Notes on Cognition Decision Making Language Khurshid Ahmad

Notes on Cognition, Decision Making, Language Khurshid Ahmad, Chair of Computer Science Trinity College, Dublin, IRELAND 15 -17 th November, 2010

Being intelligent being? Knowledge Intelligence Cognition

Being intelligent being? Herbert Simon in conclusion to his Nobel Lecture (1978) said that: “Today, we have a large mass of descriptive data, from both laboratory and field, that show human problem solving and decision making actually take place in a wide variety of situations. A number of theories have been constructed to account for these data, and while these theories certainly do not yet constitute a single coherent whole, there is much in common among them. In one way or another, they incorporate the notions of bounded rationality: the need to search for decision alternatives, the replacement of optimization by targets and satisficing goals, and mechanisms of learning and adaptation. ” Simon, Herbert. (1978). RATIONAL DECISION-MAKING IN BUSINESS ORGANIZATIONS. Nobel Lecture (http: //nobelprize. org/nobel_prizes/economics/laureates/1978/simon-lecture. pdf)

Being intelligent being? Herbert Simon in characterising bounded rationality notes that: “it is now clear that the elaborate organizations that human beings have constructed in the modern world to carry out the work of production and government can only be understood as machinery for coping with the limits of man’s abilities to comprehend and compute in the face of complexity and uncertainty” Simon, Herbert. (1978). RATIONAL DECISION-MAKING IN BUSINESS ORGANIZATIONS. Nobel Lecture (http: //nobelprize. org/nobel_prizes/economics/laureates/1978/simon-lecture. pdf)

Genesis of the term ‘bounded rationality’ in Simon Behavioral theories of rational bounded rationality choice - theories of bounded rationality negatively sloping demand curves could result from a wide range of behaviors satisfying the assumptions of Becker indicates that he denotes “bounded rationality” as irrational “[A]ny deviation from utility maximization. ” Thus, what I have called strong positive case for replacing bounded rationality the classical theory by a model of rather than those of utility maximization. is “irrationality” in Becker’s terminology. begins to emerge when we examine situations involving decision making under uncertainty and imperfect competition. Simon, Herbert. (1978). RATIONAL DECISION-MAKING IN BUSINESS ORGANIZATIONS. Nobel Lecture (http: //nobelprize. org/nobel_prizes/economics/laureates/1978/simon-lecture. pdf)

Genesis of the term ‘bounded rationality’ in Simon a theory bounded rationality general features of bounded rationality must incorporate a theory of search. had been proposed as an alternative to classical omniscient rationality - selective search, satisficing Simon, Herbert. (1978). RATIONAL DECISION-MAKING IN BUSINESS ORGANIZATIONS. Nobel Lecture (http: //nobelprize. org/nobel_prizes/economics/laureates/1978/simon-lecture. pdf)

Genesis of the term ‘bounded rationality’ in Simon Satisficing, a "handy blended word combining satisfy with suffice", [1] is a decision-making strategy that attempts to meet criteria for adequacy, rather than to identify an optimal solution. A satisficing strategy may often be (near) optimal if the costs of the decision-making process itself, such as the cost of obtaining complete information, are considered in the outcome calculus. http: //en. wikipedia. org/wiki/Satisficing

Genesis of the term ‘bounded rationality’ in Simon The word satisfice was coined by Herbert Simon in 1956. He pointed out that human beings lack the cognitive resources to maximize: we usually do not know the relevant probabilities of outcomes, we can rarely evaluate all outcomes with sufficient precision, and our memories are weak and unreliable. A more realistic approach to rationality takes into account these limitations: This is called bounded rationality. http: //en. wikipedia. org/wiki/Satisficing

Being intelligent being? The foundational statement that lays the groundwork for much of the work in behavioural finance, was made by one of the key workers in computing (artificial intelligence), psychology (problem solving), and economics (organisational economics) Herbert Simon. For Simon, there are four main areas which have a symbiotic relationship with behavioural finance: 1. Utility Theory and Human Choice 2. Psychology of Problem Solving 3. Organisational Decision Making 4. Theories of the Business Firm Simon, Herbert. (1978). RATIONAL DECISION-MAKING IN BUSINESS ORGANIZATIONS. Nobel Lecture (http: //nobelprize. org/nobel_prizes/economics/laureates/1978/simon-lecture. pdf)

Being intelligent being? For Simon, there are four main areas which have a symbiotic relationship with behavioural finance: Key Symbiosis Exemplars Utility Theory and Human Choice Framing that results in Organisational Decision Making apparently contradiction to utility maximisation) The use of heuristics; bounded rationality Decision making by collectives Theories of the Business Firm Selective Searching, staisficing Psychology of Problem Solving Simon, Herbert. (1978). RATIONAL DECISION-MAKING IN BUSINESS ORGANIZATIONS. Nobel Lecture (http: //nobelprize. org/nobel_prizes/economics/laureates/1978/simon-lecture. pdf)

Being intelligent being? Cleverly searching a solution in a large space Starting from a question “F”, I divide the search space into E and E’ ; then onto D, and onto C. . . until I reach the solution the colored dices. F E D C C A A A B B A A A

Being intelligent being? Cleverly searching a solution in a large space One can traverse all the paths, sequentially or in parallel, but a clever search strategy will be to have a good guess, based on experience, to choose a ‘plausible’ path E F D C C A A A B B A A A

Being intelligent being? with apologies to Plato Knowledge about, knowledge by description: knowledge of a person, thing, or perception gained through information or facts about it rather than by direct experience. Language; Images Symbols; Planning; Learning, Thinking; Creativity An impersonation of intelligence; an intelligent or rational being; esp. applied to one that is or may be incorporeal; a spirit COGNITION: The action or faculty of knowing taken in its widest sense, including sensation, perception, conception, etc. , as distinguished from feeling and volition.

Knowledge, Cognition and Intelligence • Knowledge is acquired and disseminated by intelligent and cognate beings. The terms knowledge, cognition and intelligence are used interchangeably. • And there is a good reason for this: Various cognitive processes help in converting information and stimuli into knowledge. Knowledgeable beings then act intelligently because of their greater awareness.

Knowledge, Cognition and Intelligence Information exchange, processing and decision making; Knowledge is acquired and disseminated by intelligent and cognate beings. Knowledge Language; Images Symbols; Planning; Learning, Thinking; Creativity Intelligence Cognition

Knowledge, Cognition and Intelligence Human Information Exchange: The role of cognition, perception and movement In everyday language cognition is used to refer to the 'higher' mental processes. In psychology cognition would generally be taken to include a variety of mental activities.

Knowledge, Cognition and Intelligence Human Information Exchange: The role of cognition, perception and movement Cognitive faculties include attention, control, categorisation, creativity, decision making, language, learning, mental imagery, memory, problem solving, reasoning, representation. Perceptive capabilities enable humans to hear, see, smell, taste, and touch. These capabilities help humans to translate a variety of environmental input, for example, acoustic, chemical, electromagnetic, mechanical, thermal, into a language which can be understood by the human nervous system. Motor skills underpin the cognitive faculties and perceptive capabilities through the complex network of muscles and nerve fibres for receiving inputs from and providing output to the external environment. Cognition, perception and movement helps humans to exchange

Knowledge, Cognition and Intelligence Kinds of Knowledge: Cognitive psychologists have studied experts, in the physical, medical and engineering sciences, involved in problem solving, ranging from diagnosis, mental calculation, design and planning for example. The psychologists have also observed skilled performance in taxi driving, typing for instance. The observations have led to six major findings (Glaser 1994: 140141):

Cognitive Processes • Cognition is a broad term which is used to refer to activities like thinking, reasoning, conceiving, solving problems, learning, communicating through language and through other symbol systems. 19

Cognitive Processes • Cognition, or rather cognitive, is almost invariably used whenever an agent (ANIMAL, HUMAN or ROBOT) is • seen to be using abstraction; • seen to be using complex rules; mental • seen to be using imagery; • said to have intended to act on his, her or its own; • said to have used a symbol system. 20

Cognitive Processes: Some Definitions INTELLIGENCE : = Perception+Cognition+Motor Control. Perception : Reception/analysis of sensory stimuli Motor control: Pertaining to or characterizing that which involves the systematic use of muscles; Cognition: Related to activities that involve abstraction, symbolization, insight, rule use, imagery, belief, internationality, problem-solving, language -based communication 21

Percepts, Movements and Concepts? • The sensory organs receive information about the world about us; this information is processed by the brain; and the recipient ignores/reacts to the processed information. The reception, processing and reaction involves muscular movement • The perception of sound can relate to the cognition of speech or music; the controlled movement of limbs can relate to the cognition of dance movement. 22

Cognitive Processes • COGNITIVE PSYCHOLOGY is a branch of psychology that emphasises internal, mental processes. • In cognitive psychology (COG PSY) human behaviour is discussed not in terms of its overt properties but at an abstract level: • • mental events Mental representations beliefs intentions 23

Cognitive Processes: An example ~ Information Processing • Any intended input, any idea, image, fact, knowledge, and so on, counts as information in COG PSY. • Processing in COG PSY usually means moving towards some GOAL by going through a series of STAGES or a SEQUENCE of acts. 24

Cognitive Processes: An example ~ Information Processing • Information processing involves cognitive processes that can deal with the organization, interpretation and responding to an incoming stimulation; PROCESSING : = ORGANISATION+INTERPRETATION+RESPONSE; INFORMATION: = INCOMING STIMULATION 25

Behaviour and Cognition The Nature of Expertise One view of human expertise is that some people have spent so much time solving problems in one particular domain that they ‘know all there is to know’ (nearly) and are able to see any problem as an instance of a class of problems with which they have been confronted before. Once the expert has successfully classified or recognised a new problem as an instance of a previously experienced problem type, all the expert has to do is apply whatever solution proved successful in dealing with that type of problem in the past.

Behaviour and Cognition Cognitive psychologists have studied experts, in the physical, medical and engineering sciences, involved in problem solving, ranging from diagnosis, mental calculation, design and planning for example. The psychologists have also observed skilled performance in taxi driving, typing for instance. The observations have led to six major findings (Glaser 1994: 140 -141):

Behaviour and Cognition Cognitive psychologists have studied experts, in the physical, medical and engineering sciences, involved in problem solving, ranging from diagnosis, mental calculation, design and planning for example. The psychologists have also observed skilled performance in taxi driving, typing for instance. The observations have led to six major findings (Glaser 1994: 140 -141):

Behaviour and Cognition: A Typology of knowledge Knowledge Type Elaboration Structured, Principled As competence is acquired, elements of knowledge become integrated and Knowledge the experts store (and retrieve) coherent chunks of knowledge Procedural The experts’ declarative knowledge appears to be bound with conditions of Knowledge applicability and procedures for use, e. g. condition-action rules. Skilled Memory Experts and novices have similar memory storage and retrieval capacities, but experts appear to use long-term memory in a way it resembles shortterm memory. Automaticity Proficiency apparently requires that some competent skills must become automatic, so that conscious processing capacity can be devoted reasoning and decision making. Effective Problem Experts appear to spend time in initial analysis of a problem: they assess Representation the problem, build mental models to make inferences and add constraints to reduce problem space. Strong Self- Their experience helps the experts to develop a critical set of self. Regulatory Skills regulatory or metacognitive skills. These skills are used by experts to control their performance.

Knowledge Management: Key Issues • OLD VIEW: Knowledge should ‘flow’ through an organisation from the knowledge officers (top executives) to the knowledge engineers (middle management), and from the engineers to the knowledge workers (experts, practitioners) 30

Knowledge Management: Key Issues • POST-INDUSTRIAL VIEW: Knowledge should ‘flow’ through an organisation amongst the knowledge officers (top executives), the knowledge engineers (middle management), and the knowledge workers (experts, practitioners) 31

Knowledge & Change Management Post Modern Organisation (Pre 1950’s) Post Industrial Organisation (Post 1990’s) Structure PASSIVE, STATIC REACTIVE, DYNAMIC Products DURABLE, DULL DISPOSABLE, STYLISH STABLE CHANGING GEOGRAPHICALLY WELL DEFINED FUZZILY DEFINED IDENTIFIABLE RIVALS: WAR OF CHANGING RIVALS: Consumer Needs Markets Competition POSITION WAR OF MOVEMENT 32

Knowledge Spiral & Innovation 1980’s Product Evolution Calculator Fax VCR 1985’s Knowledge Spiral at SHARP 1970’s Mask ROM Liquid Crystal Display CMOS Semi-conductor Opto-device 1990’s Electronic Organiser Home Fax Word Processor LCD TV Components Technology 33

Knowledge Spiral & Innovation 1980’s Product Evolution Calculator Fax VCR Knowledg e Spiral at SHARP P 1970’s R Mask ROMO CMOS D Liquid Crystal CONCEPTS/DEVICE Semi-conductor U Display Opto-device C 1990’s T S Electronic Organiser Home Fax Word Processor LCD TV 1985’s Components Technology 34

Product Evolution Knowledge Spiral & Innovation 2000 Personal Office Assistant; High Definition Television; Multimedia Systems 1980’s Calculator Fax VCR 1995’s 1985’s ? ? Mask ROM Liquid Crystal Display 1970’s CMOS Semi-conductor opto device Flash Memory; TFT; LCD; Solar Power 1990’s Electronic Organiser Home Fax Word Processor LCD TV ? ? Components Technology 35

Knowledge Spiral & Innovation Products/Services Scientific Progress & Technical Change Social Attitudes 36

Knowledge Conversion Two dimensions of knowledge creation in organisation: explicit and tacit. knowledge Explicit Knowledge of rationality Knowledge Sequential knowledge (OBJECTIVE) (mind); (there and then); Digital knowledge (theory). Tacit Knowledge of experience Knowledge Simultaneous knowledge (SUBJECTIVE) (skills); (here and now); Analog knowledge (practice). 37

Knowledge Conversion Two dimensions of knowledge creation in organisation: explicit and tacit. knowledge Dimension Type Explicit Symbolic Implicit Embodied Implicit/Tacit Ingrained Tacit Culturally acquired 38

Knowledge Conversion Nonaka & Takeuchi’s Knowledge Conversion Modes Process Socialisation Tacit Externalisation Tacit Explicit Task Share experience; Transfer skills; Explain models Articulate knowledge; concepts, hypotheses Explicit Tacit Transfer or acquire knowledge: by ‘doing’; by teaching; project work Combination Systematise knowledge; Evaluation; Testing Internalisation Explicit 39

Behaviour and Cognition: Knowledge Evolution Nonaka & Takeuchi’s Knowledge Conversion Modes Tacit Knowledge Explicit Knowledge To Tacit Knowledge Socialisation Sympathised Knowledge Externalisation Conceptual Knowledge Internalization Operational Knowledge Combination Systemic Knowledge From Explicit Knowledge

Behaviour and Cognition: Knowledge Evolution Nonaka & Takeuchi’s Knowledge Conversion Modes Dialogue Socialisation Externalisation Field Building Internalisation Combination Learning by Doing Linking Explicit Knowledge

Behaviour and Cognition: Knowledge Evolution Nonaka & Takeuchi’s Knowledge Conversion Modes Tacit Knowledge Explicit Knowledge To Tacit Knowledge Socialisation Sympathised Knowledge Externalisation Conceptual Knowledge Internalisation Operational Knowledge Combination Systemic Knowledge From Explicit Knowledge

Behaviour and Cognition: Knowledge Evolution Dialogue Socialization Externalisation Linking Explicit Knowledge Field Building Internalisation Combination Learning by doing

Behaviour and Cognition: The role of knowledge Wang (2009) looked at the relationship between the ‘increasingly complex financial products in the marketplace’ and ‘investors’ financial literacy’. The author conducted a questionnaire survey to see ‘how different male and female investors’ financial knowledge and risk-taking behavior are’ (ibid: 204). (Wang 2009). Wang, Alex. (2009). Interplay of Investors’ Financial Knowledge and Risk Taking. The Journal of Behavioral Finance. Vol 10, pp 204 -213.

Behaviour and Cognition: The role of knowledge Wang used ‘survey data focusing on investing in mutual funds as tested knowledge domain and measured behavior’ (ibid: 208): 524 participants took part, 317 male and 207 female. 37 questions were used to measure participants’ objective knowledge regarding investing in mutual funds; these questions were based on the work in consumer research, especially on attention and comprehension of a consumer (Celsi and Olson 1988), and based on work in marketing research on the knowledge of a consumer (Moreau, Lehmann and Markman 2001). • 10 multiple-choice questions were used to reflect participants’ objective knowledge regarding investing in mutual funds • 27 true-false questions were used to measure participants’ objective knowledge about investing in mutual funds Celsi, R. L. and J. C. Olson. “The Role of Involvement in Attention and Comprehension Processes. ” Journal of Consumer Research, 15, (1988), pp. 210– 224. Moreau, C. P. , D. R. Lehmann and A. B. Markman. “Entrenched Knowledge Structures and Consumer Response to New Products. ” Journal of Marketing Research, 38, (2001), pp. 14– 29.

Behaviour and Cognition: The role of knowledge Distribution of scores in an on-line questionnaire on ‘investment in mutual funds’; 37 questions on the survey (Wang 2009). Marks <40% ≥ 40% & <50% ≥ 50% & <60% ≥ 60% & <70% ≥ 70% & <80% ≥ 80% Total Number of Percentage of respondents 9 2% 43 8% 139 27% 152 29% 155 30% 26 5% 524 100% Grade Fail III II. 2 II. 1 I Distinction

Behaviour and Cognition: The role of knowledge Wang showed that 1. at ‘least for investors, their objective knowledge, subjective knowledge, and risk taking are highly correlated. 2. The gender of the respondent is an important factor that differentiates investors’ levels of objective knowledge, subjective knowledge, and risk taking. Wang has argued that ‘it is investors’ subjective knowledge that mediates their objective knowledge on risk-taking behavior. Since male investors have higher subjective knowledge and objective knowledge than female investors, they often takemore risks because of the mediation effect of subjective knowledge’ (2009: 212). Wang, Alex. (2009). Interplay of Investors’ Financial Knowledge and Risk Taking. The Journal of Behavioral Finance. Vol 10, pp 204 -213.

Behaviour and Cognition: The role of knowledge The management of financial risk depends upon an organisation’s base of knowledge, access to capital and ICT resources, and the accumulated experiential knowledge. An organisation is in itself an agencement: The knowledge, capital and technological resources, have to be seen in the context of the manner in which individuals manage and operate within the organisations, what is the balance of rights and duties, rewards and punishments: in short what is the culture of the organisation, the skills of its owners and workers, and how is it the agencement works.

Behaviour and Cognition: The role of knowledge • There is a need to facilitate the communication across all the facets of the organisation. Knowledge has to be created, shared, validated and REGULARLY pruned. Seeding, fertilising, nourishing and pruning are the HALLMARKS of a sustainable eco system. • A sustainable eco-system has redundancy built into its operational mechanisms and allows the system to take advantage of opportunities, to weather dearth in opportunities, and to recover from disasters and overindulgence. • Sustainable eco-systems have well integrated components and have contingencies to deal with failures in the various sub-systems: Each subsystem is familiar with the operation of other proximate sub-systems. • A sustainable eco-system is an OPEN system

Behaviour and Cognition: The role of knowledge Post Modern Organisation Post Industrial Organisation Structure PASSIVE, STATIC REACTIVE, DYNAMIC Products DURABLE, DULL DISPOSABLE, STYLISH Consumer Needs STABLE Markets GEOGRAPHICALLY WELL DEFINED Competition IDENTIFIABLE RIVALS: WAR OF POSITION CHANGING FUZZILY DEFINED CHANGING RIVALS: WAR OF MOVEMENT

Behaviour and Cognition: Knowledge Evolution Nonaka & Takeuchi’s Knowledge Conversion Modes Tacit Knowledge Explicit Knowledge To Tacit Socialisation Risk heuristics Knowledge Externalisation Strategic Vision, Financial Innovation From Explicit Knowledge Internalisation Back Office; Regulatory Instruments Combination Financial Models; Asset Performance; News Management

Behaviour and Cognition: The role of knowledge Three major financial risk management disasters usually have three ingredients: 1. Dysfunctional Culture (e. g. ENRON) 2. Unmanaged Organisational Knowledge (e. g. Barings, Kitter-Peabody, Salomon Brothers) 3. Ineffective Controls (e. g. 2008 credit crunch) Marshall, Chris. , Prusak, L. , & Shpilberg, D. (1997). ‘Financial Risk and the Need for Superior Knowledge Management. In (Eds) Laurence Prusak. Knowledge in Organisations: Resources for a Knowledge-Based Economy. Newton (MA, USA): Butterworths-Heinemann, Chapter 11.

Behaviour and Cognition: The role of knowledge Three major financial risk management disasters: Metallgesellschaft Refining & Marketing Marshall, Chris. , Prusak, L. , & Shpilberg, D. (1997). ‘Financial Risk and the Need for Superior Knowledge Management. In (Eds) Laurence Prusak. Knowledge in Organisations: Resources for a Knowledge-Based Economy. Newton (MA, USA): Butterworths-Heinemann, Chapter 11.

Behaviour and Cognition: The role of knowledge Three major financial risk management disasters: Kidder Peabody Marshall, Chris. , Prusak, L. , & Shpilberg, D. (1997). ‘Financial Risk and the Need for Superior Knowledge Management. In (Eds) Laurence Prusak. Knowledge in Organisations: Resources for a Knowledge-Based Economy. Newton (MA, USA): Butterworths-Heinemann, Chapter 11.

Behaviour and Cognition: The role of knowledge Three major financial risk management disasters: Baring Securities Marshall, Chris. , Prusak, L. , & Shpilberg, D. (1997). ‘Financial Risk and the Need for Superior Knowledge Management. In (Eds) Laurence Prusak. Knowledge in Organisations: Resources for a Knowledge-Based Economy. Newton (MA, USA): Butterworths-Heinemann, Chapter 11.

Behaviour and Financial Markets Traditional Finance Theory Criticism Behavioural Finance Response Theoretical behavioural models are somewhat ad hoc and designed to explain specific stylised facts Behavioural models are based on how people actually behave based on extensive experimental evidence, and explain evidence better than traditional ones Empirical work is plagued by data-mining (that is, if researchers set out to find deviations from rational pricing by running numerous regressions, ultimately they will be successful). Much empirical work has confirmed the evidence out-of-sample, both in terms of time-periods as well as cross-sectionally across different countries Behavioural finance presents no unified Traditional risk-based theories do not theory unlike expected utility maximisation appear to be strongly supported by the data. using rational beliefs. Avanidhar Subrahmanyam (2007)Behavioural Finance: A Review and Synthesis. European Financial Management, Vol. 14, No. 1, 2007, 12– 29

Neuroscience and Economics It can be hypothesized that different criteria are applied to select one or more features of each of the interacting modalities – sometimes the features can aggregated to achieve super-addition, such that the whole is greater than the sum of the individual features, and at other times some features can be relegated in importance such the whole is less that sum leading to sub-addition. Yet, sometimes a simple addition of the modalities suffices. The well-known cocktail party effect relies on the super-addition of low-level linguistic information with the visual information of facial changes that enables listeners to ‘listen’ in noisy environments. The collapse of enterprises and markets on rumours, despite encouraging quantitative information about the performance their assets, is the sub-addition of linguistic information with numerical. .

Processes in Prospect Theory Multi-criteria decision making has a long history in social sciences and recently have been used in environmental sciences, images classification and financial forecasting. The different ways in which features are aggregated depends on context, data density and uncertatinity and it appears that the importance of criteria is measured by means of a capacity. In effect, it has been found out the criteria can be aggregated by means of the socalled fuzzy integrals – for cardinal evaluations it is the Choquet integral appears to be the key and for ordinal evaluations it is the Sugeno integral.