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Judgement and Decision Making

Judgement and Decision Making. Amnesia . Clive Waring no longer has memory of what has gone before. Every morning when I wake up it is as if I have woken up for the first time. Showing obvious frustration “The problem is I just can’t think” .

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Judgement and Decision Making

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  1. Judgement and Decision Making

  2. Amnesia • Clive Waring no longer has memory of what has gone before. • Every morning when I wake up it is as if I have woken up for the first time. Showing obvious frustration “The problem is I just can’t think”

  3. If Memory is important to thinking then memory must also be important in judgement and in decision making

  4. Cognitive processes in Decision Making Decision making research has catalogued the situations in which people use heuristics and/or are biased. Decision theorists: focus on mathematic models that describe data assume normative rationale appears at odds with what is known about human cognition. Cognitive theorists : develop quantitative models that describe processes assume rationale is bounded. Many phenomena better understood by examining how information is represented and retrieved from memory.

  5. “How is judgement affected by (i) encoding(ii) representational assumptions(iii) retrieval operations(iv) experience?” Dougherty et al (2003) Memory perspective on decision making • Decision making as processing of stored representations of the decision maker’s past environment • Assumes environmental stimuli are encoded into memory, but traces are imperfectreplicas - dependent on attention at the time of encoding the copies are degraded. • Trace theory of memory leads to imperfect retrieval- leads to systematic biases in judgement.

  6. Influence of memory on decision making • Memory structures enable people to construct representations of decision problems (Pennington & Hastie, 1993) • Decision may not be based on the data provided in the decision task, instead being based on data retrieved from memory. • Extent of informational data in memory is one’s expertise, and to some extent will determine the accuracy of the decision.

  7. Theories of Memory Representation • Environmental stimuli stored as specific instances, each experience as a separate memory trace = verbatim copy • Environmental stimuli stored as gists, only a summary of stimulus is stored, details are lost, but meaning information is retained Fundamentally different types of representation they have different implications for decision making.

  8. Encoding 1. Instance-based encoding 2. Gist-based encoding

  9. 1. Encoding quality of individual events Specific instances as exemplarsMultiple trace Memory Model • Attention: high quality of encoding for events attended to; low for those in which there is inattention • Time: familiarity and visualisation increases with study time (Bower, 1970), generation of the stimulus can improve memory retrieval (Slamecka & Graf, 1978). • Judgements of frequency are increased by how well the information is encoded in memory Better calibration of probability judgements when encoding quality is high Quality high when the stimulus event is central to the focus of attention. Peripheral attentional resources produce overconfidence, poorer decisions.

  10. What about biased encoding? • Differential encoding leads to bias and increased encoding quality in this case will lead to poorer judgement. Attention to exciting/important information. EXAMPLE: overestimation of the frequency of events perceived as catastrophic. • Related to how often reported in media (biased reporting of events) - locus of overestimation in the environment • More attentional resources to catastrophies (higher fidelity of encoding) – locus of overestimation in the decision maker

  11. Begg et al (1985): effect of differential encoding on validity judgements. Participant given statements for 50% encouraged to engage in more effortful process. These were later rated of higher validity that statements viewed effortlessly. validity increased as encoding quality increased. Ogden et al (1999): effect of differential encoding on frequency judgements Participants given adjectives: asked to self-reference 15 (deep), asked if they contained an “i” in 16 (superficial). Self-referenced adjectives were deemed more frequent than those containing ‘i’

  12. Christianson et al (1996)(sociopaths vs non-sociopaths) Percentage of participants correctly recalling central or peripheral information of a critical picture in 2 conditions. Emotional condition Neutral Condition

  13. Specific instance Encoding: summary • In instance-based representations encoding can produce both good and bad judgements • Good encoding produces better judgement • Unless encoding is differential - some representations are likely to be more accessible than they should be and judgement will be poorer. • Much evidence to suggest we differentially encode, particularly if emotional content, eg gun focus.

  14. 2. Gist (abstract) encoding Pennington & Hastie (1993): we do not make a veridical copy of decision making information, instead a ‘story’ interpretation of the information is constructed – a causal model that is the interpretation of the evidence Brainerd & Reyna (1990a): fuzzy trace theory – information is encoded on a gist-to-verbatim continuum. We have a preference to reason at the lowest level of specificity that can accomplish the task (gist). Gists are retained for longer than verbatim traces.

  15. 1. Effect of gist versus verbatim representations on judgement? Gist only formed for meaningful. • Justin, Winman & Persson (1994) Participants presented with meaningful and nonmeaningful text at study. At test tested for their memory for the stimulus information and asked to rate their confidence. Even after 2 months good for meaningful text. Participants could rely on their ‘gist’ representations when judging the text information but had to rely on the verbatim (visual??) representation when judging the nonsense syllables.

  16. 2. Effect of Gist vs Verbatim information on Choice? Choice between: A. £100 for certain • 50% chance of winning £200, 50% chance of winning nothing Most people go for the safe option Unless the framing is reversed from winning to losing. Lose averse we choose the risker option: 50% chance of losing £200, 50% chance of loosing nothing. • Traditional decision theorists assume the processing of numerical data is the reason choice behaviour is affected by framing effects BUT expected value theory finds it difficult to explain why a change from +ve to –ve framing effects the choice! • The effect occurs even if figures are not included (e.g word used: some) Reyna & Brainerd (1991):framing effects are attributable to a reliance on gist, qualitative processing. Not using the verbatim numerical information but an abstract simplification to make their choice.

  17. Reyna & Brainerd (1991) also showed framing effects depended on complement information: the zero complement 10% chance of winning £100 Then the zero complement = 90% chance of not winning £200. Reyna & Brainerd argued the zero complement instilled a pivotal qualitative contrast, if zero contrast was available it triggered the encoding of the gist. (more than/less than rather than values)

  18. Wedell & Böckenholt (1990): reasoners use lowest level of representation that will accomplish the task : One-time or repeated plays in a gamble are different tasks and operate at different level of precision. Repeated plays produced a shift from gist to verbatim processing. Taking the example of Choice between: A. £100 for certain • 50% chance of winning £200, 50% chance of winning nothing Only allowed one play: GIST – categorical distinction only risk averse – take sure option: £100. A categorical distinction at the ‘gist’ level is sufficient to make this decision. Repeated Plays:VERBATIM – finer distinction. the long-running payoff between the 2 choices becomes clear, attention is paid to the verbatim numerical information, participants make finer distinctions. With experience the perception of the utilities changes and so can risk preferences.

  19. The effect of the encoded properties of representations on decision making If the decision problem is expressed verbally/ text based Gist processes take precedence. If the decision problem relies on past frequentistic experience Verbatim/specific exemplar processing may take place. FUTURE RESEARCH: 1. delineate the domains of gist and verbatim processing 2. antecedent conditions that lead us to rely on abstraction-based or specific exemplar-based processing.

  20. Characteristics of Memory Retrieval that affect decision making • Primacy and Recency effects • Biased retrieval mechanisms

  21. 1. Serial position effects in judgement • Serial position effects will only affect memory-based judgements, not on-line processing judgements • Weber et al (1995): primary/recency effects do not assume participants consciously recall individual items from memory.

  22. Serial position effects in judgement Across a number of situations, LTM & STM tasks show: typically performance is better for information at the beginning (primacy) and at the end (recency) of a list of items(Baddeley, 1998) Ubiquity of order effects in recall and in memory-based judgement: • sensitivity to the order in which the outcomes appear. • Preference for +ve outcomes appearing at the start and end of a sequence. Examples: Weber,Goldstein & Barlas (1995) - +ve pay-off of gambles Anderson & Hubert (1963) - impression formation.

  23. Serial position effects in judgement Weber et al (1991): effects can be accounted for by assuming a memory decay mechanism operates on a distributed memory representation. Unlike a instance-based representation, in distributed memory systems all informational items are superimposed into a single “composite” trace whose retrieval would be sufficient to account for recency and primary effects. Retrieval of specific Instances would not be necessary. EVIDENCE: Weber et al (1995). If judgement depends on the conscious recall of the individual items, then there should be a set size effect: longer lists should elicit longer reaction times in making a decision. Attractiveness ratings were unaffected by set size : judgement based on composite representation and not recall of individual attributes.

  24. Boundary conditions: Serial position effects in judgement Hastie & Park (1986) Order effects occur when judgements are made from memory from previously stored information. Participants tended to do this when they had no warning they were about to do a judgement task. Order effects do not occur when judgements are being made “online” as the information is being received. Participants did this if they were warned of the impending judgement task. ON-LINE judgements do not require memory retrieval and are unaffected by the order in which information is presented MEMORY judgements are affected by order effects.

  25. 2. Biased Retrieval in judgementEven if information is represented in memory in a veridical and non-biased form, memory can be biased by retrieval processes and lead to judgement errors. • Base-rate Neglect: cueing the incorrect subset of instances in a conditional probability judgement leads to the neglect of the base-rate (Sherman et al, 1992). • Magnitude of Probability: • an unspecified or biased cue in memory search affects probability judgements. • Predicted probability increases if there are more details in the retrieval cue (Dougherty et al, 1999)

  26. 1. Base-rate neglect in judgement • Fundamental Property of Memory: Categorical (Rosch et al, 1976) : Categories partition continuum of data. • Categories define information subsets in memory. Crucial to a correct categorical decision (e.g is he an extroverted male) is the activation of the correct subset of instances - affected by structure of memory and retrieval factors.

  27. Base-rate neglectRetrieval factors affecting activation of an appropriate set of instances in judgement • Categorical cueing (priming) • Individuating information • Confusion of the inverse

  28. 1. Categorical Cueing When a category is primed judgement is based on the primed category regardless of its appropriateness (Hanita et al, 1997) Participants had to make a conditional probability judgement Prior to the judgement asked to recall either 5 instances from the appropriate subset (likes the film) or from an inappropriate (likes torfu) subset. Either one or other of the subsets was primed. Appropriate subset primed: deviated slightly from objective probabilities Inappropriate subset primed: neglected base rate.

  29. 2. Individuating information • Task becomes more difficult because it restricts the number of instances that belong to the conjunctive category. • May obscure subset of instances that should be searched Both result in a simpler search strategy: search memory for which ever subset is most accessible. If this subset is inappropriate then base-rate neglected! EXAMPLE (Gavanski & Hui, 1992) What is the probability that Mary is an engineering student given that she is carrying a pocket calculator, enjoys building models, enjoys maths. The appropriate subset of instances relevant to the judgement are all these Conjoint characteristics, BUT people are likely to search subset “engineers” because it is more accessible than the others BUT this is an inappropriate subset. Although easier, the base-rate is neglected, because the sub-set was larger.

  30. 3. Explicit confusion of the inverse We equate likelihood probability with posterior probability Eddy (1982) Experienced physicians consistently confused the diagnosticity of a test with its posterior probability. Hamm (1993) Base-rate information and likelihood information provided. Asked to Assess posterior probability. They did not calculate the posterior probability but instead gave the likelihood probability. May also extend to memory We do not distinguish between the two conditional probabilities. Instead we confuse inverse probabilities When making conditional likelihood judgements we may not search the appropriate subset of instances, only the posterior probability subset, neglecting the base-rate information necessary to the calculations.

  31. Summary • Categorical cueing, individuating information and confusion of the inverse operate at retrieval stage • All affect a participant’s tendency to activate the inappropriate subset of instances in memory • What happens when 2 or more of these factors operate simultaneously or in competition requires further research.

  32. Summary: Memory Retrieval in judgement • Judgement affected by Order effects • Judgement affected by how information becomes active in memory

  33. Experience and Domain Knowledge Process-performance Paradoxcontrast between expert and superior decision quality (Camerer & Johnson, 1991) Mixed Findings variability in expert decision makers’ performance, superior to novice in some cases but not in others Expert performance is constrained by task characteristics. Experts perform well in tasks • Static • High degree of predictability • Feedback readily available (Shanteau, 1992)

  34. Role of Memory processes in expert decision making(Dougherty, 2003) Little research in this area: Relevant Memory Theories. • COGNITIVE ADJUSTMENT • LOGAN’S THEORY OF AUTOMATICITY • WORKING MEMORY & LONG-TERM MEMORY

  35. 1. Cognitive Adjustment in expert decision making Memory becomes more/less a veridical representation of the environmental cue structure. The sources of error variance are FUNDAMENTAL TO THE ACCURACY OF PROBABILITY : • Response Error • Sampling Error • Retrieval Error EXPERTS may have enhanced encoding for domain-specific stimuli so that increased experience may lead to better calibrated probability judgements because they have a more veridical memory base (Dougherty et al, 2001).

  36. 1. Cognitive Adjustment in expert decision making • Response-Error Increase in domain experience ⇨ increase in the frequency of similar Traces being stored in memory ⇨ reduction in error variance in memory retrieval, same response! • Sampling-Error Increase in domain experience ⇨ random variation (associated with Sampling the environmental stimuli) will decrease, less sampling! • Retrieval-Error Process of memory retrieval may account for random variation. With expertise there will be less variance in what is retrieved and may be fundamental to overconfidence phenomena.

  37. 2. Logan’s Theory of Automaticity (1988) MEMORY-BASED Retrieval of solution from memory RULE-BASED Computing solution via an Algorithm Problem Solving No prior experience – assume compute Prior Experience - race between retrieving relevant instances from storage and computing solution Increase in task relevant experience – number of traces competing increases and the probability increases that the solution will be retrieved from memory rather than being computed.

  38. What happens in rule-based decision making? • Smith et al (1992) In the absence of obvious choices in deliberative decision making: (i) inferential rules are used (logical, statistical, causal deduction, contractual, cost-benefit), (ii) decision alternatives are judged, (iii) a decision strategy is adopted (iv) and an explicit choice made. • If experience is gained in the judgement domain there may be a shift from rule-based to memory-based processing. • situation-specific cues will trigger the retrieval of prestored solutions. (Klein, 1997; case-based reasoning: Kolodner, 1993)

  39. Switching between memory-based and exemplar-based processing dependent on task. Role of Memory in Expert Air Traffic Controllers ( Gronlund et al, 1998) Rely on exemplar representations to remember altitude (exact) Rely on gist-type representations to remember speed (relative) Reliance on verbatim representations: exact attitudes to control traffic. Reliance on gist representations: relative speed is sufficient to know whether one aircraft is overtaking another. Role of Memory dependent on task novelty Between the end points novice (rule-based) /expert (exemplar based) there should be a high degree of variability - switching between memory and rule based processing: is it this that accounts for variability in expert performance?? Expert - familiar situation - memory-based judgement if decision problem is familiar, Expert - novel situation - rule-based judgement, may be common in complex and dynamic environments.

  40. 3. Working & LT Memory • Limited Capacity of Working Memory (7+/- 2 chunks). Weber et al (1995): finite information processors, rationale is bounded, issue is therefore of strategy selection. • Expert superior performance (e.g. chess, waiter) challenges the notion that WM limitations restrict performance. • WM accounts for performance on unfamiliar tasks, but not in the performance of skilled activities. • LT-WM = retrieval structure, pointers in WM point to information in LTM. Information can remain in LTM during interruptions (that clear WM) and access to this information can be reinstated by reactivating the relevant retrieval structure [character is strong spatial for waiters & hierarchical for doctors] (Ericsson & Kintsch, 1995).

  41. 3. Working & LT Memory LT-WM theory • Selection of decision strategies by experts is not contingent on lack of processing capacity • Expert should be able to make compensatory decision strategies so they can deal with more cues/information simultaneously but they don’t! (Shanteau, 1988) • Improvement in expert performance should capitalise on their pre-existing retrieval structures (spatial rather than hierarchical would not help doctors) • Decisions aids compatible with prior experience enhance rather than interfere with decision quality Thought! Restructuring of prior-experience difficult? Use of Mind-maps in restructuring when predictability of environment changes ??

  42. Do you remember first tying a shoe? • How did you do it? • How do you do it now?

  43. Is there any relationship among all these Decision Models?

  44. Dougherty et al’s (2003)Decision Making Space Each model relating memory and decision making • Describe fundamentally different memory processes! • Apply to fundamentally different types of decision situation! Framework • Familiarity of the decision situation • Level of effortful processing

  45. Decision Making processes and Memory Construction-Integration decision making • Explanation-based story Highly deliberative effortful processing within familiar situations • Rule-based Highly deliberative effortful processing within novel situations. Novice reliant on rule-based decisions. Instance-based routine decision making • Instance-based pattern-recognition Nondeliberative, automatic (out of awareness) within familiar situations. Expertise reliant on pattern-recognition. • Heuristic-based Nondeliberative effortless processing in less familiar situations.

  46. very familiar Primed pattern recognition theory of Automaticity Exemplar-based Story model Explanation-based Familiarity of decision situation Fast Frugal Heuristics Rule-based novel deliberative nondeliberative Amount of effortful processing

  47. Questions ???? No answers at present? Where do gists fit into this framework?Gists are not specific verbatim exemplarsWhen are gists used rather than a specific exemplar? One answer: depends upon the taskSpecific exemplars only used when the task requires it! Gist comparison is easier! Other theories: Dual process model (Jacoby, 1991) assume separate processes for recall (know/recollection) & recognition (familiarity). What is the implication for decision making? Recognition (non-declarative): is familiarity equivalent to pattern recognition? – may be intrusions errors (false positive) Recall (declarative): active search of memory? We can recognise more items than we can recall (exclusion error false negative) from a memorised list but intrusion errors.

  48. Newell (1990) • In 40 years of research I have estimated that there are 3,000 quantitative regularities that are important in understanding human cognition. It takes 10 good experiments to establish a regularity that adds to the body of knowledge now available. How do these regularities integrate into some sort of theory? Unless this is done we are going to be overwhelmed by microtheories. We need a framework to keep these regularities useful.

  49. Doughery et al’s (2003) theory of memory and decision space provides a framework of familiarity and degree of effortful processing. Rettinger & Hastie (2003) take a different approach and look at how the actual content of the decision affects decision outcomes. What is needed is to combine these 2 approaches. How do different memory processes (Doughery et al) interact with decision content (Rettinger & Hastie) ? What is the structure of memory and how does this influence the interaction between memory processes & decision making processes? There is a great deal more to find out!

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