## Highlights - Speaker 1: insurance. It might be that if you happen to get a quote that's too high, you might end up being uninsured or you might be spending more on insurance that you need to be spending. There is sort of a general human cost to these errors, not just in terms of the bottom line for the insurance company. Speaker 2: Well, of course, when you have a noisy underwriting system, then the customer is facing a lottery that the customer has not signed up for. And that is true everywhere. That is wherever people reach a judgment or a decision by using their mind, rather than computing wherever there is judgment, there is noise and there is more of it than you think [(Time 0:07:12)](https://www.airr.io/quote/63c307147f205624b62afd1f) - notes:: Where there is judgment, there is noise. And there is more of it than you think.  - Speaker 1: of candidates on cloudy days and a non academic attributes when the weather is sunny, he titled his paper clouds make nerds look good. Talk about this idea that extraneous factors, whether someone's hungry, what the weather is like, that can affect people's judgment to Speaker 2: Indeed, it's been established in the justice system. If you're a defendant, you have to hope for good weather because on very hot days, judges assigned more severe sentences. And that is true though. Judges are air conditioned, but it's the outside temperature nevertheless seems to have an effect. It's been established in at least one study that for judges who are keen on football, [(Time 0:11:00)](https://www.airr.io/quote/63c30a997f205624b62b5cfa) - notes:: Outside temperature, a.k.a. environmental factors can affect decision, making for those in the judicial system to the detriment of the accused - Speaker 2: is true and it makes it very difficult to believe and to imagine that someone else looking at the same reality is going to see it differently. But in fact, we are struck by how different they are in the context of criminal justice. The variability and sentences is shocking. Speaker 3: But Speaker 2: when you're looking at it from the perspective of a judge who looks at cases individually and feels that he or she is making correct judgments for every case individually, then it looks as if any attempt to restrict their freedom is going to cause [(Time 0:23:53)](https://www.airr.io/quote/63c30ac07f205624b62b64ae) - notes:: Naïve realism: when you’re fundamentally shaken, by the reality, that somebody else’s interpretation of a situation could be fundamentally or radically different from yours, might also be related to cognitive dissonance  - Speaker 1: a mistake is made and algorithms of course can make mistakes and humans can make mistakes. He's saying that you prefer the human to make the mistake. And I think intuitively that feels correct to me. If I'm going to get a misdiagnosis when I go to a doctor, I would feel better if it's the doctor who's made the mistake than an unfeeling unthinking algorithm. Speaker 2: I think that's absolutely true. And you know when we're looking at a road accident we somehow feels less bad about it if it was a driver error than if it was a self driving car that caused the accident algorithms they make errors. The error they make by the way, are different from the errors that people would make and they look stupid to people algorithm make errors that people [(Time 0:31:00)](https://www.airr.io/quote/63c3322b7f205624b62f8153) - notes:: People prefer other people to make mistakes rather than machines and algorithms, I would prefer the machine over the person, because the machine doesn’t have biases and prejudice and if those things are prison, it’s because of its training data, and that can be improved, whereas a humans prejudice.. - Speaker 1: and algorithms of course can make mistakes and humans can make mistakes. He's saying that you prefer the human to make the mistake. And I think intuitively that feels correct to me. If I'm going to get a misdiagnosis when I go to a doctor, I would feel better if it's the doctor who's made the mistake than an unfeeling unthinking algorithm. Speaker 2: I think that's absolutely true. And you know when we're looking at a road accident we somehow feels less bad about it if it was a driver error than if it was a self driving car that caused the accident algorithms they make errors. The error they make by the way, are different from the errors that people would make and they look stupid to people algorithm make errors that people think are [(Time 0:31:01)](https://www.airr.io/quote/63c334c57f205624b62fd76b) - notes:: Where is I feel better about the algorithm because at least in my mistake, I help improve the algorithm because statistically it’s more accurate - Speaker 1: only by studying statistical averages, how do I reduce noise in decisions I am making as an individual? The answer try to make the same decision over and over under different conditions. One way to tell if noises behind my decision to propose marriage is to ask myself whether I would make the same decision under different circumstances, not just on a moonlit night in the springtime, but in the heat of summer or in the dead of winter. If I reach the same answer in these different settings, it's possible I could still be making a mistake, but at least I can be somewhat reassured that my decision is not the result of random extraneous factors. [(Time 0:40:59)](https://www.airr.io/quote/63c337637f205624b630155e) - notes:: A way to reduce random variability noise decision, making in regards to your own decisions, is to make the same decision under variant conditions, and then average out the responses - Speaker 2: The main thing to do if you're attempting to improve the judgment of people in an organization is to convince those people that they want their judgments to be better. If you impose it as a set of rules that all of them will follow. They will resist it. They will feel they're being roboticist and they're likely to sabotage whatever you propose. I mean, this is well known in insurance companies that provide the underwriters in many cases with information or even with the technical price with the suggestion about what premium should be assigned. And underwriters are very likely to completely ignore those and to [(Time 0:48:59)](https://www.airr.io/quote/63c4500b7f205624b64d82cf) - notes:: People don’t like being told what to do and how to do things  --- tags: 📥️/🎧️/🟥️ publish: true aliases: - Our Noisy Minds cover: '' general_subject: specific_subject: source: airr isbn: doi: url: 'https://www.airr.io/episode/60a2df9da10eb714c1b986ac' author: "[[@Hidden Brain]]" guest: publish_date: reviewed_date: ---  ## Highlights - Speaker 1: insurance. It might be that if you happen to get a quote that's too high, you might end up being uninsured or you might be spending more on insurance that you need to be spending. There is sort of a general human cost to these errors, not just in terms of the bottom line for the insurance company. Speaker 2: Well, of course, when you have a noisy underwriting system, then the customer is facing a lottery that the customer has not signed up for. And that is true everywhere. That is wherever people reach a judgment or a decision by using their mind, rather than computing wherever there is judgment, there is noise and there is more of it than you think [(Time 0:07:12)](https://www.airr.io/quote/63c307147f205624b62afd1f) - notes:: Where there is judgment, there is noise. And there is more of it than you think.  - Speaker 1: of candidates on cloudy days and a non academic attributes when the weather is sunny, he titled his paper clouds make nerds look good. Talk about this idea that extraneous factors, whether someone's hungry, what the weather is like, that can affect people's judgment to Speaker 2: Indeed, it's been established in the justice system. If you're a defendant, you have to hope for good weather because on very hot days, judges assigned more severe sentences. And that is true though. Judges are air conditioned, but it's the outside temperature nevertheless seems to have an effect. It's been established in at least one study that for judges who are keen on football, [(Time 0:11:00)](https://www.airr.io/quote/63c30a997f205624b62b5cfa) - notes:: Outside temperature, a.k.a. environmental factors can affect decision, making for those in the judicial system to the detriment of the accused - Speaker 2: is true and it makes it very difficult to believe and to imagine that someone else looking at the same reality is going to see it differently. But in fact, we are struck by how different they are in the context of criminal justice. The variability and sentences is shocking. Speaker 3: But Speaker 2: when you're looking at it from the perspective of a judge who looks at cases individually and feels that he or she is making correct judgments for every case individually, then it looks as if any attempt to restrict their freedom is going to cause [(Time 0:23:53)](https://www.airr.io/quote/63c30ac07f205624b62b64ae) - notes:: Naïve realism: when you’re fundamentally shaken, by the reality, that somebody else’s interpretation of a situation could be fundamentally or radically different from yours, might also be related to cognitive dissonance  - Speaker 1: a mistake is made and algorithms of course can make mistakes and humans can make mistakes. He's saying that you prefer the human to make the mistake. And I think intuitively that feels correct to me. If I'm going to get a misdiagnosis when I go to a doctor, I would feel better if it's the doctor who's made the mistake than an unfeeling unthinking algorithm. Speaker 2: I think that's absolutely true. And you know when we're looking at a road accident we somehow feels less bad about it if it was a driver error than if it was a self driving car that caused the accident algorithms they make errors. The error they make by the way, are different from the errors that people would make and they look stupid to people algorithm make errors that people [(Time 0:31:00)](https://www.airr.io/quote/63c3322b7f205624b62f8153) - notes:: People prefer other people to make mistakes rather than machines and algorithms, I would prefer the machine over the person, because the machine doesn’t have biases and prejudice and if those things are prison, it’s because of its training data, and that can be improved, whereas a humans prejudice.. - Speaker 1: and algorithms of course can make mistakes and humans can make mistakes. He's saying that you prefer the human to make the mistake. And I think intuitively that feels correct to me. If I'm going to get a misdiagnosis when I go to a doctor, I would feel better if it's the doctor who's made the mistake than an unfeeling unthinking algorithm. Speaker 2: I think that's absolutely true. And you know when we're looking at a road accident we somehow feels less bad about it if it was a driver error than if it was a self driving car that caused the accident algorithms they make errors. The error they make by the way, are different from the errors that people would make and they look stupid to people algorithm make errors that people think are [(Time 0:31:01)](https://www.airr.io/quote/63c334c57f205624b62fd76b) - notes:: Where is I feel better about the algorithm because at least in my mistake, I help improve the algorithm because statistically it’s more accurate - Speaker 1: only by studying statistical averages, how do I reduce noise in decisions I am making as an individual? The answer try to make the same decision over and over under different conditions. One way to tell if noises behind my decision to propose marriage is to ask myself whether I would make the same decision under different circumstances, not just on a moonlit night in the springtime, but in the heat of summer or in the dead of winter. If I reach the same answer in these different settings, it's possible I could still be making a mistake, but at least I can be somewhat reassured that my decision is not the result of random extraneous factors. [(Time 0:40:59)](https://www.airr.io/quote/63c337637f205624b630155e) - notes:: A way to reduce random variability noise decision, making in regards to your own decisions, is to make the same decision under variant conditions, and then average out the responses - Speaker 2: The main thing to do if you're attempting to improve the judgment of people in an organization is to convince those people that they want their judgments to be better. If you impose it as a set of rules that all of them will follow. They will resist it. They will feel they're being roboticist and they're likely to sabotage whatever you propose. I mean, this is well known in insurance companies that provide the underwriters in many cases with information or even with the technical price with the suggestion about what premium should be assigned. And underwriters are very likely to completely ignore those and to [(Time 0:48:59)](https://www.airr.io/quote/63c4500b7f205624b64d82cf) - notes:: People don’t like being told what to do and how to do things  --- tags: 📥️/🎧️/🟥️ publish: true aliases: - Our Noisy Minds cover: '' general_subject: specific_subject: source: airr isbn: doi: url: 'https://www.airr.io/episode/60a2df9da10eb714c1b986ac' author: "[[@Hidden Brain]]" guest: publish_date: reviewed_date: ---  ## Highlights - Speaker 1: insurance. It might be that if you happen to get a quote that's too high, you might end up being uninsured or you might be spending more on insurance that you need to be spending. There is sort of a general human cost to these errors, not just in terms of the bottom line for the insurance company. Speaker 2: Well, of course, when you have a noisy underwriting system, then the customer is facing a lottery that the customer has not signed up for. And that is true everywhere. That is wherever people reach a judgment or a decision by using their mind, rather than computing wherever there is judgment, there is noise and there is more of it than you think [(Time 0:07:12)](https://www.airr.io/quote/63c307147f205624b62afd1f) - notes:: Where there is judgment, there is noise. And there is more of it than you think.  - Speaker 1: of candidates on cloudy days and a non academic attributes when the weather is sunny, he titled his paper clouds make nerds look good. Talk about this idea that extraneous factors, whether someone's hungry, what the weather is like, that can affect people's judgment to Speaker 2: Indeed, it's been established in the justice system. If you're a defendant, you have to hope for good weather because on very hot days, judges assigned more severe sentences. And that is true though. Judges are air conditioned, but it's the outside temperature nevertheless seems to have an effect. It's been established in at least one study that for judges who are keen on football, [(Time 0:11:00)](https://www.airr.io/quote/63c30a997f205624b62b5cfa) - notes:: Outside temperature, a.k.a. environmental factors can affect decision, making for those in the judicial system to the detriment of the accused - Speaker 2: is true and it makes it very difficult to believe and to imagine that someone else looking at the same reality is going to see it differently. But in fact, we are struck by how different they are in the context of criminal justice. The variability and sentences is shocking. Speaker 3: But Speaker 2: when you're looking at it from the perspective of a judge who looks at cases individually and feels that he or she is making correct judgments for every case individually, then it looks as if any attempt to restrict their freedom is going to cause [(Time 0:23:53)](https://www.airr.io/quote/63c30ac07f205624b62b64ae) - notes:: Naïve realism: when you’re fundamentally shaken, by the reality, that somebody else’s interpretation of a situation could be fundamentally or radically different from yours, might also be related to cognitive dissonance  - Speaker 1: a mistake is made and algorithms of course can make mistakes and humans can make mistakes. He's saying that you prefer the human to make the mistake. And I think intuitively that feels correct to me. If I'm going to get a misdiagnosis when I go to a doctor, I would feel better if it's the doctor who's made the mistake than an unfeeling unthinking algorithm. Speaker 2: I think that's absolutely true. And you know when we're looking at a road accident we somehow feels less bad about it if it was a driver error than if it was a self driving car that caused the accident algorithms they make errors. The error they make by the way, are different from the errors that people would make and they look stupid to people algorithm make errors that people [(Time 0:31:00)](https://www.airr.io/quote/63c3322b7f205624b62f8153) - notes:: People prefer other people to make mistakes rather than machines and algorithms, I would prefer the machine over the person, because the machine doesn’t have biases and prejudice and if those things are prison, it’s because of its training data, and that can be improved, whereas a humans prejudice.. - Speaker 1: and algorithms of course can make mistakes and humans can make mistakes. He's saying that you prefer the human to make the mistake. And I think intuitively that feels correct to me. If I'm going to get a misdiagnosis when I go to a doctor, I would feel better if it's the doctor who's made the mistake than an unfeeling unthinking algorithm. Speaker 2: I think that's absolutely true. And you know when we're looking at a road accident we somehow feels less bad about it if it was a driver error than if it was a self driving car that caused the accident algorithms they make errors. The error they make by the way, are different from the errors that people would make and they look stupid to people algorithm make errors that people think are [(Time 0:31:01)](https://www.airr.io/quote/63c334c57f205624b62fd76b) - notes:: Where is I feel better about the algorithm because at least in my mistake, I help improve the algorithm because statistically it’s more accurate - Speaker 1: only by studying statistical averages, how do I reduce noise in decisions I am making as an individual? The answer try to make the same decision over and over under different conditions. One way to tell if noises behind my decision to propose marriage is to ask myself whether I would make the same decision under different circumstances, not just on a moonlit night in the springtime, but in the heat of summer or in the dead of winter. If I reach the same answer in these different settings, it's possible I could still be making a mistake, but at least I can be somewhat reassured that my decision is not the result of random extraneous factors. [(Time 0:40:59)](https://www.airr.io/quote/63c337637f205624b630155e) - notes:: A way to reduce random variability noise decision, making in regards to your own decisions, is to make the same decision under variant conditions, and then average out the responses - Speaker 2: The main thing to do if you're attempting to improve the judgment of people in an organization is to convince those people that they want their judgments to be better. If you impose it as a set of rules that all of them will follow. They will resist it. They will feel they're being roboticist and they're likely to sabotage whatever you propose. I mean, this is well known in insurance companies that provide the underwriters in many cases with information or even with the technical price with the suggestion about what premium should be assigned. And underwriters are very likely to completely ignore those and to [(Time 0:48:59)](https://www.airr.io/quote/63c4500b7f205624b64d82cf) - notes:: People don’t like being told what to do and how to do things