemology: knowledge is a “picture” of reality

The view of epistemology

The biology of cognition vs. the observer as a social participant

Realism vs. ConstructivismReality vs. scientific theories

A key distinction

Explain the relationship between the natural and the social sciences

Include the observer within the domain of science

Construct theories which explain observed phenomena

The puzzle to be solved

How people create, maintain, and change social systems through language and ideas

How an individual constructs a “reality”

How the world worksWhat must be explained

Ideas are accepted if they serve the observer’s purposes as a social participant

Ideas about knowledge should be rooted in neurophysiology.

Natural processes can be explained by scientific theories

A key assumption

By transforming conceptual systems (through persuasion, not coercion), we can

If people accept constructivism, they will be more tolerant

Scientific knowledge can be used to modify natural processes to benefit people

An important consequence

participant

50Three Versions of Cybernetics

)change society

p p

After Stuart A. Umpleby

C b ti i f i tifiCybernetics view of scientific progress:the Correspondence Principle

Proposed by Niels Bohr when developing the quantum theory

Any new theory should reduce to the old theory to which itAny new theory should reduce to the old theory to which it corresponds for those cases in which the old theory is known to hold

A new dimension is required


New philosophy of science

Old hil h f iOld philosophy of science

Amount of attention paid to the observerthe observer

An Application of the Correspondence Principle


NEW PARADIGM OF COMPUTING:Organic computing

Organic computing is a form of biologically-inspired computingwith organic properties. It has emerged recently as awith organic properties. It has emerged recently as a challenging vision for future information processing systems. Organic Computing is based on the insight that we will soon be surrounded by large collections of autonomous systems whichsurrounded by large collections of autonomous systems, which are equipped with sensors and actuators, aware of their environment, communicate freely, and organise themselves in order to perform the actions and services that seem to beorder to perform the actions and services that seem to be required.

http://en.wikipedia.org/wiki/Organic_computing

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ORGANIC COMPUTING

The presence of networks of intelligent systems in our environment opens fascinating application areas but, at the same time, bearsopens fascinating application areas but, at the same time, bears the problem of their controllability.

Hence, we have to construct such systems — which we increasingly depend on as robust safe flexible andincreasingly depend on — as robust, safe, flexible, and trustworthy as possible.

In particular, a strong orientation towards human needs as opposed to a pure implementation of the technologically possible seems absolutely central.

In order to achieve these goals our technical systems will have toIn order to achieve these goals, our technical systems will have to act more independently, flexibly, and autonomously, i.e. they will have to exhibit life-like properties. We call those systems "organic"organic .

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ORGANIC COMPUTING

• An "Organic Computing System" is a technical system, which adapts dynamically to the current conditions of its environment.adapts dynamically to the current conditions of its environment. It is characterised by the self-X properties:

• self-organization, • self-configuration (auto-configuration), • self-optimisation (automated optimization), • self-healing• self-healing, • self-protection (automated computer security), • self-explaining, • and context-awareness.

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ORGANIC COMPUTING

• In order to be able to build huge intelligent organic-computingsystems we have to learn from variety of fields – from physics,systems we have to learn from variety of fields from physics, chemistry, genetics, biology to sociology and linguistics.

• In other words we have to learn to manage complexity of knowledge production from different research fields.

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CONCLUSIONS: TRANSDISCIPLINARY INTERDISCIPLINARY AND CROSSTRANSDISCIPLINARY, INTERDISCIPLINARY AND CROSS

DISCIPLINARY RESEARCH

Modern sciences are stretching through several classical fields.

Computer science e.g. includes the field of AI that has its roots in mathematical logic and mathematics but uses physics, chemistryand biology and even parts where medicine and psychology areand biology and even parts where medicine and psychology are important.

Examples: Environmental studies, Cognitive sciences, Cultural studies, Policy sciences, Information sciences, Women’s studies, Molecular biology Philosophy of Computing and InformationMolecular biology, Philosophy of Computing and Information, Bioinformatics, ..

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CONCLUSIONS:CONCLUSIONS: TRANSDISCIPLINARY, INTERDISCIPLINARY AND CROSS


Research into complex phenomena has led to an insight that research problems have many different facets which may beresearch problems have many different facets which may be approached differently at different levels of abstraction and that every knowledge field has a specific domain of validity.

This new understanding of a multidimensional many-layered knowledge space have among others resulted in an ecumenical conclusion of science wars by recognition of the necessity of an inclusive and complex knowledge architecture which recognizes importance of a variety of approaches and types of knowledge. p y pp yp g

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REPRESENTATIVE WORK:TRANSDISCIPLINARY, INTERDISCIPLINARY AND CROSS


Based on sources in philosophy, sociology, complexity theory, systems gy p y y ytheory, cognitive science, evolutionary biology and fuzzy logic, Smith and Jenks present a new interdisciplinary perspectivepresent a new interdisciplinary perspective on the self-organizing complex structures.

They analyze the relationship between the process of self-organization and its environment/ecology. Two central factors are the role of information in the formation of complex structure and the development of topologies of possible outcome spaces.

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o topo og es o poss b e outco e spaces

The authors argue for a continuous development from emergent complex orders in physical systems to cognitive capacity of livingcomplex orders in physical systems to cognitive capacity of living organisms to complex structures of human thought and to cultures.

This is a new understanding of unity of interdisciplinary knowledge, unity in structured diversity, also found in Mainzer. g y y

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REPRESENTATIVE WORK

“Cosmic evolution leads from

REPRESENTATIVE WORK

Cosmic evolution leads from symmetry to complexity by symmetry breaking and phase t iti Th ftransitions. The emergence of new order and structure in nature and society is explained by physical, chemical, biological, social and economic self-organization, according to the laws of nonlinear dynamics.

All these dynamical systems areAll these dynamical systems are considered computational systems processing information

dand entropy.”61

“Are symmetry and complexity only useful models of science or are they universals of reality? Symmetry and Complexity discusses the fascinating insights gained from natural, social and computer sciences, philosophy and the arts.

With many diagrams and pictures, this book illustrates the spirit and beauty of nonlinear science. In the complex world of globalization it strongly argues for unity in diversity ”globalization, it strongly argues for unity in diversity.

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REPRESENTATIVE WORK

Preface ix

Part IThe Simple and the

Part IComplex

1 Prologue: An Encounter in the Jungle 3g

2 Early Light 11

3 Information and Crude C l it 23Complexity

4 Randomness 43

5 A Child Learning a 515 gLanguage 51

6 Bacteria Developing Drug Resistance 63Resistance

7 The Scientific Enterprise 758 The Power of Theory 89

639 What Is Fundamental? 107

P t III S l ti d FitPart II The Quantum Universe

10 Simplicity and Randomness in 123

Part III Selection and Fitness

16 Selection at Work in Biological Evolution and Elsewhere 235

10 p ythe Quantum Universe 123

A Contemporary View of Q t M h i

17 From Learning to Creative Thinking 261

18 S i i d Sk i i 27511 Quantum Mechanics: Quantum Mechanics and the Classical Approximation

135 18 Superstition and Skepticism 275

19 Adaptive and Maladaptive Schemata 291

12 Quantum Mechanics and Flapdoodle 167

13 Quarks and All That: The 177

20 Machines That Learn or Simulate Learning 307

13 Qua s a d at: eStandard Model 177

14 Superstring Theory: Unification L ? 199

Part IV Diversity and Sustainability

21 Diversities Under Threat 32914 at Last? 199

15 Time's Arrows: Forward and Backward Time 215

22 Transitions to a More Sustainable World 345

23 Aft d 367

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Backward Time 23 Afterword 367

REPRESENTATIVE WORKREPRESENTATIVE WORK

Philosophy of Information (Handbook of the Philosophy of Science) (Hardcover)Science) (Hardcover)by Pieter Adriaans & Johan F.A.K. van Benthem (Editors), 2008

DM. Gabbay, P Thagard & J Woods (Series Editors)

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AND AN EXAMPLE OF THE ROLE OF PERSPECTIVE AT THE END!

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