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Chapter 8.doc

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University of Toronto St. George
Ashley Waggoner Denton

Chapter 8- Thinking and Intelligence • German psychologist Gerd Gigerenzer proposed that low- probability events that are highly publicized and have serious consequences (9/11 hijackings) result in fears called dread risks, which can profoundly affect reasoning and decision making Cognition: Mental activity such as thinking or representing information • Analogical representation: a mental representation that has some of the physical characteristics of an object, it is analogous to the object Ex: actual image of a violin, maps, etc. • Symbolic representation: an abstract mental representation that does not correspond to the physical features of an object or idea Ex: VIOLIN Mental images are analogical representations • Think of lemon- yellow, waxy skin • “R” study- R rotated, presented in different positions- participants asked if image was normal orientation or mirror image • Participants developed mental images of the objects and rotated these images to view objects in their upright position. The farther object was rotated from the upright position, the longer the discrimination took. • Same brain areas activated when you visualize something as when you first saw that image (Kosslyn et al) Limit of analogical representations • If something cannot be perceived wholly by our perceptual system, we cannot form a complete analogical representation of it Ex: visualize map of Africa’s contours even though we’ve never seen actual contours (thus, mental maps= combination of analogical and symbolic representations) • Symbolic representations can lead to errors, b/c we can represent only a limited range of knowledge analogically and thus use memory shortcuts unconsciously (ex: San Diego more east than Jasper) Concepts are symbolic representations • Categorization: grouping object into categories according to the object’s shared properties (violin, guitar musical instruments) • Concept: mental representation that groups or categorizes objects, events, relations around common themes (violins have 4 strings, guitars have 6) • Ensures that we don’t have to store every instance of an object individually Defining attribute model of concepts • Each concept is characterized by a list of features that are necessary to determine if an object is a member of the category Ex: bachelor= male, unmarried • Suggests that membership within category all or none basis, however we often make exceptions, along members into groups even if they don’t have the attributes Ex: all birds fly (still consider penguins birds) • Suggests that all attributes equally weighted however, often not the case Ex: birds (wings, warm blooded wings what comes to mind first, more weight) • Considers all members of category equal, no item better fit than any other Ex: 16 year old boy= bachelor, 25 year old man= bachelor Prototype model of concepts • Some items within a group or class are more representative or prototypical of that category than are other items within that group or class • Pick best example for that category (animal dog, hero superman) • Problem: particular prototype can be chosen for different reasons, also influenced by culture/life experiences Exemplar model • All examples of category members form the concept • Our representation of dog made up of all dogs we’ve seen in our life, no single representation of a concept • Account for the observation that some category members more prototypical than others- prototypes= members we have encountered more often Schemas organize useful info about environments • We develop schemas about the different types of real-life situations we encounter, know what behaviours appropriate for different social contexts Ex: Ok to squeeze into a black jack table, not OK to squeeze into stranger’s dinner at restaurant • Roger Schank & Robert Abelson- schemas about the sequences of events in certain situations= scripts (ex: script to go to movies) • Scripts dictate appropriate behaviour, what we view as appropriate shaped by culture • Relational schemas: influence what people expect from others in their social interactions (expect guy to pay on a date) Why schemas work? • Common situations have consistent attributes • People have specific roles within situational contexts • Adaptive value- minimize amounts of attention required to navigate familiar enviros • Problem: schemas and scripts, like prototypes sometime have unintended consequences, such as reinforcing sexist or racist beliefs • Ex: gender roles type of schemas that operates at unconscious level- orchestra gender difference Reasoning: using information to determine if a conclusion is valid or reasonable Decision making: attempting to select the best alternative among several options Problem solving: finding a way around an obstacle to reach a goal Deductive reasoning • Using a belief or rule to determine if a conclusion is valid, reason from general to specific • Use logic to draw specific conclusions under certain assumptions or premises however, conclusion may or may not be true • Ex: Bonnie tells you new Thai food restaurant is good, you like Thai food, you decide to try it • Deductive reasoning tasks often presented as syllogisms (logical arguments containing statements and a conclusion) • Conditional syllogism: “if A is true, then B is true” (Bonnie has good taste, therefore restaurant must be good) • Categorical syllogism: logical argument contains 2 premises and a conclusion, which can be determined to be either valid or invalid Ex: all people from Vancouver= friendly, some friendly people like Thai food, all Vancouver people like Thai Food (invalid conclusion) Ex: All chimps are primates, all primates are mammals, all chimps are mammals (valid conclusion) Inductive Reasoning • Using examples or instances to determine if a rule or conclusion is likely to be true, reasoning from specific to general • Determining general principles form specific instances ex: friend shows up late numerous times, induce general conclusion that friend is usually tardy • Use of scientific method to discover general principles Ex: students who join clubs higher GPA, using researchers inducing general principle from specific instances of the students in the experiment • We are often strongly influenced by anecdotal reports (a close friend’s experience) vs. listening to a general consensus of strangers Normative models of decision making: view humans as optimal decision makers, who usually select choices that yield the largest gains • Expected Utility Theory- von Neumann & Morgenstern • Decision making based on utility, the value of each possible outcome • We make decisions after evaluating all possible alternatives, pick most desirable one Descriptive models of decision making: account for human’s tendencies to misinterpret and misrepresent the probabilities underlying many decision making scenarios and to act irrationally even though they know the probabilities • Heuristics- Amos Tversky & Dnaiel Kahneman • Mental shortcuts or rules of thumb people typically use to make decisions • Different than an algorithm which will always lead you to correct answer • Require minimal cognitive reasoning, allows us to focus attention elsewhere Ex: buy the second-cheapest item, buy brand names, higher price= higher quality Availability heuristic: making decision based on answer that most easily comes to mind Ex: more farmers or librarians? Think or people you know know more librarians ∴ ↑ librarians (reality they’re more farmers) Representativeness heuristic: base decision based on extent to which each option reflect what we already believe about a situation Ex: person who enjoys math, working with ppl, gardening psych or postal worker? • Most people think psych, even if base rate suggests that there are more postal workers therefore chances are higher she is a postal worker Framing effects: the effect of presentation on how info is perceived • Framing decisions differently (highlighting gains or losses) affects decision making • Prospect theory: Kahneman &Tversky 1. Need to take into account a person’s wealth in predicting choices Ex: win 200$ guarantee, or 20% chance of winning 1000$  rich person more likely to gamble vs. poor student 2. Losses feel worse than gains, ∴ people try to avoid losses • Loss aversion: potential losses affect decision making more than potential gains do • Affective forecasting: people do poor at forecasting/ predicating future feelings • can influence our perception of positive events • Medvec et al.  bronze medal winners happier than those who won silver • Kawakami et al may also be involved in racism • Those who believe that they would take action and condemn racist behaviours respond with indifference when they actually confront these acts • Good decision makers lead better lives! (Bruine de Bruin, Parker, Fischoff) • Participants who performed better on decision making tests repo
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