Sources of Power: How People Make Decisions

Sources of Power: How People Make Decisions Gary Klein Front Matter
  • Here I document human strengths and capabilities that typically have been downplayed or even ignored.
  • naturalistic decision making-that is, the study of how people use their experience to make decisions in field settings.
  • We try to understand how people handle all of the typical confusions and pressures of their environments, ronments, such as missing information, time constraints, vague goals, and changing conditions.'
  • The conventional sources of power include deductive logical thinking, analysis of probabilities, and statistical methods.3 Yet the sources of power that are needed in natural settings are usually not analytical at all-the power of intuition, mental simulation, metaphor, phor, and storytelling.
  • Features that help define a naturalistic decision-making setting are time pressure, high stakes, experienced decision makers, inadequate information (information tion that is missing, ambiguous, or erroneous), ill-defined goals, poorly defined procedures, cue learning, context (e.g., higher-level goals, stress), dynamic conditions, and team coordination (Orasanu and Connolly 1993).
  • We are interested in tasks where the goals are unclear.
  • Naturalistic decision making is concerned with poorly defined procedures. dures. Conventional laboratory studies, in contrast, prefer to keep decision sion making distinct from problem solving and do not require subjects to invent or modify procedures.
  • Cue learning refers to the need to perceive patterns and make distinctions.
  • Dynamic conditions (that is, a changing situation) are an important feature of naturalistic decision making.
  • Rarely do we find a single decision maker, such as a chess player, who does not have to coordinate with anyone else.
  • Uncertainties may be associated with missing, incomplete, or ambiguous information, mation, or with future outcomes that are unknown.
  • Rational choice strategy.
    1. Identifies the set of options.
    2. Identifies the ways of evaluating these options.
    3. Weights each evaluation dimension.
    4. Does the rating.
    5. Picks the option with the highest score.
  • The commanders did not consider two. In fact, they did not seem to be comparing any options at all.
  • "I don't make decisions," he announced to his startled listeners. "I don't remember when I've ever made a decision."
  • He agreed that there were options, yet it was usually obvious what to do in any given situation.
  • Analogies. We expected to see a heavy use of analogous cases. We found very little. Never was there an entire fire that reminded a commander of a previous one.
  • People who are good at what they do relish the chance to explain it to an appreciative audience.
  • nonroutine and had demanded special experience.
  • The commander did not seem to be making any decisions at all if a decision results from actively comparing two or more options in a process of comparative evaluation.
  • Singular evaluation means evaluating each option on its own merits, even if we cycle through several possibilities.
  • Simon (1957) identified a decision strategy he calls satisficing: selecting the first option that works. Satisficing is different from optimizing, which means trying to come up with the best strategy.
  • The singular evaluation strategy is based on satisficing.
  • Our model of recognitional decision making was starting to fit together. The experienced fireground commanders could judge a situation as prototypical totypical and know what to do.' If their first choice did not work out, they might consider others-not to find the best but to find the first one that works.
  • Fireground ground commanders use the power of mental simulation, running the action through in their minds.
  • Before we did this study, we believed that novices impulsively jumped at the first option they could think of, whereas experts carefully deliberated erated about the merits of different courses of action.
  • Now it seemed that it was the experts who could generate a single course of action, while novices needed to compare different approaches.
  • there are times for deliberating about options. Usually these are times when experience is inadequate and logical thinking is a substitute for recognizing a situation as typical.
  • Deliberating about options makes a lot of sense for novices, who have to think their way through the
  • By recognizing a situation as typical, they also recognize a course of action likely to succeed.
  • the decision makers do not start with the goals or expectancies and figure out the nature of the situation.
  • Janis and Mann are an example of the rational choice strategy that we had encountered: define the evaluation dimensions, weight each one, rate each option on each dimension, multiply the weightings, total up the scores, and determine the best option-that is, unless you do not have all the data you need.
  • There are advantages to the rational choice strategy:• It should result in reliable decisions (that is, the same result each time for the same analysis).• It is quantitative.• It helps novices determine what they do not know.• It is rigorous; it does not leave anything out.• It is a general strategy, which could apply in all sorts of situations.
  • For many tasks, we are novices, and the rational choice method helps us when we lack the expertise to recognize situations.
  • we do not make someone an expert through training in formal methods of analysis.
  • If the purpose is to train people in time-pressured decision making, we might require that the trainee make rapid responses rather than ponder all the implications.
  • we should be able to improve the trainee's ability to detect familiar iar patterns.
  • the goal is to show many common cases to facilitate a recognition of typicality along with different types of rare cases so trainees will be prepared for these as well.
  • Decision makers usually look for the first workable option they can find, not the best option.
  • They generate and evaluate options one at a time and do not bother comparing the advantages and disadvantages of alternatives.
  • By imagining the option being carried out, they can spot weaknesses and find ways to avoid these, thereby making the option stronger.
  • The emphasis is on being poised to act rather than being paralyzed until all the evaluations have been completed.
  • Intuition depends on the use of experience to recognize key patterns that indicate the dynamics of the situation. Because patterns can be subtle, people often cannot describe what they noticed, or how they judged a situation as typical or atypical. Therefore, intuition has a strange reputation.
  • My claim in this chapter is that intuition grows out of experience.
  • Wilson and Schooler (1991) shows that people do worse at some decision tasks when they are asked to perform analyses of the reasons for their preferences or to evaluate all the attributes of the choices.
  • use their experience to notice anomalies.
  • Perhaps such instances are difficult to articulate because they depend on a deviation from a pattern rather than the recognition of a prototype.
  • expertise that the person clearly has but cannot describe.
  • cues and patterns
  • not relying on any single cue.
  • often reacted to a pattern of cues,
  • If you want people to size up situations quickly and accurately, you need to expand their experience base. One way is to arrange for a person to receive more difficult cases.
  • training program, perhaps with exercises and realistic scenarios,
  • A good simulation can sometimes provide more training value than direct experience.
  • Another training strategy is to compile stories of difficult cases and make these the training materials.
  • embedded the cues in the stories themselves so that the nurses could see how the cue appeared in context.
  • rapid pattern-matching exercises
  • pattern matching seemed more useful than lessons on formal analysis of alternate options.
  • a heuristic strategy decision researchers call mental simulation, that is, the ability to imagine people and objects consciously and to
  • transform those people and objects through several transitions, finally picturing them in a different way than at the start.
  • Mental simulation about the past can be used to explain the present. It can also be used for predicting dicting the future from the present.
  • the mental simulations were not very elaborate.
  • result of limited working memory.
  • chunk several transitions into one unit.
  • save memory space by treating a sequence of steps as one unit rather than representing all the steps.
  • Another strategy for overcoming memory limits is to write things down and draw diagrams to keep track of the transitions.
  • without a sufficient amount of expertise and background knowledge, edge, it may be difficult or impossible to build a mental simulation.
  • Models
  • coherence
  • applicability
  • completeness
  • Projecting
  • So we use intuition to form an emotional reaction of optimism or worry. In his research with chess masters, Adriaan de Groot found that they frequently formed these global impressions of whether a line of play was going to work, even before they studied the sequence.
  • Finally, you can use mental simulation to prepare for carrying out a course of action, by rehearsing what you are going to do.
  • You assemble the action sequence of what is going to change from one state to the next. Then you evaluate this sequence.
  • Perrow (1984)
  • de minimus explanations-explanations that try to minimize the inconsistency.3 The operator forms an explanation tion and then proceeds to explain away disconfirming evidence.
  • One reason for problems such as de minimus explanations that discard disconfirming evidence is that once we have built a mental simulation, we tend to fall in love with it.
  • Mental simulation takes effort. Using it is different from looking at a situation and knowing what is happening. Mental simulation is needed when you are not sure what is happening so you have to puzzle it out. When you are pressed for time, you may not do as careful a job in building ing or inspecting the mental simulations
  • A final shortcoming is that we have trouble constructing mental simulations lations when the pieces of the puzzle get too complicated-there are too many parts, and these parts interact with each other.
  • Despite these limitations, mental simulation allows us to make decisions sions skillfully and solve problems under conditions where traditional decision analytic strategies do not apply.
  • until we have an alternate mental simulation, we will keep patching the original one.
  • The problem is that we lose track of how much contrary evidence we have explained away so the usual alarms do not go off. This has also been called the garden path fallacy: lacy: taking one step that seems very straightforward, and then another, and each step makes so much sense that you do not notice how far you are getting from the main road.

  • the premortem mortem strategy

  • We hypothesized that people may feel too confident once they have arrived at a plan, especially cially if they are not highly experienced.
  • Our exercise is to ask planners to imagine that it is months into the future and that their plan has been carried out. And it has failed.
  • We have tested this premortem method, and it seems to reduce confidence in the original plan, as we expected.
  • Decision scenarios, in contrast, were built to describe the forces that were operating so the executives could use their own judgment.
  • expectancy bias, in which a person sees what he is expecting to see, even when it departs from the actual stimulus.
  • subjects jects cannot be trusted to make accurate identifications because their expectancies get in the way.
  • decision biases.
  • Situation awareness can be formed rapidly, through intuitive matching of features, or deliberately, through mental simulation.
  • comparative rather than a singular evaluation of options.
  • we will be more likely to compare options when faced with unfamiliar situations.
  • lack of experience rience will prevent us from generating reasonable options, recognitional ognitional decision making is a common strategy and that comparing options is fairly infrequent.
  • To summarize, the RPD model was developed on the basis of field studies of the way that experienced personnel actually make decisions. The model explains how people can use experience to react rapidly and make good decisions without having to contrast options. The model has been tested and has been supported by different research teams working in a variety of settings.
  • The standard advice for making better decisions is to identify all the relevant options, define all the important evaluation criteria, weight the importance of each evaluation criterion, evaluate each option Bookmark - Page 102
  • on each criterion, tabulate the results, and select the winner.
  • the rigorous, analytical lytical approach cannot be used in most natural settings.
  • recognitional strategies that take advantage of experience are generally successful, not as a substitute for the analytical methods, but as an improvement provement on them.
  • analytical methods may be helpful for people who lack experience.
  • the closer together the advantages and disadvantages of competing options, the harder it will be to make a decision but the less it will matter.5
  • if we cannot teach people to think like experts, perhaps we can teach them to learn like experts. After reviewing the literature, I identified a number of ways that experts in different fields learn Klein (1997):
  • They engage in deliberate practice, so that each
  • opportunity for practice tice has a goal and evaluation criteria.
  • They compile an extensive experience bank.• They obtain feedback that is accurate, diagnostic, and reasonably timely.• They enrich their experiences by reviewing prior experiences to derive new insights and lessons from mistakes.

  • deliberate practice.

  • articulate goals and identify the types of judgment and decision skills they need to improve.
  • The experiences need to include feedback that is accurate, diagnostic, and timely.'
  • mere accumulation of experience does not appear to result in growth of decision expertise.
  • opportunity to reflect on experiences.
  • But afterward, there is time to go over the game record to look for opportunities that were missed, early signals that were not noticed, or assessments and assumptions that were incorrect.
  • developing the discipline of reviewing the decision-making processes for each incident can be valuable.
  • the decision requirements let the squad leaders identify their own needs, for their own missions, and let them discover ways to engage in deliberate practice and obtain feedback for their judgments and decisions.
  • Tactical decision games are low-fidelity, paper-and-pencil simulations of incidents that might occur in the field decision requirements
  • This includes the decisions that are required by the task, as well as the cues, information, and strategies required to make the decisions.
  • leverage points-a small difference that makes a large difference, ence, a small change that can turn a situation around-to
  • Skillful problem solving is impresive because after the fact, the solution seems obvious, yet we know that, without any guidance, most people would miss the answer.
  • identify leverage points as opportunities where a need existed and the technology had become sufficiently mature.
  • Unless they had a sense of how the problem could be solved, they did not get engaged.
  • Leverage points are just possibilities-pressure points that might lead to something useful, or might go nowhere.
  • Leverage points provide fragmentary action sequences, kernel ideas, and procedures for formulating a solution.
  • leverage points that can work against us, in order to learn the weaknesses in our plans. These are sometimes called choke points.
  • To solve ill-defined problems, we need to add to our understanding of the goal at the same time we generate and evaluate courses of action to accomplish it.
  • Failures, when properly analyzed, are sources of new understanding about the goal.
  • We can think of problem solving as consisting sisting of four processes: problem detection, problem representation, option generation, and evaluation
  • The goals determine how we assess the situation, and the things we learn about the situation change the nature of the goals. Goals define the barriers and leverage points we search for, and the discovery of barriers and leverage points alters the goals themselves.
  • The problem representation function covers the way a person identifies and represents the problem.3
  • Both gaps and opportunities can trigger problem-solving efforts, either to remove the gap (and obtain what you want) or to harvest vest the opportunity.
  • ill-defined goals, we can expect to see a lot of goal modification during the problem-solving effort.5
  • We have to balance between looking for ways to reach goals and looking for opportunities that will reshape the goals.
  • The concept of problem solving appears incomplete without the aspect of discovering opportunities.
  • De Groot (1945) and Isenberg (1984) have suggested that what triggers active problem solving is the ability to recognize when a goal is reachable.
  • We do not investigate problem-finding skills in studies where we present subjects with a problem or puzzle that is ready made.
  • a generic four-stage model that comes reasonably close to these varieties: 1. Define the problem. 2. Generate a course of action. 3. Evaluate the course of action. 4. Carry out the course of action.
  • Most natural goals seem to be ill defined.
  • Most of the studies of problem solving and decision making have centered tered on well-defined goals-solving mathematical equations, physics problems, or syllogisms in deductive logic, for example.
  • Problems can be unstructured in several ways, not just through vague goals.
  • a problem can be ill structured if the initial state is not defined, the terminal state is undefined, or the
  • procedure for transforming the initial state into the terminal state is undefined.
  • the focus of problem solving can be very different depending on the nature of the problem.
  • In 1972, Allen Newell and Herbert Simon published Human Problem Solving, describing their success in writing computer programs that could emulate human thought processes for tasks such as chess and puzzles.
  • The potential for this work is limited because artificial cial intelligence is primarily about well-defined problems.
  • the idea of a problem space does not match anything we know of experience about human problem solving.
  • For situations that are more complex or less precise, we would usually not try to lay out the problem space of objects, relations, tions, and properties.
  • the idea of searching through a problem space misses the experience rience we have of noticing things we had not considered before, and discovering covering or synthesizing a new approach.
  • in solving problems we do not reformulate goals merely by removing constraints.
  • they did not require a standard sequence of steps,
  • Forming an accurate problem representation was the most common activity for this incident.
  • Some prefer to treat problem solving as a subclass of decision making
  • Some prefer to see decision making as a subclass of problem solving
  • In order to define problems and generate novel courses of action, we need to draw on our experience to make judgments about:
      • Reasonable goals and their attributes. • The appearance of an anomaly. • The urgency of solving a problem (whether to take anomalies seriously or treat them as transients that will go away). • What constitutes an opportunity worth pursuing. • Which analogues best fit the situation, and how to apply them. • The solvability of a problem.
  • two primary sources of power for individual decision making and problem solving:
      • Pattern matching (the power of intuition). • Mental simulation.
  • My skepticism about rational problem-solving methods is that they do not prepare you to improvise, act without all of the relevant information, or cope with unreliable liable data or shifting conditions. They do not prepare you to learn about the goals throughout the problem-solving process.
  • brainstorming, a method that has been around for decades, seems primarily a social activity. If the participants ipants generate
  • their ideas individually, the resulting set of suggestions is usually longer and more varied than when everyone works together. Mullen, Johnson, and Salas (1991) have documented the finding that brainstorming reduces productivity.
  • A rapidly changing environment ment favored modular plans because these permitted rapid improvisation.
  • Mintzberg (1994) has written a comprehensive account of the failures of strategic planning and of its inherent limitations.
  • To solve an ill-defined problem, we have to clarify the goal even as we are trying to achieve it, rather than keeping the goal constant.
  • Often experts do not realize that the rest of us are unable to detect what seems obvious to them.
  • Novices have difficulty seeing relationships that are obvious to experts.
  • Novices are confused by much that happens to them because they have so much trouble forming expectancies. They keep encountering events they did not anticipate. As they begin to form expectancies, they also begin to get surprised each time an expectancy
  • One critical type of cue that surprises experts, but not novices, is the absence of a key event.
  • In the recognition-primed decision model, proficient decision makers are described as being able to detect patterns and typicality. They can size up a situation in a glance and realize that they have seen it, or variants of it, dozens or hundreds of times before.
  • The opposite side of this coin is noticing when a pattern is broken or an expectancy is violated.
  • Experts see inside events and objects.
  • They have mental models of how tasks are supposed to be performed, teams are supposed to coordinate, equipment is supposed to function.
  • Since the experts have a mental model of the task, they know how the subtasks fit together and can adapt the way they perform individual subtasks tasks to blend in with the others.
  • As part of their mental model of the task, experts know various tricks of the trade, along with the conditions for using them.
  • leverage points may be visible to experts but invisible to novices.
  • ability of experts to generate counterfactuals: explanations and predictions that are inconsistent with the data.
  • Experienced decision makers appear to be able to spot opportunities where the information that can be helpful can be readily obtained.
  • Skilled decision makers may be able to seek information more effectively than novices. This skill in information seeking would result in a more efficient search for data that clarify the status of the situation.
  • In aviation, there is a term to describe people who are so wrapped up in what they are doing that they are insensitive to what lies ahead: flying behind the plane. It describes people who are either so novice or so overworked worked or have such poor situation awareness that they are not generating ing expectancies; they are not preparing themselves properly.

    time horizon

  • Jacobs and Jaques have suggested that as people move up the organizational ladder in industry, they need to look further ahead.
  • A president of a company who wants to make some change should be looking years out into the future.
  • The appropriate time horizon depends on the reaction time of the system at different levels.6
  • The ability to see the past and the future rests on an understanding of the primary causes in a domain and the ability to apply these causes to run mental simulations.
  • Another aspect of mental simulation is to be able to
  • decenter, to see the world through the eyes of others.
  • Experts can detect differences that novices cannot see, cannot even force themselves to see. Experts see inside their own thought processes-the process of metacognition, cognition, which means thinking about thinking.
  • Four components of metacognition seem most important: memory limitations, having the big picture, self-critiques, and strategy selection.8
  • Experts can critique themselves.
  • Experts also seem more likely to critique their judgments and their plans, since they can use their experience to see where the judgments might be wrong and their plans weak.
  • The point of this exercise is to show how much perceptual experience is needed to carry out tasks that may seem simple because they can be reduced to rules and procedures.
  • Rules tell you that when a certain condition occurs, initiate a certain action. The trick is knowing when the first condition has occurred. The recipe can state, "When it is brown on top, take it out of the oven," but brown on top is not so obvious. Brown on top stretches from "just starting to change color" all the way to "beginning to smoke."
  • Skilled decision makers can generate feasible courses of action as the first ones they consider, so there is no need to generate lots of options.
  • Expertise is learning how to perceive. The knowledge and rules are incidental.
  • Hubert Dreyfus and Stuart Dreyfus (1986) have described how people move from the level of novices to experts. They claim that novices follow rules, whereas the experts do not.
  • Cognitive task analysis is the description of the expertise needed to perform complex tasks.
  • locate sources of expertise (and acquire background knowledge in the process), evaluate the quality of the expertise, perform knowledge elicitation to get inside the head of the skilled decision makers, process the findings so they can be interpreted to others, and apply the findings.
  • These methods include structured interviews, interviews about actual events that were challenging, interviews about the concepts experts use to think about a task, and simulated tasks that require the expert to think aloud during performance or respond to interview questions after completion.
  • A good story is a package of different causal relationships-what factors tors resulted in what effects. It has to draw together different components clearly and memorably orably and show their connection.
  • Besides drama, empathy, and wisdom, good stories have a number of more mundane but still necessary features:
  • Plausibility. The elements are believable. We have to be able to accept each step and action, or should expect an explanation if elements do not seem plausible. These anomalies have to be explained away.2• Consistency. The elements fit with each other.• Economy. The range of details is complete without getting too inclusive.• Uniqueness. We prefer stories that are not open to alternate explanations.
  • There is a definite overlap between stories and mental simulation.
  • The major difference is that mental simulations are stories we run inside our head, where there is less room for complexity. Note - Page 183 stories create a vicarious experience from which one can learn how to do something better or at all if a scenario like that one or one analagous to it arrises. Seems blindingly obvious so i must be missing something.
  • We like to ask about hypotheticals. For instance, if a piece of information had not arrived, what would the person son have most likely done?
  • People use analogues and metaphors to perform a variety of difficult tasks: understanding situations, generating predictions, solving problems, anticipating events, designing equipment, and making plans. An analogue logue is an event or example drawn from the same or a related domain as the task at hand; a metaphor comes from a markedly different domain.
  • Metaphor does more than adorn our thinking. It structures our thinking. ing. It conditions our sympathies and emotional reactions.
  • Effective metaphors were the ones helping to organize action.
  • Amos Tversky (1977), who had proposed a method for defining similarity in terms of the number of elements two items shared in common.
  • The features in common had to be important portant ones.
  • Metaphors and analogues direct thinking by framing situation awareness, ness, identifying appropriate goals, and flagging relevant pieces of information.• Analogues provide a structure for making predictions when there are many unknown factors.• Analogues function like
  • experiments, linking interactive sets of causes to outcomes.• By taking into account the difference between the analogue and the current case, we can adjust the analogue data to derive a prediction.• Analogical predictions are most helpful when there is a good database but not enough information to apply more rigorous analyses.• Analogues are useful for generating expectancies and solving problems.
  • When you communicate intent, you are letting the other team members operate more independently and improvise as necessary.
  • If you just tell me a sequence of steps to carry out, I am always wondering if I am doing them right ("Is this what you wanted?") and waiting for permission to start the next step.
  • When we both know the goal, I should be able to perform at a higher level. I should be better able to tell if I am making a mistake. Additionally, I can make better use of my experience to notice errors in your planning, along with problems that might arise.
  • They should be able to understand the goals well enough to set and revise priorities, to decide when to grasp an opportunity and when to let it go.
  • The Commander's Intent statement helps the soldiers read the commander's mind if they run into uncertainty about how to carry out the orders under field conditions.
  • William Crain (1990) found that only 19 percent of the Commander's Intent statements said anything about the purpose of the mission and that communication of intent was mediocre.
  • The purpose of the task (the higher-level goals). 2. The objective of the task (an image of the desired outcome). 3. The sequence of steps in the plan. 4. The rationale for the plan. 5. The key decisions that
  • may have to be made. 6. Antigoals (unwanted outcomes). 7. Constraints and other considerations.
  • To improve the ability to communicate intent, we cannot try to teach a checklist or set of procedures. A more valuable approach is to set up exercises to provide feedback to leaders about how well their intent is understood.
  • Situation awareness incorporates the nature of the goals, and teams have to work to communicate intent.
  • The ability to manage the flow of ideas is one of the central skills that distinguishes immature from experienced teams.
  • Their shift in strategy isn't easy. The hardest part is to let some fires go.
  • Research in neurophysiology has shown that individuals can have the delusion that they are controlling their own thinking when this is not the case.
  • The Illusion of Rationality The neuropsychologist Michael Gazzaniga (1985) conducted a study of patients whose uncontrollable epilepsy was so severe that the treatment was to cut the connections between the two hemispheres of the brain so the epileptic seizures would not have a path for spreading throughout the brain. Working with these patients individually, Gazzaniga presented a written message to the visual field that fed into the right hemisphere, asking the patient to perform some simple act, like standing up and walking around. Next, he presented a written message to the left hemisphere, which controls speech, asking the person why he or she was walking around. Invariably, the person could make up an answer, such as "I just felt like stretching my legs," or "I felt thirsty and wanted to find a Coke." The left hemisphere could not
  • know the true reason for the action, but it showed no hesitation in making up a plausible reason. One speculation is that we have some sort of rational engine whose job it is to observe our behaviors and make inferences about rational causes.
  • Hyperrationality is a mental disturbance in which the victim attempts to handle all decisions and problems on a purely rational basis, relying on only logical and analytical forms of reasoning.
  • observe an unwillingness to act without a sound, empirically or logically supported basis.

  • paralysis by analysis

  • Rational analysis is a cornerstone of intellectual activities and a very important source of power. We do not want to encourage people to make ill-informed, impulsive decisions.
  • Decompose. We have to analyze a task-break the task, idea, or argument ment into small units, basic elements, so we can perform different calculations lations on them. Seeing how to break something into its components is a source of power in its own right.• Decontextualize. Since context adds ambiguity, we must try to find units that are independent of context. We want to represent the important tant parts of context as additional facts and rules
  • and elements. To accomplish this, we try to find a formal way to represent the world, to treat it as a representation, a picture, a model. We try to build theories and maps to substitute for having a sense of the task or the equipment.
  • a theory or mental model of the layout of the plant;
  • the hard part is figuring out if the antecedent condition, dition, the "if" part of the rule, has been met.3 That is why researchers prefer to work on rational inference using context-free artificial problems that leave no ambiguity.
  • The context of the situation, the ambiguities, make it hard to judge
  • When the calculations lations require people to estimate probabilities or utilities, to estimate their values or to make other unnatural judgments, we are going to have trouble.
  • inconsistent beliefs but does not make the connection because the beliefs are stored in different ent contexts in memory.
  • an inconsistency sistency between the set of beliefs held and the actions taken.
  • Rigor is not a substitute for imagination.
  • Consistency is not a replacement placement for insight.
  • Logic is indifferent to truth.
  • goal of logic is to root out inconsistent beliefs and generate new beliefs consistent with the original set.
  • The inconsistencies in our beliefs were due to memory compartmentalization.
  • Poor outcomes are different from poor decisions.
  • Kahneman, Slovic, and Tversky (1982) present a range of studies showing ing that decision makers use a variety of heuristics, simple procedures that usually produce an answer but are not foolproof.'
  • "heuristics and biases" paradigm.
  • Many researchers searchers interpret this research as showing that people are inherently biased and will misconstrue evidence. Therefore, decision errors must be caused by these biases.
  • One of the primary "biases" is confirmation bias-the search for information that confirms your hypothesis even though you would learn more by searching for evidence that might disconfirm confirm it. The confirmation bias has been shown in many laboratory studies (and has not been found in a number of studies conducted in natural settings).
  • Naturalistic decision-making researchers are coming to doubt that errors can be neatly identified and attributed to faulty reasoning.
  • My claim is that stress does affect the way we process information, but it does not cause us to make bad decisions based on the information at hand.
  • The stressors do not give us a chance to gather as much information.• The stressors disrupt our ability to use our working memory to sort things out.• The stressors distract our attention from the task at hand.
  • Where experience enables decision makers to take action rapidly, uncertainty results in doubt.
  • Uncertainty:
  • 1. Missing information.
  • Unreliable information.
  • Ambiguous or conflicting information.
  • Complex information.
  • we cannot be optimistic that increasing information will necessarily reduce uncertainty. It is more likely that the information age will change the challenges posed by uncertainty.
  • Often we believe that we can improve the decision by collecting more information, but in the process we lose opportunities.
  • Skilled decision makers appear to know when to wait and when to act.
  • We can learn the wrong lessons from experience.
  • the risk of getting it wrong and stamping in the wrong strategy.
  • In short, our lives are just as governed by superstitions as those of less advanced cultures. The content of the superstitions has changed but not the degree to which they control us.
  • We must act on faith, rumor, and precedent.
  • Lia Di Bello gave people a task that violated the rules they had been using, the experts would quickly notice the violation and find a way to work around it.
  • They could improvise to achieve the desired goal.
  • One way to improve performance is to be more careful in considering alternate explanations

  • Premortem

  • The crystal ball method is not well suited for time-pressured conditions.
  • instead of erecting defenses, accept malfunctions and errors, and make their existence more visible.
  • Expertise depends on perceptual skills.
  • The computer metaphor of thinking is incomplete. Mechanistic descriptions scriptions of skilled problem solving and decision making emphasize the storage, retrieval, and manipulation of data elements.
  • using stories and analogues, personal as well as borrowed from others, to learn about the important causal factors
  • Skilled problem solvers and decision makers are chameleons. They can simulate all types of events and processes in their heads.
  • They are generative, channeling the decision making from opportunity to opportunity rather than exhaustively filtering through all the permutations.
  • They enable the decision maker to redefine goals and also to search for ways to achieve existing goals.
  • They trade accuracy for speed and therefore allow errors.
  • Experience can be codified as stories and analogues.
  • There are additional sources of power, such as analysis and calculation, that break tasks down into abstract elements and perform operations on these elements. In many difficult tasks, we blend the different ent sources of power and integrate them to fit the needs of the situation.
    1. Intuition
    2. Mental simulation
    3. Using leverage points to solve ill-defined problems
    4. Seeing the invisible
    5. Storytelling
    6. Analogical and metaphorical reasoning
    7. (communicating intent)
    8. Team mind (drawing on the experience base of the team)
    9. Judging the typicality of a situation
    10. Judging typical goals
    11. Recognizing typical courses of action
    12. Judging the solvability of a problem
    13. Detecting anomalies
      • • Judging the urgency of a problem
      • • Detecting opportunities
      • • Making fine discriminations
      • • Detecting gaps in a plan of action
      • • Detecting barriers that are responsible for gaps in a plan of action
    14. the two primary sources of power are pattern recognition (the power of intuition) and mental simulation.
    15. Expertise (the power to see the invisible) derives from both pattern recognition and mental simulation.
    16. Our ability to read minds depends on how well we can mentally simulate the thinking of the person.
    17. That is one reason I spent so much time describing how we ran the studies, to allow you to judge for yourself how much confidence to have in the findings.
    18. Regarding the nature of our data, one weakness of our work is that most of the studies relied on interviews rather than formal experiments to vary one thing at a time and see its effect.
    19. Naturalistic decision making research may be closer to anthropology than psychology.
    20. Orasanu and Connolly (1993) have questioned whether findings that are carefully obtained under laboratory conditions apply outside the laboratory.
    21. An "unreasonable" person is one who refuses to argue, refuses to examine the reasons for beliefs or actions.