maybe a few floors above us and yeah so yeah is it everything ready yeah okay perfect so I'm still on it can you can you speak hi can you hear me yes we can Alex perfect so all right so I shut my screen yeah if you can please I think I can we'll see do you see yeah we do we do we do so our Zoom speaker Zoom but closed-room speaker of today it's Alexander Stewart and he comes from the University of St Andrews and he's going to talk about models for the onset and resolution of effective polarizing all right thank you very much everyone I'm sorry I'm not down there in person I have been feeling very unwell last night in this morning and I was worried I had COVID I do not I should emphasize but I'm nonetheless not feeling great so I figured it was probably better for everyone if I stay up here and talk to you from a distance so yeah I'm gonna talk about some modeling work that I've done with some collaborators looking at the relationship between polarization and inequality so why talk about polarization it's a workshop in inequality and to some extent we've already answered that question we've had other talks that discussed polarization in some depth and I don't think it's necessarily a sort of counterintuitive idea that polarization and equality should be linked but I do just want to flag up one one strand of the empirical case for the relationship which is shown in the figure here can people see my mouse by the way yeah okay so this is taken from Nolan McCarty's book polarization what everyone needs to know and the models I'm gonna show you are done in collaboration with Nolan and some other people although of course the usual caveat applies that anything that sucks about them is my fault not theirs but what this figure here shows is in red we have the degree of polarization in the United States over the course of the century from 1917 to 2017 polarization here is elite polarization it's measured using the DW nominate metric which captures the extent to which political parties in Congress are polarized and plotted against it are both the genie coefficients in the United States in blue and the income share of the top 1% of taxpayers in green and what you see is that both polarization by these by this DW nominate measure and inequality by these two similar measures follow a u-shaped distribution in the United States over the course of that century now of course just because two things trend in the same direction doesn't mean they're causally related but it is very suggestive especially because there's good a priori reasons to think that polarization and inequality should interact with each other so what is what could be the causal relationship between polarization and inequality well inequality may cause polarization by exam is exacerbating tensions between groups with different levels of wealth polarization may increase inequality by preventing redistributive policy and when polarization leads to legislative deadlock is arguably it has in the United States over the past decades reversing it may become a necessary but not sufficient condition for tackling high levels of inequality so the work I'm going to show you is trying to unpack this relationship the dynamics that arise from this interaction between inequality inequality and polarization using mathematical and computational models the work I'm going to present is based mostly on these two papers and which if you want to I'm obviously not going to have time to go into infinite detail here so if you want to get into the details of these models I very much encourage you to look and of course site these papers and I'm not going to show I'm not going to show a great deal of data here because although I emphasized in my introduction introducing myself and my research that I'm very keen on collecting mechanistic models to data the data side of it is still sort of ongoing and so I will talk about future plans but not really any many results along those lines so my talk is going to be split into three parts time permitting in the first part I'm going to talk about models of mass polarization and in particular I'm going to focus on effective polarization as instantiated in as a form of loss of cooperation and then I'm going to talk about the relationship between risk aversion identity and sorting and I'll explain what what those terms mean in this context in a moment in part who I'm going to talk about the relationship between inequality and polarization I'm going to show that polarization can be sticky under some fairly simple assumptions and that when it is and that the polarization can exacerbate the effects of inequality and then finally I'm going to talk about the bit that everybody always asks when you talk about these models is alright so what what does that tell us about how we fix polarization and I'm going to talk about redistribution as a preventive but not corrective measure for fixing polarization and then I'm going to show briefly some new results on how we can use heterogeneity and influence to a modeling of a modeling of good behavior as a way to potentially reverse polarization so polarization in public discourse tends to refer nebulously to a wide range of interconnected phenomena we talk about polarization a lot but we don't necessarily obviously in this audience we do but in in general discourse we don't necessarily pin down exactly what we mean and so I'm going to talk about polarization and think about polarization in at least three interrelated but distinct ways the first way is I'm going to refer to a sorting which is clustering of people into competing groups typically aligned with a political identity antagonism between identity groups so this is known as effective polarization and is usually measured by asking for example in the US case Republicans and Democrats to rate their attitudes towards the political outgroup and their political in group on a zero to 100 feelings thermometer and looking at the difference between those two numbers and when the difference between those two numbers is large that means you like your in group a lot and you dislike your outgroup a lot and then of course the sense of polarization which we saw in the first slide in which distinct clusters of policy preferences arise in a group or population and I refer to this as ideological polarization so obviously all of those things interact with each other but they are also clearly distinct and of course it's also important to talk about who we're interested in being polarized so this could we could talk about mass polarization i.e. voters as opposed to political elites or we could talk about political elites and so in this talk I'm going to focus mainly on mass polarization and I'm mainly going to focus on effective polarization and sorting and I'm going to defer that there's any discussion of elite polarization and ideological polarization to discussion or to another time and what we're particularly going to be interested in trying to capture in these models and what's originally motivated these models is how things like inequality and more generally this term economic anxiety which is not a great term but it's a commonly used term how these this kind of idea of economic anxiety can lead to polarization and we're going to conceptualize polarization for the purposes of this talk as willingness to cooperate with political in versus outgroup so we're going to be interested in the population dynamics of polarized attitudes so we're inherently adopting a mechanistic worldview here i.e. we're thinking that ideas and attitudes emerge and spread in a population through a process that is less than rational i.e. we're thinking of the spread of polarization as something more like an epidemiological process as opposed to a decision-theoretic rational process and the mechanism of spread that we're going to focus on for the purposes of these models is utility based social learning so what do I mean by that? Well I mean something relatively simple we're going to assume that social learning occurs through observing and imitating others and that payoff-based or utility-based imitation occurs according to this function where the probability that a player i imitates a player j's strategy is equal to 1 over 1 plus e to the sigma wi minus wj where wi and wj are the utilities of the respective players and sigma is a global parameter that basically controls the strength of selection or the amount of noise in the imitation process so it's not super important that you i'm not going to dwell on the details of the math but it is i think useful for people who are familiar with these models to just see what we're assuming and the key thing that we're going to assume about the utility function is that it is non-linear and s-shaped and that's the and that it is and that utility of all individuals in the population arises both from their interactions their cooperative or not interactions with other people and also from some sort of underlying state of the environment so utility arises from multiple social interactions with during a given period of time and also the underlying economic environments and we assume that it follows qualitatively the form shown in this figure where when the underlying environment is is bad when you're down here where my cursor is then your utility is low and as the underlying environment increases utility increases and what the effect that this has is that when you are when the underlying environment is very good you're sort of risk neutral so you don't you know you neither risk tolerance or nor risk averse but as you start to approach this cliff here where your utility decreases rapidly with the underlying environments you become risk averse and then as you get down close to zero you become risk tolerant so that's just to do with the curvature of the utility function but this assumption that you took the level of risk aversion that's a population feels varies with the underlying environment is key for studying this question of how so-called economic anxiety and inequality interact with polarization in our model so that's the utility as I said utility arises from a combination of the underlying environments and from social interactions occurring between members of the population so we're going to assume that these social interactions take the form of cooperative cooperation in which individuals choose whether to interact with members of their in-group or members of their out-group with a probability p and if they do choose to interact with a member of their in-group then the success of that interaction that's sorry that interaction is successful with a probability qi to generate a benefit bi and it fails with probability 1 minus qi and for out-group interactions the probability of success is different it's qo and the benefit that you generate is qo and in particular what we assume is that when you choose to engage in out-group interactions those interactions are more risky but more beneficial so why do we assume that well this is basically a priori assumption that we assumed to capture the idea that polarization can in principle be generated by risk aversion by economic anxiety so in order for a risk aversion to generate high levels of polarization i.e. to generate a high level of interactions with in-groups as opposed to out-groups you need to assume something like this you need to assume that out-group interactions are perceived as more risky or are in fact more risky than in-group interactions and then so the level of polarization in our model is measured via this parameter p which is the each individual in the population strategy and we also make an additional assumption that in order for an out-group interaction to successfully occur both players have to be willing to participate in it i.e. if polarization is equal to or close to one for all members of the population then even if one individual decides to try not being polarized they won't get anywhere because of the members of the population that are not willing to interact with them so i've thrown a lot of information at you i hope it's not too confusing but this is the basic setup of the model which i just wanted to give you a sense of before i start to move on to some of the results i guess i'll kind of skip over the additional mathematical descriptions here because i want to get to the actual things that we find but we have this utility function which i showed you before and we parameterize it in a particular way that depends both on the underlying environment and the benefits that arise from these social interactions that i just described to you and then a particular individual's utility depends on their strategy individual i that has a utility wi that depends on their strategy pi and the probabilities of success and failure of interactions and of this utility function f and i'm not going to belabor that because i don't really have time to go into it so the basic thing to understand about this model is that if most players have high levels of polarization meaning p is equal to one or close to one interactions will tend to remain within group and that means that polarization is high because people don't attempt to cooperate with people outside of their political in group if most players have a low level of polarization p equals zero that means interactions occur commonly between groups and we think of polarization as being low and what we want to study is the population dynamics of this level of polarization p under different underlying environments theta so these social learning models are stochastic and complicated to analyze and we use a combination of agent-based modeling and adaptive dynamics to do so i'm again i'm not going to belabor that but i can return to it in the discussion if people are interested but what we find when we carry out this analysis that combines sort of adaptive dynamics analysis if that means anything to anyone and agent-based modeling yes ask a question just to clarify so when you imitate you copy also p yeah you copy p that's exactly right so the imitation process is the copying of another player's strategy and in this context you call it's it's p and i realize now that my notation is actually bad because i also use p to mean the probability of copying sorry about that but yes you copy p okay great okay so now now what we can do is look at the the dynamics of the the polarization the level of polarization p in the whole population as a function of the underlying which we call this the economic environment theta and so at the top on if you look at this figure on the right you see this is a sort of phase diagram i've labeled roughly the regions where the underlying utility function is risk tolerance risk averse or risk neutral respectively and what you see is that if you're in the risk neutral region you have bi-stability where both low polarization and high polarization is is stable so if you initialize your population in this white region here where my cursor is p will evolve down to zero if you initialize it in the blue region p will evolve up to one similarly in the risk tolerant regime you see that there's a there's bi-stability there's a very small region under these parameters in which if you start just up here where my cursor is p will evolve to high levels of polarization if you start in this big white region you'll evolve to low levels of polarization however if you're in the risk averse region the bi-stability disappears and you only evolve towards and i'm using evolve here to mean population dynamics change over time you only evolve towards p equals one i.e. you only ever evolve to high levels of polarization there's no longer any bi-stability why is that important well it's important because if we consider a time-varying economic environment so here in this figure at the bottom we have theta the economic underlying environment varying sort of sigmoidally um so initially the environment is good so we're risk tolerance and if we initialize our population this is the this is the level of polarization as a result of agent based simulations we initialize our population in the basin of attraction for low polarization you tend to stay there until the environment becomes sufficiently bad that you end up in the risk averse regime in which case you tend to evolve towards high levels of polarization and when you the system um when so when theta goes back up to high levels of um um this is to being a good environment again you don't go back to the low levels of polarization because of this bi-stability so you start off down here say but then the environment gets worse so then you end up following this arrow up here and then when the environment improves again you're still up here stuck in the stuck in the high levels of polarization um due to the bi-stability and so what you see in this model is first of all that polarization can arise from um essentially economic anxiety from risk aversion in certain underlying environmental states and that polarization is sticky in the sense that once it emerges in the population it doesn't disappear when the environment improves again and so this is obviously bad but um I think sort of an interesting um hypothesis about the nature it generates in the interesting hypothesis about the nature of polarization and the relationship between things like economic anxiety and polarization okay so so far we've made implicitly made some very simplistic assumptions about the nature of identity in particular that political in-groups and political out-groups are the only feature of identity that matters and that people make their decisions about who to cooperate with based on political identities this is obviously not reasonable uh and not a reasonable account um of reality and it doesn't allow us to study other forms of polarization than effective polarization such as sorting which as I mentioned is the sort of alignments between political identities and other forms of identity so in order to capture this we um made our model more complicated and allowed um identities to be multi-dimensional such that in-groups encompass multiple fat sets of identity possibly including political party but also including other features of identity that are not to do with politics could be race religion etc and what we study is and we assume rather that an individual strategy is not only their willingness to interact without groups so there's probability p but also their political identity so we allow them to both switch political identity and to switch their willingness to interact without groups now this gets rather complicated so I'm not going to go into it in detail but I do just want to flag up one particular result that we get when we once we make this complicated more complicating assumption so we keep fixed group identities such as race or religion allow party identities to change over time and we look at how both the level of sorting i.e the alignment between fixed features of identity and political identity change alongside the degree of effective polarization i.e the willingness to cooperate without groups and what we find is that in all of the regime's um risk tolerant risk averse or risk neutral the we will see evolution of high levels of sorting which is given so the here in all of these three figures we're showing um the the the possible trajectory is that the population can undergo the red dots indicate stable equilibria and so you see that sorting i.e the alignment between fixed forms of identity and political identity reaches high levels it's symmetrical because you we we don't assume any particular bias in one way or the other um and we also see we get this by stability in the risk tolerance and risk neutral regimes why is this important well the reason it's important is that it suggests and I don't really have time to go into the details of this but I'd be happy to discuss it with you is that as political identity becomes more salience in decision making at the expense of other forms of identity um what that means is that we will see increased levels of sorting um along such that political identities align with other forms of identity and that is precisely what we see in the United States over the course of more or less the last century depending depending on which of these figures you're looking at so here what we are showing is the degree of racial polarization as measured by um on the left here as measured by um the same kind of feelings thermometer type questions that define effective polarization so you ask people their opinions about racial outgroups and this is specifically showing the responses for white people in the United States about other racial outgroups over the course of sort of like 1960 to 2020 and we see that the expressed level of polarization racial polarization in this sense is decreasing over time but at the same time effective polarization is increasing and the degree of sorting i.e. the tendency of race to align with per political identity is also increasing and so what this suggests is that we're seeing political identity becoming more salient in the way that people think about themselves and think about others that's leading to greater levels of sorting and rather than actually say oh right whilst if you just looked at the left hand figure this would suggest a sort of positive world view in which the world is becoming less racially polarized what we think is actually happening here is that um racial political identity is becoming a proxy for race essentially and so the effective polarization is a sort of more acceptable way of expressing racial dislike which is great um okay so i've talked a lot about polarization and sorting affect polarization and sorting but this is a workshop on inequality so what about the relationship between polarization and inequality so we go what we're going to do now is take the same basic model that i've described to you again rather quickly and we're going to instantiate the idea of inequality by assuming that different subgroups of the population experience different underlying environments theta and we're also in order to study the relationship between polarization inequality and redistribution we're going to also assume that there's a possibility of redistribution via public goods at rate alpha such that the group um in the if we increase the amounts of redistribution we we improve the environments of the people experiencing the worst underlying environments and make and decrease the economic environments of the people in the good environments so the first question we want to ask is is this kind of inequality sufficient to generate polarization in our model and secondly we want to ask can redistribution make things better and i'm sort of giving away the answer to the first question by asking the second yes inequality can generate polarization in our model and then we're going to ask can redistribution make things better so to capture this idea of inequality and redistribution we assume that the underlying economic environment um theta depends on again i'm not going to go into this in detail but happy to discuss later um redistribution from these cooperative interactions between members of the population um plus a baseline environment theta zero minus a baseline environment theta zero so what we're doing what we then do here in this figure is compare the first of all on the left the level of polarization evolving over time in a scenario where there's inequality in the sense that some people experience a bad environment and some people experience a good environment um and we're comparing this to a scenario which has the same average environment but everybody faces the same you know if everybody gets the same theta and what we see is that polarization under inequality tends to evolve to high levels and much higher levels than we see when there is no inequality and even more striking if we look at the effects on utility under our model is so if you look on the left here initially where the difference in utility between the high quality environments and the good quality environment the red and the blue lines is very small but as polarization increases the people in the low quality environments gets increased in the low levels of utility whilst the people in the red environments end up once we reach equilibrium having kind of the same level of utility as they had to start with and the population average utility in the unequal environment versus the same faces the same average environment where there is no inequality has lower average utility so the effect of inequality here is to increase polarization and the effect of polarization is to increase the the manifested effects of inequality as understood through utility under this model and so this is capturing the idea of this feedback loop between inequality and utility as inequality and polarization where inequality exacerbates polarization and polarization exacerbates inequality of course there are other mechanisms for this but I think this is nonetheless an interesting way of looking at it in the space of mass polarization or effect of polarization so the way this happens just to give you a little bit of intuition is that the people in the low quality environments are experienced essentially a risk averse environment which leads them to adopt start adopting high polarized strategies but because of this process of social learning this quickly spreads to the whole population even though the people in the high quality environment are not really advantaged by adopting a risk averse attitude because they're fine and so you get this same kind of dynamic that we saw previously where once polarization takes hold it becomes sticky and it's not easy to reverse and this can happen if only a subset of the population become risk averse or economically anxious or whatever you want to call it okay so I have literally no idea how I'm doing for time by the way because I'm sick and I'm confused so people should please shout at me if I'm going on too long so I finally want to talk about the thing that I guess is the sort of important point so what lessons can we take from this kind of modeling for fixing polarization and what are we going to do in the future to try and understand address these questions better using these kinds of models so the first thing I want to note is that sufficient levels of redistribution meaning high levels of this parameter alpha that I mentioned before can prevent the onset of polarization in the low quality risk averse environment so if we haven't if we haven't initially unequal environments but we engage in redistribution such that environments become more equal between the two groups we see that as we oh I missed an N off the axis there but as we increase the level of redistribution alpha inequality declines and polarization declines and the average utility of the population increases in response so that's really kind of to be expected right if we I already showed you that if you start off with the same average environments without inequality you get less polarization than if you assume that one group has a worse environment than the other just a side note that if we include some form of dead weight loss due to taxation in our public goods model then this makes reducing polarization and notably harder to do so here on the left we see that increasing redistribution does decrease in equality by necessity but it doesn't do such a good job of reducing polarization when there is this dead weight loss due to taxation but that's a bit of a side note that I again happy to discuss towards the end so this redistribution is sufficient to prevent the onset of polarization in our model but it is not sufficient to reverse polarization because polarization is sticky and essentially the only way to reverse polarization under this model is to knock the population out of the basin of attraction for high polarized behavior high polarized strategies one thing that's sort of neat here in this model is that it sort of builds what emerges from it is the idea that a so-called you know shock and economic shock or some kind of other shock that such as a war or something which vastly decreases the utility of the population can actually be effective in reducing polarization and you can see this this figure isn't ideal for the points I want to make but I didn't have time to make a better one so here we have the baseline environment theta zero on the x-axis and the color indicates the size of the basin of attraction of polarization so where the darker the color the harder it is to reverse polarization and if the baseline environment becomes bad enough then you the basin of attraction for high polarization becomes sufficiently small that it's pretty easy to escape it and generate low polarization in the population and so if I just very quickly zoom back to this figure that basically what I'm saying is if the environment theta goes from kind of here you're up here at high polarization and the environment theta goes down here it's very easy to escape this basin of attraction because it's so small so that's one way of escaping polarization you in our model the only way of escaping polarization is to knock the population out of the basin of attraction for high levels of polarization and you can try to enact policies which essentially shrink the the size of the basin of attraction for high levels of polarization. One way that you can try to generate this kind of knocking the population out of the basin of attraction for high polarization is via so-called coordinated efforts in which you get enough people to start being unpolarized that basically you escape the basin of attraction for high levels of polarization. How could you do that? Well one way you could do that is by having elites who model good behavior and so we've started recently to look at the idea of influence inequality in which the population has people with heterogeneous levels of influence such that people with high influence will tend to be copied by people with low influence but will not tend to copy people with low influence and we show that this can be actually quite successful and again I apologize for the bad notation here I've repeated the use of gamma but the way to read this heat map is that when the proportion of low influence individuals becomes high enough and when the relative influence of the high influence individuals is high enough then the then you will end up getting low levels of polarization i.e you so in the blue region you tend to get you tend to be able to successfully reverse polarization quickly and the yellow region you tend to be able to not reverse polarization quickly and so what this is showing is that it is possible to model good behavior and push these dynamics out of the bad basin of attraction of high polarization provided the group of low high influence individuals is small enough and that their levels of influence are big enough okay so finally I just wanted to say a couple of notes about where we're going next with this work so we obviously haven't presented very much data here connected to this model and I would like to correct that so one thing that we're looking at doing and that we're piloting a version of this but it's not yet connected to polarization but what we're doing is um carrying out multi-scale public goods games in which individuals have to choose whether to invest in their local group or in a global group in this figure it's called Westville Eastburg and Allshire um so it's a regular public goods game where people invest if also yeah so it's a threshold public goods game excuse me if enough people invest then everybody gets a payoff within the group be it Allshire Westville or Eastburg or of course people can choose to defect and keep the coin what we want to do with polarization of course is to make these groups aligned with people's political identity and make the degree of that political identity sufficiently salient um or vary the degree of salient to that political identity in order to see how that affects their willingness to engage in um cooperation at different scales we're also measuring the extent to which people identify with different groups be it they're in group they're out group or the whole group using the dynamic identity fusion index and again that will be interesting to look at when the different populations different subgroups are divided according to um political identity um okay and that's all I have to say I hope that wasn't too confusing as I say I'm a little sick so I don't not totally sure whether what I said made sense but hopefully there's some interesting stuff there and I'm happy to discuss um I'd like to thank my collaborators and my funders and especially as I said at the start Nolan McCarty who is a political scientist and who is sort of the why why I'm happy to work on this um because I have a political scientist to talk to who who's willing to sort of like keep me grounded and not wander off into weird model worlds that doesn't connect to reality okay thank you very much okay so well there are a few questions so I keep track of you okay uh thank you really great talk great work I now I realize I read some of your papers and I really was very impressed by your work so cool stuff um yeah I've actually two questions um if I may um the first one is um so it's in in the model uh you you presented a very crucial assumption is that if people let's say from a low income group interact with people from a high income group that is a risky thing and it's even more risky if there's more inequality um and and how does that relate uh to say also the the economic benefits that you get particularly in an unequal society if you get the chance to interact so say you are poor and you get the chance to work for an employer who is rich so you have a job you make uh an earning uh as compared to and you are better off than other poor people who don't have a job and don't make an earning so that's a positive interaction say with a rich out group member so there must be somehow a trade-off somehow a balance uh or a trade-off between these things and I wonder how that figures into your modeling yeah it's it's really interesting actually so in the initial model we don't assume that the so what I was showing you here we don't assume that these groups are unequal in wealth we just assume that they having different identities is perceived or for some reason is in fact more risky now this is sort of why I got into the identity sorting stuff because what we assume is that different that wealth does not like inherently vary with political identity but it may vary with other facets of identity and then and so if what happens is sorting i.e political identities align with other facets of identity then you end up with a scenario like you describe in which um you have a wealthy group is perceived as the out group and the non-wealthy group is perceived as the in group so that doesn't answer your question but that's just to clarify the model um so the I guess I think that the there's a that what we've assumed is very simplistic there is there are some interesting studies that show for example um how people's attitudes vary when hiring someone from a different identity group so there is evidence for example that people are you know engaging racial bias in hiring and that sort of thing and I think that speaks to what you're describing if it's literally the case that there's just a rich group and a poor group like everybody in one group is rich and everyone in one group is poor I don't think I think you're right and you wouldn't sort of have this risk aversion that we're assuming but I think if on average one group is rich but the both groups are heterogeneous then what we're sort of assuming is that people within a given identity group who are rich will give the opportunities to the people who all who share their identity and they will perceive giving an opportunity to someone in the poorer group who also has a different identity as risky does that make sense yeah I think so yeah maybe short second no okay as okay where no I save it for later I save it for later okay thanks a lot thank you no I'm going to ask you something Andrew I mean would you feel okay just having one more question taking a break now and then continuing later would it be okay for you or yeah I may even talk to here and later yes no no I'm just saying it because I mean well also for logistic reasons but then since then we have more discussion so just one more question you can take a break and rest a little and then we go back okay okay so one more yeah just like and so Eduardo and then Alexander I just need to talk enough to the camera focus on me here so thank you for the talk so in particular going through these distinctions about polarizations I always found that very confusing I learned a lot and that's my questions just to see if I understand because the identities you had where always a binary decision or a discrete set of options so while I could think about examples where the opinion or a stance on a political issue could be better modeled by maybe a real variable I just want to to clarify from you whether this is indeed a different type of problem or you can map this to the things you did and if it is a different type whether you think that is different dynamics or if that aspect is relevant or the discreteness is not important yeah thank you I think the discreteness is important and it's sort of important for the definition of sorting so that isn't to say that you can't have sorting along lines of continuous identity just as you can have sort of bimodal policy preferences when policy preferences are continuous but that is obviously much more complex to model and we haven't done it yet but I think that you're right that it's an important thing to think about and actually one of the things I'm very interested in doing which is semi-related is to connect these kinds of models more explicitly to both opinion dynamics of the type that we heard about in some of the previous talks and also a more sort of nuanced model of identity dynamics itself so where its identity is continuous and where you can feel more or less attuned to a particular identity in response to both your opinion and your economic environments and all that sort of thing so I think it's a really important point but I don't really have a lot of intuition about how it will change the results at this point. Yes it's more of a reminder but then we'll come back for the discussion so just before the so let's perhaps thanks again Alex.


Well, we're back here the Riser's town sports flex after an outstanding effort here by Stevenson and the women's hockey program 10 to 1 winning today against Levin and Valley. My name is Adam Polan. I'm joined by Stevenson head coach in Tracy Johnson and Tracy Everybody got into the act today, but Monica Posit was just so outstanding with a hat trick here this evening Yeah, as of late, you know, she's really been finding a way to put the puck in the net And it's been really fun to watch normally. She's on the assist side of things But she's been burying it and no complaints for me on that and your power play I know your power play took a big step forward here today, which is something that you're really trying to drive Here as you head towards the postseason.  So, you know to see them put up points on the power play is good that gives us a little bit of confidence with that moving forward and We just want to keep plugging away at that and what did you think about the kind of relentless push of your team? It just seemed like you came in waves you put up more than 80 shots Which almost never see it a hockey game and and with that it just seemed that it was a great 60 minute effort Yeah, I think, you know the last 40 minutes for sure. We put I thought we started a little slow energy was kind of at a lull and we talked about that going into the second and just making sure we're playing Mustang hockey and I thought they definitely did that so we want to keep that moving forward for tomorrow night Well, congrats and once again tomorrow night the women's hockey team takes on living in Valley on the road again And then you're back for what is I guess your senior day here this next week on Friday at 3 30 against Newman And good luck here in the what is this last stretch of the year? Thank you so much


What's so amazing today is being here with all the other young filmmakers. Every single one of them has come up to me and said you have no idea how much you've influenced me. The National Lottery raised 30 million a week for good causes. They support filmmakers all over the UK. It's incredible. I love film. I love the communities. I get to meet through it. I love the stories I get to tell. I know that the lottery gives a lot of money to the British Film Institute so that they can finance filmmakers who might not otherwise get their films made. It's all about what do you want to make of the trust and the support. They give you is incredible and I think that is down to the National Lottery. When I got the lottery money to make my film I remember my parents were really happy because they were like well we won in a different way. I remember saying to people do you play the lottery and they went yes and I said thank you very much.


Let's go to Bogota What do you think about Bogota until the moment you like it Well, I'm local I'm from Bogota and I'm so excited and it's an honor to have you all you to have all you guys in In my city. This is like a dream for us so We're very thankful with the Ethereum Foundation because there was a a lot of effort I know that the work that they did for for for having all of us together here And it's an honor also to be here today with these amazing leaders that We are we are going to discuss About what they are building and to learn how and this is the name of the panel. We don't have it right now, but We've by the way, my name is Mauricio to our from traffic goes and Colombian guy and we the name of the panel is We're free it's going great and I want to start asking that is We're free going well and I'm going to introduce our amazing panelist Brian from zero a spark foundation And up from build guilt a Jacob from it global Amazing weekend we had hearing in Bogota and Romina crypto Chica from it let down Let's start with that question Romina, do you want to start? Do you have a microphone? Okay? We need to chair. I can share it with you So you have either it started is we can start with you Yeah, for sure. So it's a hard question to start with I'm sad that I came last to answer it first But basically yeah, I think it's well, there's a lot of improvements to do But even like when I look one year back to where it was I think there's been a lot of improvements and Yeah, I'm just very glad to have entered the ecosystem And I think there's again a lot of improvements to do but it's yeah There's like many steps, which are kind of incremental increases Nice Romina. What do you think? I think that what tree is well right now in All that I'm cause I'm from Argentina Well, a lot of people who are there knows me and there's people from Honduras, Ecuador, Mexico and a lot of people from from different countries from Latin and we I think that what tree in the present is it's a good tool for us to Have an alternative for the different for the traditional system Between I mean the the government's the bank system We we really use crypto and blockchain to in our day in la cotidian a that And then in a dated in a daily basis. Yeah, just if you want to Send value or send money to your friend or family or whatever So I think that we we are not thinking in the future We are thinking in the present It's a different approach Yeah, what do you think Jake? Yeah, I think it's an interesting question I think there's also a satirical Twitter account called web3 is going great Which posts about all the hacks that happen all the time So I mean it depends on how you look at that sentence I think like overall like having seen the last kind of five years of the global hackathons and also just like in general watching the ecosystem I think like a really good signal is just a lot of really smart people have kind of come to the space and stayed It's like a really kind of interesting environment where it is the frontier in a lot of ways And I think we don't really quite know exactly what we're doing But that's actually like a really exciting opportunity for smart people to come in and like think about these problems think about how they can serve You know underserved communities how they can kind of serve like with these new Kind of primitives that we've been building in web3 So I think like just overall like seeing kind of the community grow Significantly and having smart people stay and continue building is at least a really positive great sign So I think from that aspect web3 has been going great, and I think there's a lot of other aspects in which it is Brian Yeah, I think there are a couple of different dimensions along which we can try to answer this question First off, I think that you know to echo what the other Folks on the panel have mentioned there are a lot of things that we should be very proud of I think there's a lot of really promising Seeds around community I'm really excited just to see you know with DevCon being in Bogota and just looking at how much Global activity there is worldwide around Ethereum development. I think that's you know so so promising to see At the same time I think it's important that we're continually taking a very like critical Perspective on what can we doing better? What can we be doing better? What value have we really created so far right like at the end of the day? This is technology that has to impact end users, and I think that's been one of the challenges, you know for Web3 for you know a long time. I mean it's really fantastic to see that payments Actually have taken off and are serving so many financially underserved people You know when our crew from Xerox Park came out here to Bogota I've been super surprised by how many of our you know Transactions actually involve people requesting us to send cryptocurrency That's like a really encouraging sign at the same time when we look at like various industries for example crypto gaming I would wager that there's like despite all the speculative hype around that There are fewer than 10,000 people in the world who have probably had a fun time playing a crypto game And for the size of that industry the industry that's actually something that we need to be really critical of and that we should be Continually raising the bar and challenging ourselves on so I think that there's a lot of promising seeds, but you know like Eda said there's a lot to think about improving on Okay, I want to talk later about the Latin American and real users but first of all I want to For the audience to understand what are your product your projects What are the problems that you are trying to solve and What kind of impact does your team hope to live on the web free ecosystem and the world in general? Maybe we can start with you. Yeah, for sure So I mean my answer to this is gonna be a little bit perhaps hypocritical given what I just said about the importance of Connecting to end user, but I do think that there is actually really very deep and important connection So the Xerox Park Foundation focuses on what we call application level research and development And that basically means trying to understand what are the technologies today that enable use cases? Perhaps two to five years out thinking beyond things like you know I know in the last couple of years There's been this massive bull run and all this activity on the application level But a lot of it looks like you know quite incremental improvements things like oh, you know Let's build another DeFi app. That's that like the sixth level of financial engineering or let's build You know and accessibility is very important But once you get to like here's the end wallets application with like a marginally better mobile UX or something How do we encourage the space to think bigger about like how might things like zero knowledge proofs or things coming out of you know cryptography Academic literature impact the ways that we think about privacy and you know digital transactions online So that's mostly what we focus on and you know We're just hoping to start planting the seeds for impactful technologies that that might reach those end users two to five years down the line Yeah, sure Yeah, so I work with ETH Global what ETH Global does is primarily kind of grow the Ethereum developer ecosystem By bringing in web to developers being them where they are helping them with education Through the hackathons that we run like ETH Bogota this past weekend and then ultimately kind of helping them through that journey If you think about it joining what three is always like a very kind of stressful situation There's a lot of stuff that's happening lots of noise. ETH Global kind of tries to be the signal And then the other thing that's really important about us and of course the second part of our name global Is that there are talented people all around the world whether Latin India? North America Europe whatever There's just like tons of talent in the world and not everybody has the same Opportunities to kind of travel the world or go to the right institutions or whatever So what ETH Global also tries to do is bring our events our community the Ethereum community in general To these places all around the world And help kind of kind of bolster their local communities as much as possible Through our hackathons in our events. So that's what we've been up to for the last five years It was created this year So we are so young it's a young project and I think that it was created With the vision of the road to the outcome. So I Think that we have a lot of community in Latin. I don't know Chile Peru As I say or Honduras, Ecuador Argentina all the countries has leaders Has Communities so we try to improve the Connections between the countries and the communities and the first step was create it La Tambueno Aires to to have a big event Argentina has a strong community with builders on Ethereum, but we never We have never been We have never been an event a big event Yeah, I had problems with these things But what we had it global into? 2018 but we had a big pause a bit So many years without nothing just small events and Now now well, yes Mondays we had it Latin Bogota and it was a point of meeting Bundo Encuentro for all the leaders and we have to create our identity It Latin is growing Is involving so we don't have to We don't have the Objectives of the goals we are creating because we We have never been in touch together between the communities or yeah, I Think that we we were in our countries with our ideas with our context But this is the first time that we are talking between us and it's amazing In person in person. Yeah in person and we now we are We are working like it Latin with all the latino-americanos and latino-americanos and we are trying to Find what are our problems how to solve it It's a hard working a hard work, but we are walking to the to the goals Amazing that they are doing an amazing job between the communities. I have to say that either Yeah, so I'm part of bill guild or bitter Giddle Basically what we are is we're a web 3 developer community We think a lot about onboarding developers and providing the right tool set to them like giving them opportunity to learn and prototype As well as like while doing this also earn some income at the same time We also have our hackathon starter kit scaffold eat as well So we maintain that we create like different prototypes and it's a way for developers to kind of start Experimenting without moving full-time and you know, it's kind of a way where you know You can graduate to either building your own product or also go work at a web 3 community as a developer So yeah, that's kind of what we're up to Great what one thing that is different from web 2 is that web 3? Have a very important Actor in the in in in your projects is the community, right? What is the role of your community in the decision-making of what you do and how you? Listen to them and what they they want You have the microphone Yeah, for sure. So I think Actually a big part of ETH global's journey over the last little while has been kind of realizing actually exactly this that community is centered to what we do and actually thinking about actually global the company is more of kind of a Project that helps service that existing community that we've been able to build So yeah from that perspective, we're certainly thinking a lot about Different things in which we can do to help support them So we actually just kind of publicly announced this past weekend at East Bogota a couple of new ways We're thinking about doing that so we've been doing hackathons obviously over the last few years But now we've also launched guides which are kind of self-serve education platform Kind of think of that as like kind of maybe the minus one to zero the hackathons Then being the zero to one and then we also want to help people on their journey from kind of going from web to Building a web three for the first time and then joining a web three company with jobs So we just announced jobs as well So this is all kind of based on feedback that we've learned from our community and just sort of what we've seen over The last few years that you know We've been able to see kind of a lot of awesome people come through our doors stay a lot of them are actually in the audience so hi everybody and Then yeah, I should kind of come into the community and either build something great and kind of have that be part of the community And their way of kind of impacting it or joining an existing project in the space and and taking it from there So we're just trying to support people within our community now within you know more different ways than just the hackathons We've been doing traditionally and in your case head up Yeah, so basically What we tried to do a lot is So we don't yeah, like I think it's nice for developers because we don't provide them like a specific You don't have to do X project But you have the flexibility to kind of choose what you're interested in and kind of build that so let's say, you know You're interested in Integrating with Lance protocol you can do that you can have different alternatives in that sense and you can kind of Yeah, it's a very free community in the terms that you know Every developer is welcome to build whatever they're interested in and kind of earn money for their contributions into the community And all the all the resources we provide are completely free and accessible all online We also like it's a yeah It's a public good for the ecosystem that we don't like take anything from the developers contributing or Yeah, it kind of just you can meet other people you can network with other people create different projects together So yeah, I think it's a very core developer centric community in that sense I'm going to introduce you in a moment I need to find the info and Until that please You're yet the role of your community and how you listen to them. Yeah, I think that something really powerful happens when you approach R&D or development from a bottom-up rather than a top-down kind of perspective I think that there's you know one world where you can imagine a lot of the Research being done in the space being instigated by like monolithic organizations that have top-down research agendas Which they hire researchers for and then you know manage them to hit specific research outcomes And I think that this early on in a technology's life cycle, you know a technology so early and promising as a theory And we can't predict no single person can predict what the most interesting Directions are going to be and so we rely very heavily on our community And you know we frame ourselves as largely in service to a community of people who are really owning their own visions So what we try to do is we try to educate folks I think there's a lot of similarities here for example with with global But we take people in we try to educate them in a lot of these new tools And then we have some general areas that we think are interesting to explore for example like zero-knowledge Machine learning or something like that and let's take a machine learning specialist teach them how zero knowledge works and then Leave it to them to start to articulate like a research agenda or vision for that sub-domain And then our role starts to become like connecting them with the experts on the cryptography side Or providing financial support via grants or educating or those kinds of things So I think the community-driven development here is really important That that's what may we're pretty friend welcome Oren From from jailer dot one is quadratic finding right? Can you please introduce yourself and the question that we are answering right now is What is the role of the community and how you listen to them to make decisions? Right start for being later on. I got double booked but Yeah, hey, I'm Aaron from clear fund in terms of the role for the community I guess very much depends on the the context or what kind of a Yeah, the context In in the context of clear find I think that the role of the community there is essentially helping to Allocate funds to public goods projects. So quadratic funding is this really neat mechanism where you take Inputs from a whole bunch of different people in in the form of contributions to projects that they value and then quadratic funding the CLR mechanism essentially spits out an allocation that Reflects both the preference and the strength of preference of all of the individuals in the community that contributed to projects that they value So in the context of clear find I think the community's Biggest input is that it's helping to allocate funding to public goods great Thank you and Romina in Latin America the Latin American communities I think that we have to create our own flows our own criteria to Start creating metrics and how to Medir To mention to mention the the impact for example, I was talking with Carlos Melgar from Honduras. He's from the nice land in Othila And we are I'm collaborating when with the quadratic funding team the of the Ethereum foundation we have to The applicants has to pass a KYC and Carlos Say he he told me two days ago. Hi, Crypto Chica. How are you? I applied to the quadratic funding brown, but I'm a bit worried cause They they are asking me for my bank An account and my address and I don't have address and I say what do you do? I don't understand and he told me yeah, because I live in a in a nice land So I don't have an an account We don't have address if you want to go to the house of a friend you have Reference, but you don't have a on the street or a number and I don't have a personal account bank and we paid our Electricity and lights in a prepaid way. So it's very different of any capital or big city They have a specific requirements We have to know Like it Latin like leaders of Latin we have to Talk a lot with our communities and with other communities to understand Where is the Where is the starting point the starting point cause I think we have a lot of pre-concept Some now notions But I think that we have to Check with numbers and data hard data strong data and then we need to start to design The the solutions but now we are exploring and we are trying to understand Don't know This is my first time talking in in English in a panel Romina if you want to know more about her there is a knee and the New York Times article so good That Presented that the story of Romina around 50 currencies. So I encourage you to read it I I I listen to your to your page and your projects and everything is perfect What are the challenges that you're facing who wants to start I Mean for us we're Building on really novel technology. I mean Ethereum itself is a very novel technology And then we're kind of taking that a step further building on top of zero knowledge proofs using Macy this minimal anti-collusion infrastructure Built by Privacy and scaling solution to a team funded by the Ethereum foundation And this yeah, it's it's bleeding edge technology. It's it's really incredible. It basically allows us to Run a quadratic funding round or kind of more generally run a vote in a way where the inputs are secrets and you have no receipts So you cannot tell how I voted I cannot tell how you voted and because of this quality It it makes it much less effective to attempt to collude to bribe to coerce people into voting or contributing in a way that's different from how they would like to But building using this stack of novel technologies that are upgrading frequently and Not yet audited had not yet been tested at scale Is a constant challenge we run into hiccups and roadblocks and whatnot constantly but I think that's part of the challenge that's part of what we kind of sign up for when we're again building on this on this stack of novel technology on novel technology on novel technology and The the reward is really worth it. You know, ultimately what we're creating is this this system for permissionless trustless private voting quadratic funding which is a really really powerful tool to Enable all kinds of communities from from the Ethereum community to the broader Latin American community and Outward and onward from there I think Jacob you have the microphone. Yeah, that's right. I should stop holding the mic Yeah, I think on on our end You know, I think one of the biggest challenges is you know, we haven't actually found a sort of ceiling for demand for our events Like they've been continually growing. We've been doing more and more But you know as a small team We probably just can't service as many different regions around the world as as we'd like to like Romino pointed out like we hadn't done an event in Latam until this year since 2018. Sorry for that by the way and but you know, it's not for a lack of caring about these markets and and also You know folk is just literally we just don't have enough time or people to run more than six in person events a year It's they're all huge undertakings So yeah, I mean on our end. I think you know trying to find ways to make each global more efficient as an organization to empower other organizations To frankly just hire great talent internally to be able to do more and more of our mission I think those are probably some of our biggest challenges right now It's just just you know trying to do more of what we're doing and to support our community even more It's not only Difficult to find it's so expensive right now. Sure. Yeah, it's very expensive right now. Yeah, either Um, yeah, I could actually also double click on what Jacob kind of mentioned So at bill guilds like I think we think a lot about developer onboarding developer tooling and education and We like create different content or tools to do that But also like try to understand what is the most effective like sometimes, you know We try to gather a lot of people in a telegram group, but that's not the most effective way to communicate So we try like different ways to approach like to create new projects highlight the prototypes We're building Yeah, I think like those are some of the main challenges because it's like very new We just try to experiment with different things see what's going well and kind of continue with that But again, we're also limited by size and the technology is kind of all new So building on new technology with small team with everyone learning They're like a lot of challenges which you kind of face and determine what to do next at that point Yeah, I'm gonna maybe highlight another dimension of Like some of the challenges that these kinds of orgs might face so I think that in crypto and Web3 broadly there's this massive iceberg of Value creation across different levels of the stack whether that be from community management Or from, you know, maintaining infrastructure open-source software research and development that kind of thing and only a small kind of you know Relatively small tip of this iceberg is capable is capable of being value-capturing and so one thing that is just a difficult problem to face is the incentives problem of You know, for example, if you have folks coming into the ecosystem How do you get them excited about contributing to all of that core infrastructure that? Actually, you know kind of powers everything like it's both from an incentives perspective as well as from the fairness perspective as well as from a resource allocation perspective, it's not necessarily going to be sustainable if you have people coming in and You know, there's a ton of work being done by open-source developers community managers educators a lot of grant money coming in from nonprofit foundations to help support or instigate these new kinds of you know, whether it's like product directions or whatever else it is and All that all those resources come flowing in and then afterwards, you know, like a venture capital firm Like swoops in and sort of takes kind of like all of the upside from that and it goes up to all these LPs And not saying like there isn't like that capital markets are not important They're very important actually for driving specific types of progress and innovation But then there's this big looming question around like how do we continue to incentivize people to work on the things? That power this whole thing that are kind of under the surface that don't have as direct of a value-capturing mechanism And that's one thing that we've been you know, trying to think hard about and I love these experiments like protocol guild and You know, everything that clear fund is doing around supporting these public goods Popular popularizing those mechanisms is just as important also as the technology that that powers them So I think that's a really big focus as well and you Romina Well it let them at the at the time we only had to Event in the past but we we have a lot of goals and priorities one of the of our Priorities the education Right now we have some companies in La Tom Who made who make customer acquisition in our communities? So we try to create communities like public goods with Cop Cooperative for free For everyone, but we don't have an strong alternative. So one of the Goals of in the future for it Latin is to create an educational hub And it's very important for us because here in La Tom. There is a lot of ghost chains and scummy chains We have the opportunity to Connect with the users and the builders again in when we experiment in the past that defi summer a lot of people knows ethereum and knows NFTs and then the expensive gas fees Alejo push away a lot of people just because the people couldn't deploy or Send money or whatever in on chain. So if we Create a strong of a strong education I have to Share the knowledge about a layer two's and public goods I think we have a an historical opportunity to onboard a lot of Latin Americanos That's true education in Latin America and in developing countries is so important as I have so many top topics to talk but we are out of time


We filled a one liter round bottom flask with ammonia gas. We're going to put in a medicine dropper that's sealed with a little bit of grease. The medicine dropper contains a small amount of water and phenothaline, which is an acid-based indicator. We're going to lower the tube connected to the round bottom flask into a large beaker of water. We're going to inject the water from the dropper into the flask. The ammonia gas is very soluble in the water and very rapidly dissolves in the water, creating a low pressure situation inside the flask. Atmospheric pressure will force the water up into the flask. We get a fountain. The solution is pink because ammonia dissolved in water is basic and turns the acid-based indicator pink.