1. CDT403 Research Methodology in Natural Sciences and Engineering
Theory of Science
SCIENCE, RESEARCH, TECHNOLOGY, SOCIETY, COMPLEXITY AND INTERDISCIPLINARITY
Gordana Dodig-Crnkovic
School of Innovation, Design and Engineering
Mälardalen University

2. THEORY OF SCIENCE
Lecture 1 INFORMATION, COMPUTATION, KNOWLEDGE AND SCIENCE
Lecture 2 SCIENCE AND CRITICAL THINKING. PSEUDOSCIENCE AND WISHFUL THINKING - DEMARCATION
Lecture 3 SCIENCE, RESEARCH, TECHNOLOGY, SOCIETY, COMPLEXITY AND INTERDISCIPLINARITY
Lecture 4 VALUES AND ETHICS - PROFESSIONAL & RESEARCH ETHICS

3. SCIENCE, RESEARCH, TECHNOLOGY
Aristotle'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 complexity
Process
conceptualizing
optimizing
Innovation form
discovery
invention
Type of result
law-like statements
rule-like statements
Time perspective
long-term
short-term

4. Sciences, Objects and Methods
SCIENCE IN MICRO AND MACROCOSMOS Levels of abstraction/Levels of organization
Sciences, Objects and Methods
zoom in – zoom out
SCIENCE
OBJECTS
DOMINATING METHOD
Simple
Reductionism (analysis)
Logic & Mathematics
Abstract objects: propositions, numbers, ...
Deduction
Natural Sciences
Natural objects: physical bodies, fields and interactions, living organisms ...
Hypothetico-deductive method
Social Sciences
Social objects: human individuals, groups, society, ..
Hypothetico-deductive method + Hermeneutics
Humanities
Cultural objects: human ideas, actions and relationships, language, artefacts…
Hermeneutics
Complex
Holism (synthesis)

5. SCIENCE, RESEARCH, DEVELOPMENT AND TECHNOLOGY

6. CLASSICAL SCIENCES LANGUAGE BASED SCHEME
Natural Sciences
(Physics,
Chemistry,
Biology, …)
Social Sciences
(Economics,
Sociology,
Anthropology, …)
The Humanities
(Philosophy, History, Linguistics …)
Logic
&
Mathematics
Culture
(Religion, Art, …)
Computing

7. SCIENCES BASED ON SEVERAL RESEARCH FIELDS – CROSS DISCIPLINARY RESEARCH
Our basic scheme represents classical sciences.  
Many modern sciences however are stretching over several research fields of our scheme. Computing is typical cross-disciplinary research field.
Computer science e.g. includes the field of AI that has its roots in mathematical logic and mathematics but uses physics, chemistry and biology and sometimes even parts where medicine and psychology are very important.
Software Engineering includes both formal methods and project management.
HCI, human-computer interaction, combines knowledge from “hard” and “soft” sciences.
Computer games border with arts.

8. TECHNOLOGY
crows cracking nuts
tool making crow
monkeys using tools

9. ANTIBIOTICS ANESTHETICS DNA SEQUENCING
WRITING
RAILWAYS
ELECTRICITY
COMPUTER
TELEVISION
AUTOMOBILE
CAMERA/TELESCOPE
SEWING MACHINE
INTERNET
ANTIBIOTICS ANESTHETICS DNA SEQUENCING

10. PROCESS OF VIRTUALIZATION IN TECHNOLOGY
Top 10 greatest inventions
The History of Technological Innovations Video
The History of Information Technology
syosseths.com/z/technology.html

11. TECHNOLOGY EXPANDS OUR WAYS OF
THINKING ABOUT THINGS, EXPANDS
OUR WAYS OF DOING THINGS.
Herbert A. Simon
TECHNOLOGY IS PART OF OUR EXTENDED COGNITION.
(Andy Clark & David J. Chalmers )

12. SCIENCE AND SOCIETY THE “TRIPLE HELIX” MODEL
Knowledge society based on ICT
The triple helix model:
ACADEMIA
PRODUCTION (ECONOMY)
GOVERMENT
CULTURE
SCIENCES & HUMANITIES

13. SOCIETAL ASPECTS OF SCIENCE
Science has several important facets:
- insights in foundational issues (understanding of the world)
- applications (practical use)
- societal aspects (impact on the society – human relations)
Sciences are promoting rational and analytical discussions of the central issues of concern to scientists and other scholars, and to the public at large, both in terms of knowledge production and in practical applications.

14. SOCIETAL ASPECTS OF SCIENCE RESEARCH COMMUNITY AS INFORMATIONAL NETWORK
“ .. if we consider Galileo alone in his cell muttering, ‘and yet it moves,’ with the recent meeting at Kyoto – where heads of states, lobbyists, and scientists were assembled together in the same place to discuss the Earth – we measure the difference ..”
Bruno Latour

15. SOCIETAL ASPECTS OF SCIENCE
Further reading on current topics:
Essays on Science and Society
Science magazine

16. POSTMODERNISM AND THE NATURE OF SCIENCE
Modernism may be seen as the height of the Enlightenment's* quest for an rational knowledge, aesthetics, and ethics.
Postmodernism is a cultural and philosophical movement which formed in reaction to modernism.
Postmodernism is concerned with how the authority of rational ideals, sometimes called meta-narratives**, are undermined through fragmentation and deconstruction.
*The Age of Enlightenment (or simply the Enlightenment or Age of Reason) was a cultural movement of intellectuals in 18th century Europe, that sought to mobilize the power of reason in order to reform society and advance knowledge. It promoted intellectual interchange and opposed intolerance and abuses in Church and state.
**Meta-narratives - "grand narratives“, form of ‘universal truth'

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

18. 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 for humans (or any other intelligent agents).
From that correct observation, postmodernist draw a very far-reaching conclusion: “Science is merely one story among others.”
The world we know is one that is constructed by human discourses. (correct) From the point of view of knowledge (epistemology ), a scientific text is understood as being on a par with a literary text. (false)

19. TWO CULTURES - C. P. SNOW
2009 marked the 50th anniversary of C. P. Snow’s famous “Two Cultures” essay, in which he lamented the great cultural divide that separates two great areas of human intellectual activity, “science” and “the arts.”
Snow argued that practitioners in both areas should build bridges, to further the progress of human knowledge and to benefit society.
Image: Matt Collins
Our Two Cultures
Consilience: The Unity of Knowledge is a 1998 book by biologist E. O. Wilson.

20. SCIENCE WARS (1)
In early 1996 the physicist Alan Sokal who was provoked by postmodernist negative attitude to science caused a controversy by publishing two provocative 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 in modern physics, and vice-versa.

21. SCIENCE WARS (2)
The second article, A Physicist Experiments with Cultural Studies, appeared in the journal Lingua Franca just as issue of Social Text containing the first article was published. It revealed that the first article was a hoax.

22. SCIENCE WARS (3) But why did Sokal do it? He says:
“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. “
Allan Sokal

23. SCIENCE WARS (4)
“To test the prevailing intellectual standards, I decided to try a 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

24. SCIENCE WARS (5)
The post modern ideas were known as Social Constructivism and Deconstructionism.
The branch of sociology, Sociology of Scientific Knowledge (SSK) and Science and Technology Studies (STS) were influences by postmodern movements 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 society. 

25. POSTMODERNIST 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 rejected. 
According to postmodernism, the natural world has a subordinated role 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.

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

27. AN EXAMPLE OF PROGRESS - TRANSPORTATION

28. AN EXAMPLE OF PROGRESS - TRANSPORTS
“Beam me up Scotty” next?

29. SCIENCE WARS (6) Sources for further reading:

30. WHAT HAVE WE LEARNED FROM SCIENCE WARS?
Humans 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 provide resources for science.
In a given context, by scientific methods we can construct our best knowledge, which is constantly improving.
If not seen as absolute, but our best common knowledge about the physical world, science has a very distinct position among different possible descriptions of the world.

31. END OF SCIENCE WARS AND NEW EMERGING ALLIANCES
At present, a lot of activity in cross-disciplinary, multi-disciplinary and inter-disciplinary collaborations.
Examples: Computing and Philosophy
and
Interdisciplines (Topics: Adaptation and Representation, Art and Cognition, Causality, Enaction (Action and perception intertwined), Issues in Coevolution of Language and Theory of Mind.)

32. RESEARCH, COMMUNICATION AND ICT
New development of collaborations between different research disciplines is enabled by the progress of technology.
However, there is a problem of communication: Different knowledge fields traditionally have different languages.

33. 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.
However, access to knowledge have become easy and communication between sciences, arts and humanities more and more common.

34. Cybernetics as a Language for Interdisciplinary Communication
Stuart A. Umpleby
The George Washington University
Washington, DC

35. 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 origins 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
After Stuart A. Umpleby

36. COMMON PROCESSES IN THE EXTERNAL WORLD
James G. Miller’s suggests that living systems exist at seven levels:
- cell, - organ, - organism, - group, - organization, - nation, - supranational organization
After Stuart A. Umpleby

37. BASIC CONCEPTS In cybernetics there are three fundamental concepts:
Regulation
Self-organization
Reflexivity
After Stuart A. Umpleby

38. REGULATION
Regulation is based on two elements – regulator and system being regulated
Engineering examples – thermostat and heater, automatic pilot and airplane
Biological examples – feeling of hunger and food in stomach, light in eye and iris opening
Social system examples – manager and organization, therapist and patient
After Stuart A. Umpleby

39. THE LAW OF REQUISITE VARIETY
Information and selection
“The 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”
W. Ross Ashby
After Stuart A. Umpleby

40. COPING WITH COMPLEXITY
When faced with a complex situation, there are two choices
Increase the variety in the regulator: hire staff or subcontract
Reduce the variety in the system being regulated: reduce the variety one chooses to control
After Stuart A. Umpleby

41. 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”
Their view is that complexity is observer dependent, that the system to be regulated is defined by the observer
After Stuart A. Umpleby

42. 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 conditions
– open to energy (hence dynamic)
– structures closed to information (interaction rules do not change during the period of observation)
Complex Systems and Self-organization Modelling
After Stuart A. Umpleby

43. 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 slag
Biological examples – food in the stomach is transformed into usable energy and materials, species compete to yield animals adapted to their environments, insect swarms
After Stuart A. Umpleby

44. SELF-ORGANIZATION IN ARTIFACTS
Biologically-inspired Models of Cell Differentiation and Morphogenesis
Robots with minds of their own
Self-organization resources

45. DIGITAL VIDEO FEEDBACK AND MORPHOGENESIS
Video Feedback systems tend toward either stability or chaos. 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 is to catch the movement of ‘catching a shape’ in a particular temporal phase to feed back into the system advancing the complexity and initiating lifelike morphogenesis.

46. Four Important Characteristics of Complexity: Self-Organization
COMPLEX SYSTEMS
Self-organizing adaptive systems
Regime shifts
Four Important Characteristics of Complexity:
Self-Organization
Non-Linearity
Order/Chaos Dynamic
Emergent Properties

47. COMPLEX SYSTEMS
Computer Programming approaches used for demonstrating, simulating, and analyzing Complex Systems:
Artificial Life
Genetic Algorithms
Neural Networks
Cellular Automata
Boolean Networks

48. SELF-REFERENCE
Computational Reflection

49. 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 reporters, 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 to represent or refer to themselves somehow, to designate themselves (or elements of themselves) within 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 hallucination perceived by a hallucination, which sounds pretty strange, or perhaps even stranger: the “I” as a hallucination hallucinated by a hallucination.”
(I Am a Strange Loop, p. 293 )

50. SELF-REFERENCE (REFLEXIVITY)
This model has traditionally been avoided and is logically difficult.
Inherent in social systems where observers are also participants, in individual living organisms.
Every statement reveals an observer as much as what is observed.
After Stuart A. Umpleby

51. EXAMPLES OF SELF-REFERENCE: RECURSIVE ALGORITHMS
This graph is based on a simple recursive algorithm. Recursion is a popular technique used to describe trees and the like, because of the self-referential nature of a tree.
Self-reference can lead to undecidability (and paradoxes like set of all sets that are not members of themselves)

52. Self-reference (Reflexivity)
Observation
Self-awareness
After Stuart A. Umpleby

53. Reflexivity in a social system
Stuart A. Umpleby

54. After Stuart A. Umpleby

55. CYBERNETICS 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 it corresponds for those cases in which the old theory is known to hold
A new dimension is required
After Stuart A. Umpleby

56. An Application of the Correspondence Principle
NEW PHILOSOPHY OF SCIENCE
An Application of the Correspondence Principle
Old philosophy of science
Amount of attention paid to the observer
After Stuart A. Umpleby

57. NEW PARADIGM OF COMPUTING: Organic computing
Organic computing is a form of biologically-inspired computing with 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, 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 be required.

58. ORGANIC COMPUTING
The presence of networks of intelligent systems in our environment opens 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, 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 to act more independently, flexibly, and autonomously, i.e. they will have to exhibit life-like properties. We call those systems "organic".

59. ORGANIC COMPUTING
An "Organic Computing System" is a technical system, which 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-protection (automated computer security),
self-explaining,
and context-awareness.

60. ORGANIC COMPUTING
In order to be able to build huge intelligent organic-computing 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.

61. CONCLUSIONS: TRANSDISCIPLINARY, 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, chemistry and 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 Information, Bioinformatics, ..

62. CONCLUSIONS: TRANSDISCIPLINARY, INTERDISCIPLINARY AND CROSS DISCIPLINARY RESEARCH
Research into complex phenomena has led to an insight that research 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.

63. REPRESENTATIVE WORK: TRANSDISCIPLINARY, INTERDISCIPLINARY AND CROSS DISCIPLINARY RESEARCH
Based on sources in philosophy, sociology, complexity theory, systems theory, cognitive science, evolutionary biology and fuzzy logic, Smith and Jenks present 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.

64. REPRESENTATIVE WORK: TRANSDISCIPLINARY, INTERDISCIPLINARY AND CROSS DISCIPLINARY RESEARCH
The authors argue for a continuous development from emergent complex 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.

65. REPRESENTATIVE WORK
“Cosmic evolution leads from symmetry to complexity by symmetry breaking and phase transitions. 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 are considered computational systems processing information and entropy.”

66. REPRESENTATIVE WORK
“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.”

67. REPRESENTATIVE WORK Preface ix The Simple and the Complex 1
Part I
The Simple and the Complex 1
Prologue: An Encounter in the Jungle 3 2
Early Light 11
Information and Crude Complexity 23 4
Randomness 43 5
A Child Learning a Language 51 6
Bacteria Developing Drug Resistance 63 7
The Scientific Enterprise 75 8
The Power of Theory 89 9
What Is Fundamental?
107

68. Selection at Work in Biological Evolution and Elsewhere 235 17
Part III
Selection and Fitness 16
Selection at Work in Biological Evolution and Elsewhere
235 17
From Learning to Creative Thinking
261 18
Superstition and Skepticism
275 19
Adaptive and Maladaptive Schemata
291 20
Machines That Learn or Simulate Learning
307
Part IV
Diversity and Sustainability 21
Diversities Under Threat
329 22
Transitions to a More Sustainable World
345 23
Afterword
367
Part II
The Quantum Universe 10
Simplicity and Randomness in the Quantum Universe
123 11
A Contemporary View of Quantum Mechanics: Quantum Mechanics and the Classical Approximation
135 12
Quantum Mechanics and Flapdoodle
167 13
Quarks and All That: The Standard Model
177 14
Superstring Theory: Unification at Last?
199 15
Time's Arrows: Forward and Backward Time
215

69. REPRESENTATIVE WORK
Philosophy of Information (Handbook of the Philosophy of Science) (Hardcover)
by Pieter Adriaans & Johan F.A.K. van Benthem (Editors), 2008
DM. Gabbay, P Thagard & J Woods (Series Editors)

70. Philosophy of Science/Theory of Science Assignments
Assignment 2: Demarcation of Science vs. Pseudoscience (in groups of two)
Discussion of Assignment 2 - compulsory
Assignment 2-extra (For those who miss the discussion of the Assignment 2)
Assignment 3: GOLEM: Three Cases of Theory Confirmation (in groups of two)
Discussion of Assignment 3 - compulsory
Assignment 3-extra (For those who miss the discussion of the Assignment 3)

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