Transcript lecture2-CriticalThinking

CDT403 Research Methodology in Natural Sciences and Engineering
Theory of Science
MEANING, LANGUAGE AND COMMUNICATION,
CRITICAL THINKING AND PSEUDOSCIENCE
Gordana Dodig-Crnkovic
School of Innovation, Design and Engineering
Mälardalen University
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THEORY OF SCIENCE
Lecture 1 TRUTH, MEANING. FORMAL LOGICAL SYSTEMS
LIMITATIONS SCIENCE, KNOWLEDGE,
Lecture 2 LANGUAGE AND COMMUNICATION. CRITICAL
THINKING. PSEUDOSCIENCE - DEMARCATION
Lecture 3 SCIENCE, RESEARCH, TECHNOLOGY, SOCIETAL
ASPECTS. PROGRESS. HISTORY OF SCIENTIFIC THEORY.
POSTMODERNISM AND CROSSDISCIPLINES
Lecture 4 GOLEM LECTURE. ANALYSIS OF SCIENTIFIC
CONFIRMATION: THEORY OF RELATIVITY, COLD FUSION,
GRAVITATIONAL WAVES
Lecture 5 COMPUTING HISTORY OF IDEAS
Lecture 6 PROFESSIONAL & RESEARCH ETHICS
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Lecture 1 Summary
SCIENCE, KNOWLEDGE, TRUTH, MEANING.
FORMAL LOGICAL SYSTEMS LIMITATIONS
The science is not about the search for truth (“absolute truth”)
but the search for meaning in the form of explanations/models/
simulations that work:
“No such (scientific) model, however comprehensive, coherent
or well entrenched it might be, can lay an automatic claim to
objective truth, even though contextually it may provide a
reliable and successful explanatory tool for making sense of
what is going on around us.” Edo Pivčević, The Reason Why: A
Theory of Philosophical Explanation, KruZak, 2007
Knowledge networks in communities of practice - Language
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Classical Sciences in their Cultural Context –
A Language Based Scheme
Logic
&
Mathematics
1
Natural Sciences
(Physics,
Chemistry,
Biology, …)
2
Social Sciences
(Economics,
Sociology,
Anthropology, …)
3
Culture
(Religion, Art,
…)
5
The Humanities
(Philosophy, History,
Linguistics …)
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SEMIOTICS (1)
Semiotics, the science of signs, which looks at how humans search
for and construct meaning.
Semiotics: reality is a system of signs!
(with an underlying system which establishes mutual relationships
among those and defines identity and difference, i.e. enables
the description of the dynamics.)
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SEMIOTICS (2)
Three Levels of Semiotics (Theory of Signs)
syntactics
semantics
pragmatics
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SEMIOTICS (2A)
pragmatics
semantics
syntactics
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SEMIOTICS (3)
Reality is a construction.
Information or meaning is not 'contained' in the (physical) world and
'transmitted' to us - we actively create meanings (“make
sense”!) through a complex interplay of perceptions, and agency
based on hard-wired behaviors and coding-decoding
conventions.
The study of signs is the study of the construction and
maintenance of reality.
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SEMIOTICS (4)
'A sign... is something which stands to somebody for something in
some respect or capacity'.
Sign takes a form of words, symbols, images, sounds, gestures,
objects, etc.
Anything can be a sign as long as someone interprets it as
'signifying' something - referring to or standing for something.
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SEMIOTICS (5)
(signified)
(signifier)
CAT
The sign consists of
– signifier (a pointer)
– signified (that what pointer points to)
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SEMIOTICS (6)
This is Not a Pipe . . . by Rene Magritte. . . . Surrealism
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SEMIOTICS (7)
– Reality is divided up into arbitrary categories by every language.
[However this arbitrariness is essentially limited by our physical
predispositions as human beings. Our cognitive capacities are
defined to a high extent by our physical constitution.]
– The conceptual world with which each of us is familiar with,
could have been divided up in a very different way.
– The full meaning of a sign does not appear until it is placed in its
context, and the context may serve an extremely subtle function.
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COMMUNICATION
– Communication is imparting of information, interaction
through signs/messages.
– Information is the meaning that a human gives to signs by
applying the known conventions used in their representation.
– Sign is any physical event used in communication.
– Language is a vocabulary and the way of using it.
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LANGUAGE (1)
Examples
The sign said "fine for parking here", and since it was fine, I parked.
Last night he caught a burglar in his pyjamas.
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LANGUAGE (2)
The Oracle of Delphi told Croseus that if he pursued the war he
would destroy a mighty kingdom.
(What the Oracle did not mention was that the kingdom he
would destroy would be his own. From: Heroditus, The
Histories.)
The first mate, seeking revenge on the captain, wrote in his journal,
"The Captain was sober today."
(He suggests, by his emphasis, that the Captain is usually drunk.
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LANGUAGE - THOUGHT - WORLD
Two approaches:
– Translation is possible (linguistic realism).
– Translation is essentially impossible (linguistic relativism) Sapir-Whorf hypothesis .
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LANGUAGE - THOUGHT- WORLD
BASIC STRUCTURE: DICHOTOMY
yes/no
before/after
right/wrong
true/false
open/closed
in/out
up/down
simple/complex
straight/curved
text/context
central/ peripheral
stability/change
mind/body
question/answer
positive/negative
active/passive
theory/practice
art/science
quantity/quality
knowledge/ignorance
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LANGUAGE -THOUGHT- WORLD
Eskimo Terms for Snow
Snow Particles
Snowflake
qanuk 'snowflake'
qanir- 'to snow'
qanunge- 'to snow' [NUN]
qanugglir- 'to snow' [NUN]
Frost
kaneq 'frost'
kaner- 'be frosty/frost sth.‘
Fine snow/rain particles
kanevvluk 'fine snow/rain particles
kanevcir- to get fine snow/rain particles
Drifting particles
natquik 'drifting snow/etc'
natqu(v)igte- 'for snow/etc. to drift along ground'.'
Clinging particles
nevluk 'clinging debris/
nevlugte- 'have clinging
debris/...'lint/snow/dirt...'
Fallen Snow
Fallen snow on the ground
aniu [NS] 'snow on ground'
aniu- [NS] 'get snow on ground'
apun [NS] 'snow on ground'
qanikcaq 'snow on ground‘
qanikcir- 'get snow on ground‘
……
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LANGUAGE AND THOUGHT
Eskimo Terms for Snow
“Horse breeders have various names for breeds, sizes, and ages of
horses; botanists have names for leaf shapes; interior
decorators have names for shades of mauve; printers have
many different names for different fonts (Caslon, Garamond,
Helvetica, Times Roman, and so on), naturally enough. If these
obvious truths of specialization are supposed to be interesting
facts about language, thought and culture, then I’m sorry, but
include me out.“
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HIERARCHICAL STRUCTURE
OF LANGUAGE
Object-language  Meta-language
In dictionaries of SCIENCE there is no definition of science!
The definition of SCIENCE can be found in PHILOSOPHY
dictionaries.
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AMBIGUITIES OF LANGUAGE (1)
Lexical ambiguity
Lexical ambiguity, where a word have more than one meaning:
meaning (sense, connotation, denotation, import, gist;
significance, importance, implication, value, consequence, worth)
– sense (intelligence, brains, intellect, wisdom, sagacity, logic, good
judgment; feeling)
– connotation (nuance, suggestion, implication, undertone,
association, subtext, overtone)
– denotation (sense, connotation, import, gist) …
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AMBIGUITIES OF LANGUAGE (5)
Syntactic ambiguity like in “small dogs and cats”
(are cats small?).
Semantic ambiguity comes often as a consequence of syntactic
ambiguity. “Coast road” can be a road that follows the coast, or a
road that leads to the coast.
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AMBIGUITIES OF LANGUAGE (6)
Referential ambiguity is a sort of semantic ambiguity (“it” can refer
to anything).
Pragmatic ambiguity (If the speaker says “I’ll meet you next
Friday”, thinking that they are talking about 17th, and the
hearer think that they are talking about 24th, then there is
miscommunication.)
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AMBIGUITIES OF LANGUAGE (8)
Vagueness is an important feature of natural languages. “It is
warm outside” says something about temperature, but what
does it mean? A warm winter day in Sweden is not the same
thing as warm summer day in Kenya.
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AMBIGUITIES OF LANGUAGE (9)
Ambiguity of language results in its flexibility, that makes it possible
for us to cover the whole infinite diversity of the world we live in
with a limited means of vocabulary and a set of rules that
language is made of.
On the other hand, flexibility makes the use of language all but
uncomplicated.
Nevertheless, the languages, both formal and natural, are the main
tools we have on our disposal in science and research.
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USE OF LANGUAGE IN SCIENCE. LOGIC AND
CRITICAL THINKING. PSEUDOSCIENCE
• LOGICAL ARGUMENT
• DEDUCTION
• INDUCTION
• REPETITIONS, PATTERNS, IDENTITY
• CAUSALITY AND DETERMINISM
• FALLACIES
• PSEUDOSCIENCE
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LOGICAL ARGUMENT
An argument is a statement logically inferred from premises.
Two sorts of arguments:
– Deductive
general  particular
– Inductive
particular  general
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LOGICAL ARGUMENT
Constituents of a logical argument:
– premises
– inference and
– conclusion
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But Everything Basically Depends on
Judgement
Now, the question, What is a judgement? is no small question,
because the notion of judgement is just about the first of all the
notions of logic, the one that has to be explained before all the
others, before even the notions of proposition and truth, for
instance.
Per Martin-Löf
On the Meanings of the Logical Constants and the Justifications of the
Logical Laws; Nordic Journal of Philosophical Logic, 1(1):11 60, 1996.
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INDUCTION
• Empirical Induction
• Mathematical Induction
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EMPIRICAL INDUCTION
The generic form of an inductive argument:
• Every A we have observed is a B.
• Therefore, every A is a B.
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An Example of Inductive Inference
• Every instance of water (at sea level) we have
observed has boiled at 100 C.
• Therefore, all water (at sea level) boils at 100 C.
Inductive argument will never offer 100% certainty!
A typical problem with inductive argument is that it is
formulated generally, while the observations are made
under some particular, specific conditions.
( In our example we could add ”in an open vessel” as well. )
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An inductive argument have no way to logically (with certainty, with
necessity) prove that:
• the phenomenon studied do exist in general domain
• that it continues to behave according to the same pattern
According to Popper, inductive argument only supports working
theories based on the collected evidence.
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Counter-example
Perhaps the most well known counter-example was the discovery
of black swans in Australia. Prior to the point, it was assumed
that all swans were white. With the discovery of the counterexample, the induction concerning the color of swans had to be
re-modeled.
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MATHEMATICAL INDUCTION
The aim of the empirical induction is to establish the law.
In the mathematical induction we have the law already formulated.
We must prove that it holds generally.
The basis for mathematical induction is the property of the wellordering for the natural numbers.
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THE PRINCIPLE OF MATHEMATICAL
INDUCTION
Suppose P(n) is a statement involving an integer n.
Than to prove that P(n) is true for every n  n0 it is sufficient to
show these two things:
1.
2.
P(n0) is true.
For any k  n0, if P(k) is true, then P(k+1) is true.
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THE TWO PARTS OF INDUCTIVE PROOF
• the basis step
• the induction step.
• In the induction step, we assume that statement is true in the
case n = k, and we call this assumption the induction
hypothesis.
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THE STRONG PRINCIPLE OF
MATHEMATICAL INDUCTION (1)
Suppose P(n) is a statement involving an integer n. In order to
prove that P(n) is true for every n  n0 it is sufficient to show
these two things:
1.
2.
P(n0) is true.
For any k  n0, if P(n) is true for every n satisfying
n0  n  k, then P(k+1) is true.
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THE STRONG PRINCIPLE OF
MATHEMATICAL INDUCTION (2)
A proof by induction using this strong principle follows the same
steps as the one using the common induction principle.
The only difference is in the form of induction hypothesis.
Here the induction hypothesis is that k is some integer k  n0 and
that all the statements P(n0), P(n0 +1), …, P(k) are true.
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Example. Proof by Strong Induction
• P(n): n is either prime or product of two or more primes, for n  2.
• Basic step. P(2) is true because 2 is prime.
• Induction hypothesis. k  2, and for every n satisfying
2  n  k, n is either prime or a product of two or more primes.
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• Statement to be shown in induction step:
If k+1 is prime, the statement P(k+1) is true.
• Otherwise, by definition of prime, k+1 = r·s, for some positive
integers r and s, neither of which is 1 or k+1. It follows that 2  r
 k and 2  s  k.
• By the induction hypothesis, both r and s are either prime or
product of two or more primes.
• Therefore, k+1 is the product of two or more primes, and P(k+1)
is true.
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The strong principle of induction is also referred to as the principle
of complete induction, or course-of-values induction. It is as
intuitively plausible as the ordinary induction principle; in fact,
the two are equivalent.
As to whether they are true, the answer may seem a little
surprising. Neither can be proved using standard properties of
natural numbers. Neither can be disproved either!
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This means essentially that to be able to use the induction
principle, we must adopt it as an axiom.
A well-known set of axioms for the natural numbers, the Peano
axioms, includes one similar to the induction principle.
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PEANO'S AXIOMS
1. N is a set and 1 is an element of N.
2. Each element x of N has a unique successor in N denoted x'.
3. 1 is not the successor of any element of N.
4. If x' = y' then x = y.
5. (Axiom of Induction) If M is a subset of N satisfying both:
1 is in M
x in M implies x' in M
then M = N.
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INDUCTION VS DEDUCTION,
TWO SIDES OF THE SAME COIN
Deduction and induction occur as a part of the common
hypothetico-deductive method, which can be simplified in the
following scheme:
• Ask a question and formulate a hypothesis (educated guess) induction
• Derive predictions from the hypothesis - deduction
• Test the hypothesis and its predictions - induction.
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INDUCTION VS DEDUCTION,
TWO SIDES OF THE SAME COIN
Deduction, if applied correctly, leads to true conclusions. But
deduction itself is based on the fact that we know something for
sure (premises must be true). For example we know the general
law which can be used to deduce some particular case, such as
“All humans are mortal. Socrates is human. Therefore is
Socrates mortal.”
How do we know that all humans are mortal? How have we arrived
to the general rule governing our deduction? Again, there is no
other method at hand but (empirical) induction.
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INDUCTION VS DEDUCTION,
TWO SIDES OF THE SAME COIN
In fact, the truth is that even the process of induction implies use of
deductive rules. On our way from specific (particular) up to
universal (general) we use deductive reasoning. We collect the
observations or experimental results and extract the common
patterns or rules or regularities by deduction. For example, in
order to infer by induction the fact that all planets orbit the Sun,
we have to analyze astronomical data using deductive
reasoning.
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INDUCTION & DEDUCTION:
Traditional View
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Deduction-Induction Roller Coaster
general
deduction
induction
particular
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GENERAL
INDUCTION & DEDUCTION
PARTICULAR
Problem domain
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INDUCTION & DEDUCTION
“There is actually no such thing as a distinct process of induction”
said Stanly Jevons; “all inductive reasoning is but the inverse
application of deductive reasoning” – and this was what
Whewell meant when he said that induction and deduction went
upstairs and downstairs on the same staircase.”
…(“Popper, of course, is abandoning induction altogether”).
Peter Medawar, Pluto’s Republic, p 177.
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INDUCTION & DEDUCTION
In short: deduction and induction are - like two sides of a piece of
paper - the inseparable parts of our recursive thinking process.
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FALLACIES
What about not properly built arguments? Let us make the following
distinction:
• A formal fallacy is a wrong formal construction of an argument.
• An informal fallacy is a wrong inference or reasoning.
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FORMAL FALLACIES
“Affirming the consequent"
"All fish swim. Kevin swims. Therefore Kevin is a fish", which
appears to be a valid argument. It appears to be a modus
ponens, but it is not!
If H is true, then so is I.
(As the evidence shows), I is true.
H is true
This form of reasoning, known as the fallacy of "affirming the
consequent" is deductively invalid: its conclusion may be false
even if premises are true.
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FORMAL FALLACIES
Incorrect deduction when using auxiliary hypotheses
If H and A1, A2, …., An is true, then so is I.
But (As the evidence shows), I is not true.
H and A1, A2, …., An are all false
(Comment: One can be certain that H is false, only if one is certain
that all of A1, A2, …., An are all true.)
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FORMAL FALLACIES
“Affirming the consequent"
And now again the fallacy of affirming the consequent:
If H is true, then so are A1, A2, …., An.
(As the evidence shows), A1, A2, …., An are all true.
H is true
(Comment: A1, A2, …., An can be a consequence of some other
premise, and not H.)
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INFORMAL FALLACIES (1)
An informal fallacy is a mistake in reasoning related to the content
of an argument.
Appeal to Authority
Ad Hominem (personal attack)
False Cause (synchronicity; unrelated facts that appear at the
same time coupled)
Leading Question
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INFORMAL FALLACIES (2)
Appeal to Emotion
Straw Man (attacking the different problem)
Equivocation (not the common meaning of the word)
Composition (parts = whole)
Division (whole = parts)
See more on: http://www.intrepidsoftware.com/fallacy/toc.htm
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SOME NOT ENTIRELY UNCOMMON
“PROOF TECHNIQUES”
Proof by vigorous hand waving
Works well in a classroom or seminar setting.
Proof by cumbersome notation
Best done with access to at least four alphabets and special
symbols.
Proof by exhaustion
Proof around until nobody knows if the proof is over or not…
READ THE REST ON PAGE 42 OF THE COMPENDIUM!
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CAUSALITY AND DETERMINISM
CAUSALITY
Causality refers to the way of knowing that one thing causes
another.
Practical question (object-level):
what was the cause (of an event)?
Philosophical question (meta-level):
what is the meaning of the concept of a cause?
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CAUSALITY
Early philosophers, concentrated on conceptual issues and
questions (why?).
Later philosophers concentrated on more concrete issues and
questions (how?).
The change in emphasis from conceptual to concrete coincides
with the rise of empiricism.
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ARISTOTLE’S CAUSALITY:
The Four Causes
The material cause - constituents, substratum or materials. This
reduces the explanation of causes to the parts (factors,
elements, constituents, ingredients).
The formal cause - form, pattern, essence, whole, synthesis or
archetype. The account of causes in terms of fundamental
principles or general laws - the influence of the form (essence).
The efficient cause - 'what makes what is made and what causes
change of what is changed - agency, nonliving or living, acting
as the sources of change.
The final cause or telos is the purpose or end that something is
supposed to serve. Omitted from present day causal
explanations.
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CAUSALITY
Hume is probably the first philosopher to postulate a wholly
empirical definition of causality. Of course, both the definition of
"cause" and the "way of knowing" whether X and Y are causally
linked have changed significantly over time.
Some philosophers deny the existence of "cause" and some
philosophers who accept its existence, argue that it can never
be known by empirical methods. Modern scientists, on the other
hand, define causality in limited contexts (e.g., in a controlled
experiment).
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CAUSALITY
What does the scientist mean when (s)he says that event b was
caused by event a?
Other expressions are:
– bring about, bring forth
– produce
– create…
…and similar metaphors of human activity.
Strictly speaking it is not a thing but a process that causes an
event.
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CAUSALITY
Analysis of causality, an example (Carnap): Search for the cause of
a collision between two cars on a highway.
• According to the traffic police, the cause of the accident was too
high speed.
• According to a road-building engineer, the accident was caused
by the slippery highway (poor, low-quality surface)
• According to the psychologist, the man was in a disturbed state
of mind which caused the crash.
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CAUSALITY
• An automobile construction engineer may find a defect in a
structure of a car.
• A repair-garage man may point out that brake-lining of a car was
worn-out.
• A doctor may say that the driver had bad sight. Etc…
Each person, looking at the total picture from certain point of
view, will find a specific condition such that it is possible to say:
if that condition had not existed, the accident might not have
happened.
But what was The cause of the accident?
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CAUSALITY
• It is quite obvious that there is no such thing as The cause!
• No one could know all the facts and relevant laws.
(Relevant laws include not only laws of physics and technology, but
also psychological, physiological laws, etc.)
• But if someone had known, he could have predicted the
collision!
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CAUSALITY
The event called the cause, is a necessary part of a more complex
web of circumstances. John Mackie, gives the following
definition:
A cause is an Insufficient but Necessary part of a complex of
conditions which together are Unnecessary but Sufficient for the
effect.
This definition has become famous and is usually referred to as the
INUS-definition: a cause is an INUS-condition.
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CAUSALITY
The reason why we are so interested in causes is primarily that we
want either to prevent the effect or else to promote it. In both
cases we ask for the cause in order to obtain knowledge about
what to do.
Hence, in some cases we simply call that condition which is easiest
to manipulate as the cause.
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CAUSALITY
Summarizing: Our concept of a cause has one objective and
subjective component. The objective content of the concept of a
cause is expressed by its being an INUS condition. The
subjective part is that our choice of one factor as the cause
among the necessary parts in the complex is a matter of
interest, and not a matter of fact.
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CAUSE AND CORRELATION
Instead of saying that the same cause always is followed by the
same effect it is said that the occurrence of a particular cause
increases the probability for the associated effect, i.e., that the
cause sometimes but not always are followed by the effect.
Hence cause and effect are statistically correlated.
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CAUSE AND CORRELATION
X and Y are correlated if and only if:
P(X/Y) > P(X)
and
P(Y/X) > P(Y)
[The events X and Y are positively correlated if the conditional
probability for X, if Y has happened, is higher than the
unconditioned probability, and vice versa.]
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CAUSE AND CORRELATION
Reichenbach's principle:
If events of type A and type B are positively correlated, then one of
the following possibilities must obtain:
i)
A is a cause of B, or
ii) B is a cause of A, or
iii) A and B have a common cause.
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CAUSE AND CORRELATION
The idea behind Reichenbach’s principle is:
Every real correlation must have an explanation in terms of causes. It
just can’t happen that as a matter of mere coincidence that a
correlation obtains.
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CAUSE AND CORRELATION
We and other animals notice what goes on around us. This helps us
by suggesting what we might expect and even how to prevent it,
and thus fosters survival. |However, the expedient works only
imperfectly. There are surprises, and they are unsettling. How
can we tell when we are right? We are faced with the problem of
error.
W.V. Quine, 'From Stimulus To Science', Harvard University Press,
Cambridge, MA, 1995.
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DETERMINISM
Determinism is the philosophical doctrine which regards everything
that happens as solely and uniquely determined by what preceded
it.
From the information given by a complete description of the world at
time t, a determinist believes that the state of the world at time t + 1
can be deduced; or, alternatively, a determinist believes that every
event is an instance of the operation of the laws of Nature.
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HISTORICAL DEVELOPMENT OF THINKING
MYTHOPOETIC THINKING
Mythopoetic (myth + poetry)
truth is revealed through
myths, stories and rituals.
Myths are stories about
persons, where persons may
be gods, heroes, or ordinary
people.
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MYTHOPOETIC THINKING
Myth allows for a multiplicity of
explanations, where the
explanations are not logically
exclusive (can contradict each
other) and are often humorous,
exciting and colorful.
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MYTHOPOETIC THINKING
Mythic traditions are conservative.
Innovation is slow, and radical
departures from tradition rarely
tolerated.
The Egyptian king Akhenaton and Queen
Nefertiti making offerings to the Aton.
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MYTHOPOETIC
THINKING
Myths are self-justifying. The
inspiration of the gods was
enough to ensure their validity,
and there was no other
explanation for the creativity of
poets, seers, and prophets than
inspiration by the gods. Thus,
myths are not argumentative.
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THE MYTHO-POETIC UNIVERSE
In ancient Egypt the
dome of the sky was
represented by the
goddess Nut, She
was the night sky,
and the sun, the god
Ra, was born from
her every morning.
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THE MEDIEVAL UNIVERSE
WITH EARTH IN THE CENTRE
From Aristotle Libri de caelo (1519).
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THE CLOCKWORK UNIVERSE
The mechanicistic paradigm which systematically revealed physical
structure in analogy with the artificial. The self-functioning automaton
- basis and canon of the form of the Universe.
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Newton Principia, 1687
THE UNIVERSE AS A COMPUTER
We are all living inside a
gigantic computer. No,
not The Matrix: the
Universe.
Every process, every
change that takes place
in the Universe, may be
considered as a kind of
computation.
E Fredkin, S Wolfram
http://www.nature.com/nsu/020527/020527-16.html
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ISLANDS OF KNOWLEDGE
“You see, you have all of mathematical truth, this ocean of
mathematical truth. And this ocean has islands. An island here,
algebraic truths. An island there, arith-metic truths. An island
here, the calculus. And these are different fields of mathemat-ics
where all the ideas are interconnected in ways that
mathematicians love; they fallinto nice, interconnected patterns.
But what I've discovered is all this sea around the islands.”
Gregory Chaitin, an interview, September 2003
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CRITICAL THINKING (1)
What is Critical Thinking?
Critical thinking is rationally deciding what to believe or do. To
rationally decide something is to evaluate claims to see whether
they make sense, whether they are coherent, and whether they
are well-founded on evidence, through inquiry and the use of
criteria developed for this purpose.
Critical Thinking
http://www.criticalreflections.com/critical_thinking.htm
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CRITICAL THINKING (2)
How Do We Think Critically?
A. Question
First, we ask a question about the issue that we are wondering
about.
For example, "Is there right and wrong?"
B. Answer (hypothesis)
Next, we propose an answer or hypothesis for the question raised.
A hypothesis is a "tentative theory provisionally adopted to explain
certain facts." We suggest a possible hypothesis, or answer, to
the question posed.
For example, "No, there is no right and wrong."
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CRITICAL THINKING (3)
C. Test
Testing the hypothesis is the next step. With testing, we draw out
the implications of the hypothesis by deducing its consequences
(deduction). We then think of a case which contradicts the
claims and implications of the hypothesis (inference).
For example, "So if there is no right or wrong, then everything has
equal moral value (deduction); so would the actions of Hitler be
of equal moral value to the actions of Mother Theresa
(inference)? as Value nihilism ethics claims"
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CRITICAL THINKING (4)
1. Criteria for truth
Criteria are used for testing the truth of a hypothesis. The criteria
may be used singly or in combination.
a. Consistent with a precondition
Is the hypothesis consistent with a precondition necessary for its
own assertion?
For example, is the assertion "there is no right or wrong" made
possible only by assuming a concept of right or wrong - namely,
that it is right that there is no right or wrong and that it is wrong
that there is right or wrong?
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CRITICAL THINKING (5)
b. Consistent with itself
Is the hypothesis consistent with itself?
For example, is the assertion that "there is no right or wrong" itself
an assertion of right or wrong?
c. Consistent with language
Is the hypothesis consistent with the usage and meaning of
ordinary language?
For example, do we use the words "right" or "wrong" in our
language and do the words refer to concepts and meanings
which we consider "right" and "wrong"?
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CRITICAL THINKING (6)
d. Consistent with experience
Is the hypothesis consistent with experience?
For example, do people really live as if there is no right or wrong?
e. Consistent with the consequences
Is the hypothesis consistent with its own consequences, can it
actually bear the burden of being lived?
For example, what would the consequences be if everyone lived as
if there was no right or wrong?
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PSEUDOSCIENCE (1)
A pseudoscience is set of ideas and activities resembling science
but based on fallacious assumptions and supported by
fallacious arguments.
Martin Gardner: Fads and Fallacies in the Name of Science
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PSEUDOSCIENCE (2)
Motivations for promotion of pseudoscience range from simple lack
of knowledge about the nature of science or of the scientific
method, to deliberate deception for winning a power, financial
or other benefit.
Some people consider some or all forms of pseudoscience to be
harmless entertainment.
Others, such as Richard Dawkins, consider all forms of
pseudoscience to be harmful, whether or not they result in
immediate harm to their followers.
http://www.simonyi.ox.ac.uk/dawkins/WorldOfDawkinsarchive/index.shtml Richard Dawkins, Professor of the Public
Understanding of Science at Oxford University web page.
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PSEUDOSCIENCE (3)
Typically, pseudoscience fails to meet the criteria met by science generally
(including the scientific method), and can be identified by one or more of
the following rules of thumb:
• asserting claims without supporting experimental evidence;
• asserting claims which contradict experimentally established results;
• failing to provide an experimental possiblity of reproducible results; or
• violating Occam's Razor (the principle of choosing the simplest
explanation when multiple viable explanations are possible); the more
egregious the violation, the more likely.
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PSEUDOSCIENCE (4)
•
•
•
•
•
•
•
•
•
•
Astrology
Dowsing
Creationism
ETs & UFOs
Supernatural
Parapsychology/Paranormal
New Age
Divination (fortune telling)
Graphology
Numerology
• Velikovsky's, von Däniken's,
and Sitchen's theories
• Pseudohistory
• Homeopathy
• Healing
• Alternative Medicine
• Cryptozoology
• Lysenkoism
• Psychokinesis
• Occult & occultism
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PSEUDOSCIENCE (5)
http://skepdic.com/ The Skeptic's Dictionary,
Skeptical Inquirer
http://www.physto.se/~vetfolk/Folkvett/199534pseudo.html
The Swedish Skeptic movement (in Swedish)
Scientific Evidence For Evolution
Scientific American, July 2002: 15 Answers to Creationist Nonsense
Human Genome, Nature 409, 860 - 921 (2001)
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THE PROBLEM OF DEMARCATION (1)
After more than a century of active dialogue, the question of what
marks the boundary of science remains fundamentally
unsettled. As a consequence the issue of what constitutes
pseudoscience continues to be controversial. Nonetheless,
reasonable consensus exists on certain sub-issues.
97
THE PROBLEM OF DEMARCATION (2)
Criteria for demarcation have traditionally been coupled to one
philosophy of science or another.
Logical positivism, for example, supported a theory of meaning
which held that only statements about empirical observations
are meaningful, effectively asserting that statements which are
not derived in this manner (including all metaphysical
statements) are meaningless.
98
THE PROBLEM OF DEMARCATION (3)
Karl Popper attacked logical positivism and introduced his
own criterion for demarcation, falsifiability.
Thomas Kuhn and Imre Lakatos proposed criteria that
distinguished between progressive and degenerative
research programs.
http://www.freedefinition.com/Pseudoscience.html#The_Problem_of
_Demarcation
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Assignment 2: Demarcation: Pseudoscience
vs. Science (done in groups of two)
• Popper on Demarcation (Stanford Encyclopedia):
http://plato.stanford.edu/entries/popper/
• The Astrotest A tough match for astrologers (Rob Nanninga),
http://www.skepsis.nl/astrot.html
• Astrology Fact Sheet (North Texas Skeptics),
http://www.ntskeptics.org/factsheets/astrolog.htm
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Assignment 2: Demarcation: Pseudoscience
vs. Science (done in groups of two)
• Answer Form
• Use the template (answer form)
• Leave the template unchanged, write down your answer after each
question.
• Think critically!
• You are expected to work in groups of two.
• Your text should not be shorter than two A4 pages written in usual text
format.
• Prepare for the discussion in the class!
•
Please write the file name in the following format:
name1_name2_a2.doc
•
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Assignments 1, 2 and 3
• Assignment 1 (Scientific papers review) September 4
• Assignment 2 (Demarcation) September 9
• Assignment 3 (Golem) September 30
•
http://www.idt.mdh.se/kurser/ct3340/ht08/deadlines.html
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THE PROBLEM OF DEMARCATION (4)
Read a book by astrophysicist Carl
Sagan against pseudoscience:
http://www.scribd.com/doc/2896840/Th
e-Demon-Haunted-World-CarlSagan
The book explains the scientific method
and encourage people to learn
critical thinking. It explains methods
to help distinguish between science,
and pseudoscience by means of
critical thinking.
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