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, 1social/post-queue,

(highlight:: People's Understanding of Others' Lives Is Biased Based on the Structure of Their Social Network
Summary:
Social sampling reveals that biases in judgments of the broader population are influenced by the structure of social networks rather than cognitive deficits or motivational biases.
The context of memory shapes this bias, not the content of one's memory.
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
- equity, collective_understanding, bias, polarization, social_networks, availability_bias, perception, memory, 1social/post-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
- decision-making, policy, collective_understanding, network_diversity, perception, policymaking, 1social/post-queue,

(highlight:: The Value of Opinion Diversity Depends on the Complexity of the Problem and How Close Good Solutions
Summary:
Opinions within a group can be both beneficial and detrimental, depending on the task at hand.
Simple tasks, like basic math equations or finding the shortest path, are better solved by following someone knowledgeable. However, most real-life situations require diverse perspectives to achieve optimal solutions.
It's crucial to engage with diverse individuals and explore different options.
On the other hand, for certain straightforward problems, like simple math calculations, it's best to follow the person with the best solution without extensive discussion.
There are instances where excessive diversity hinders progress. Once society reaches a consensus on longstanding issues, like the existence of God or anthropogenic climate change, continuing to invite opinions can be counterproductive. Ultimately, there's a delicate balance between the amount of diversity needed depending on the problem complexity and proximity to a solution.
Transcript:
Speaker 1
But the diversity of opinion in a group is sometimes good, sometimes bad. Again, it depends on the task. Sometimes the task is so simple that we should just follow the one who seems to know the area best, who seems to have the best solution and we will all be better off, like a simple mathematical Equations or finding the shortest way from A to B. But most things in life are more complex than that. There are many ways to bake a cake or to make a new computer or to write a scientific paper or to arrange a political system. And so, zeroing in on a first solution that seems reasonable, it will often lead to suboptimal overall solution for the society. In my work, I like to question concepts, even those that we hold dear, like diversity. And indeed, diversity is important in many real-life contexts, in which we need to solve complex tasks, where there are many possible solutions and many possible ways to go. Then it's really important to surround ourselves with diverse people, to use decision rules that enables us to open up and to explore many different options. However, there is some situation when the solution is there. It is known, I mean, it is easy to know, or maybe it's already found. And maybe there is no need to hear many different opinions about a simple thing like how much is 2 plus 2, or what is the shortest distance between A and B. You should just follow the one who seems to have the best solution. And oftentimes, we will be better off than discussing about it for a long period of time. In this case, this extra diversity is not that good, which brings me to a controversial issue, if you want to. Which is like, once the society comes to a solution to a long-standing problem, such as, is there God? My Catholic family is now giving up on me in creation. Like, is there God? Or should we allow? No, it's anthropogenic climate change happening. There seems to be abundant evidence that this is happening. But somehow, in the society that values diversity, we are still inviting people to have opinions about it. And I wonder, you know, this is a controversial issue at some point, when we reached, when we are close to a particular solution, whether some mechanism for reducing diversity actually Might be better for the society. So I think there is a delicate balance between more diversity, less diversity, depending on the complexity of the problem, on how close we are to the solution.)
- Time 0:30:10
- group_dynamics, diversity_of_opinion, network_diversity, consensus, consent, decision-making, 1todo evernote,

(highlight:: Empirical v.s. Social Truth
Summary:
The distinction between empirical truth (972 beings in a jar) and social truth (driving on the right side of the street) is explored by Jessica Flax.
It highlights how it can be difficult to determine the truth in certain situations.
Transcript:
Speaker 1
Yeah, you know, so much of this is about, you know, I'm reminded of Jessica Flax work on collective computation and talks about the difference between an actual ground truth. You know, there are 972 beings in that jar versus an effective ground truth. Like, we're all going to drive on the right side of the street, because that's what we all agree that we're going to do. And, you know, this is, this is something that's been coming up a lot, is this, the distinction between the empirical and the social in terms of the truth, and how sometimes it's not easy To tell,)
- Time 0:32:38
- empirical_truth, imagined_orders, social_constructs, social_truth, truth,

(highlight:: Smaller Teams Perform Better At Solving Problems With Highly Uncertain Solutions
Summary:
In a study by Casico Palis and Barcausin, they found that when faced with uncertainty about the difficulty of the next task, it is more beneficial to make decisions in small groups rather than rely on a large group or a single leader.
The drawbacks of a large group or an incompetent leader are mitigated in a small group, resulting in optimal performance in various situations.
Transcript:
Speaker 1
And so this paper with Casico Palis and Barcausin shows that when you don't know whether the next task is going to be simple or difficult, it actually is better to make decision in relatively Small groups rather than follow this kind of wisdom of crowd approach where you want to have as large group as possible or to fall over single leader. When you don't know, it's best to have a small group. Somehow in this with a small group the drawbacks of a large group when the problem is difficult or the or of the idiotic leader somehow cancel out and you get the best performance across Across a range of situations.)
- Time 0:35:25
- group_dynamics, problem_solving, group_performanceeffectiveness, uncertainty,

(highlight:: Decision-Making Performance: Share Information Widely, Get Diverse Feedback, Decide in Small Group
Summary:
In the decision-making process, it is important to gather a lot of information from diverse sources.
Once enough information has been collected, smaller groups of experts should make the decisions, rather than having everyone vote. This approach results in better performance.
Transcript:
Speaker 1
So there are two stages of decision process collecting of information where we want to collect as much information as possible to communicate with as many and as many diverse people As possible. And making of a decision, when once we collected enough information so that we are kind of pretty confident at least in the long run we make better-than-chance decisions, then it pays Off statistically, as we show in this paper, to have smaller groups of decision makers. Basically randomly selected from everyone who has sufficient expertise about the topic. So voting is kind of out. Like, you know, this is a, you know, that's what it shows. So if you have 200 people who studied everything about the world, and now they're maybe confident that they will make a little bit better-than-chance decisions, and they need to make 20 decisions about the world, it is actually better that not all 200 vote about each decision, but that to select smaller groups of them to vote about these decisions. And across the 20 decisions they will achieve better performance.)
- Time 0:40:16
- decision-making, diversity_of_opinion, feedback_solicitation, participatory_democracy, policy, policymaking,

(highlight:: Group Performance Depends on Network Connectedness and How Well Information Is Integrated
Summary:
People solving complex problems can perform better in both well connected networks and less connected networks, depending on how they integrate information.
If individuals in a well connected network only follow a few people, they essentially limit their access to information and perform similarly to individuals in a less connected network. However, individuals in a well connected network who actively listen to and integrate information from everyone can get stuck in solutions that may not be optimal in the long run.
By considering the elements of task complexity, social network structure, and human cognition in problem-solving, researchers can reconcile the contradictory findings in the literature.
Transcript:
Speaker 1
Some researchers find that people solving complex problems solve them better if they're well connected to each other, if they work in well connected communities where they constantly Communicate. Other researchers find that it's the opposite, that actually complex problems solve better in networks that are not well connected, where people communicate rarely, they do come In about rarely. So we're wondering, and both of these kinds of findings are published in prestigious journals by prestigious authors. So we're wondering what is, what is the catch? How can this be? And we think that the answer is in the way we integrate information from the, from the group. If you're in a well connected network, but you're following one or two people that currently seem the best, you're essentially not using the whole information in the network. And so it is as if you're basically in a less connected network. If you're in a less connected network, but you are taking care to listen to everyone and to integrate information from everyone, you're essentially, you know, you can actually receive More information than if you're a well connected network, but only listening to one person. And so by introducing this decision rules, this cognitive part, in this traditionally more machine learning, sociology, computational problem, we were able to show that you can Get both effects. So you can be in a well connected network. But if you listen to one or two people, then you, then you will be actually quite good on complex tasks. But if you're in a well connected network, and you also listen to everyone, and integrate information from everyone, you could get stuck, you know, you can maybe like we are today in This world, we are, we are assuming from one solution to the other, everything is changing very fast, and you're, you can get stuck in something that seems like a good solution, but in The long run is not a good solution. So by, by, so the study so far that found the contradictory findings had only two elements, they have task, task complexity and social network structure. And they find that either for complex tasks, either the more connected or less connected network is better, and the findable ways. But now I introduced the first element, that's the human cognition, the way the information is integrated. And so we see that people are using the decision rule that integrates the whole information from a less connected network. They, they solve problems as if they're in a well connected network. And vice versa, people who are in a well connected network, but are not using all of the information from it. It's kind of similar to the situation of the people who are in actually in a less connected network. And basically by introducing, by by seeing this whole complex social system together, the mind, the network, the task, we can, we can, we can explain this apparent contradictions In the literature.)
- Time 0:43:27
- information_dynamics, information_flow, decision-making, group_performanceeffectiveness, network_connectedness, information_integration,

(highlight:: Changing People's Minds: The Social and Semantic Influences That Underly Moral Beliefs
Summary:
Being wrong about climate change is less costly than losing friends over the issue.
Climate change has been tightly related to political ideology, with Democrats and Republicans holding opposing beliefs. Beliefs about vaccinations and gene food are also tied to moral values.
Changing beliefs may require addressing other values or packaging facts in a way that resonates with individuals.
Transcript:
Speaker 1
So being wrong about something might be less costly than losing friends over this issue, especially when it comes to issues such as until relatively recently did not have huge consequences For their life like climate change. So it's fine to be wrong about climate change as long as you can keep your friends. So there is this social network aspect, but then there is also another kind of network, and there's this semantic network. And these are all kinds of different values that we have that are surrounding this issue. So especially climate change famously, and after decades of political manipulation is tightly related to political ideology, and Democrats believe one thing, Republicans believe One thing, whereas the issue of climate change should not be related to any political ideology. It's a human natural phenomenon that has nothing to do with political ideology, but it is in our heads. It is related in a way you cannot be a good Republican if you're believing in other words, any climate change, and you cannot be a good Democrat if you're not believing in it. Similar to it is in a similar way, beliefs about vaccinations and about gene food are related to our moral values of fairness, whether something is natural, whether something is in Line with our tradition, whether somebody's profiting over some people without much power, whether we have freedom to decide and so on. And so changing beliefs about vaccinations, for example, or climate change might actually require to first change other beliefs around that issue so that people can open up and take The scientific fact. Or the fact needs to be packaged in such a way so that it somehow resonates with other values people have.)
- Time 0:55:10
- moral_foundationsbeliefs, bias, influence, moral_behavior, belief_changerevision,

(highlight:: Theories Are Like Toothbrushes - Everybody Has Their Own and No One Wants to Use Anyone Else's
Summary:
In psychology, there is a saying that theories are like toothbrushes.
Each person has their own and doesn't want to use anyone else's.
Transcript:
Speaker 1
At the same time, there is a saying in psychology, which I noticed now in Santa Fe, that it's not present in many other communities, that theories are like toothbrushes. Everybody has their own, and nobody wants to use anyone's else.)
- Time 1:15:39
- academics, analogies, funny, theories,

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, 1social/post-queue,

(highlight:: People's Understanding of Others' Lives Is Biased Based on the Structure of Their Social Network
Summary:
Social sampling reveals that biases in judgments of the broader population are influenced by the structure of social networks rather than cognitive deficits or motivational biases.
The context of memory shapes this bias, not the content of one's memory.
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
- equity, collective_understanding, bias, polarization, social_networks, availability_bias, perception, memory, 1social/post-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
- decision-making, policy, collective_understanding, network_diversity, perception, policymaking, 1social/post-queue,

(highlight:: The Value of Opinion Diversity Depends on the Complexity of the Problem and How Close Good Solutions
Summary:
Opinions within a group can be both beneficial and detrimental, depending on the task at hand.
Simple tasks, like basic math equations or finding the shortest path, are better solved by following someone knowledgeable. However, most real-life situations require diverse perspectives to achieve optimal solutions.
It's crucial to engage with diverse individuals and explore different options.
On the other hand, for certain straightforward problems, like simple math calculations, it's best to follow the person with the best solution without extensive discussion.
There are instances where excessive diversity hinders progress. Once society reaches a consensus on longstanding issues, like the existence of God or anthropogenic climate change, continuing to invite opinions can be counterproductive. Ultimately, there's a delicate balance between the amount of diversity needed depending on the problem complexity and proximity to a solution.
Transcript:
Speaker 1
But the diversity of opinion in a group is sometimes good, sometimes bad. Again, it depends on the task. Sometimes the task is so simple that we should just follow the one who seems to know the area best, who seems to have the best solution and we will all be better off, like a simple mathematical Equations or finding the shortest way from A to B. But most things in life are more complex than that. There are many ways to bake a cake or to make a new computer or to write a scientific paper or to arrange a political system. And so, zeroing in on a first solution that seems reasonable, it will often lead to suboptimal overall solution for the society. In my work, I like to question concepts, even those that we hold dear, like diversity. And indeed, diversity is important in many real-life contexts, in which we need to solve complex tasks, where there are many possible solutions and many possible ways to go. Then it's really important to surround ourselves with diverse people, to use decision rules that enables us to open up and to explore many different options. However, there is some situation when the solution is there. It is known, I mean, it is easy to know, or maybe it's already found. And maybe there is no need to hear many different opinions about a simple thing like how much is 2 plus 2, or what is the shortest distance between A and B. You should just follow the one who seems to have the best solution. And oftentimes, we will be better off than discussing about it for a long period of time. In this case, this extra diversity is not that good, which brings me to a controversial issue, if you want to. Which is like, once the society comes to a solution to a long-standing problem, such as, is there God? My Catholic family is now giving up on me in creation. Like, is there God? Or should we allow? No, it's anthropogenic climate change happening. There seems to be abundant evidence that this is happening. But somehow, in the society that values diversity, we are still inviting people to have opinions about it. And I wonder, you know, this is a controversial issue at some point, when we reached, when we are close to a particular solution, whether some mechanism for reducing diversity actually Might be better for the society. So I think there is a delicate balance between more diversity, less diversity, depending on the complexity of the problem, on how close we are to the solution.)
- Time 0:30:10
- group_dynamics, diversity_of_opinion, network_diversity, consensus, consent, decision-making, 1todo evernote,

(highlight:: Empirical v.s. Social Truth
Summary:
The distinction between empirical truth (972 beings in a jar) and social truth (driving on the right side of the street) is explored by Jessica Flax.
It highlights how it can be difficult to determine the truth in certain situations.
Transcript:
Speaker 1
Yeah, you know, so much of this is about, you know, I'm reminded of Jessica Flax work on collective computation and talks about the difference between an actual ground truth. You know, there are 972 beings in that jar versus an effective ground truth. Like, we're all going to drive on the right side of the street, because that's what we all agree that we're going to do. And, you know, this is, this is something that's been coming up a lot, is this, the distinction between the empirical and the social in terms of the truth, and how sometimes it's not easy To tell,)
- Time 0:32:38
- empirical_truth, imagined_orders, social_constructs, social_truth, truth,

(highlight:: Smaller Teams Perform Better At Solving Problems With Highly Uncertain Solutions
Summary:
In a study by Casico Palis and Barcausin, they found that when faced with uncertainty about the difficulty of the next task, it is more beneficial to make decisions in small groups rather than rely on a large group or a single leader.
The drawbacks of a large group or an incompetent leader are mitigated in a small group, resulting in optimal performance in various situations.
Transcript:
Speaker 1
And so this paper with Casico Palis and Barcausin shows that when you don't know whether the next task is going to be simple or difficult, it actually is better to make decision in relatively Small groups rather than follow this kind of wisdom of crowd approach where you want to have as large group as possible or to fall over single leader. When you don't know, it's best to have a small group. Somehow in this with a small group the drawbacks of a large group when the problem is difficult or the or of the idiotic leader somehow cancel out and you get the best performance across Across a range of situations.)
- Time 0:35:25
- group_dynamics, problem_solving, group_performanceeffectiveness, uncertainty,

(highlight:: Decision-Making Performance: Share Information Widely, Get Diverse Feedback, Decide in Small Group
Summary:
In the decision-making process, it is important to gather a lot of information from diverse sources.
Once enough information has been collected, smaller groups of experts should make the decisions, rather than having everyone vote. This approach results in better performance.
Transcript:
Speaker 1
So there are two stages of decision process collecting of information where we want to collect as much information as possible to communicate with as many and as many diverse people As possible. And making of a decision, when once we collected enough information so that we are kind of pretty confident at least in the long run we make better-than-chance decisions, then it pays Off statistically, as we show in this paper, to have smaller groups of decision makers. Basically randomly selected from everyone who has sufficient expertise about the topic. So voting is kind of out. Like, you know, this is a, you know, that's what it shows. So if you have 200 people who studied everything about the world, and now they're maybe confident that they will make a little bit better-than-chance decisions, and they need to make 20 decisions about the world, it is actually better that not all 200 vote about each decision, but that to select smaller groups of them to vote about these decisions. And across the 20 decisions they will achieve better performance.)
- Time 0:40:16
- decision-making, diversity_of_opinion, feedback_solicitation, participatory_democracy, policy, policymaking,

(highlight:: Group Performance Depends on Network Connectedness and How Well Information Is Integrated
Summary:
People solving complex problems can perform better in both well connected networks and less connected networks, depending on how they integrate information.
If individuals in a well connected network only follow a few people, they essentially limit their access to information and perform similarly to individuals in a less connected network. However, individuals in a well connected network who actively listen to and integrate information from everyone can get stuck in solutions that may not be optimal in the long run.
By considering the elements of task complexity, social network structure, and human cognition in problem-solving, researchers can reconcile the contradictory findings in the literature.
Transcript:
Speaker 1
Some researchers find that people solving complex problems solve them better if they're well connected to each other, if they work in well connected communities where they constantly Communicate. Other researchers find that it's the opposite, that actually complex problems solve better in networks that are not well connected, where people communicate rarely, they do come In about rarely. So we're wondering, and both of these kinds of findings are published in prestigious journals by prestigious authors. So we're wondering what is, what is the catch? How can this be? And we think that the answer is in the way we integrate information from the, from the group. If you're in a well connected network, but you're following one or two people that currently seem the best, you're essentially not using the whole information in the network. And so it is as if you're basically in a less connected network. If you're in a less connected network, but you are taking care to listen to everyone and to integrate information from everyone, you're essentially, you know, you can actually receive More information than if you're a well connected network, but only listening to one person. And so by introducing this decision rules, this cognitive part, in this traditionally more machine learning, sociology, computational problem, we were able to show that you can Get both effects. So you can be in a well connected network. But if you listen to one or two people, then you, then you will be actually quite good on complex tasks. But if you're in a well connected network, and you also listen to everyone, and integrate information from everyone, you could get stuck, you know, you can maybe like we are today in This world, we are, we are assuming from one solution to the other, everything is changing very fast, and you're, you can get stuck in something that seems like a good solution, but in The long run is not a good solution. So by, by, so the study so far that found the contradictory findings had only two elements, they have task, task complexity and social network structure. And they find that either for complex tasks, either the more connected or less connected network is better, and the findable ways. But now I introduced the first element, that's the human cognition, the way the information is integrated. And so we see that people are using the decision rule that integrates the whole information from a less connected network. They, they solve problems as if they're in a well connected network. And vice versa, people who are in a well connected network, but are not using all of the information from it. It's kind of similar to the situation of the people who are in actually in a less connected network. And basically by introducing, by by seeing this whole complex social system together, the mind, the network, the task, we can, we can, we can explain this apparent contradictions In the literature.)
- Time 0:43:27
- information_dynamics, information_flow, decision-making, group_performanceeffectiveness, network_connectedness, information_integration,

(highlight:: Changing People's Minds: The Social and Semantic Influences That Underly Moral Beliefs
Summary:
Being wrong about climate change is less costly than losing friends over the issue.
Climate change has been tightly related to political ideology, with Democrats and Republicans holding opposing beliefs. Beliefs about vaccinations and gene food are also tied to moral values.
Changing beliefs may require addressing other values or packaging facts in a way that resonates with individuals.
Transcript:
Speaker 1
So being wrong about something might be less costly than losing friends over this issue, especially when it comes to issues such as until relatively recently did not have huge consequences For their life like climate change. So it's fine to be wrong about climate change as long as you can keep your friends. So there is this social network aspect, but then there is also another kind of network, and there's this semantic network. And these are all kinds of different values that we have that are surrounding this issue. So especially climate change famously, and after decades of political manipulation is tightly related to political ideology, and Democrats believe one thing, Republicans believe One thing, whereas the issue of climate change should not be related to any political ideology. It's a human natural phenomenon that has nothing to do with political ideology, but it is in our heads. It is related in a way you cannot be a good Republican if you're believing in other words, any climate change, and you cannot be a good Democrat if you're not believing in it. Similar to it is in a similar way, beliefs about vaccinations and about gene food are related to our moral values of fairness, whether something is natural, whether something is in Line with our tradition, whether somebody's profiting over some people without much power, whether we have freedom to decide and so on. And so changing beliefs about vaccinations, for example, or climate change might actually require to first change other beliefs around that issue so that people can open up and take The scientific fact. Or the fact needs to be packaged in such a way so that it somehow resonates with other values people have.)
- Time 0:55:10
- moral_foundationsbeliefs, bias, influence, moral_behavior, belief_changerevision,

(highlight:: Theories Are Like Toothbrushes - Everybody Has Their Own and No One Wants to Use Anyone Else's
Summary:
In psychology, there is a saying that theories are like toothbrushes.
Each person has their own and doesn't want to use anyone else's.
Transcript:
Speaker 1
At the same time, there is a saying in psychology, which I noticed now in Santa Fe, that it's not present in many other communities, that theories are like toothbrushes. Everybody has their own, and nobody wants to use anyone's else.)
- Time 1:15:39
- academics, analogies, funny, theories,