People have more accurate models of people in close proximity than they do of people far away (socially
Summary:
People have a good understanding of their friends and are accurate in predicting their behavior.
This is shown by their ability to accurately predict election results based on their friends' voting preferences. However, biases arise when people are asked to judge unfamiliar populations.
These biases can be attributed to the structure of their personal social networks.
The more biased their social networks are, the more biased their estimates of the general population will be.
Transcript:
Speaker 1
Oh yeah, after seven years of research on this paper, that people actually have a quite a good idea about their friends, family, acquaintances, people that they meet on every day basis And then we'd whom they need to cooperate with, learn from or avoid. And that they're actually not that not as biased as a traditional social psychology would like us to think. And we see that because when we ask people about their friends, we see that this predicts societal trends quite well. So in one line of research, we asked a national probabilistic sample of people to tell us who their friends are going to vote for. We average those things across the national sample and got better prediction of election results than when we asked people about their own behavior. And this would not have happened if people were biased in reporting their friends. They must have told us something that must have given us information that's accurate and that's goes beyond their own behavior in order for that to happen to predict the elections better. And by now we saw that in four further, so we five elections all together in the US 2016 in France, the Netherlands, the Sweden and US 2018, and we hope to predict again 2020. So things like that tell us that people are actually pretty good in understanding their social circles and then the apparent biases show up when people are asked to judge people that They don't know so well. So when I'm asked to tell you something about people in another state or another country or people from another socioeconomic cluster, which I don't know well, then I am likely to have Some biases. But these biases we show can be explained by what I know about my friends. So if you ask me something like that, I will really try to answer your question honestly. And to do that, I will try to recall from my memory everything that I know about our social my social world. But you know, if I'm surrounded by rich people like here on the East side of Santa Fe, it could be very difficult to imagine in what poverty people can live in other parts. And so even if I'm trying my best to recall, you know, the most poor person I know, I might never recall such poverty that actually exists in the world. And when asked about the overall level of income in the US, I'm likely to overestimate the overall level. And similarly, if you are poor, you're people who are poor might have problems imagining the wealth of really rich people and they will typically underestimate the wealth of the country. So okay, so let me let me summarize this. So this piece actually suggests that people are not that biased when it comes to judging their immediate friends. They have a lot of useful information about their friends and pretty accurate. The bias is show up when people are asked about other populations that they don't know so well. And they can be mostly explained by the structure of their own personal social networks. The more biased your social networks are, the more biased your estimates will be about the general population.)
- Time 0:13:58
- collective_understanding, perception, social_networks, 1socialpost-queue,

(highlight:: People's Understanding of Others' Lives Is Biased Based on the Structure of Their Social Network
Transcript:
Speaker 1
So there's something in that that I found really interesting about this social sampling, which is that as you mentioned, like if you happen to be worse off and everyone else is worse Off, as is the case with like income, for example, then being worse off, you're going to project your bias into that general population more accurately than if you're better off in some Situation for which the most of the population is worse off. And that these biases are not all created equal. Yes. It has to do with how they stand relative to the broader population. So what we show is that this kind of biases of judgments of the broader population can be explained by the structure of social network and not by some cognitive deficit or motivational, Motivational bias, some desire to be better than others or that or some idea that everybody's like me or some cognitive deficit that people cannot, that people are too stupid to understand How other people live. It's really determined by the context of memory, that by the content of one's memory, which comes from one social circle.)
- Time 0:17:09
- availability_bias, bias, collective_understanding, equity, memory, perception, polarization, social_networks, 1socialpost-queue,

(highlight:: The people with the most accurate models of others tend to have diverse social networks
Summary:
To correct for this handicap, we need to listen to the oppressed in the population.
This includes laborers, students, and others who are usually not given a political voice. By expanding our social networks to include more diverse perspectives, policymakers can make better decisions based on a deeper understanding of societal trends and people's desires.
Transcript:
Speaker 1
But it sounds like this gives us a really clear pointer on how to correct for this handicap. And that we really ought to be like, perhaps when it comes time to make decisions on behalf of everyone, we should really be listening to whomever the oppressed are in that population. We should be really paying attention, for example, to laborers and students and people that are ordinarily not historically, not given a lot of political voice. And what you're saying, yeah, it's in other words, what we need to do is broader our social networks include in our social networks, those people who are typically not there. So if the policymakers who are making these important decisions should know as many different people as possible. And we show in related studies that people who have most diverse social circles are also best able to predict societal trends and to understand how the overall population lives and What people want.)
- Time 0:18:32
- collective_understanding, decision-making, network_diversity, perception, policy, policymaking, 1socialpost-queue,

People have more accurate models of people in close proximity than they do of people far away (socially
Summary:
People have a good understanding of their friends and are accurate in predicting their behavior.
This is shown by their ability to accurately predict election results based on their friends' voting preferences. However, biases arise when people are asked to judge unfamiliar populations.
These biases can be attributed to the structure of their personal social networks.
The more biased their social networks are, the more biased their estimates of the general population will be.
Transcript:
Speaker 1
Oh yeah, after seven years of research on this paper, that people actually have a quite a good idea about their friends, family, acquaintances, people that they meet on every day basis And then we'd whom they need to cooperate with, learn from or avoid. And that they're actually not that not as biased as a traditional social psychology would like us to think. And we see that because when we ask people about their friends, we see that this predicts societal trends quite well. So in one line of research, we asked a national probabilistic sample of people to tell us who their friends are going to vote for. We average those things across the national sample and got better prediction of election results than when we asked people about their own behavior. And this would not have happened if people were biased in reporting their friends. They must have told us something that must have given us information that's accurate and that's goes beyond their own behavior in order for that to happen to predict the elections better. And by now we saw that in four further, so we five elections all together in the US 2016 in France, the Netherlands, the Sweden and US 2018, and we hope to predict again 2020. So things like that tell us that people are actually pretty good in understanding their social circles and then the apparent biases show up when people are asked to judge people that They don't know so well. So when I'm asked to tell you something about people in another state or another country or people from another socioeconomic cluster, which I don't know well, then I am likely to have Some biases. But these biases we show can be explained by what I know about my friends. So if you ask me something like that, I will really try to answer your question honestly. And to do that, I will try to recall from my memory everything that I know about our social my social world. But you know, if I'm surrounded by rich people like here on the East side of Santa Fe, it could be very difficult to imagine in what poverty people can live in other parts. And so even if I'm trying my best to recall, you know, the most poor person I know, I might never recall such poverty that actually exists in the world. And when asked about the overall level of income in the US, I'm likely to overestimate the overall level. And similarly, if you are poor, you're people who are poor might have problems imagining the wealth of really rich people and they will typically underestimate the wealth of the country. So okay, so let me let me summarize this. So this piece actually suggests that people are not that biased when it comes to judging their immediate friends. They have a lot of useful information about their friends and pretty accurate. The bias is show up when people are asked about other populations that they don't know so well. And they can be mostly explained by the structure of their own personal social networks. The more biased your social networks are, the more biased your estimates will be about the general population.)
- Time 0:13:58
- collective_understanding, perception, social_networks, 1socialpost-queue,

(highlight:: People's Understanding of Others' Lives Is Biased Based on the Structure of Their Social Network
Transcript:
Speaker 1
So there's something in that that I found really interesting about this social sampling, which is that as you mentioned, like if you happen to be worse off and everyone else is worse Off, as is the case with like income, for example, then being worse off, you're going to project your bias into that general population more accurately than if you're better off in some Situation for which the most of the population is worse off. And that these biases are not all created equal. Yes. It has to do with how they stand relative to the broader population. So what we show is that this kind of biases of judgments of the broader population can be explained by the structure of social network and not by some cognitive deficit or motivational, Motivational bias, some desire to be better than others or that or some idea that everybody's like me or some cognitive deficit that people cannot, that people are too stupid to understand How other people live. It's really determined by the context of memory, that by the content of one's memory, which comes from one social circle.)
- Time 0:17:09
- availability_bias, bias, collective_understanding, equity, memory, perception, polarization, social_networks, 1socialpost-queue,

(highlight:: The people with the most accurate models of others tend to have diverse social networks
Summary:
To correct for this handicap, we need to listen to the oppressed in the population.
This includes laborers, students, and others who are usually not given a political voice. By expanding our social networks to include more diverse perspectives, policymakers can make better decisions based on a deeper understanding of societal trends and people's desires.
Transcript:
Speaker 1
But it sounds like this gives us a really clear pointer on how to correct for this handicap. And that we really ought to be like, perhaps when it comes time to make decisions on behalf of everyone, we should really be listening to whomever the oppressed are in that population. We should be really paying attention, for example, to laborers and students and people that are ordinarily not historically, not given a lot of political voice. And what you're saying, yeah, it's in other words, what we need to do is broader our social networks include in our social networks, those people who are typically not there. So if the policymakers who are making these important decisions should know as many different people as possible. And we show in related studies that people who have most diverse social circles are also best able to predict societal trends and to understand how the overall population lives and What people want.)
- Time 0:18:32
- collective_understanding, decision-making, network_diversity, perception, policy, policymaking, 1socialpost-queue,