(highlight:: The Map is not the Territory
Summary:
Humans often confuse maps with territories, despite evidence from various disciplines.
We wrongly assume that what we measure is what matters, but our values may not have quantifiable metrics. Biometric data can oversimplify complex discussions on health.
This conundrum becomes more significant when considering governance on a larger scale.
How do we count and operate a nation state wisely?
Can social science inform smarter political economies? We must escape the false clarity of information systems that lack collective wisdom.
Transcript:
Speaker 3
There are maps and there are territories and humans frequently confuse the two. No matter how insistently this point has been made by cognitive neuroscience, epistemology, economics, and a score of other disciplines, one common human error is to act as if we know What we should measure and that what we measure is what matters. But what we value doesn't even always have a metric and even reasonable proxies can distort our understanding of and behavior in the world we want to navigate. Even carefully collected biometric data can include the other factors that determine health or can oversimplify a nuanced conversation on the plural and contextual dimensions Of health, transforming goals like functional fitness into something easier to quantify but far less useful. This philosophical conundrum magnifies when we consider governance at scales beyond those at which homo sapiens evolved to grasp intuitively. What should we count to wisely operate a nation state? How do we practice social science in a way that can inform new, smarter species of political economy? And how can we escape this seductive but false clarity of systems that reign information but do not enhance collective wisdom?)
- Time 0:01:22
- complexity, plurality, collective_wisdom, intergenerational_learning, measurability_bias, measurement, metrics, 1social/post-queue,

(highlight:: Perverse Incentives Select for People Who Are the Best at Exploiting a Given System
Summary:
The original deans and administrators burn out due to their dislike of the US News and World Report rankings and are replaced by individuals driven by ranking success.
This shift reflects a difference in mentality between valuing money as a means of support versus valuing money as the sole purpose of life. Similarly, pursuing publications and citations for a job versus making them the ultimate goal shows a significant distinction.
However, these differences are connected through a temporal dynamic where initially people adapt their behavior to succeed in a flawed system.
The system then filters out those who can best exploit it, resulting in the selection of individuals with specific values.
Transcript:
Speaker 2
What happens later on, the original deans and administrators burn out because of how much they hate the US news and rule report rankings, and they get replaced by people who are all it. They think the only point is to rise in the rankings. And those people don't hold back. They only have one target. I think something similar is the difference between so realizing I need a lot of money in order to a decent amount of money to support my family, but not thinking money is the point of life. And similarly, realizing that getting a decent number of publications and citations is necessary for a job versus thinking the goal of my life is to max out citations. And for me, there's a huge gulf between those things.
Speaker 1
Well, here's where I think they're connected because I see the difference and I understand the difference you're talking about. But I think the difference is that is this temporal dynamic, right, where you start out with, let's say, perverse incentives and people saying, well, I don't necessarily value these Things, but I have to shape my behavior in order to succeed in this system. But the thing is, the system being the way it is creates a filter. And the people who are the best at figuring out how to operate in that are the ones that then end up being successful. And they're the ones that teach the next generation or emulated by the next generation. And over time, the people for whatever reasons, psychologically or behaviorally or ever their path is, are best able to exploit the system are going to be able to thrive in it. And I think that because of that, you end up selecting for people with certain kinds of values, because they're going to be the people who there's always exceptions, but are going to Be best able to thrive in this kind of thing.)
- Time 0:12:16
- metrics, perverse_incentives, evolution, natural_selection, exploitation, 1social/post-queue,

(highlight:: Perspectives on Organizational Strategy & Coordination: Optimizing for Few Coherent Goals v.s. Many Incoherent Goals
Summary:
The corporate world is better at defining goals than the academic world.
Educational institutions struggle to articulate their goals due to disagreement. University administrators have competing goals, which leads to constant infighting.
The speaker prefers universities with plural goals and worries that focusing on one outcome leads to the loss of other important aspects of education.
However, top-level administrators should have reasonably well-defined goals that trickle down and create incentives.
Transcript:
Speaker 1
I think one of the things where the corporate world is actually much better at this than the academic world or the educational world, because their goal is profit. So it's very clear. It's much harder to say what the goal of an educational institution is. It feels like it should be obvious, but within the general goal of like we want to produce successful, well-rounded people, there's a lot of disagreement about what the goals are. And so shaping the institutional incentives around those goals becomes extremely difficult, because not only do we have to worry about perverse incentives, but we have to worry about Vigorous disagreement about the kinds of things that are valued in the first place. And I think exactly what you're talking about, T, is something that if you went to a bunch of university administrators, let's say, or medical school administrators or doctors, and You said, what is the point to what you're doing? Is it to produce wise, well-rounded people? Is it to minimize costs to insurance companies? Is it to increase donor contributions? What is it? And there are all these competing goals. And so there's this constant infighting about among different people who have different versions of what the best version of their institution is, and it's so difficult to articulate What that is.
Speaker 2
I wonder if we're in different sides of this, because are you like worried about the hardness of it? It sounds like you think it's a problem that it's hard to come to agreement and articulate a goal, where I actually prefer the university that disagrees, has many incuit and plural goals, And worry that when it articulates an outcome clearly and starts orienting around that outcome, that's when it starts shedding a lot of what was good about the kind of pluralistic more. So let me just give you this is like from my life, right? So a university I've been employed at has started moving toward orienting everything around student success, where student success is defined as graduation rate, graduation speed, Salary after graduation. When you define that outcome, it becomes really easy to target, and the people that are targeting it, as you say, the people that target it well tend to rise, people that are willing to Go all in on targeting that stuff instead of caring about all the other weird shit that education might be for, tend to have better recordable outcomes and tend to rise in the university Structure. So I actually am happier for something as complicated with education, in which different groups have different conceptions of values about what they're doing, and we don't actually Try to settle it, and we don't hold them all to a high articulability constraint, because I think the business school and the CS department have more easily articulable outcomes than The creative writing department, art history department. A lot of the stuff that I'm writing right now is about like this defense of the inarticulable.
Speaker 1
It's a hard question to answer because I think that there are multiple levels of organization going on here. There's like a top administrator level, because these institutions tend to be pretty hierarchical. I think at the top of the hierarchy, there has to be some sort of reasonably well-defined goal, even if it doesn't specify what every individual component of the organization or institution Would do it. And I think that that trickles down to those levels though, and creates incentives. Regardless of whether or not it's a good thing, I think there has to be some sort of coherence at the very top level, even if it doesn't dictate what each individual component is doing.)
- Time 0:17:04
- goals, group_dynamics, group_governance, incentives, organizational_incentives, organizational_strategy, strategy, group_performanceeffectiveness, 1social/posted/linkedin, 1social/post-queue, 1social/posted/twitter,

(highlight:: Ambiguity in Communication is Both a Feature and a Bug
Summary:
In 1984, Eisenberg proposed that ambiguity in communication is important and influential.
This idea suggests that being too clear can limit interpretation and hinder coalition-building. Ambiguity can be used to evade accountability, but it is also a general principle of communication.
Transcript:
Speaker 1
It's Eisenberg in 1984 in communication monographs or something. It's this great rambling paper and this idea has been massively influential to me, but he's basically arguing that it would seem like the point of communication should be clarity, To be as clear as possible. For me to say, I mean this and you do know exactly what I mean and that's the goal and ambiguity is therefore a bad thing. He argues that actually no ambiguity is a really important thing and other people have expanded on this. Now the way I think about this is like a blend of Eisenberg and then other people who've come a bit later, but that in a lot of ways if you're trying to get let's say a coalition, you don't Want to say this is exactly what our goal is and this is what we're trying to do. You want to use vague terms so that a bunch of people can sort of map whatever they think that the goal is onto and say that's consistent. It also leads to a reduction in accountability because after you do something and someone says, you said you were going to do this and you say, nah-ah listen to what I said, it's consistent With what I did because what I said was ambiguous. So it's pernicious in a way too. It's used nefariously in a lot of ways by let's say politicians and other kinds of leaders to avoid accountability, but it's also just a general principle of communication I think.)
- Time 0:27:20
- communication, communication_clarity, accountability, deception, alignment, goal_coherence, communication_ambiguity, political_ambiguity, 1social/post-queue,

(highlight:: The tension between the ambiguity of individuals' goals and large scale collective organization
Summary:
Living in an ambiguous environment with diverse goals is good for human beings, but it conflicts with the need for clear policies in large organizations.
As organizations prioritize coherence and clear outcomes, the world will be filled with large organizations staffed with individuals focused on achieving specific outcomes, which may be inhumane and undesirable.
Transcript:
Speaker 2
Here's the pessimistic nightmare. It is really good and healthy for human beings to live in an ambiguous environment with a pluralistic set of goals, many of which are in Kuwait. That is an essential tension with the methods of large scale collective organization. If it's true that for an organization to cohere, it needs to have clear policies so it can act coherently, then we should not expect that kind of ambiguity to survive at scale. And I think what you're describing, so I tend to think about since I'm a philosopher like what makes something constitutively coherent. And what you're describing is a kind of evolutionary process. You know, some organizations are going to be more coherent than others and some people are more interested in coherence. And the people that are more interested in following the strict outcome are going to arise in the organization. And the organizations that have clear outcomes are going to be better at achieving those outcomes. And so our world is going to be full of large organizations staffed with people that have very, very clear specifications of outcomes. And there's something inhumane and bad about that for individuals. But that's what happens when we need to organize in large scale collectives.)
- Time 0:29:12
- goal_coherence, pluralism, favorite, coordination, collective_intelligence, incentives, 1social/post-queue,

(highlight:: The Danger of Incorrectly Mapping Between Scientific Measures and Truth
Summary:
Scientific culture should strive for minimal ambiguity in mature theories.
Metrics can create false mappings if used to impose value judgments. Rigorous and unambiguous measures like the genie coefficient and GDP can be used to compare things, but should not be solely relied upon for determining superiority.
Transcript:
Speaker 1
And it's a problem when scientific culture tolerates too much ambiguity. There's always a caveat there, which is that at the early stage of theory development, sometimes you need ambiguity because you don't actually know really what you're talking about Yet. And so you need to allow for multiple interpretations to be possible until you can figure out what you mean. But a mature theory should be minimally ambiguous. This is at odds with things like metrics in terms of let's say how to evaluate something because people think, oh, well, it's scientific. Therefore, I want to use this to then therefore impose a value judge on something. It's better because it has a higher score on it. But that's not what science is actually able to do. Science can say, it has this score and it measures this thing because what it measures is this. If you say what it measures is this, and therefore it means this other thing, that's a problem because that's a false mapping. And it's not really about ambiguity versus precision. It's about, I think, the imprecision of the mapping between the measure and the term. So if you want to measure something like happiness or economic prosperity, you can say, well, we'll measure the genie coefficient, we'll measure GDP. But those are rigorous, clearly unambiguous measures. They have a meaning. This is what they are. This is how we measure them. We can compare things on this measure. And that's not problematic until you then say, and it is better to have a higher GDP full stop.)
- Time 0:31:04
- scientific_measurement, measurability_bias, metrics, truth, causality, 1social/post-queue,
- [note::See also: "the map is not the territory"]

(highlight:: How Measurability/Mathematical Bias Limits the Scope of Scientific Inquiry and Human Discovery
Summary:
In a fun and intriguing paper, Nobel Prize physicist Eugene Vigner explores the seemingly unreasonable effectiveness of mathematics in predicting and describing the world.
While mathematics is undeniably impressive, it may not be applicable to everything, particularly in social, cognitive, and philosophical fields where constructs and relationships are harder to quantify. This presents a gap that may be difficult to bridge.
Transcript:
Speaker 1
So there's this old paper from the, I think, 1960s by Eugene Vigner, the Nobel Prize physicist. It's called something like, on the unreasonable effectiveness of mathematics. The fun paper, and he's like, there's no good reason why mathematics should work as well as it does. And there's no good reason why there should be a tool that allows humans to predict things as well as math does. There's no good reason. It's kind of nuts. And we should all just be grateful. And he says some other things, but he's basically just kind of being all about how great mathematics is and how there's no good reason why it should be. And it's pretty cool that it does work so well. I think that there's a counter to that, which is that not everything is that easily described that mathematics. And there's lots of things for which mathematics is not that effective at describing. And it's actually just the things that were well described or easily described by mathematics are the things that were discovered using mathematical tools. They're the things that lend themselves that were amenable to mathematical inquiry. And a lot of the things that we're interested in terms of social science and cognitive science and the related philosophical inquiry are things that are much less tangible in terms Of this kind of specification. And you can see it like in a physics equation, right, a physical theory, whether it's about mass or electricity or something else, right, you have a theory about how things work. And then you can write out equations. And all the terms in the equations have units. And they are all directly related to the things that are measurable. The theories are directly about relationships between things that are measured. And in social theories and cognitive theories, so often our theories are about relating constructs. And then we have proxy measurements, but the theory isn't about the relationship between the proxy measures. The theory is about the constructs and the relationships between the constructs that are social in nature, that are cognitive in nature, but aren't the things that are being measured. And so there's this gap. And I don't know the extent to which that gap can be overcome.)
- Time 0:33:58
- natural_selection, measurability_bias, scientific_measurement, 1social/post-queue,
- [note::Reminds me of homophily i.e. "the problems that scientists are drawn to and eventually solve are the problems those scientists' tools are best suited to solve" - ultimately, an individual's or group's capacity to innovate is limited by the tools and methodologies they have at their disposal.]

(highlight:: Metrics: Something That Is Measurable Across Contexts?
Summary:
The difference between evaluation and a metric lies in the fact that a metric proceeds from the shared application of a measurement procedure that can be executed by different people across different contexts.
For something to be considered a metric, the measurement input procedure must be exportable across context, and the criteria for the metric must be something that many people can share and understand. However, there are many standards of evaluation that don't allow for this cross-contextual universalization, posing a challenge similar to the barrier of meaning in artificial intelligence and the elusive nature of trans-contextuality in machine learning.
Transcript:
Speaker 2
So you said that there must be a package of metrics. And I really wonder where that must come from if it's really true that there must be. Now, we're distinguishing two questions that there must be some way of evaluating something and there must be a metric for evaluation because metrics are really different. So here's a worry, and this is a little detour through a literature from science and technology studies. What makes a metric? So if you listen to people like Theodore Porter, this historian of quantification, the difference between just an evaluation and a metric is a metric proceeds from the shared application Of some kind of measurement procedure that can be executed by different people across different contexts. So I can evaluate all kinds of things for which there is no metric, right? I have complex, intuitive, aesthetic evaluations about things I love that when I try to articulate them, they fall apart. And those evaluations, different people can't perform the same kind of evaluation because that evaluation requires some kind of subtle sensitivity. So if you buy this view that what it is to be a metric is for the measurement input procedure to be exportable across context, that requires that the criteria for the metric be something That many people can share and understand. But one worry might be that there are a lot of standards of evaluation that don't admit of this kind of cross-contextual universalization.
Speaker 3
This is akin to Melanie Mitchell's barrier of meaning with artificial intelligence and the fact that trans-contextuality is the holy grail, elusive in machine learning.)
- Time 0:41:04
- metrics, measurability, measurement, evaluation, collective_intelligence, collective_understanding, context_independence, 1social/dont-post,

(highlight:: The Tension Between Organized Behavior at Scale and Individual Needs
Summary:
Large-scale organizations aim for legibility and coherence, but this may lead to a lack of diversity and individual needs.
The educational system's emphasis on GPA overlooks other important skills and qualities.
Transcript:
Speaker 2
One of the most influential ideas for me recently has been from James South's book Seeing Like a State. And Scott has this idea that like what large-hill organizations wants its legibility and legibility is a kind of clear coherence that's aggregatable to a kind of higher level view. So a simple version might be like look if you're a CEO you can't have every department have its own obscure little value system. You need a single collective value system or something close to it so you can get production and profit measures and aggregate them in what Scott says is bring the whole organization Into view. So one way to put my worry is that what would be good for human life is an incredible diversity of bottlenecks which work on different often non-metrified systems. If Scott is right large-scale institutions will tend towards is a kind of monolithic measurement system that moves towards let's have a small number of bottlenecks and let's have A unified measure. And so like the heart of my worry is that organized behavior at scale is inevitably in tension with what a diverse population of individuals needs. And that's just an unfixable problem. Let me just give one quick example. In the educational system the dominant measure is GPA. You can add other like I can write in my notes all kinds of other shit about what students are good at. That barely matters because that's not aggregatable. When a law school admissions officer is doing their spreadsheet to do the first main cutoff nothing in my weird little notes is going to make it into that first level cutoff. The big moving forces just look at GPA.)
- Time 0:49:47
- collective_values, information_aggregation, alignment, institutions, organizational_incentives, collective_behavior, coordination, organized_behavior, metrics, natural_selection, aggregate_measurement, employee_engagement, human_welfare, individual_welfare, work_satisfaction, 1social/post-queue,

(highlight:: Have we overshot the scale at which humans can effectively coordinate?
Summary:
We need Jim Rutt to join the conversation to discuss whether we have exceeded our ability to coordinate effectively.
The slow progress of science and the population growth curve are related to this question. Sam Bowles and his work on behavioral engineering and the return of civil society are also important in this discussion.
We are currently witnessing a clash between institutions and individuals, and something has to give.
Transcript:
Speaker 3
We need Jim Rutt on this conversation right because ultimately this is about have we actually overshot the scale at which we can effectively coordinate and all these studies like you Know this I know it's controversial but like the slowed canonical progress of science these kinds of questions they seem related in a way to the sigmoidal curve of population growth. Have we risen above a level at which intelligibility can actually happen and if so where was that level. I mean I remember you know Sam Bowles is another person who has been looming large for me over this whole conversation not only for his work on the problems of viewing humans as agents That can be governed through behavioral engineering via incentive but also because of the paper that he wrote with Wendy Carlin the article he wrote in Vox EU in 2020 on the battle for The COVID-19 narrative which talked about the return of the civil society you know meaning that the Mesoscopic world of guilds and church groups and sports clubs and pubs and neighborhood Organizations mutual aid networks and all of these other human scale sub-done bar number structures that we found ourselves suddenly very much in need of and yet were eroded by the Radical success of both state power and market power in every way it feels like we are in a kind of clash of the titans right now we're like you know we watch institutions going up against Large institutions and people are struggling to remain unpolverized underfoot. At some point something has to give right.)
- Time 0:52:51
- coordination, large-scale_cooperation, polarization, goal_coherence, influence, civil_society, communities, 1social/post-queue,

(highlight:: The Problem of Scale Clash in Human Collaboration
Summary:
The problem goes beyond ideal scale of humanity.
Different things we want involve different scales. Science works on a huge scale for problems like climate change while other things work on medium or small scales.
There is a clash of different scales and no optimal scale.
The big scales tend to win and squash out the small scales.
However, over long time scales, these complex systems tend to implode. It's about a dynamic balance where different forces coexist. How do we handle this in light of global coordination, bioregional organization, and personal relationships at the neighborhood level?
Transcript:
Speaker 2
I think the problem is even worse than what you're describing I'm going to try to pessimize what you said I mean when you ask me a question like have we gone past the ideal scale of humanity That implies that there is an ideal scale that we could plausibly hit if we could somehow convince people to scale back. For me the real worry is there's no ideal scale of humanity because different things we want to be involved in demand different scales science works really big good on a huge scale solving Problems like climate change our massive scale problems that everyone has to get together on and then there are other things that work at medium or small scales and there's just this Unsolvable scale clash my real worry is that different parts of us and our needs call us to different scales and there is not an optimal scale and so I have to participate in these different Scales or in tension with each other and also the big scales tend to win because they get really powerful and so they squash out the small scales.
Speaker 3
Over short time scales though right because over long time scales those like you know this is the Bob May will a complex system large complex system be stable question it's like at some Point those things tend to implode so it's not about like an equilibrium so much as it is about a a dynamic balance or a zone at which these different forces are able to coexist how do you Deal with all of this in light of both the need for global coordination and bioregional organization and neighborhood level personal relationships etc.)
- Time 0:54:50
- collaboration, scale_of_cooperation, innovation, large-scale_cooperation, scale_of_innovation, scale, 1social/post-queue,

(highlight:: Feeling like a speck in the wind amongst massive Societal systems
Summary:
The constant change in society and the environment has shaped human history for thousands of years.
Looking at these changes on a population scale rather than an individual scale can help us understand how society will evolve in the future. By recognizing patterns in how we all navigate through life together, we can gain valuable insights to inform our actions and make a positive impact on the world.
Transcript:
Speaker 1
I mean we have thousands of years of human history where you know since the agricultural revolution and the dawn of city-states it's just been constant change and one could argue that On a longish you know say century timescale we haven't been at equilibrium in 10,000 years what's next right how are all these nested feedback loops churning around between you know Societal structure and environmental structure to change the shape of society in the next couple hundred years Peter Turchin probably knows this better than I do but this is where I think thinking about these things at population scales rather than individual scales is it really helps me because when I think about things at the individual level like what can I do how do I live in the society right I find myself slightly distraught about like well I don't know I'm just a speck in the wind getting blown around by this maelstrom of society by trying To sort of think about the way the whole system is of all thing I can see it's not that I'm hurtling through space it's that we're all hurtling through space together in similar ways and That creates patterns that can then be identified what do you do with those patterns well then you know you get a professorship and you get to talk about it that helps sometimes)
- Time 0:56:45
- relatable, societal_complexity, societal_progress, scale, collective_behavior, individual_action, 1social/post-queue,

(highlight:: The Challenges and Risks of Understanding Social Dynamics at Scale
Key takeaways:
• Currently, there is a lack of coherent theories about social dynamics that work at scale in modern diverse societies.
• Many existing models for cultural evolution were developed for pre-industrial societies.
• Communication is a crucial aspect as the dissemination of understanding is important.
• A good formal theory about social systems can be both difficult to understand and potentially dangerous if exploited by nefarious actors.
• Understanding certain actors' behavior and the consequences of their actions allows for informed decision-making and intervention.
Transcript:
Speaker 1
That what you say is also correct right and it's something that so to speak keeps me up at night which is that a we are not there now we don't have currently very good coherent theories about Social dynamics that work at scale we know almost nothing about how cultural evolution works in a modern wired large scale diverse society because all of the models you know or so many Of the models were developed for sort of pre-industrial societies because the systems are simpler there's also you know the communication aspect right which is we can come up with Let's say I have an amazing theory that it's a really I've managed you know me and my team and collaborators have come up with a really coherent formal theory about the way things work One such a theory is going to be flawed and potentially dangerous in the wrong hands because if we really have a good formal theory about the way social systems work it can be immediately Exploited by you know nefarious actors also it's going to be really difficult to understand but it's also important to disseminate that understanding because people should know What to look out for right if you know how let's say certain actors are behaving and what the consequences of those actions are you're more likely to be able to say wait a second I know the Consequences of you doing that I don't want you to do that whereas if you don't know why some actor is doing something you're like well I don't know why they pass that well I guess it's fine.)
- Time 1:06:27
- cultural_evolution, scale, group_dynamics, social_dynamics, societal_complexity, systems_modelling, societal_progress, exploitation, 1social/dont-post,

(highlight:: The Expert Identification Problem and the Challenges of Democratic Decision-Making
Key takeaways:
• The expert identification problem is a major concern when it comes to trusting experts in a democracy.
• Democracies aim to harness the intellectual power of diversity for better solutions.
• The challenge lies in recognizing the best solutions when they require expertise that the democratic entity may not possess.
• There is no clear solution to this problem, and democracy remains the best way to organize society according to the speaker.
Transcript:
Speaker 2
So for a long time I would say that the problem I've been most obsessed with is something I call the expert identification problem it's like how does the non-expert figure out which expert To trust if they don't have the expertise and one of the worries about a democracy is that it runs straight into the expert identification problem right like if we're democratically Voting on what to do we are aggregate non-experts I mean I'm not talking here about like oh we are the experts and you all are not even if you are the world expert in X you're a non-expert In a million other fields right so as an aggregate we are non-expert so here's the real worry for me if you have the right solution how would that get democratically approved Helen Landemore Is this a political theorist I really like she's part of a movement who are epistemic democrats and they think that democracies are the best way to harness the intellectual power of Diversity and the basic model is something like diverse people will come up with a better set of solutions and when you put them together the best solutions will rise to the top and my Worry is how will the democratic entity recognize which are the best solutions because if the best solution requires expertise to recognize and the democratic entity as an aggregate Is not an expert how will they figure it out and that's a problem I'm not sure there's a solution to and I also can't think of a better way to organize the world than democratically)
- Time 1:10:06
- export_identification, decision-making, large-scale_decision-making, trust_economics, participatory_democracy, trust, collective_decision-making, democratic_decision-making, election_science, political_science, 1social/post-queue,

(highlight:: The Map is not the Territory
Summary:
Humans often confuse maps with territories, despite evidence from various disciplines.
We wrongly assume that what we measure is what matters, but our values may not have quantifiable metrics. Biometric data can oversimplify complex discussions on health.
This conundrum becomes more significant when considering governance on a larger scale.
How do we count and operate a nation state wisely?
Can social science inform smarter political economies? We must escape the false clarity of information systems that lack collective wisdom.
Transcript:
Speaker 3
There are maps and there are territories and humans frequently confuse the two. No matter how insistently this point has been made by cognitive neuroscience, epistemology, economics, and a score of other disciplines, one common human error is to act as if we know What we should measure and that what we measure is what matters. But what we value doesn't even always have a metric and even reasonable proxies can distort our understanding of and behavior in the world we want to navigate. Even carefully collected biometric data can include the other factors that determine health or can oversimplify a nuanced conversation on the plural and contextual dimensions Of health, transforming goals like functional fitness into something easier to quantify but far less useful. This philosophical conundrum magnifies when we consider governance at scales beyond those at which homo sapiens evolved to grasp intuitively. What should we count to wisely operate a nation state? How do we practice social science in a way that can inform new, smarter species of political economy? And how can we escape this seductive but false clarity of systems that reign information but do not enhance collective wisdom?)
- Time 0:01:22
- complexity, plurality, collective_wisdom, intergenerational_learning, measurability_bias, measurement, metrics, 1social/post-queue,

(highlight:: Perverse Incentives Select for People Who Are the Best at Exploiting a Given System
Summary:
The original deans and administrators burn out due to their dislike of the US News and World Report rankings and are replaced by individuals driven by ranking success.
This shift reflects a difference in mentality between valuing money as a means of support versus valuing money as the sole purpose of life. Similarly, pursuing publications and citations for a job versus making them the ultimate goal shows a significant distinction.
However, these differences are connected through a temporal dynamic where initially people adapt their behavior to succeed in a flawed system.
The system then filters out those who can best exploit it, resulting in the selection of individuals with specific values.
Transcript:
Speaker 2
What happens later on, the original deans and administrators burn out because of how much they hate the US news and rule report rankings, and they get replaced by people who are all it. They think the only point is to rise in the rankings. And those people don't hold back. They only have one target. I think something similar is the difference between so realizing I need a lot of money in order to a decent amount of money to support my family, but not thinking money is the point of life. And similarly, realizing that getting a decent number of publications and citations is necessary for a job versus thinking the goal of my life is to max out citations. And for me, there's a huge gulf between those things.
Speaker 1
Well, here's where I think they're connected because I see the difference and I understand the difference you're talking about. But I think the difference is that is this temporal dynamic, right, where you start out with, let's say, perverse incentives and people saying, well, I don't necessarily value these Things, but I have to shape my behavior in order to succeed in this system. But the thing is, the system being the way it is creates a filter. And the people who are the best at figuring out how to operate in that are the ones that then end up being successful. And they're the ones that teach the next generation or emulated by the next generation. And over time, the people for whatever reasons, psychologically or behaviorally or ever their path is, are best able to exploit the system are going to be able to thrive in it. And I think that because of that, you end up selecting for people with certain kinds of values, because they're going to be the people who there's always exceptions, but are going to Be best able to thrive in this kind of thing.)
- Time 0:12:16
- metrics, perverse_incentives, evolution, natural_selection, exploitation, 1social/post-queue,

(highlight:: Perspectives on Organizational Strategy & Coordination: Optimizing for Few Coherent Goals v.s. Many Incoherent Goals
Summary:
The corporate world is better at defining goals than the academic world.
Educational institutions struggle to articulate their goals due to disagreement. University administrators have competing goals, which leads to constant infighting.
The speaker prefers universities with plural goals and worries that focusing on one outcome leads to the loss of other important aspects of education.
However, top-level administrators should have reasonably well-defined goals that trickle down and create incentives.
Transcript:
Speaker 1
I think one of the things where the corporate world is actually much better at this than the academic world or the educational world, because their goal is profit. So it's very clear. It's much harder to say what the goal of an educational institution is. It feels like it should be obvious, but within the general goal of like we want to produce successful, well-rounded people, there's a lot of disagreement about what the goals are. And so shaping the institutional incentives around those goals becomes extremely difficult, because not only do we have to worry about perverse incentives, but we have to worry about Vigorous disagreement about the kinds of things that are valued in the first place. And I think exactly what you're talking about, T, is something that if you went to a bunch of university administrators, let's say, or medical school administrators or doctors, and You said, what is the point to what you're doing? Is it to produce wise, well-rounded people? Is it to minimize costs to insurance companies? Is it to increase donor contributions? What is it? And there are all these competing goals. And so there's this constant infighting about among different people who have different versions of what the best version of their institution is, and it's so difficult to articulate What that is.
Speaker 2
I wonder if we're in different sides of this, because are you like worried about the hardness of it? It sounds like you think it's a problem that it's hard to come to agreement and articulate a goal, where I actually prefer the university that disagrees, has many incuit and plural goals, And worry that when it articulates an outcome clearly and starts orienting around that outcome, that's when it starts shedding a lot of what was good about the kind of pluralistic more. So let me just give you this is like from my life, right? So a university I've been employed at has started moving toward orienting everything around student success, where student success is defined as graduation rate, graduation speed, Salary after graduation. When you define that outcome, it becomes really easy to target, and the people that are targeting it, as you say, the people that target it well tend to rise, people that are willing to Go all in on targeting that stuff instead of caring about all the other weird shit that education might be for, tend to have better recordable outcomes and tend to rise in the university Structure. So I actually am happier for something as complicated with education, in which different groups have different conceptions of values about what they're doing, and we don't actually Try to settle it, and we don't hold them all to a high articulability constraint, because I think the business school and the CS department have more easily articulable outcomes than The creative writing department, art history department. A lot of the stuff that I'm writing right now is about like this defense of the inarticulable.
Speaker 1
It's a hard question to answer because I think that there are multiple levels of organization going on here. There's like a top administrator level, because these institutions tend to be pretty hierarchical. I think at the top of the hierarchy, there has to be some sort of reasonably well-defined goal, even if it doesn't specify what every individual component of the organization or institution Would do it. And I think that that trickles down to those levels though, and creates incentives. Regardless of whether or not it's a good thing, I think there has to be some sort of coherence at the very top level, even if it doesn't dictate what each individual component is doing.)
- Time 0:17:04
- goals, group_dynamics, group_governance, incentives, organizational_incentives, organizational_strategy, strategy, group_performanceeffectiveness, 1social/posted/linkedin, 1social/post-queue, 1social/posted/twitter,

(highlight:: Ambiguity in Communication is Both a Feature and a Bug
Summary:
In 1984, Eisenberg proposed that ambiguity in communication is important and influential.
This idea suggests that being too clear can limit interpretation and hinder coalition-building. Ambiguity can be used to evade accountability, but it is also a general principle of communication.
Transcript:
Speaker 1
It's Eisenberg in 1984 in communication monographs or something. It's this great rambling paper and this idea has been massively influential to me, but he's basically arguing that it would seem like the point of communication should be clarity, To be as clear as possible. For me to say, I mean this and you do know exactly what I mean and that's the goal and ambiguity is therefore a bad thing. He argues that actually no ambiguity is a really important thing and other people have expanded on this. Now the way I think about this is like a blend of Eisenberg and then other people who've come a bit later, but that in a lot of ways if you're trying to get let's say a coalition, you don't Want to say this is exactly what our goal is and this is what we're trying to do. You want to use vague terms so that a bunch of people can sort of map whatever they think that the goal is onto and say that's consistent. It also leads to a reduction in accountability because after you do something and someone says, you said you were going to do this and you say, nah-ah listen to what I said, it's consistent With what I did because what I said was ambiguous. So it's pernicious in a way too. It's used nefariously in a lot of ways by let's say politicians and other kinds of leaders to avoid accountability, but it's also just a general principle of communication I think.)
- Time 0:27:20
- communication, communication_clarity, accountability, deception, alignment, goal_coherence, communication_ambiguity, political_ambiguity, 1social/post-queue,

(highlight:: The tension between the ambiguity of individuals' goals and large scale collective organization
Summary:
Living in an ambiguous environment with diverse goals is good for human beings, but it conflicts with the need for clear policies in large organizations.
As organizations prioritize coherence and clear outcomes, the world will be filled with large organizations staffed with individuals focused on achieving specific outcomes, which may be inhumane and undesirable.
Transcript:
Speaker 2
Here's the pessimistic nightmare. It is really good and healthy for human beings to live in an ambiguous environment with a pluralistic set of goals, many of which are in Kuwait. That is an essential tension with the methods of large scale collective organization. If it's true that for an organization to cohere, it needs to have clear policies so it can act coherently, then we should not expect that kind of ambiguity to survive at scale. And I think what you're describing, so I tend to think about since I'm a philosopher like what makes something constitutively coherent. And what you're describing is a kind of evolutionary process. You know, some organizations are going to be more coherent than others and some people are more interested in coherence. And the people that are more interested in following the strict outcome are going to arise in the organization. And the organizations that have clear outcomes are going to be better at achieving those outcomes. And so our world is going to be full of large organizations staffed with people that have very, very clear specifications of outcomes. And there's something inhumane and bad about that for individuals. But that's what happens when we need to organize in large scale collectives.)
- Time 0:29:12
- goal_coherence, pluralism, favorite, coordination, collective_intelligence, incentives, 1social/post-queue,

(highlight:: The Danger of Incorrectly Mapping Between Scientific Measures and Truth
Summary:
Scientific culture should strive for minimal ambiguity in mature theories.
Metrics can create false mappings if used to impose value judgments. Rigorous and unambiguous measures like the genie coefficient and GDP can be used to compare things, but should not be solely relied upon for determining superiority.
Transcript:
Speaker 1
And it's a problem when scientific culture tolerates too much ambiguity. There's always a caveat there, which is that at the early stage of theory development, sometimes you need ambiguity because you don't actually know really what you're talking about Yet. And so you need to allow for multiple interpretations to be possible until you can figure out what you mean. But a mature theory should be minimally ambiguous. This is at odds with things like metrics in terms of let's say how to evaluate something because people think, oh, well, it's scientific. Therefore, I want to use this to then therefore impose a value judge on something. It's better because it has a higher score on it. But that's not what science is actually able to do. Science can say, it has this score and it measures this thing because what it measures is this. If you say what it measures is this, and therefore it means this other thing, that's a problem because that's a false mapping. And it's not really about ambiguity versus precision. It's about, I think, the imprecision of the mapping between the measure and the term. So if you want to measure something like happiness or economic prosperity, you can say, well, we'll measure the genie coefficient, we'll measure GDP. But those are rigorous, clearly unambiguous measures. They have a meaning. This is what they are. This is how we measure them. We can compare things on this measure. And that's not problematic until you then say, and it is better to have a higher GDP full stop.)
- Time 0:31:04
- scientific_measurement, measurability_bias, metrics, truth, causality, 1social/post-queue,
- [note::See also: "the map is not the territory"]

(highlight:: How Measurability/Mathematical Bias Limits the Scope of Scientific Inquiry and Human Discovery
Summary:
In a fun and intriguing paper, Nobel Prize physicist Eugene Vigner explores the seemingly unreasonable effectiveness of mathematics in predicting and describing the world.
While mathematics is undeniably impressive, it may not be applicable to everything, particularly in social, cognitive, and philosophical fields where constructs and relationships are harder to quantify. This presents a gap that may be difficult to bridge.
Transcript:
Speaker 1
So there's this old paper from the, I think, 1960s by Eugene Vigner, the Nobel Prize physicist. It's called something like, on the unreasonable effectiveness of mathematics. The fun paper, and he's like, there's no good reason why mathematics should work as well as it does. And there's no good reason why there should be a tool that allows humans to predict things as well as math does. There's no good reason. It's kind of nuts. And we should all just be grateful. And he says some other things, but he's basically just kind of being all about how great mathematics is and how there's no good reason why it should be. And it's pretty cool that it does work so well. I think that there's a counter to that, which is that not everything is that easily described that mathematics. And there's lots of things for which mathematics is not that effective at describing. And it's actually just the things that were well described or easily described by mathematics are the things that were discovered using mathematical tools. They're the things that lend themselves that were amenable to mathematical inquiry. And a lot of the things that we're interested in terms of social science and cognitive science and the related philosophical inquiry are things that are much less tangible in terms Of this kind of specification. And you can see it like in a physics equation, right, a physical theory, whether it's about mass or electricity or something else, right, you have a theory about how things work. And then you can write out equations. And all the terms in the equations have units. And they are all directly related to the things that are measurable. The theories are directly about relationships between things that are measured. And in social theories and cognitive theories, so often our theories are about relating constructs. And then we have proxy measurements, but the theory isn't about the relationship between the proxy measures. The theory is about the constructs and the relationships between the constructs that are social in nature, that are cognitive in nature, but aren't the things that are being measured. And so there's this gap. And I don't know the extent to which that gap can be overcome.)
- Time 0:33:58
- natural_selection, measurability_bias, scientific_measurement, 1social/post-queue,
- [note::Reminds me of homophily i.e. "the problems that scientists are drawn to and eventually solve are the problems those scientists' tools are best suited to solve" - ultimately, an individual's or group's capacity to innovate is limited by the tools and methodologies they have at their disposal.]

(highlight:: Metrics: Something That Is Measurable Across Contexts?
Summary:
The difference between evaluation and a metric lies in the fact that a metric proceeds from the shared application of a measurement procedure that can be executed by different people across different contexts.
For something to be considered a metric, the measurement input procedure must be exportable across context, and the criteria for the metric must be something that many people can share and understand. However, there are many standards of evaluation that don't allow for this cross-contextual universalization, posing a challenge similar to the barrier of meaning in artificial intelligence and the elusive nature of trans-contextuality in machine learning.
Transcript:
Speaker 2
So you said that there must be a package of metrics. And I really wonder where that must come from if it's really true that there must be. Now, we're distinguishing two questions that there must be some way of evaluating something and there must be a metric for evaluation because metrics are really different. So here's a worry, and this is a little detour through a literature from science and technology studies. What makes a metric? So if you listen to people like Theodore Porter, this historian of quantification, the difference between just an evaluation and a metric is a metric proceeds from the shared application Of some kind of measurement procedure that can be executed by different people across different contexts. So I can evaluate all kinds of things for which there is no metric, right? I have complex, intuitive, aesthetic evaluations about things I love that when I try to articulate them, they fall apart. And those evaluations, different people can't perform the same kind of evaluation because that evaluation requires some kind of subtle sensitivity. So if you buy this view that what it is to be a metric is for the measurement input procedure to be exportable across context, that requires that the criteria for the metric be something That many people can share and understand. But one worry might be that there are a lot of standards of evaluation that don't admit of this kind of cross-contextual universalization.
Speaker 3
This is akin to Melanie Mitchell's barrier of meaning with artificial intelligence and the fact that trans-contextuality is the holy grail, elusive in machine learning.)
- Time 0:41:04
- metrics, measurability, measurement, evaluation, collective_intelligence, collective_understanding, context_independence, 1social/dont-post,

(highlight:: The Tension Between Organized Behavior at Scale and Individual Needs
Summary:
Large-scale organizations aim for legibility and coherence, but this may lead to a lack of diversity and individual needs.
The educational system's emphasis on GPA overlooks other important skills and qualities.
Transcript:
Speaker 2
One of the most influential ideas for me recently has been from James South's book Seeing Like a State. And Scott has this idea that like what large-hill organizations wants its legibility and legibility is a kind of clear coherence that's aggregatable to a kind of higher level view. So a simple version might be like look if you're a CEO you can't have every department have its own obscure little value system. You need a single collective value system or something close to it so you can get production and profit measures and aggregate them in what Scott says is bring the whole organization Into view. So one way to put my worry is that what would be good for human life is an incredible diversity of bottlenecks which work on different often non-metrified systems. If Scott is right large-scale institutions will tend towards is a kind of monolithic measurement system that moves towards let's have a small number of bottlenecks and let's have A unified measure. And so like the heart of my worry is that organized behavior at scale is inevitably in tension with what a diverse population of individuals needs. And that's just an unfixable problem. Let me just give one quick example. In the educational system the dominant measure is GPA. You can add other like I can write in my notes all kinds of other shit about what students are good at. That barely matters because that's not aggregatable. When a law school admissions officer is doing their spreadsheet to do the first main cutoff nothing in my weird little notes is going to make it into that first level cutoff. The big moving forces just look at GPA.)
- Time 0:49:47
- collective_values, information_aggregation, alignment, institutions, organizational_incentives, collective_behavior, coordination, organized_behavior, metrics, natural_selection, aggregate_measurement, employee_engagement, human_welfare, individual_welfare, work_satisfaction, 1social/post-queue,

(highlight:: Have we overshot the scale at which humans can effectively coordinate?
Summary:
We need Jim Rutt to join the conversation to discuss whether we have exceeded our ability to coordinate effectively.
The slow progress of science and the population growth curve are related to this question. Sam Bowles and his work on behavioral engineering and the return of civil society are also important in this discussion.
We are currently witnessing a clash between institutions and individuals, and something has to give.
Transcript:
Speaker 3
We need Jim Rutt on this conversation right because ultimately this is about have we actually overshot the scale at which we can effectively coordinate and all these studies like you Know this I know it's controversial but like the slowed canonical progress of science these kinds of questions they seem related in a way to the sigmoidal curve of population growth. Have we risen above a level at which intelligibility can actually happen and if so where was that level. I mean I remember you know Sam Bowles is another person who has been looming large for me over this whole conversation not only for his work on the problems of viewing humans as agents That can be governed through behavioral engineering via incentive but also because of the paper that he wrote with Wendy Carlin the article he wrote in Vox EU in 2020 on the battle for The COVID-19 narrative which talked about the return of the civil society you know meaning that the Mesoscopic world of guilds and church groups and sports clubs and pubs and neighborhood Organizations mutual aid networks and all of these other human scale sub-done bar number structures that we found ourselves suddenly very much in need of and yet were eroded by the Radical success of both state power and market power in every way it feels like we are in a kind of clash of the titans right now we're like you know we watch institutions going up against Large institutions and people are struggling to remain unpolverized underfoot. At some point something has to give right.)
- Time 0:52:51
- coordination, large-scale_cooperation, polarization, goal_coherence, influence, civil_society, communities, 1social/post-queue,

(highlight:: The Problem of Scale Clash in Human Collaboration
Summary:
The problem goes beyond ideal scale of humanity.
Different things we want involve different scales. Science works on a huge scale for problems like climate change while other things work on medium or small scales.
There is a clash of different scales and no optimal scale.
The big scales tend to win and squash out the small scales.
However, over long time scales, these complex systems tend to implode. It's about a dynamic balance where different forces coexist. How do we handle this in light of global coordination, bioregional organization, and personal relationships at the neighborhood level?
Transcript:
Speaker 2
I think the problem is even worse than what you're describing I'm going to try to pessimize what you said I mean when you ask me a question like have we gone past the ideal scale of humanity That implies that there is an ideal scale that we could plausibly hit if we could somehow convince people to scale back. For me the real worry is there's no ideal scale of humanity because different things we want to be involved in demand different scales science works really big good on a huge scale solving Problems like climate change our massive scale problems that everyone has to get together on and then there are other things that work at medium or small scales and there's just this Unsolvable scale clash my real worry is that different parts of us and our needs call us to different scales and there is not an optimal scale and so I have to participate in these different Scales or in tension with each other and also the big scales tend to win because they get really powerful and so they squash out the small scales.
Speaker 3
Over short time scales though right because over long time scales those like you know this is the Bob May will a complex system large complex system be stable question it's like at some Point those things tend to implode so it's not about like an equilibrium so much as it is about a a dynamic balance or a zone at which these different forces are able to coexist how do you Deal with all of this in light of both the need for global coordination and bioregional organization and neighborhood level personal relationships etc.)
- Time 0:54:50
- collaboration, scale_of_cooperation, innovation, large-scale_cooperation, scale_of_innovation, scale, 1social/post-queue,

(highlight:: Feeling like a speck in the wind amongst massive Societal systems
Summary:
The constant change in society and the environment has shaped human history for thousands of years.
Looking at these changes on a population scale rather than an individual scale can help us understand how society will evolve in the future. By recognizing patterns in how we all navigate through life together, we can gain valuable insights to inform our actions and make a positive impact on the world.
Transcript:
Speaker 1
I mean we have thousands of years of human history where you know since the agricultural revolution and the dawn of city-states it's just been constant change and one could argue that On a longish you know say century timescale we haven't been at equilibrium in 10,000 years what's next right how are all these nested feedback loops churning around between you know Societal structure and environmental structure to change the shape of society in the next couple hundred years Peter Turchin probably knows this better than I do but this is where I think thinking about these things at population scales rather than individual scales is it really helps me because when I think about things at the individual level like what can I do how do I live in the society right I find myself slightly distraught about like well I don't know I'm just a speck in the wind getting blown around by this maelstrom of society by trying To sort of think about the way the whole system is of all thing I can see it's not that I'm hurtling through space it's that we're all hurtling through space together in similar ways and That creates patterns that can then be identified what do you do with those patterns well then you know you get a professorship and you get to talk about it that helps sometimes)
- Time 0:56:45
- relatable, societal_complexity, societal_progress, scale, collective_behavior, individual_action, 1social/post-queue,

(highlight:: The Challenges and Risks of Understanding Social Dynamics at Scale
Key takeaways:
• Currently, there is a lack of coherent theories about social dynamics that work at scale in modern diverse societies.
• Many existing models for cultural evolution were developed for pre-industrial societies.
• Communication is a crucial aspect as the dissemination of understanding is important.
• A good formal theory about social systems can be both difficult to understand and potentially dangerous if exploited by nefarious actors.
• Understanding certain actors' behavior and the consequences of their actions allows for informed decision-making and intervention.
Transcript:
Speaker 1
That what you say is also correct right and it's something that so to speak keeps me up at night which is that a we are not there now we don't have currently very good coherent theories about Social dynamics that work at scale we know almost nothing about how cultural evolution works in a modern wired large scale diverse society because all of the models you know or so many Of the models were developed for sort of pre-industrial societies because the systems are simpler there's also you know the communication aspect right which is we can come up with Let's say I have an amazing theory that it's a really I've managed you know me and my team and collaborators have come up with a really coherent formal theory about the way things work One such a theory is going to be flawed and potentially dangerous in the wrong hands because if we really have a good formal theory about the way social systems work it can be immediately Exploited by you know nefarious actors also it's going to be really difficult to understand but it's also important to disseminate that understanding because people should know What to look out for right if you know how let's say certain actors are behaving and what the consequences of those actions are you're more likely to be able to say wait a second I know the Consequences of you doing that I don't want you to do that whereas if you don't know why some actor is doing something you're like well I don't know why they pass that well I guess it's fine.)
- Time 1:06:27
- cultural_evolution, scale, group_dynamics, social_dynamics, societal_complexity, systems_modelling, societal_progress, exploitation, 1social/dont-post,

(highlight:: The Expert Identification Problem and the Challenges of Democratic Decision-Making
Key takeaways:
• The expert identification problem is a major concern when it comes to trusting experts in a democracy.
• Democracies aim to harness the intellectual power of diversity for better solutions.
• The challenge lies in recognizing the best solutions when they require expertise that the democratic entity may not possess.
• There is no clear solution to this problem, and democracy remains the best way to organize society according to the speaker.
Transcript:
Speaker 2
So for a long time I would say that the problem I've been most obsessed with is something I call the expert identification problem it's like how does the non-expert figure out which expert To trust if they don't have the expertise and one of the worries about a democracy is that it runs straight into the expert identification problem right like if we're democratically Voting on what to do we are aggregate non-experts I mean I'm not talking here about like oh we are the experts and you all are not even if you are the world expert in X you're a non-expert In a million other fields right so as an aggregate we are non-expert so here's the real worry for me if you have the right solution how would that get democratically approved Helen Landemore Is this a political theorist I really like she's part of a movement who are epistemic democrats and they think that democracies are the best way to harness the intellectual power of Diversity and the basic model is something like diverse people will come up with a better set of solutions and when you put them together the best solutions will rise to the top and my Worry is how will the democratic entity recognize which are the best solutions because if the best solution requires expertise to recognize and the democratic entity as an aggregate Is not an expert how will they figure it out and that's a problem I'm not sure there's a solution to and I also can't think of a better way to organize the world than democratically)
- Time 1:10:06
- export_identification, decision-making, large-scale_decision-making, trust_economics, participatory_democracy, trust, collective_decision-making, democratic_decision-making, election_science, political_science, 1social/post-queue,