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Questions and Answers
What was Paul Meehl's profession?
What was Paul Meehl's profession?
In which departments did Paul Meehl have faculty appointments at the University of Minnesota?
In which departments did Paul Meehl have faculty appointments at the University of Minnesota?
What was the topic of Paul Meehl's 'disturbing little book'?
What was the topic of Paul Meehl's 'disturbing little book'?
What was the purpose of the 20 studies reviewed in Meehl's book?
What was the purpose of the 20 studies reviewed in Meehl's book?
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What type of information did the statistical algorithm use in the study on predicting freshmen grades?
What type of information did the statistical algorithm use in the study on predicting freshmen grades?
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How many of the 14 counselors' predictions were less accurate than the statistical algorithm's prediction in the study on freshmen grades?
How many of the 14 counselors' predictions were less accurate than the statistical algorithm's prediction in the study on freshmen grades?
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What was the outcome of Meehl's book on the field of clinical psychology?
What was the outcome of Meehl's book on the field of clinical psychology?
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How long has the controversy started by Meehl's book continued to engender research?
How long has the controversy started by Meehl's book continued to engender research?
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What is the approximate number of studies comparing clinical and statistical predictions?
What is the approximate number of studies comparing clinical and statistical predictions?
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What is the title of Robyn Dawes's famous article?
What is the title of Robyn Dawes's famous article?
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What is the logic of multiple regression?
What is the logic of multiple regression?
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What percentage of studies have shown better accuracy for algorithms?
What percentage of studies have shown better accuracy for algorithms?
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What is the advantage of using statistical rules over expert judgment?
What is the advantage of using statistical rules over expert judgment?
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What did Dawes observe about multiple regression?
What did Dawes observe about multiple regression?
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What is the term used to describe the domains where algorithms have been shown to be more accurate?
What is the term used to describe the domains where algorithms have been shown to be more accurate?
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What is the implication of Dawes' research?
What is the implication of Dawes' research?
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What is the topic of Orley Ashenfelter's research?
What is the topic of Orley Ashenfelter's research?
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What is the formula that predicts marital stability?
What is the formula that predicts marital stability?
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Who developed the simple algorithm that has saved the lives of hundreds of thousands of infants?
Who developed the simple algorithm that has saved the lives of hundreds of thousands of infants?
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What three features of the weather does Ashenfelter's formula use to predict the price of a wine?
What three features of the weather does Ashenfelter's formula use to predict the price of a wine?
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Why are experts often inferior to algorithms in making predictions?
Why are experts often inferior to algorithms in making predictions?
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What did Virginia Apgar use to assess the health of newborn infants?
What did Virginia Apgar use to assess the health of newborn infants?
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What is the purpose of the Apgar score?
What is the purpose of the Apgar score?
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What is the correlation between Ashenfelter's predictions and actual prices?
What is the correlation between Ashenfelter's predictions and actual prices?
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What is the title of Atul Gawande's book that discusses the virtues of checklists and simple rules?
What is the title of Atul Gawande's book that discusses the virtues of checklists and simple rules?
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What is the advantage of using algorithms in making predictions?
What is the advantage of using algorithms in making predictions?
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What is the name of the economist who demonstrated the power of simple statistics to outdo world-renowned experts?
What is the name of the economist who demonstrated the power of simple statistics to outdo world-renowned experts?
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What is the general conclusion of the research on predictive models?
What is the general conclusion of the research on predictive models?
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What is a key advantage of using formulas over human judgment?
What is a key advantage of using formulas over human judgment?
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What is the term coined by Meehl to describe a rare and decisive event that can override a formula?
What is the term coined by Meehl to describe a rare and decisive event that can override a formula?
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What is the approximate percentage of inconsistency found in experienced radiologists when evaluating the same chest X-rays on separate occasions?
What is the approximate percentage of inconsistency found in experienced radiologists when evaluating the same chest X-rays on separate occasions?
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What is the main reason for the inferiority of human judgment compared to formulas?
What is the main reason for the inferiority of human judgment compared to formulas?
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What is the likely effect of conducting an interview on the accuracy of a selection procedure in medical school admissions?
What is the likely effect of conducting an interview on the accuracy of a selection procedure in medical school admissions?
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Why do formulas not suffer from the problems of human judgment?
Why do formulas not suffer from the problems of human judgment?
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What is the main reason for the context dependency of human judgment?
What is the main reason for the context dependency of human judgment?
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What is the conclusion suggested by the research reviewed by Meehl and his followers?
What is the conclusion suggested by the research reviewed by Meehl and his followers?
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What was the reaction of French wine circles to the use of algorithms?
What was the reaction of French wine circles to the use of algorithms?
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What is the likely effect of wine experts' ability to taste the wine on the accuracy of their predictions?
What is the likely effect of wine experts' ability to taste the wine on the accuracy of their predictions?
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What is the primary concern of clinicians when it comes to algorithmic decisions?
What is the primary concern of clinicians when it comes to algorithmic decisions?
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What is the primary reason why humans are unable to maintain the consistency of a formula?
What is the primary reason why humans are unable to maintain the consistency of a formula?
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What is the author's perspective on the use of algorithms in decision-making?
What is the author's perspective on the use of algorithms in decision-making?
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What is the expected outcome of the increasing use of algorithms in everyday life?
What is the expected outcome of the increasing use of algorithms in everyday life?
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What is the primary benefit of using algorithms in decision-making, according to Meehl and other proponents?
What is the primary benefit of using algorithms in decision-making, according to Meehl and other proponents?
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What is the author's role in the Israeli Defense Forces?
What is the author's role in the Israeli Defense Forces?
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What was the goal of the interview system in the Israeli Defense Forces?
What was the goal of the interview system in the Israeli Defense Forces?
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What was the problem with the original interview procedure in the Israeli Defense Forces?
What was the problem with the original interview procedure in the Israeli Defense Forces?
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What was the author's task in the Israeli Defense Forces?
What was the author's task in the Israeli Defense Forces?
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What was the author's qualification for being assigned to design a new interview procedure?
What was the author's qualification for being assigned to design a new interview procedure?
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What was the initial response of clinical psychologists to Meehl's ideas?
What was the initial response of clinical psychologists to Meehl's ideas?
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What type of predictions do clinicians typically make in therapy sessions?
What type of predictions do clinicians typically make in therapy sessions?
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Why do clinicians fail to make accurate long-term predictions?
Why do clinicians fail to make accurate long-term predictions?
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What is the moral dimension of the debate about clinical and statistical prediction?
What is the moral dimension of the debate about clinical and statistical prediction?
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Why do people prefer the 'all natural' option, even when informed that it has the same nutritional value and health benefits as the commercially grown option?
Why do people prefer the 'all natural' option, even when informed that it has the same nutritional value and health benefits as the commercially grown option?
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What is the reason for the resistance to algorithms making decisions that affect humans?
What is the reason for the resistance to algorithms making decisions that affect humans?
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What was the reaction of the European wine community to Ashenfelter's formula for predicting the price of Bordeaux wines?
What was the reaction of the European wine community to Ashenfelter's formula for predicting the price of Bordeaux wines?
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What is the difference between the tasks that clinicians are skilled at and the tasks that they are not good at?
What is the difference between the tasks that clinicians are skilled at and the tasks that they are not good at?
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What is the reason for the illusion of clinical skill among clinicians?
What is the reason for the illusion of clinical skill among clinicians?
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What is the criticism of the statistical method by experienced clinicians?
What is the criticism of the statistical method by experienced clinicians?
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What is the key lesson the author learned from the finding?
What is the key lesson the author learned from the finding?
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What is the purpose of telling the candidates 'Close your eyes' during the interview process?
What is the purpose of telling the candidates 'Close your eyes' during the interview process?
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What is the recommended number of traits to select for a job interview?
What is the recommended number of traits to select for a job interview?
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Why should the information on each trait be collected separately?
Why should the information on each trait be collected separately?
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What should the interviewer do to resist the temptation to change the ranking of the candidates?
What should the interviewer do to resist the temptation to change the ranking of the candidates?
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What is the result of using the interview procedure described in the chapter?
What is the result of using the interview procedure described in the chapter?
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What should the interviewer do before conducting the interview?
What should the interviewer do before conducting the interview?
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What is the benefit of using a disciplined scoring system in the interview process?
What is the benefit of using a disciplined scoring system in the interview process?
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Why should the interviewer avoid making an overall intuitive judgment about the candidates?
Why should the interviewer avoid making an overall intuitive judgment about the candidates?
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What is the recommended duration for preparing the interview procedure?
What is the recommended duration for preparing the interview procedure?
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What was the main reason for the failure of the original interview process?
What was the main reason for the failure of the original interview process?
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What was the main idea behind the new interview process?
What was the main idea behind the new interview process?
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How did the author combat the halo effect?
How did the author combat the halo effect?
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What was the task of the interviewers in the new interview process?
What was the task of the interviewers in the new interview process?
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What was the outcome of the new interview process?
What was the outcome of the new interview process?
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What was the result of the 'close your eyes' exercise?
What was the result of the 'close your eyes' exercise?
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What was the main reason for the interviewers' initial resistance to the new interview process?
What was the main reason for the interviewers' initial resistance to the new interview process?
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How many personality traits were evaluated in the new interview process?
How many personality traits were evaluated in the new interview process?
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What was the sequence of the traits evaluation in the new interview process?
What was the sequence of the traits evaluation in the new interview process?
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What was the purpose of the final score in the new interview process?
What was the purpose of the final score in the new interview process?
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Study Notes
Paul Meehl and Clinical vs. Statistical Prediction
- Paul Meehl was a psychologist who wrote a book titled "Clinical vs. Statistical Prediction: A Theoretical Analysis and a Review of the Evidence" in 1954, which challenged the idea that clinical predictions made by trained professionals are more accurate than statistical predictions.
- Meehl reviewed 20 studies that compared clinical predictions with statistical predictions and found that statistical predictions were more accurate in 11 out of 14 cases.
- The book provoked shock and disbelief among clinical psychologists, but it started a stream of research that has continued to this day, with over 200 studies conducted since then.
The Superiority of Algorithms
- Studies have consistently shown that algorithms outperform human experts in making predictions, with algorithms being more accurate in about 60% of cases.
- Algorithms are better than humans because they are not affected by biases, emotions, and other factors that can influence human judgment.
- Humans are also inconsistent in making summary judgments of complex information, which can lead to inaccuracies.
The Apgar Score
- The Apgar score is a simple algorithm developed by Virginia Apgar in 1953 to assess the health of newborn babies.
- The score is based on five variables: heart rate, respiration, reflex, muscle tone, and color, with a score of 0, 1, or 2 for each variable.
- The Apgar score has been credited with reducing infant mortality and is still used in every delivery room today.
The Hostility to Algorithms
- Many people, including clinicians, have been resistant to the idea of using algorithms to make predictions, preferring to rely on human judgment.
- This resistance is often due to a prejudice against the use of machines and algorithms, and a preference for the "natural" and "human" approach.
- However, the use of algorithms can lead to more accurate and fair decisions, and can also help to reduce errors and biases.
The Importance of Algorithms
- Algorithms are becoming increasingly important in our daily lives, and are being used in a wide range of applications, from medicine to finance to sport.
- The use of algorithms can help to improve decision-making, reduce errors, and increase efficiency.
- As algorithms become more widespread, it is likely that the resistance to their use will decrease, and they will become more accepted as a valuable tool.### The Interview Process
- The author was tasked with designing a new interview process to assess recruits for combat duty in the army.
- The previous interview process was deemed "almost useless" in predicting future success of recruits.
- The author was inspired by Paul Meehl's book, which argued that statistical rules are superior to intuitive judgments.
The New Interview Process
- The author designed a new interview process that focused on obtaining specific, factual information about the recruit's life.
- The process involved evaluating six relevant personality traits, including responsibility, sociability, and masculine pride.
- The interviewers were instructed to ask standardized, factual questions and score each trait on a 5-point scale.
- The interviewers were also instructed to go through the six traits in a fixed sequence to avoid halo effects.
Results and Lessons Learned
- The new interview process was a significant improvement over the previous one, with the sum of the six ratings predicting soldiers' performance more accurately.
- The intuitive judgment of the interviewers also performed well, but only after a disciplined collection of objective information.
- The author learned that intuition adds value, but only when combined with a disciplined approach.
- The author also learned not to simply trust intuitive judgment, but not to dismiss it either.
Applying the Lessons to Other Areas
- The message of the chapter can be applied to tasks other than making manpower decisions for an army.
- Implementing interview procedures in the spirit of Meehl and Dawes requires relatively little effort but substantial discipline.
- The author provides an example of how to apply the lessons to hiring a sales representative, including selecting a few traits, making a list of factual questions, and scoring each trait on a 5-point scale.
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Description
Learn about the life and work of Paul Meehl, a renowned psychologist who made significant contributions to various fields, including psychology, law, and philosophy. Take this quiz to discover more about his research and interests.