Selected topics in general
psychology II.
Lubomír Kostron 2020
The course structure, 2nd part.
1. Introduction
2. Perception, judgment (and behavioral activities)
3. social judgment theory and the nature of information
4. A model of personality – what is missing?
5. The theory o tasks, situations and the
environment/ecology
6. The role of emotions and group support in the
solution of ill defined problems
7. System dynamics - learning to „see“ processes
8. The decision-making under uncertainity
9. Interpersonal cognitive conflict solution
(workshop with POLICY)
10. The puzzle of Consciousness
11. The aultimate knowledge – the art of asking the
smart questions (workshop with „unknown
objects“)
Students are expected to turn in a paper on one of
the issues, listed above. For more detailes see the
sylabus.
4. What do we miss so far?
Toward a personality model: the „central region“ of mind.
The central region structure
The origin of
causal relationships :
Children, when was Napoleon Bonaparte born?
A 1000 years ago, say children.
A 100 years ago, say children.
No one knows.
Children, what Napoleon
Bonaparte did?
He did win the war, say children.
He did loose the war, say children.
No one knows.
Our butcher had a dog called
Napoleon, said little Francis.
The dog was beaten and died
by starvation about a year ago.
And all the choldren feel sorry
for Napoleon.
Miroslav Holub, poet
The process of idea emergence :
Eva Jiřičná, architect
„…It is only with the heart that one can see rightly;
what is essential is invisible to the eye“.
Antoine de Saint-Exupery
„The heart has its reasons of which reason
knows nothing“.
Blaise Pascal.
Experiencing, emotions, motivation
Albert Einstein´s letter to his doughter Liserl:
„…there is an extremely powerfull force, for which there is no formal scientific
explanation yet. This force includes and rules all the other forces and it is even
contained in all the phenomenae operating in the universe, but we did not identify
it yet. This universal force is love. When the scientists seeked for an universal
unifying theory of the universe, they omited the most powerfull, invisible force.
Love is the light which lits those, who give it and those who obtain it. Love is the
gravitation, since it causes that some people are being attracted to the other ones
….“
„… this force explains all and gives a meaning to the life. It is a variable, which we
ignored too long time maybe becouse we are scared of it, for love is the only
energy in the universe, which we did not learn how to subdue it to our will…“
„… To make love visible, I simply replaced one value in my most famous equation.
If we would instead E= mc2 accept, that the energy to cure the world may be
obtained through the love times the square of light speed, we would conclude, that
love is the strongest force in existence, since it has no limits….“
https://wearelightbeings.wordpress.com/2015/04/15/a-letter-from-albert-einstein-to-his-daughter-about-the-
universal-force-which-is-love/
The thinking and feeling; the meaning of experiencing
and emotions
(an example the organizational structure and culture)
The thinking and feeling; the meaning of experiencing
and emotions
(an example of the organizational structure and culture)
The transformation of motivation: external x internal motivation
The sophistications of organization´s processes and the level of
self-control
(adapted from Hroník, Galuška, Kopčaj)
How does it all fit together?
Consider the case of
- an individual,
- social setting,
- a civilization
There is a catch, a witchious circle:
in order to determine a tool, which would
serve us to understand a person´s behavior,
we need to understand that person first!
5. The tasks, situations, environments the
psychological theory of ecology
The Brunswik ´s requirement of representative experimental design
(representative samaples of subjects as well as their ecology)
The Hammond´s theory of ecology is based on formal characterists of
stimulae/cues/information, which the ecology presents
(any classification based upon the „content“ is not realistic).
The cues/incoming information induces either more analytical
processes, or intuition: the „quasirational thinking“ consists of a mixture
of both (see picture 16).
Which exceptional situations/tasks induce usualy rational thinking or
intuition?
The personality and the environment problem
• There are many psychological theories of
personality;
• Psychological theories of the
environments/situations are rare;
• The perception of a situation is influenced by its
meaning for a given person. However, the
understanding of the meaning may be influenced
by an understanding of a much wider
framework/context ( for instance - history).
differentiation
integration
analysis (criteria
previously agreed upon)
intuition (usual
solution possibilities)
Negotiation, common
goals
New information seeking
Exploration,
problem solving
Assessment, decision -
making
The typology of intelectual tasks by John
Rohrbaugh, S.U.N.Y. at Albany, Rockefeller College of Public
Affairs and Policy
More parties, many criteria,
different interests. Agreement
negotiations. The conflict of
interests.
More solutions possible with outcomes,
which may be divided; a co-operation is
not necessary; creative generation of
ideas.
Few possibilities of a solution;
total co-operation is important;
the cognitive conflict.
The making of strategies and
planing.
http://grantome.com/grant/NSF/IIA-9014357
The situational - experiencing space
(a metaphore: the linear and curvilinear spacetime)
usual, common
situation.
Exceptional, significant, symbolic and
threatening situations (emotions at
play, the subjective time
experiencing changed).
individual group, crowd
Related concept
- genius loci
6. The role of emotions (and group support)
in solving ill defined problems solution.
Bill Critchley,
organizational
consultant
Dave Casey - Director at Fire
and Emergency Training Institute/
Louisiana State University
(perhaps not a picture of the right
person…? But he look good.)
Bill Critchley, David Casey : tasks, emotions, work - building of a team
7. System dynamics - learning to see…
What connects perception, thinking memory
and learning? The beginning of knowledge is:
- bringing „static order“ into chaos,
- recognizing change, processes, systems
- a single loop learning – adaptation
- a double loop generative learning
Carl von Linné or Carolus Linnaeus,
1707 – 1778
is often called the Father of Taxonomy.
Classification of plant and animals.
What are the classification kriteria?
a) The static view of the world:
Classification, bringing order/system
into chaos.
Some notable examples:
Dimitirij Ivanovič Mendelejev
8.2.1834 – 2.2.1907
What is the organizing principle?
Abraham Harold Maslow´s
hierarchy of needs
1.4.1908 Brooklyn –
8.6.1970 Menlo Park
Kenneth Ewart Boulding
18.1.1910 – 18.3.2000
Co-founders of the general systems theory :
Ludwig von Bertalanffy 19.9.1901
Vienna – 12.6.1972 Buffalo, N.Y.
Living systems are open systems,
characterized by:
• complexity,
• seeking of a dynamic equilibrium,
• use feedback – loops and,
• temporarily defy entropy by self-
organization.
Humberto R. Maturana
14.9.1928
A concept of an„autopoietic
(self-developing) system“, a
separeate system, staying as a
structure, which behavior is
governed by it. Used alo in
socials ciences.
The nervous system is coupled
to the organism that it
integrates in a manner that its
plastic connectivity is being
continuously determined
though its participation in the
autopoiesis of the oprganism.
Therefore, the connectivity of
the nervous system is coupled to
the history of interactions od the
organism to which it is coupled.
Humberto Maturana, Cognitive
strategies
Science is not a domain of objective knowledge, but a domain of
subject dependent knowledge defined by a methodology that
specifies the properties of the knower.
Two examples
of a static systems view
in the theory of organization
Jean Piaget 1896 Neuchatel - 1980 Geneva
When you teach a child
something, you take away
forever his chance of
discovering it for himself.
J.P.
The cognitive development view
Picturing change over time – evolution, development.
Linear and non-linear view (see also slides 49 – 54)
Is that stuff
working?
Did you poke
into it?
Don´t you
poke into it !
You clumsy!Did anyone
see you?
Burke it!
Did it work?
Will you get
caught?You
dumb head!
Forget it
Nothing to worry about!
Any scapegoat?
The Technology of
problem solving
yes
no
yes
yes
no
yes
yes
no
no
no
no
yes
44
time
present
decision
The continuity
of past processes
rule.
I can foresee,
but not influence
Decision - making and its consequences
Future
uncertainity
space
The past
evolution
Predictions
time
horizon
The processes,I can influence
By decisions and actions
By Jay W.Forrester
b) A way to a more advanced thinking:
the system dynamics
Peter M.Senge
1947 Stanford:
System dynamics
thinking – „The
learning organization“
John Sterman :
system dynamics
modelling – „The
Business Dynamics“
Jay Wright Forrester
14.7.1918 – 16.11.2016
founder of S.D.,
„The world dynamics“
All at the Sloan School of management, M.I.T., Boston
An example of
a dynamic structure,
consisting of feedback
loop processes:
a price inflation model
An example: how to turn the SWOT table into a set of
processes, which hide the root cause of a problem
Widows
keep cats
Cats dig out
bumblebees
Bumblebees
pollinate shamrocks
Cattle graze off
shamrocks
Cattle turns into
a canned meat
for sailors
Large supplies of cans
Increases number
of fighting sailors
The feedback loop example:
The real determinants of the British Navy size
57
Otto F. Scharmer,
M.I.T.
60
8. Decision-making under uncertainty:
Dimensions of uncertainity – the object, the ecology/situation
and the decision-maker
Uncertainty occurs when, given current knowledge, there are
multiple possible states of nature.
S.U.N.Y. at Albany
Rockefeller College of Public Affairs and Policy
Thomas Stewart
Berndt Brehmer
(1940 - 2014)
Swedish National
Defense College
Ray W.Cooksey
University of Western Australia, University
of New England, Business School
https://www.youtube.com/watch?v=g2or-MWzwWQ
https://www.youtube.com/watch?v=PJ1uYgRyssI
https://www.une.edu.au/staff-profiles/business/rcooksey
Daniel Kahneman, psychologist,
2002 Nobel Price in Economics
64
Tom Steward´s slides: Probability is the
most widely used measure of uncertainty
• Relative frequency
– The probability of an event is the frequency of it’s
occurrence divided by the number of experiments, or
trials (for a very large number of trials).
• Subjective probability (Bayesian)
– The probability of an event is the degree of belief that a
person has that it will occur.
Morgan, M. G., & Henrion, M. (1990). Uncertainty: A Guide to Dealing with
Uncertainty in Quantitative Risk and Policy Analysis. New York: Cambridge
University Press.
65
• Uncertainty 1 - States (events) and
probabilities of those events are known
– Coin toss
– Die toss
– Precipitation forecasting (approximately)
Note: This is sometimes called aleatory uncertainty. It reflects the nature of random
processes. For example, even though you know a fair die has six sides, you
cannot reduce the uncertainty about what the next roll will show. But you can
quantify the uncertainty. For the simple case of the die, the odds are 1 in 6 of
any particular face turning up.
Types of Uncertainty
66
• Uncertainty 2 - States (events) are known,
probabilities are unknown
– Elections
– Stock market
– Forecasting severe weather
Types of Uncertainty
Brno, November 1999 67
• Uncertainty 3 - States (events) and
probabilities are unknown
– Y2K
– Global climate change
• The differences among the types of
uncertainty are a matter of degree.
Types of Uncertainty
Brno, November 1999 68
Uncertainty 2 and 3 include epistemic uncertainty. This is uncertainty
due to incomplete knowledge of processes that influence events.
Incomplete knowledge results from the sheer complexity of the world,
particularly with respect to issues at the interface of science and society.
As a result, models (computer or mental) necessarily omit factors that
may prove to be important. It is possible to judge the relative level of
epistemic uncertainty, i.e., because of the time frames and number of
potentially confounding factors, it is higher in nuclear waste disposal and
climate prediction than in the prediction of weather and asteroid
impacts. Total uncertainty is the sum of epistemic and aleatory
uncertainty.
(see Brunswik)
Epistemic Uncertainty
69
Picturing uncertainty
• There are many ways to depict uncertainty. For
example,
0
20
40
60
80
100
0 20 40 60 80 100
Forecast
Event
Continuous events:
scatterplot
Discrete events:
decision table
69
Picturing uncertainty
• There are many ways to depict uncertainty. For
example,
0
20
40
60
80
100
0 20 40 60 80 100
Forecast
Event
Continuous events:
scatterplot
Discrete events:
decision table
Any taxonomy –
For instance see slide 28
70
Continuous Judgments and Events
Consider the case of a continuous judgment
about a continuous event. Examples:
– Weather forecasts of windspeed, temperature
– Economic forecasts of unemployment, inflation
– Medical diagnosis of severity of disease
– Judgment of suitability of a job applicant
– Judgment of quality of college applicant
– Judgment of need for admission to hospital
71
Scatterplot: Correlation = .50
72
Scatterplot: Correlation = .20
73
Scatterplot: Correlation = .80
74
Scatterplot: Correlation = 1.00
The perfect judgment
75
Uncertainty, Judgment, Decision, Error
• Taylor-Russell diagram
– Decision cutoff
– Criterion cutoff (linked to base rate)
– Correlation (uncertainty)
– Errors
• False positives (false alarms)
• False negatives (misses)
Taylor-Russell diagram
76
77
Tradeoff between false positives and false negatives
78
Problem: Optimal decision cutoff
• Given that it is not possible to eliminate both false
positives and false negatives, what decision cutoff
gives the best compromise?
– Depends on values
– Depends on uncertainty
– Depends on base rate
• Decision analysis is one optimization method.
79
Example: Weather forecaster’s decision to warn the
public about an approaching storm
80
Decision tree
The trouble is to create the hierarchies of
problems to be solved according to their
urgency in a constant flow of situations,
presenting us with new tasks.
What to deal with and what to forget.
What are the desired consequences of
decisions (goals) and what is the possible
array unexpected consequences?
Problem solving of well or poor structured
tasks returns us back to the cognitive
continuum theory.
10. The most difficult and ages old puzzles of self-awareness
and consciousness:
- exactly, what are they?
- Where do they come from?
- How did they evolve?
- too difficult just for psychologists:
Philosophers, shamans, clergyman, physicians,
intellectuals,
esotheric seers, psychologists, physicists,
neurologists
neuronal nets folks, artificial intelligence, artificial
life folks ….
Simple Definition of consciousness
* the condition of being conscious : the
normal state of being awake and able to
understand what is happening around you
* a person's mind and thoughts
* knowledge that is shared by a group of
people
Source: Merriam-Webster's Learner's Dictionary
Full Definition of consciousness
1 a : the quality or state of being aware especially of something
within oneself
b : the state or fact of being conscious of an external object,
state, or fact
c : awareness; especially : concern for some social or
political cause
2 : the state of being characterized by sensation, emotion,
volition, and thought : mind
3 : the totality of conscious states of an individual
4 : the normal state of conscious life <regained consciousness>
5 : the upper level of mental life of which the person is aware
as contrasted with unconscious processes
Daniel C.Dennet,
multidisciplinary approach
Some examples:
„ Grof tries to disproof materialistic world view. He claims, that the interpersonal reality
is equally real, as our usual reality, if not even more so. The criticism of his scientific
and artistic legacy (see The Sisyfos Club – Grof „breaks the bonds of spacetime and
thus he can get into anyhing at any time“) is right in a sense, that the proof of
consciouness primacy over matter is hard to defend – it assumes the a priory „absolute
consciousness“, or „the pregnant void“. I guess that this issue is primarily a matter of
belief. The western science was never able to clarify the mind – matter relation“.
Pablo Kral
Psychiatrits Stanislav Grof (1931),
transpersonal psychology
David Chalmers
philosopher
Antonio Damasio
neurologist
Stuart Hameroff
anesthesiologist
Quantum physics theory of consicousness mind.
Microtubules and quantum consciousness.
Sir Roger Penrose
Mathematics, physicist
The soul does not die , but returns to the universe
Stuart Hameroff and sir Roger Penrose claim, that human brain is a biological
computer and our consciousness is a software, which runs there. This
program does not cease to exist even after our death. The soul exists in the
structures of filamentous brain cells called microtubules. When people enter
the stage of clinical death, their microtubulae loose their quantum state, but
the information contained there changes into a wave state and stays
preserved. Quantum information can not be destroyed, it can only
disseminate into a larger space.
Thus our soul is rather as program and our consciousness is a result of
“quantum gravitation” processes within the microtubular structures
(“orchestrated objective reductions” – Orch-OR).
http://www.quantumconsciousness.org/
cybernetics;
A.I., A.L.
groups
Marvin Minsky
M.I.T.
11. The ultimate knowledge – the art of asking the smart
questions see III. the Art of Asking Smart Questions series.
Will you contribute to these explorations in any way?
Original views are of those, who know less!
Now read some more, think, submerge into your
own imagination, make a choice
and write!
Look forward to see what you come up with…
Literature:
Bill Critchley, David Casey building of a team http://www.newparadigm.co.uk/Team
Dev.htm
Hammond, K. R. (1996). Human Judgment and Social Policy: Irreducible
Uncertainty, Inevitable Error, Unavoidable Injustice. New York: Oxford
University Press.
Hammond K.R., Judgment under stress, Oxford University press,
Senge Peter, Sterman John, system dynamics (systems thinking and
modelling), both at the M.I.T. Sloan School of management
Thomas R. Stewart, Ph.D., Center for Policy Research, Rockefeller
College of Public Affairs and Policy, University at Albany, State
University of New York
T.STEWART@ALBANY.EDU
www.brunswik.org.
See all authors on their web pages, www.TED.com, youtoobe….