What Good Is Thinking, Anyway?

CHAPTER OUTLINE

I.BASIC FUNCTIONS OF THOUGHT

What good is thinking, anyway?

A.The Circle of Thought

1.The main functions of human thinkingare to describe, elaborate, decide, plan, and guide action. Each stage in the circle of thought is also influenced by intention.

2.An information-processing system receives information, represents it with symbols, and then manipulates those symbols. Thinking is defined as the manipulation of mental representations.

3.Information is somewhat transformed as it passes through each stage of processing and sometimes leads to new information.

II.MENTAL REPRESENTATIONS: THE INGREDIENTS OF THOUGHT

What are thoughts made of?

The ingredients of thought are called information. It can be mentally represented in many forms, including concepts, propositions, concept schemas and event scripts, mental models, images, and cognitive maps.

A.Concepts

1.Concepts are categories of objects, events, or ideas with common properties. “To have a concept” is to recognize the properties, or features, that tend to be shared by members of a category.

2.Concepts allow you to relate each object or event to a category that you already know and make logical thinking possible.

3.Types of Concepts

a)Formal concepts clearly define objects or events by a set of rules and properties, such that each member of the concept has all of the defining properties and no nonmember does. For example, “squares” are defined as “two-dimensional objects with four equal sides and four internal 90-degree angles.” All squares fit this rule, and no nonsquares fit this rule.

b)Natural concepts have a set of typical or characteristic features, and members don’t have to have all of them. For example, “home” is a concept that often includes characteristics like “house,” “family lives there,” “nice place,” “familiar,” and so on.

(1)Most of the concepts people use in thinking are natural rather than formal concepts.

(2)Some members of a natural concept are better examples than others. A member that possesses all or most of the concept’s characteristic features is called a prototype. For example, a “robin” is a prototype for “bird.”

B.Propositions

1.Propositions are mental representations that express relationships between concepts. They can be true or false.

C.Schemas, Scripts, and Mental Models

1.Sets of propositions are often so closely associated that they form more complex mental representations called schemas, generalizations we develop about categories of objects, places, events, and people from experience with the world. Schemas help us to understand the world and shape our expectations and interpretation of events.

2.Scripts are schemas about the sequences in which events and activities typically occur. For example, consider this sentence: “He stormed out the door, leaving a meager tip next to a plate of mostly untouched chili.” Your scripts of restaurants allow you to predict a whole sequence of activities that probably just occurred—a customer entered a restaurant, ordered chili, disliked the food or the service, and so on.

3.A mental model clusters many propositions together to help you understand how things work. When mental models are incorrect, people are likely to make mistakes.

For example,your mental model of a car may include propositions such as “The key goes in the ignition” and “Pushing the gas pedal makes the car move.”

D.Images and Cognitive Maps

1.Images are mental representations of visual information. Manipulations performed on images of objects are very similar to those that would be performed on the objects themselves. We create mental images that serve as mental models of descriptions we hear or read.

2.As people move around an environment, they build cognitive maps, mental models of familiar parts of their world. Visual experience is useful, but not necessary, for building cognitive maps. Blind people can use cognitive maps. The general experience of moving through space is enough to allow you to represent information.

III.THINKING STRATEGIES

Do people always think logically?

Reasoning is the process through which we generate and evaluate arguments as well as reach conclusions about them.

A.Formal Reasoning

Formal reasoning (also called logical reasoning) is the process of following a set of rigorous steps for reaching valid, or correct, conclusions.

a)Algorithms are systematic methods that always reach a correct solution to a problem, if a correct solution exists.

Example: If you lost your keys sometime between your first class and lunch, an algorithmic approach might be to retrace your every step for the entire morning.

b)Rules of logicare a set of statements that provide a formula for drawing valid conclusions about the world.

(1)Deductive reasoning takes a general rule and applies it to deduce conclusions about specific cases. It is often an “if-then” proposition.

(2)While most of us try to be logical, we often base our reasoning on false assumptions or use faulty logic, which lead to errors in reasoning.

B.Informal Reasoning

1.Informal reasoning occurs when we are trying to assess the believability of a conclusion based on the evidence available to support it. Itis also known as inductive reasoning, because its goal is to induce a general conclusion to appear on the basis of specific facts or examples. Jurors use this when weighing evidence for the guilt or innocence of a defendant.

2.Heuristics are mental shortcuts or rules of thumb that are easy to use and frequently work well. But they can bias thinking and cause errors.

Example: In the lost keys example, a heuristic approach might focus only on the most likely places the keys could have been set down.

a)In the anchoring bias (anchoring heuristic), you estimate an event’s likelihood not by starting from scratch but by adjusting an existing estimate. Thus first impressions are not easily displaced by later evidence. For example, you think that your chance of getting mugged in Los Angeles is 90 percent, but then you see evidence that the chance is closer to 1 percent. You will adjust your estimate, but it is likely to be biased toward your initial estimate.

b)The representativeness heuristic leads you to conclude that something belongs to a certain class based on how similar it is to other items in that class. For example, when you think of a kidnapper, your image is of a stranger. In reality, over 90 percent of all kidnappers are parents who are abducting their own children in defiance of court-decided custody arrangements.

c)The availability heuristic is when you judge the likelihood of an event or the correctness of a hypothesis by how easy it is to think of that event or hypothesis. For example, if you have had trouble with your car battery, when the car fails to start you may decide that the battery is the cause, even though the electrical system is operating and your gas gauge points to E.

IV.PROBLEM SOLVING

What's the best way to solve a problem?

A.Strategies for Problem Solving

1.Incubation involves putting a difficult problem aside to come back to later. Later, while engaged in unrelated activity, a solution may suddenly occur to you. The solution occurs mainly because you forget incorrect ideas that had blocked your progress.

2.Means-end analysis, also referred to as decomposition, is the strategy of continuously asking where you are in relation to your final goal and then deciding on the means by which you can get one step closer to that goal. In other words, you break a large problem into smaller, more manageable subgoals. For example, when writing a paper, the task can be broken into subgoals, such as writing the outline, meeting the criteria, researching, writing a rough draft, and so on.

3.Planning strategy by working backward from the end goal is often effective. This helps avoid getting sidetracked with dead-end choices en route to a goal.

Example: To plan a surprise party, you may first think of where and when the honoree will be arriving, then decide on where and when guests should arrive, then think about whom to invite, and so on.

4.Analogies, or similarities, between current and past problems may help you find solutions that have worked before. People are not very good at seeing the similarities between new and old problems, because they focus on the surface features.

B.Focus on Research: Problem-Solving Strategies in the Real World

It is difficult to know if the problem-solving strategies that subjects show in the laboratory are typical of “real-world” problem solving. One way to address this issue is to reconstruct problem-solving strategies associated with major inventions and scientific discoveries.

1.What was the researcher's question?

How did the Wright brothers solve the problem of creating a heavier-than-air flying machine when so many others had failed?

2.How did the researcher answer the question?

Gary Bradshaw consulted records from all the teams or individuals who worked on heavier-than-air flying machines and did a comparative case study.

3.What did the researcher find?

Bradshaw found several factors that might have contributed to the Wright brothers’ success: lots of available time, familiarity with lightweight construction methods, a good working relationship, and good manual dexterity. However, the unsuccessful teams shared many of these features as well. The Wright brothers had one feature that all the others lacked: They spent a lot of time testing the components of their machines before field-testing a completed machine.

4.What do the results mean?

The problem-solving strategy of decomposition was the basis for the Wright brothers’ success.

5.What do we still need to know?

We need to know if decomposition is used in other real-world settings.

C.Obstacles to Problem Solving

1.Multiple Hypotheses

Due to limited working memory, it is hard to consider multiple hypothesesat once. Thus the correct hypothesis may be neglected if other hypotheses are easier to think of (the availability heuristic). For example, several factors could explain why you are failing chemistry—erratic attendance, poor note-taking, inadequate reading, low motivation, or a bad teacher. You may choose one of those factors and disregard the others (e.g., a bad teacher, thereby doing nothing about attendance, reading, note-taking, or motivation).

2.Mental Sets

a)A mental setis the tendency for old problem-solving patterns to persist rather than viewing each problem freshly (anchoring heuristic).

b)Functional fixednessis a tendency to use familiar objects in familiar rather than creative ways. For example, if you run out of sugar for a cookie recipe, you may not think of using honey to serve the same function as the sugar.

3.Ignoring Negative Evidence

Ignoring negative evidence is the tendency to ignore the absence of supporting evidence for your hypothesis. For example, you may attribute your abdominal pain to appendicitis. A fever would help confirm the diagnosis, but you may focus on the pain and ignore the fact that you actually lack a fever.

4.Confirmation Bias

The confirmation bias is the tendency to confirm rather than to refute your own ideas, even if strong evidence argues against you. This bias is a kind of anchoring heuristic—a reluctance to abandon an early hypothesis.For example, you may decide your teacher is at fault for your failing chemistry grade, ignoring the facts that you may also be failing other classes, your teacher has won teaching awards, and your teacher sets up special times to help you.

D.Problem Solving by Computer

1.Artificial intelligence (AI) is a field seeking to develop computers that imitate the processes of human perception and thought.

2.Symbolic Reasoning and Computer Logic

a)Computers excel at using logical, syllogistic reasoning. However, most AI systems are successful only in narrowly defined fields.

b)Computers rely heavily on “if-then” rules. This is a problem because computers have difficulty recognizing the “if” condition in the real world.

3.Neural Network Models

a)Recognizing the problems posed by the need to teach computers to form natural concepts, many researchers in AI have moved toward the connectionist, or neural network, approach.

(1)This approach uses computers to simulate the information processing taking place at many different but interconnected locations in the brain.

(2)Computerized expert systems can now perform as well as and sometimes better than humans at solving complex problems in medical diagnosis and business decision making.

(3)However, most computer models of neural networks still fall well short of the capacities of the human perceptual system. Probably the optimal approach will be to have humans and computers work together in ways to achieve a better outcome than either could alone.

E.Creative Thinking

1.People demonstrate creativity by producing original but useful solutions to all sorts of challenges.

2.One test of creativity measures divergent thinking, the ability to think along many paths to generate multiple solutions to a problem.

3.To be productive, a creative person must be anchored in reality, understand society’s needs, and learn from the experience and knowledge of others.

4.Three kinds of cognitive and personality characteristics are necessary for creativity.

a)Expertise in the field of endeavor, which is directly tied to what a person has learned.

b)A set of creative skills, including persistence at problem solving, capacity for divergent thinking, ability to break out of old problem-solving habits (mental sets), and willingness to take risks.

c)The motivation to pursue creative work for internal reasons, such as satisfaction, rather than for external reasons, such as prize money.

5.Creativity is influenced by genetic, social, economic, and political factors.

6.The correlations between intelligence test scores and creativity are modest. Scores on most intelligence tests require convergent thinking, using logic and knowledge to narrow down the number of possible solutions to a problem.

7.Researchers have defined wisdom as the combination of intelligence and creativity.

V.DECISION MAKING

How can I become a better decision maker?

Decisions made when the outcome is uncertain are termed risky decisions or decisions under uncertainty.

A.Evaluating Options

1.Decision making ofteninvolves selecting from choices with several positive and negative features. Utility is the subjective, personal positive or negative value of a feature.

2.The best decision maximizes expected value, the average benefit predicted if you could repeat the decision many times.

B.Biases and Flaws in Decision Making

1.Gains, Losses, and Probabilities

a)People feel worse about losing a certain amount than about gaining that same amount, a phenomenon called loss aversion. For example, a person who sells a stock just before its value falls might avoid a $200 loss, which may be perceived more favorably than receiving a $200 gift from his or her parents.

b)The utility of a specific gain depends on your starting point. For example, if you already have $5,000, a summer job paying $1,000 will not seem as positive as if you had started with $500.

c)People have problems estimating probability. People tend to overestimate rare events and underestimate frequent ones. For example, lottery players typically overestimate their chances of winning.

(1)The availability heuristic, vivid memories of successes at rare events, explains the tendency to overestimate rare events.

(2)The gambler’s fallacy is the belief that the probability of future events in a random process will change depending on past events. For example, if you see “heads” on five straight coin tosses, the gambler’s fallacy predicts that the sixth coin flip is more likely to be “tails.”

d)People tend to be unrealistically confident about the accuracy of their predictions.

2.How Biased Are We?

a)It is often hard to assess how “good” or “bad” a decision is because such outcomes depend on the personal and cultural values of the individual.

VI.LINKAGES: GROUP PROCESSES IN PROBLEM SOLVING AND DECISION MAKING

Group discussions follow very typical patterns.

A.Views that are shared by the greatest number of group members will have the greatest impact on the group’s final decision.

B.Group polarizationoccurs if the group’s decision ends up being more extreme than the average group member would have chosen alone. Two mechanisms underlie this.

1.Most arguments in group discussions tend to favor the majority’s view, and most criticisms tend to attack minority views. Thus those favoring majority views tend to adopt even stronger versions of it.

2.As a group begins to agree on a “desirable” decision, members may try to associate themselves with it, perhaps by suggesting even more extreme versions.

C.Are people better at problem solving and decision making when they work in groups than when on their own?

1.When correct solutions can be easily demonstrated to everyone, groups usually outperform individuals at solving problems.

2.When the solution is less clear-cut, groups may do no better than their most talented member.