The Classification of Mistakes Mist

The Classification of Mistakes Mistakes result from the choice of inappropriate goals and plans or from faulty comparison of the outcome with the goals during eval- uation. In mistakes, a person makes a poor decision, misclassifies a situation, or fails to take all the relevant factors into account. Many
mistakes arise from the vagaries of human thought, often because
people tend to rely upon remembered experiences rather than on
more systematic analysis. We make decisions based upon what is
in our memory. But as discussed in Chapter 3, retrieval from long-
term memory is actually a reconstruction rather than an accurate
record. As a result, it is subject to numerous biases. Among other
things, our memories tend to be biased toward overgeneralization
of the commonplace and overemphasis of the discrepant.
The Danish engineer Jens Rasmussen distinguished among three
modes of behavior: skill-based, rule-based, and knowledge-based.
This three-level classification scheme provides a practical tool that
has found wide acceptance in applied areas, such as the design of

many industrial systems. Skill-based behavior occurs when work- ers are extremely expert at their jobs, so they can do the everyday, routine tasks with little or no thought or conscious attention. The most common form of errors in skill-based behavior is slips.
Rule-based behavior occurs when the normal routine is no lon- ger applicable but the new situation is one that is known, so there is already a well-prescribed course of action: a rule. Rules simply might be learned behaviors from previous experiences, but in- cludes formal procedures prescribed in courses and manuals, usu- ally in the form of “if-then” statements, such as, “If the engine will not start, then do [the appropriate action].” Errors with rule-based behavior can be either a mistake or a slip. If the wrong rule is se- lected, this would be a mistake. If the error occurs during the exe- cution of the rule, it is most likely a slip.
Knowledge-based procedures occur when unfamiliar events oc- cur, where neither existing skills nor rules apply. In this case, there must be considerable reasoning and problem-solving. Plans might be developed, tested, and then used or modified. Here, conceptual models are essential in guiding development of the plan and inter- pretation of the situation.
In both rule-based and knowledge-based situations, the most seri- ous mistakes occur when the situation is misdiagnosed. As a result, an inappropriate rule is executed, or in the case of knowledge-based problems, the effort is addressed to solving the wrong problem. In addition, with misdiagnosis of the problem comes misinterpreta- tion of the environment, as well as faulty comparisons of the cur- rent state with expectations. These kinds of mistakes can be very difficult to detect and correct.

RULE-BASED MISTAKES
When new procedures have to be invoked or when simple prob- lems arise, we can characterize the actions of skilled people as rule- based. Some rules come from experience; others are formal proce- dures in manuals or rulebooks, or even less formal guides, such as cookbooks for food preparation. In either case, all we must do is identify the situation, select the proper rule, and then follow it.

When driving, behavior follows well-learned rules. Is the light red? If so, stop the car. Wish to turn left? Signal the intention to turn and move as far left as legally permitted: slow the vehicle and wait for a safe break in traffic, all the while following the traffic rules and relevant signs and lights.
Rule-based mistakes occur in multiple ways:

• The situation is mistakenly interpreted, thereby invoking the wrong goal or plan, leading to following an inappropriate rule.
• The correct rule is invoked, but the rule itself is faulty, either because it was formulated improperly or because conditions are different than assumed by the rule or through incomplete knowledge used to determine the rule. All of these lead to knowledge-based mistakes.
• The correct rule is invoked, but the outcome is incorrectly evaluated.
This error in evaluation, usually rule- or knowledge-based itself, can lead to further problems as the action cycle continues.

Example 1: In 2013, at the Kiss nightclub in Santa Maria, Brazil, pyro- technics used by the band ignited a fire that killed over 230 people. The tragedy illustrates several mistakes. The band made a knowl- edge-based mistake when they used outdoor flares, which ignited the ceiling’s acoustic tiles. The band thought the flares were safe. Many people rushed into the rest rooms, mistakenly thinking they were ex- its: they died. Early reports suggested that the guards, unaware of the fire, at first mistakenly blocked people from leaving the building. Why? Because nightclub attendees would sometimes leave without paying for their drinks.
The mistake was in devising a rule that did not take account of emergencies. A root cause analysis would reveal that the goal was to prevent inappropriate exit but still allow the doors to be used in an emergency. One solution is doors that trigger alarms when used, deterring people trying to sneak out, but allowing exit when needed.
Example 2: Turning the thermostat of an oven to its maximum tempera- ture to get it to the proper cooking temperature faster is a mistake based upon a false conceptual model of the way the oven works. If the person wanders off and forgets to come back and check the oven

temperature after a reasonable period (a memory-lapse slip), the im- proper high setting of the oven temperature can lead to an accident, possibly a fire.
Example 3: A driver, unaccustomed to anti-lock brakes, encounters an unexpected object in the road on a wet, rainy day. The driver ap- plies full force to the brakes but the car skids, triggering the anti-lock brakes to rapidly turn the brakes on and off, as they are designed to do. The driver, feeling the vibrations, believes that it indicates mal- function and therefore lifts his foot off the brake pedal. In fact, the vibration is a signal that anti-lock brakes are working properly. The driver ’s misevaluation leads to the wrong behavior.

Rule-based mistakes are difficult to avoid and then difficult to detect. Once the situation has been classified, the selection of the appropriate rule is often straightforward. But what if the classifica- tion of the situation is wrong? This is difficult to discover because there is usually considerable evidence to support the erroneous classification of the situation and the choice of rule. In complex situations, the problem is too much information: information that both supports the decision and also contradicts it. In the face of time pressures to make a decision, it is difficult to know which evidence to consider, which to reject. People usually decide by tak- ing the current situation and matching it with something that hap- pened earlier. Although human memory is quite good at matching examples from the past with the present situation, this doesn’t mean that the matching is accurate or appropriate. The matching is biased by recency, regularity, and uniqueness. Recent events are remembered far better than less recent ones. Frequent events are remembered through their regularities, and unique events are remembered because of their uniqueness. But suppose the current event is different from all that has been experienced before: people are still apt to find some match in memory to use as a guide. The same powers that make us so good at dealing with the common and the unique lead to severe error with novel events.
What is a designer to do? Provide as much guidance as possible to ensure that the current state of things is displayed in a coherent

and easily interpreted format—ideally graphical. This is a difficult problem. All major decision makers worry about the complexity of real-world events, where the problem is often too much infor- mation, much of it contradictory. Often, decisions must be made quickly. Sometimes it isn’t even clear that there is an incident or that a decision is actually being made.

Kết quả (Việt) 1:

Kết quả phân loại sai lầm sai lầm từ sự lựa chọn của mục tiêu không phù hợp và kế hoạch hoặc từ việc so sánh kết quả với các mục tiêu trong eval uation. Trong những sai lầm, một người làm cho một quyết định người nghèo, misclassifies một tình huống, hoặc không phải tất cả các yếu tố có liên quan vào tài khoản. Nhiềusai lầm phát sinh từ các vagaries của suy nghĩ của con người, thường vìnhững người có xu hướng dựa trên những kinh nghiệm đáng nhớ hơn là trêncó hệ thống hơn phân tích. Chúng tôi đưa ra quyết định dựa trên những gì làtrong bộ nhớ của chúng tôi. Tuy nhiên, như thảo luận trong chương 3, Lấy từ long-bộ nhớ hạn là thực sự là một tái thiết thay vì một chính xáckỷ lục. Kết quả là, nó là tùy thuộc vào nhiều thành kiến. Trong số khácnhững điều, những kỷ niệm của chúng tôi có xu hướng thiên vị về hướng overgeneralizationphổ biến và overemphasis của các khác.Các kỹ sư Đan Mạch Jens Rasmussen phân biệt trong số baCác chế độ của hành vi: dựa trên kỹ năng, dựa trên quy tắc và dựa trên kiến thức.Sơ đồ phân loại ba cấp này cung cấp một công cụ thiết thực đóđã tìm thấy sự chấp nhận rộng trong lĩnh vực ứng dụng, chẳng hạn như thiết kế của nhiều hệ thống công nghiệp. Kỹ năng dựa trên hành vi xảy ra khi công việc-ers là cực kỳ chuyên gia tại công việc của họ, để họ có thể làm những công việc hàng ngày, thường xuyên với ít hoặc không có suy nghĩ hoặc ý thức sự chú ý. Các hình thức phổ biến nhất của lỗi trong kỹ năng dựa trên hành vi là phiếu.Rule-based behavior occurs when the normal routine is no lon- ger applicable but the new situation is one that is known, so there is already a well-prescribed course of action: a rule. Rules simply might be learned behaviors from previous experiences, but in- cludes formal procedures prescribed in courses and manuals, usu- ally in the form of “if-then” statements, such as, “If the engine will not start, then do [the appropriate action].” Errors with rule-based behavior can be either a mistake or a slip. If the wrong rule is se- lected, this would be a mistake. If the error occurs during the exe- cution of the rule, it is most likely a slip.Knowledge-based procedures occur when unfamiliar events oc- cur, where neither existing skills nor rules apply. In this case, there must be considerable reasoning and problem-solving. Plans might be developed, tested, and then used or modified. Here, conceptual models are essential in guiding development of the plan and inter- pretation of the situation.In both rule-based and knowledge-based situations, the most seri- ous mistakes occur when the situation is misdiagnosed. As a result, an inappropriate rule is executed, or in the case of knowledge-based problems, the effort is addressed to solving the wrong problem. In addition, with misdiagnosis of the problem comes misinterpreta- tion of the environment, as well as faulty comparisons of the cur- rent state with expectations. These kinds of mistakes can be very difficult to detect and correct.
RULE-BASED MISTAKES
When new procedures have to be invoked or when simple prob- lems arise, we can characterize the actions of skilled people as rule- based. Some rules come from experience; others are formal proce- dures in manuals or rulebooks, or even less formal guides, such as cookbooks for food preparation. In either case, all we must do is identify the situation, select the proper rule, and then follow it.

When driving, behavior follows well-learned rules. Is the light red? If so, stop the car. Wish to turn left? Signal the intention to turn and move as far left as legally permitted: slow the vehicle and wait for a safe break in traffic, all the while following the traffic rules and relevant signs and lights.
Rule-based mistakes occur in multiple ways:

• The situation is mistakenly interpreted, thereby invoking the wrong goal or plan, leading to following an inappropriate rule.
• The correct rule is invoked, but the rule itself is faulty, either because it was formulated improperly or because conditions are different than assumed by the rule or through incomplete knowledge used to determine the rule. All of these lead to knowledge-based mistakes.
• The correct rule is invoked, but the outcome is incorrectly evaluated.
This error in evaluation, usually rule- or knowledge-based itself, can lead to further problems as the action cycle continues.

Example 1: In 2013, at the Kiss nightclub in Santa Maria, Brazil, pyro- technics used by the band ignited a fire that killed over 230 people. The tragedy illustrates several mistakes. The band made a knowl- edge-based mistake when they used outdoor flares, which ignited the ceiling’s acoustic tiles. The band thought the flares were safe. Many people rushed into the rest rooms, mistakenly thinking they were ex- its: they died. Early reports suggested that the guards, unaware of the fire, at first mistakenly blocked people from leaving the building. Why? Because nightclub attendees would sometimes leave without paying for their drinks.
The mistake was in devising a rule that did not take account of emergencies. A root cause analysis would reveal that the goal was to prevent inappropriate exit but still allow the doors to be used in an emergency. One solution is doors that trigger alarms when used, deterring people trying to sneak out, but allowing exit when needed.
Example 2: Turning the thermostat of an oven to its maximum tempera- ture to get it to the proper cooking temperature faster is a mistake based upon a false conceptual model of the way the oven works. If the person wanders off and forgets to come back and check the oven

temperature after a reasonable period (a memory-lapse slip), the im- proper high setting of the oven temperature can lead to an accident, possibly a fire.
Example 3: A driver, unaccustomed to anti-lock brakes, encounters an unexpected object in the road on a wet, rainy day. The driver ap- plies full force to the brakes but the car skids, triggering the anti-lock brakes to rapidly turn the brakes on and off, as they are designed to do. The driver, feeling the vibrations, believes that it indicates mal- function and therefore lifts his foot off the brake pedal. In fact, the vibration is a signal that anti-lock brakes are working properly. The driver ’s misevaluation leads to the wrong behavior.

Rule-based mistakes are difficult to avoid and then difficult to detect. Once the situation has been classified, the selection of the appropriate rule is often straightforward. But what if the classifica- tion of the situation is wrong? This is difficult to discover because there is usually considerable evidence to support the erroneous classification of the situation and the choice of rule. In complex situations, the problem is too much information: information that both supports the decision and also contradicts it. In the face of time pressures to make a decision, it is difficult to know which evidence to consider, which to reject. People usually decide by tak- ing the current situation and matching it with something that hap- pened earlier. Although human memory is quite good at matching examples from the past with the present situation, this doesn’t mean that the matching is accurate or appropriate. The matching is biased by recency, regularity, and uniqueness. Recent events are remembered far better than less recent ones. Frequent events are remembered through their regularities, and unique events are remembered because of their uniqueness. But suppose the current event is different from all that has been experienced before: people are still apt to find some match in memory to use as a guide. The same powers that make us so good at dealing with the common and the unique lead to severe error with novel events.
What is a designer to do? Provide as much guidance as possible to ensure that the current state of things is displayed in a coherent

and easily interpreted format—ideally graphical. This is a difficult problem. All major decision makers worry about the complexity of real-world events, where the problem is often too much infor- mation, much of it contradictory. Often, decisions must be made quickly. Sometimes it isn’t even clear that there is an incident or that a decision is actually being made.