Selected topics in general psychology II. Lubomír Kostron 2019 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. C:\Users\Kostron\Documents\BIBS\výuka 2016-17\SCN_0034.jpg C:\Users\Kostron\Documents\BIBS\Výuka\Výuka 2017\bakalářské programy\obrázky k manažerské psychologii\SCN_0045.jpg C:\Users\Kostron\Documents\BIBS\Výuka\Výuka 2017\bakalářské programy\obrázky k manažerské psychologii\SCN_0044.jpg The central region structure stimulation regulation activity environment environment organism State of the body Subconscious judments and decisions Conscious judgments and decisions Motives, needs Information – novelty, truthfulness Self-assessment Images, patterns, function relations, values Means, connotations Behavioral patterns temperament emotions feelings creativity Action, Behavior goals Situations, contexts Situationscontexts stimulae objects sensors thinking memory learning Where are the feedback loops? „…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-abo ut-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. https://tse2.mm.bing.net/th?id=OIP.Mf19d5db79dc34aed5bafe4e21a83b292o0&pid=15.1&P=0&w=300&h=300 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: http://www.joksankolikot.net/setelit/ruotsi/1985-500-kruunua-etu.jpg 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 39 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 https://tse3.mm.bing.net/th?id=OIP.M3df402f683310fe6187d6d19efcc14f5o1&pid=15.1&P=0&w=300&h=300 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 52 C:\Users\Kostron\Pictures\Portréty a citáty\Otto F.Scharmer\Otto F.Scharmer (1).jpg Otto F. Scharmer, M.I.T. C:\Users\Kostron\Pictures\Portréty a citáty\Otto F.Scharmer\scharmertheoryu1.jpg C:\Users\Kostron\Pictures\Portréty a citáty\Otto F.Scharmer\screen-shot-2015-04-03-at-12-25-21-pm.png C:\Users\Kostron\Pictures\Portréty a citáty\Otto F.Scharmer\OFSch AAEAAQAAAAAAAAfmAAAAJDZmMGQyYmJiLTA5M2UtNDZhNi1iM2VlLWVlODlkNjcxOWVjNw.jpg C:\Users\Kostron\Pictures\Portréty a citáty\Otto F.Scharmer\TU_1_Threshold_850h.png 55 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 Výsledek obrázku pro ray cooksey statistics Product Details Product Details Související obrázek 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 Výsledek obrázku pro ray cooksey statistics https://www.une.edu.au/staff-profiles/business/rcooksey Výsledek obrázku pro kahneman tversky heuristics and biases Výsledek obrázku pro kahneman tversky heuristics and biases Výsledek obrázku pro kahneman tversky heuristics and biases Výsledek obrázku pro kahneman tversky heuristics and biases Daniel Kahneman, psychologist, 2002 Nobel Price in Economics Výsledek obrázku pro kahneman tversky heuristics and biases Výsledek obrázku pro kahneman tversky Nobel prize 59 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. • 60 •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 61 •Uncertainty 2 - States (events) are known, probabilities are unknown –Elections –Stock market –Forecasting severe weather Types of Uncertainty Brno, November 1999 62 •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 63 •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 64 Picturing uncertainty •There are many ways to depict uncertainty. For example, – – • Continuous events: scatterplot Discrete events: decision table 64 Picturing uncertainty •There are many ways to depict uncertainty. For example, – – • Continuous events: scatterplot Discrete events: decision table Any taxonomy – For instance see slide 28 65 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 66 Scatterplot: Correlation = .50 67 Scatterplot: Correlation = .20 68 Scatterplot: Correlation = .80 69 Scatterplot: Correlation = 1.00 The perfect judgment 70 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 71 72 Tradeoff between false positives and false negatives 73 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. 74 Example: Weather forecaster’s decision to warn the public about an approaching storm 75 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 1a : 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 3: the totality of conscious states of an individual 4 4: the normal state of conscious life 5 5 : the upper level of mental life of which the person is aware as contrasted with unconscious processes Consciousness Explained Daniel C.Dennet, multidisciplinary approach Some examples: Holotropní vědomí Revoluce vědomí „ 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 Výsledek obrázku 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.new-paradigm.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….