Category: Uncategorized

Domalde was a tragic Swede king described in the 9th century. His mother had cursed him with bad luck, which carried to his people, who were having bad harvests. As the story goes:

Domald took the heritage after his father Visbur, and ruled over the land. As in his time there was great famine and distress, the Swedes made great offerings of sacrifice at Upsalir. The first autumn they sacrificed oxen, but the succeeding season was not improved thereby. The following autumn they sacrificed men, but the succeeding year was rather worse. The third autumn, when the offer of sacrifices should begin, a great multitude of Swedes came to Upsalir; and now the chiefs held consultations with each other, and all agreed that the times of scarcity were on account of their king Domald, and they resolved to offer him for good seasons, and to assault and kill him, and sprinkle the stalle of the gods with his blood. And they did so.

https://en.wikipedia.org/wiki/Domalde

This idea of king sacrifice is intriguing. It takes head on a contradiction inherent in the idea of a king, the most valuable person. If they’re so valuable, and if sacrifice is about giving up valuable things, then naturally a king is who you murder once murder of less valuable things has failed. King Sacrifice is important to distinguish from chaotic regicide by the masses. Domalde didn’t just face an uprising or revolt, he was sacred and therefore sacrificial. Or not. Maybe it’s just a story. Maybe some mere uprising or revolt got dressed up as having a deeper purpose to make the people look less barbaric. But the trope of the Sacred/Sacrificial King, evident in examples such as Rex Nemorensis, the scapegoats of myth, and obviously Christianity, gives us a look into a world before Kings merely had a divine right to rule, when they had a divine responsibility, enforced by all people, to rule well.

The theme of King Sacrifice—in which the benefits of power are structurally outstripped by its risks and responsibilities—has great implications for governance design, a concern of mine. King sacrifice creates a frame in which leadership is inherently thankless, accountable, and fraught: an ideal environment for selecting responsible leaders.

The prompt

Once you have experienced the failures of strong leadership and the failures of extreme decentralization, you may converge on a specific place in the middle: “We should have leaders, but not anyone who wants to lead.” The collective wisdom is that reluctant leaders are more like followers. They are humble, empowering, and their use of power is seen as responsible and legitimate because everyone understands that they don’t like using it.

So let’s say we all agree: “We should have leaders, but not anyone who wants to lead.” What then? It’s a great if you happen upon the rare someone like that, but in practice they simply can’t be found and recruited reliably. Whether you’re a community group or a large firm, it’s the luck of the draw for you: to have the right person around with the right attitude and alignment, you get lucky or you don’t. In that way, the maxim is more of a description than a strategy for good centralized governance.

Of course, it would be different if we could find or create reluctant leaders. If there were a way to reliably and systematically produce and select reluctant leaders, we’d be one step closer to saving dictatorship, while creating a dictatorship that’s worth saving.

The first thing to do is break this dichotomous construct “reluctance”. It presumes that a candidate is either entirely power hungry or entirely power wary. But how a person is depends on where they are. We know that power-wary people can eventually a develop a comfort for and fluency with power that can start to look like a taste for it. And we know that many traditional authority-focused leaders can have eye-opening experiences that inspire them to open up and flatten out. We also know that your reluctance depends on simple things like how full your plate is.

Let’s take advantage of context to create reluctant leaders. And under a framing of king sacrifice, it isn’t difficult. We need to step away from a picture of leadership as providing access to power and control, in favor of the view in terms of service and collaboration. For the right person, a big sacrifice counterbalances the benefits of power and control, leaving only the value of learning and serving others.

Imagine a small group election in which each candidate has to explicitly demonstrate their reluctance, and convince people to vote for them on the faith that they don’t really want to do it. More precisely, imagine an election in which every candidate describes what they are sacrificing in order to lead.

People who already don’t want to lead will already see that they are making a sacrifice, and can just describe it. People who do want to lead, and would naturally sacrifice anything, can make themselves actually reluctant by proposing a big sacrifice that they will make if they take the position. They will take a pay cut, they will never force anyone to do anything, they will get a therapist, or make themselves recallable with a minority vote, or pay out of pocket toimplement a program that reduces the authority of the position by spreading power around.

The community will then evaluate each candidate’s sacrifice along with every other qualification of holding the position. Whether the sacrifice is big or small or credible or not can’t really be quantified in general, so it’s a subjective or political decision on the part of voters whether a person’s sacrifice is substantial and legitimate enough. But even then, the political process is more responsive to arguments that are credible, and a goal is credible that meets recognized goal evaluation criteria. One example is the SMART taxonomy, which helps you ask: Is the proposed sacrifice not just substantial, but Specific, Measurable, Achievable, Relevant, and Time-bound?

Can this sacrifice framing mechanism be gamed? Well it’s political, of course it can be gamed. This is why it’s important to assume constrained contexts, such as an organization that is small enough that it can maintain alignment and rely on social factors like trust, respect, reputation, and just deeper knowledge about the person. Whether a pay cut is a sacrifice or a token depends on inside knowledge about the person and their existing means. It’s up to the community to know their candidates well enough to know if sacrifice is being invoked authentically or only rhetorically.

Of course, I’m coming from a specific place, defining leadership as shared or cooperative leadership, dictatorship as simply unitary authority, potentially benign. It can be captured by the power hungry, but doesn’t serve them by definition. And I’m assuming a group with a basic level of mutual regard and goal alignment. So these aren’t general claims, but claims that make sense for a group that is small enough for social norms to play a role in how things work.

Where is all this coming from?

Aside from the noble project of Saving Democracy, I’ve got a side hustle of Saving “Dictatorship”. It’s not such a betrayal:

1. Systems based on authority and leadership are pragmatic, workable, and familiar.
2. They are the easiest social systems to design and implement and scale (explaining why they’ve taken over the world)
3. If you can keep them benevolent, they can also be surprisingly democratic, in the sense of integrating the needs of all stakeholders, if you define benevolence to require it
4. Power and coercion are bad, they often co-occur with authority and hierarchy, but they can be decoupled. Successfully decoupling them puts unitary structures on the map as democratic solutions. That separation has to happen both in an org and in everyone’s minds
5. While people think of leadership and democracy as opposed, I think they’re aligned. As I define those terms, strong participation is a result of strong leadership, and strong leadership is a result of strong participation. They’re no dueling alternatives to the distribution of power, but two sides of the same coin of universal empowerment.
6. Taking it all the way, I actually don’t trust a democracy to work if every member of it hasn’t had a lot of experience leading. Making unitary authority systems of every size more capable of care and accountability makes it easier to give more people more experience in leadership.

When you stumble on an excerpt that says what you want to say better than you could ever say it, you switch very eagerly from blogging to quoting. This is a long excerpt from Francesca Polletta’s 2002, “Freedom is an endless meeting,” and incredible historical book about participatory community organizing. You can tell from the title that she’s interested in the fact that all solutions come with a pet tension for struggling with. Recounting story after story of early civil rights organizers balancing idealism and pragmatism, you understand how she gets so easily to realism, and you wonder why everyone in the democracy scene hasn’t. This bit tackles the eternal question of what leadership means when your goal is cultivating leaders and the biggest threat is your own effectiveness.

The literature on organizing is rife with injunctions against leading: organizers should rather help residents articulate their own agendas and build their leadership. Yet, in the process, organizers are often expected to help identify goals, push people to question their preferences, and rally them to act. How can they do that without thereby undermining the leadership capacities of those whom they are organizing? Myles Horton’s answer was to ask questions. “I use questions more than I do anything else. They don’t think of a question as intervening because they don’t realize that the reason you asked that question is because you know something…. Instead of you getting on a pinnacle you put them on a pinnacle.” Horton described a Highlander director in a workshop who “asks one question, and that one question turned that workshop around and completely moved it in a different direction.” Was the Highlander workshop leader leading? Should one ask questions that open the whole enterprise up for scrutiny? That purposely move a discussion in a new direction? In SNCC, asking questions later became a way for organizers to hold onto their radicalism without feeling that they were imposing it on the people whom they organized. The tactic ended up alienating people more than involving them. What comes across in the stories that Horton tells, in SNCC workers’ tales of the best organizers, and in the broader literature on organizing is good organizers’ creativity: their ability to respond to local conditions, to capitalize on sudden opportunities, to turn to advantage a seeming setback, to know when to exploit teachable moments and when to concentrate on winning an immediate objective. Sometimes you insist on fully participatory decisionmaking; sometimes you do not. Albany SNCC project head Charles Sherrod urged fellow organizers not to “let the project go to the dogs because you feel you must be democratic to the letter.” Horton recounted on numerous occasions an experience that he had had in a union organizing effort. At the time, the highway patrol was escorting scabs through the picket line, and the strike committee was at its wit’s end about how to counter this threat to strikers’ solidarity. After considering and rejecting numerous proposals, exhausted committee members demanded advice from Horton. When he refused, one of them pulled a gun. “I was tempted then to become an instant expert, right on the spot!” Horton confessed. “But I knew that if I did that, all would be lost and then all the rest of them would start asking me what to do. So I said: ‘No. Go ahead and shoot if you want to, but I’m not going to tell you.’ And the others calmed him down.”

Giving in would have defeated the purpose of persuading the strikers that they had the knowledge to make the decision themselves. But Horton sometimes told another story. When he was once asked to speak to a group of Tennessee farmers about organizing a cooperative, he knew, he said, that since “their expectation was that I would speak as an expert… if I didn’t speak, and said, ‘let’s have a discussion about this,’ they’d say, that guy doesn’t know anything.” So Horton “made a speech, the best speech I could. Then after it was over, while we were still there, I said, let’s discuss this speech. Let’s discuss what I have said. Well now, that was just one step removed, but close enough to their expectation that I was able to carry them along…. You do have to make concessions like that.” What better time to make a concession than when you’re looking down the barrel of a gun? Horton presumably knew that he could get away with refusing to be an expert in the first situation and not in the second. Perhaps the difference was that he was unknown to the farmers and was known to the strikers. But one could argue that a relationship with a history could tolerate aberrant exercises of leadership while first impressions die harder. In other words, extracting rules from the stories that Horton tells is difficult. When to lead and when to defer, when to ask leading questions and when to remain silent, when to focus on the limited objective and when to encourage people to see the circumscribed character of that objective—the answers depend on the situation and are not always readily evident.

p. 76

I love how that first bit about questions turns the patronism of the Socratic method right on its big self-important head. I also like the focus on process, what Polletta calls “the developmental project of democracy.” I think the single biggest force acting against democracy is the experience of everyday people in their first organizing role trying and failing to get others involved, and coming reluctantly to the conclusion that it just doesn’t work, that people want to be told what to do. Your bad experience cultivating democrary wasn’t a lens into the fundamental architecture of human nature. You’re a person in a social reality trying to fine tune a smaller reality within it. You’re in a project, and a project has to get where it’s going by starting where it’s at.

From a developmental perspective, no compromise from your ideal is really a compromise. A compromise is a step away from the ideal, and your steps are still toward the ideal away from the status quo. They don’t approach the ideal directly, as the crow flies. They follow the landscape and its contours, avoiding the mud as much as possible. Following the hills is only a compromise in the sense that obeying gravity is.

To keep the navigational metaphors going, what does it mean to navigate by the stars? When we follow a star, it’s not with the goal of getting there. You follow a star to reach a place on Earth that’s closer to it. And that’s a meaningful, deeply idealistic journey even if, in a cosmic sense, every place on Earth you could possibly go is ultimately the same number of years away from the light. Even if, as your North Star takes you climbing along the sphere to its pole, less and less of your motion is up toward the star and more and more is sideways to the pole. That’s just physical law. Obeying gravity is not a compromise.

An especially exciting thing about Polletta is her critique of prefiguration. Prefiguration is a popular framework for activism and radical change because it offers a way to pursue an ideal in this non-ideal world. It proposes that one create little microcosms of the ideal within the real, and that your perfect bubble grows and grows until it’s as big as the world. In the prefigurative view, the root of the power of participatory approaches to community is that they prefigure the global approach by enacting it. Seems hard to fault. But Polletta holds the developmental project in contrast to the prefigurative project, arguing that prefiguration works in relation to itself, with no more influence from the outside world than is necessary, while the developmental project is about the outside world. The project of pursuing the ideal becomes the project of finding the most idealistic way of relating to the rest of the world as it is, and that being that way in this world changes the world. The great thing about Polletta is it’s all examples and history first, so these ideas are grounded in actual things that happened, giving you nuance for free. From the page before the quote above:

One can also contrast this developmental rationale for participatory democratic decisionmaking with the prefigurative commitment that commentators have attributed to SNCC and the new left. Where a prefigurative commitment envisions change through personal self-transformation and moral suasion rather than through institutional political change, a developmental commitment is not in conflict with an explicitly political one. To the contrary, its very purpose is to produce activists and organizations capable of taking on powerful officials and agencies. From early on, Horton said, he had been “more concerned with structural changes than I have with changing the hearts of people.” A prefigurative commitment tends toward absolutism since the object is both to “oppose” a current regime and to be truly “opposite”; a developmental commitment tends more toward an acceptance of the conventional. The two projects have very different views of organization. A prefigurative project is suspicious of organization, concerned that it molds people in its own image, valorizing efficiency and conformity over the purposes for which the organization was created, raising means to the level of ends. Enacting the ends in the means, committing to the “here-and-now revolution,” favoring community over organization—all these counter the oligarchical tendencies of organizations. By contrast, the broader organizing strategy of which a developmental project is a part sees organizations as one of the key arenas for developing political efficacy, leadership, and accountability and, not least, for securing power. An organization is doomed to failure unless people have a stake in its preservation, however. Participation in decisionmaking provides the sense of ownership and the pleasures of learning that sustain people’s participation.

The relationship underpinning a developmental democratic project is a pedagogical one. People learn to articulate concerns and evaluate options by doing so. At the same time, they learn from each other, and they may also learn from a facilitator or teacher, someone who encourages, guides, questions, and challenges them.

p.74

The tough thing for me about a good book is it takes years to read because I keep going into reveries. It’s been 2 years probably and I’m only 75 pages in. Here’s another great quote from earlier in the book, redeeming meetings:

Local people have really begun to find a way that they can use a meeting as a tool for running their own lives. For having someone to say about it.

That’s a line from Bob Moses, an organizer for the civil rights movement in the US South. It offers such a striking counter narrative to the modern “meetings are bad; fewer meetings” atmosphere that work culture creates. I think what’s happened is that there has been a change in the meaning of the word “meeting”. The way it is used in those quotes is as a bottom-up gathering of community members to discuss a matter of shared concern. That is so much different from what the word means today. If I were weaving conspiracy theories, I’d say that part of the project of undermining democracy has been capturing and corrupting the word. I think there’s a case to be made that meeting, not voting, is the fundamental unit of democracy.

You’ve just reached into a large opaque jar and pulled out the number 87. I could add some other structure, that the biggest number is 100, or that odd numbers are twice as common as even, and then ask clearly answerable questions. But what if we know nothing more than what we’ve seen: a ball from the jar with the number 87? What’s the biggest number in the jar? Are there even other numbers in the jar? Or you’ve reached in and pulled out a purple marble, how many colors of marble are there? Are they all round? Are there any numbers in the jar? Some of these have actual answers, and that’s important because they link to a bigger question:

What do our philosophies of statistics fill in about our world when they’ve seen almost nothing from it?

Or put another way: just how much can you know about the world with nearly no data and nearly no theory? I’m in social science, so it’s a real thrill when I find knowledge I can trust. And to do it from nearly nothing is astonishing. You can get the shape of the world from just 1 or even 0 observations. As an empirics-first person, I’m surprised to hear myself say it, but there’s so much you already know about the world when you don’t know nearly nothing. I’ve been collecting examples for year. And these examples have actually helped me do normal things, like find my keys, charge my phone, and, thanks to German tanks, take a long, hot shower.

The foggy sea, the German tank problem, and showers at a campsite.

You’ve been wandering for weeks, no map, through a foggy landscape. You reached a body of water, knowing nothing about how large it is, and decided to cross it with your inflatable raft. It’s been about 10 minutes already, so you know that this body of water is bigger than a creek, but it could be a lake, sea, or ocean. It could be another 2 minutes to the other side, or two months. Knowing nothing, what’s your best guess for the total size of the lake?

This is a continuous version of a famous statistical problem called the German tank problem. The Allies need to estimate German tank production. As they captured and examined German tank hulls, they found that their engines had serial numbers. So if you’ve captured a tank with the number 200 on the engine, you immediately know that there are at least 200 tanks. But does that also tell you anything about the total number of tanks? It does, and that’s fascinating: it’s a hint of everything you know when you know almost nothing.

And it’s not just a matter of theory. I was at a camping ground with spotty hot water. Some days there was as much as you want, and others it only lasted long enough to get your hopes up, just one minute or two, before getting icy. So if you’ve been in the shower for one minute, you know that there was at least one minute of hot water available, but do you now know anything about how much hot water is left?

Amazingly, you do. And that’s useful to know. If you need 10 minutes to wash your hair, you’ll be in a bind if the water goes icy in five. And absent the magic answer, it’s not entirely clear what you should do. Play it safe and never wash your hair? Roll the dice and have soap in your eyes when the water turns cold? Well there’s a solution to this problem, the German Tank Problem, and to the problem of the foggy sea: Your best guess at any moment is that you’re halfway through. So if you’ve been rowing for 10 minutes, then your best guess in this moment is that there are ten minutes of rowing. And every minute after that you best guess will go up (not down!). If you’ve captured tank #350 then your best guess in this moment is that there are another 350 tanks, for a total of 700. And if you don’t know if you’ll have five minutes of hot water in the shower, spend the first five minutes showering cautiously, as if the hot water could end at any moment. At the five minute mark you have a legitimate reason to feel confident that you’ll have five more minutes to wash your hair.

That’s what I did, and it worked!

Connection to science

The scientific method in the West comes out of several centuries of debate: can you know the world by reason alone? By observation alone? To skip past a lot of arguing, the answer is “both” via the scientific method, a procedure for bringing reason and observation into dialogue. But in practice they’re always in balance, and whether to center theory or data differs so much by discipline. In some areas of knowledge, like physics, data drapes beautifully off the framework of theory. In others, with phenomena that are too complex for elegant theories (e.g. social science), theory does a much more sorry job at propping up the data, so you end up using the data as its own model. that explains the role of machine theory, information theory, and statistics. As a social scientist your theories aren’t nearly good enough to really predict outcomes, and you spend a lot of time with statistics, the part of math that turns data into knowledge.

The conventional statistics that social scientists are taught can be called “small-n” statistics because it was developed in the early 20th century when it was costly to collect many independent observations (n represent your total number of observations). You had to squeeze every bit of insight from the couple dozen n you could get. The computing of the 21st century brought us big data and a switch to an alterantive philosophy of statistics that could leverage large n.

Within that frame, this exercise, “what you know when you know nothing” is a bit of a throwback. We drop from large-n statistics, down past small-n statistics, to the very smallest-n statistics of n=1.

Relevance to the philosophy of statistics

There isn’t just one statistics of n=1, and there’s actually a different answer to the German Tank problem. There are two alternative philosophies of statistics: the frequentist and Bayesian paradigms. There is a clear formal difference that is hard to cast intuitively, but narratively frequentism develops statistics by estimating what will happen from what has happened, while Bayesianism understands statistics as a problem of estimating what will happen from an observer’s beliefs about what has happened. Instead of trying to figure out how many tanks are in this world, the Bayesian observer imagines a range of possible worlds, in which the Germans have built everything from 2 to 20,000 tanks, and they work to determine which of those worlds we’re in. It may sound like a subtle distinction, but philosophically it’s big and mathematically it’s big. And, as we’ll see, the different philosophies predict very different numbers of tanks.

Between the two, Bayesianism is ascendant today because it wasn’t feasible to use before the ubiquity of cheap computing, but one isn’t better than the other. They are both ways of writing models, and all models are wrong.

One practical difference: the Bayesian approach is better for handling the complexity that comes with a lot of data, while the frequentist approach was developed for the era of “small-n” statistics, when the challenge was usually to learn as much as you could from very little data. And because the German Tank Problem is a “very very small data” problem, the frequentist answer is better. The frequentist answer is the one I’ve described, that what you’ve observed is half of the total. The Bayesian solution is that what you’ve observed is the total: if the largest serial number you’ve seen is #350, then your best guess is that there are only 350 tanks, because, assuming tanks are costly to produce, a world of 350 tanks is the one with the most evidence.

But the Bayesian way of thinking has it’s own place as well in revealing what we know when we know nothing.

How to find your keys

I lost my keys on the ride to the gym, somewhere on a mile-long stretch, and it was dark by the time I came out of the gym and realized it. I didn’t want to wait till morning, and I didn’t want to backtrack slowly and spend a half hour looking carefully. After all, they could have been anywhere. So I thought about it. Are my keys equally likely to be anywhere along the mile stretch? Or are they more likely to be in some places than others? I could be in a world in which it was very unlikely that I would lose my keys at all. In that world they really could be anywhere. I could also be in a world in which they were just waiting to be lost, as if they were scotch-taped to the outside of my side pocket. In that world I probably lost them right away, walking down my steps. I didn’t know which world I was in, or which of all the worlds in between, but in more of those worlds my keys were near my front door. So instead of searching slowly back home from the gym, I decided to ride straight home and start the search at my front door. My keys turned out to be right there. In most possible worlds, you lost your keys as soon as they were loseable, and they are most likely to be wherever you last remember having them or moving them. The power of Bayesian reasoning is that you can reason to that, and you can prove it too, which some friends helped me do in another post.

How much charge is on your phone?

If you look at your phone, it’s unlikely that it’s at 68% charge. But unless it’s constantly dead (0%), or constantly charging (100%), it is more likely to be at 68% than anything else. If you charge intermittently, but enough to stay above empty, and not enough to keep at full, then you can think of it this way: It’s morning and you’re at 100%. By evening it would be at 0%, but you charge in little moments during the day. We’ll say that you took a step down every time you were drained by a point, and a step up every time you charged by a point. We’ll say that when you hit 100% you always unplug (you can’t take a step up over 100).

A question is: how many ways are there to take 100 steps from 100%; how many paths are there in all the different combinations of up and down steps? And for any given charge level, how many ways are there to that point from 100% that involve exactly 100 steps? 0% only has one path leading to it: there is only one way to take 100 steps down from 100%. The 2% level has about 100 paths leading to it: a hundred ways to take 98 steps down with a little goosestep up and down at some point between the top and bottom. There are a lot of paths from 100% back to 100%: you can go down 50 and up 50, you can go down and up 50 times, you can go down and up by 4 then 7 then 15.

With these ideas, we’re now to our key question. Which charge level between 0 and 100 has the greatest number of paths leading to it? The 68% charge level is the one with the greatest number of paths leading to it (0% has the fewest). Another way of saying the same thing: if you randomly generate paths of length 100, up and down, over and over, the number you’ll land on the most is 68%. Not by a lot, but if I know nearly nothing about your phone—it’s got about a day of charge, it’s near the end of the day, you’re on the move enough that it’s often but not usually plugged in—the least bad guess is that you’re at about 60-70% charge by the end of the day.

The orthography of number

In the next book you pick up, keep an eye out for the first number you see, not spelled out but in digits. Will it be big, or little? Even or odd? What can we say about the numbers that are dealt to us, numbers about anything: dollars, marbles, people, fish? The fun thing about pure reason is a) you will learn something interesting, and b) you won’t get to choose what. According to Benford’s Law, the next number you see, big or small, is most likely to start with a 1. A number starting with 1 is 30%! That ends up being about 12% more likely than 2, which is about 5% more likely than 3, and so on down to 9, which initiates only 4.6% of numbers, not 11% like you’d expect (11=100/9 digits; you don’t divide by 10 because in Arabic numerals the only number than can start with the tenth digit, 0, is 0). I don’t understand it perfectly but it’s got something to do with there being more small numbers than big numbers, with logarithms, and with Arabic numerals. They come together to give 1’s center-stage. I don’t know if this is a metaphor or the actual explanation, but if you look at the way a slide rule gives physical space to each digit according to the logarithmic way of representing “bigness”, you’ll see that 1 gets more space than any of the others, and in that way gets more real estate in our lives, with pride of place on the far left of most written numbers.

It might sound far fetched to say, but pure reason, charged with statistical theory, and seeded with one observation, can help you shower comfortably, find your keys quickly, and keep your phone alive. It can probably also help you brush your teeth, clean your windows, and wash the dishes; let me know what you find.

There is a kind of problem so fundamental to organizing that we sometimes forget to think of it; common as day. You see it when

• People answering a survey tell you what they want you hear instead of the truth
• Someone lies at an interview
• Just about any time that people aren’t incentivized to be transparent

Those are all examples of mis-alignment in the sense that individual incentives don’t point to system goals. It’s called the problem of “incentive alignment” (also known as “incentive compatibility”).

The phenomenon of “buyer’s remorse” gives a clean economic example of the idea. In a normal auction, where people are bidding for a thing, it turns out that the structure of the decision doesn’t actually incentivize an honest evaluation by buyers of what they think a thing is worth. In real world auctions people often overbid, in part because they are influenced by the fear of losing. So typical “first-price” auctions are actually not incentive aligned.

But there’s an auction design out there that actually does incentivize honesty. It’s the “second-price” auction. In a second price auction the winner doesn’t pay the price they bid, but the next highest price. Why does that change anything? To see the trick you have to think a bit. At first thought you might just think that the smart strategy is to name a crazy high price and pay the losing bidder’s fair price. But what if all bidders think that? Then you’re going to overpay. You don’t want that: you don’t want to pay more for a thing than it’s worth to you. Where this reasoning gets you is that all bidders in a second-price setting will decide to name the price that they are actually willing to pay, no more, no less.

This is a good example because it also shows how small elegant tweaks you can restore alignment. In so many real world settings, incentives don’t support honest disclosure. We have workarounds in most parts of our life, but the problem still matters, and it attracts a lot of attention from economists. Their work depends crucially on the idea that incentives determine behavior.

Why save democracy when you can save dictatorship?

Incentive compatibility is especially challenging for survey design. How old are you? How much do you make? Who did you vote for in the last election? It turns out that we can’t always trust the answers to these questions. That’s important because surveys are the least bad way to learn things about people in a standardized way. But what if it was possible to pose any question—How often do you have non-PC thoughts?—in a way that people felt an incentive to answer truthfully?

For some things the problem is easy to solve once you’ve spotted it. Say you’re studying philanthropy, and you ask “Do you donate more or less to charity than your peers?” But you realize that most people will say that they donate more than they do. The incentive compatible way of getting an (honest) answer will be to invite people to non-hypothetically donate some of their survey reward to a charity. If they donate and that donation is smaller or larger than average, you the researcher found out if they donate more than others without actually having had to ask. By replacing hypothetical questions with costly behavior you get honesty.

Another strategy is to ask questions with verifiable answers. Instead of asking “What is your height and weight?” you might say “What is your height and weight? We will measure you after this and you’ll only get paid for participation if the difference is 0.” But if you’re verifying then why ask in the first place? And what if verification is impractical? And, most relevant for us, what if it’s impossible, such as with subjective self-evaluations (“Are you kind to others?”)?

Where it matters most, incentive compatible survey design is actually a real can of worms. The problem there is clearest if we hit pause on saving democracy and take a moment to try and save dictatorship. As a longtime scholar and organizer of self-governing communities, I’m comfortable saying that many communities could do worse than structure their governance under a benevolent dictatorship. A lot of groups, organizations, and communities that I admire do. In its most ideal form, benevolent dictatorship is not that different from democracy, because the dictator, being benevolent, is caring, curious, and motivated to understand and integrate everyone’s needs. As a result, the dictator will generate just the kinds of solutions that a healthy democracy would, and they’ll probably so it much more efficiently than a large governing body.

So why not replace everything with benevolent dictatorship? The main problem is fragility. Nothing systemic keeps the “benevolent” in there. If your competent leader was replaced by another competent leader, it’s generally luck. And you have to keep getting lucky because your first dictator won’t be your last. Benevolent dictatorship slips very easily into the non-benevolent kind that has reliably attended humanity’s darkest moments. Whether it’s through bad succession or the corrupting influence of power, no tool we have can reliably keep a benevolent dictatorship benevolent.

Incentive compatible survey design

Well there might be one tool. What if we had incentive compatible personality tests? It’s easy to imagine the important questions you would want to ask a candidate for dictator.

• “How likely are you to abuse power?”
• “How do you respond to disagreement?”
• “How do you respond to insults?”
• “If a brakeless trolley is hurtling toward a loved one, and you’re at the switch that can divert it on to another track with n people you’ve never met, what is the largest n you’ll tolerate.”
• You’re infuriated after reading a personal attack by a journalist in a major newspaper. Will you act on that journalist? If so, what will you do?

Asking is easy; what’s hard is to know if their answer is honest. If there was a way to know what someone really thinks, you’d just disqualify the people who give bad answers and appoint the people who give good answers.

I have lots of bad ideas on how to solve this, such as what I call “double-blind policy“, and is based on the premise that you can’t lie about a question if nobody knows what was asked.

But generally this is more likely to remain the name of a major challenge rather than the name of a class of solutions. Still: if we could solve it, I’m not entirely positive that I’d remain a scholar of classic democratic systems. I mean I would, but it would be harder not to admire the green grass on the other side.

“… The raft came ashore at Ta’doikö, and the place can be seen today.”

That’s the ending to a story that captured my imagination over 15 years ago in this 2007 post. It’s the creation myth of the Maidu indians, a people that lived in today’s Northern California all along the Sierra foothills, north of Sacramento, south of Redding, centered around Marysville Butte and Chico, CA (The full creation myth is here; I love it.).

Unfortunately according to the Wikipedia page the place Taodoiko has been lost.

Except that I found it, in this 2008 post. The key was in a map from the Handbook of the Indians of California (1967) written by the father of Ursula K. LeGuin, Berkeley anthropologist Alfred Louis Kroeber.

The key with Maidu (instead of Miwok) names for these places is on page 394 of the book.

With help from some historical maps of the area (in which the stream landmarks haven’t been developed away), that places Tadoiko right between Chico and Durham, CA.

You’d think I would have gone sooner. But I finally made it to the place, now a Walnut Orchard off of Fimple Rd. in Butte County twenty minutes south of Chico. The place where the world was created.

It was special to go. Where it describes thing coming from the North, I can see the north. Where it describes the sun, I could point. As in the story “And all around were mountains, as far as the eye could see.”

Another powerful thing about the piece: The companion to this story of the Earth’s creation is the one of humanity’s creation, which takes place in a different location, Marysville Butte. I’d always treated the like two separate stories but upon going it’s clear that they’re the same: from Tadoiko, Marysville Buttes is one of the most prominent features.

Less powerful of the place is that there’s no sign of it. It has ben replaced by walnut tree fields as far as the eye can see. I’d be curious if, among the residents, there was any inkling that their far is at the place of an old storied settlement.

This visualization effort was clearly inspired by Edwin Abbott’s book Flatland. It’s in French but Youtube’s automatic translations became excellent in the last few years. Plus you can put together most of the content from the visuals, which are the best part. I’m enough into the look of this retro stuff (the staid narration! the graininess! the effects! the props!) that I don’t really need comprehension to get from this everything I need.

Jean Painlevé may have been the first science documentarian. He’s best know for his sea life documentaries, which precede Jacques-Yves Cousteau’s, but as you can see he did lots of other stuff. His parents were Victorian-era free-love anarchist aristocrats.

I crush majorly on Painlevé; look up his other stuff as well.

Social justice activism is bringing changes to culture and discourse, especially in the US. Those changes can cause a lot of communication breakdown, even among people who should be aligned. If you can’t stand how old liberals put so much on civility when the world is burning or, if you’re baffled that today’s social justice has thrown freedom of expression under the bus, or if you just think there’s too much infighting all around, then there’s a solution. It’s actually not hard to reconcile the ethics behind broad-minded liberalism and confrontational identity-driven progressivism into one framework, to explain how they can co-exist, and actually always have, serving different purposes.

Two spaces

The worldviews seem incompatible because they exist in two different spaces built on different assumptions. They are the “dialogue-first” and “politics-first” spaces. Dialogue-first spaces exist when there is physical security and everyone can assume the good faith of everyone else. These get you the familiar ideal of older liberals: unity is a goal, good intentions behind a bad action matter, civility matters, there are no bad ideas, you attack the idea not the person, speech is free but yelling doesn’t work, content trumps style, you can discuss abhorrent ideas, defend people with abhorrent views, due process is respected by all, and reason prevails.

Politics-first spaces are wild: none of the above is true. You don’t assume good intentions of others who have wronged you, you can attack people rather than ideas, vulnerability can be weakness, interest in other cultures is appropriation, race and other identity differences are recognized and even emphasized, affiliation and trust are based on those identities, the legitimacy of your input depends on them, mobbing is legitimate, a witchhunt is a tactic, silence is assent, self-censorship is tact, shutting someone down is fair game, how you come off is as important as how you are, and the weak are strong en masse.

You’re clearly in politics-first space on social media, in opinion columns, during protests, pretty much anytime that you’re in a position to offend people who are loud, effective, and enflamed enough to take you down. You’re in dialogue space when you can ask challenging, ignorant, vulnerable questions and count on sympathy, patience, and an explanation. Close family and friends, sometimes the classroom. I’ve seen that people who experience the world as hostile to their existence are often tuned for politics-first exchange.

The tensions play out

The catch is that a space can claim to be dialogue-first but be politics-first in secret. In fact, I wonder if most spaces that call themselves dialogue-first have the other dynamic under the hood. And that’s dangerous: when a political space projects dialogue values, the emphasis on good faith makes it easier to hide abusive dynamics. If there’s no blatant evidence of sexual assault, and good faith means taking assailants at their word, then the veneer for dialogue-first dynamics can perpetuate awful behavior.

In politics-first spaces, appearance is reality, and creepiness can’t lurk as easily. Politics-first spaces can be more transparent, in the sense that your happiness doesn’t depend on other people being honest. You also have more strategies. “Safe spaces” are ridiculed in dialogue space, but they are adaptive in political space. Call-out culture, cancel culture, and other seemingly unaccountable tactics are fair game, even strategic, in political space. This is all good. On the very edge of social change and activism, dialogue is naive because the consensus conspiracy of institutional violence has bad faith at it’s core: the civil rights movement, Apartheid resistance, and BLM. In those cases, the politics-first headspace is the right headspace.

The only truly dialogue-first spaces are those that maintain consensus from all participants all the time. If one person’s experience is that they don’t believe others are acting in good faith, it’s literally not a dialogue space anymore, no matter how many other people still believe. That sounds like an overstatement, but the proof is easy. Say someone in a dialogue-first space speaks up after covert discrimination or harassment. Do you take their claim seriously or not? If you take them seriously, then you’re acknowledging that bad faith is happening somewhere. And if you don’t, then you’re rejecting their experience out of hand, in bad faith, and the person who just broke the space is you. No matter what you do, you’ll help them break consensus.

Since anyone can call bullshit at any time, true dialogue-first spaces are fragile. Dialogue-first spaces are little islands surrounded by the political spaces that call themselves dialogue-first, which are surrounded in turn by the seas of openly political spaces. When minorities in universities say that academia isn’t actually a field of pure ideas that rewards all equally, they are saying that they are experiencing the university’s founding ideal of dialogue as just a veneer. If that’s their experience, then good faith means assuming they’re right unless proven otherwise. So universities today are listening, foregrounding their political side, and asking critically whether that founding ideal really exists for everyone. That has upsides and downsides. Firing profs for assigning Huck Finn without proper warning is the other side of the coin of finally being able to fire them for sexual harassment. And it will continue this way until affected communities feel represented and are ready to buy in again to the university’s ideal. It will take time to build back up. The thing about the university’s fragile ideal is that if it can’t be broken it’s not real.

What to do

Everyone deserves to have a dialogue space they connect with. Dialogue space is less stressful and creates more room for growth. It’s important to want and have dialogue-first spaces. But it’s also important that whatever space you’re in has the right name. So within both spaces there are important things to do.

In a dialogue-first space. It’s easy to get nostalgic for a time when people could just talk about ideas without getting mobbed on social media. But there are people who are saying that that time only existed for you. If you don’t accept their experience as true, then you are making it true by perpetuating their marginalization. So the first thing to do is take a person seriously when they are challenging the consensus of your dialogue-first spaces. Victims who come out to expose violence in superficially dialogue-first spaces often get hostility for questioning the consensus, when they should get rewarded for finding the right name. You listen to challenges because you cherish your spaces enough to question them.

In a politics-first space. The fragile consensus of dialogue-first spaces makes it hard to build back up. You can, but you need the capacity. Capacity is how much bullshit you can take before losing patience, getting frustrated, or otherwise losing good faith. People don’t get to pick their capacity, and many don’t have much. Your capacity might be higher because of your privilege or your personality or your training. Here’s how:

1. To get two people assuming good faith from neither assuming good faith you need one person to assume good faith. That first mover should be the person with more capacity. If you’ve been blessed with high capacity, the tax on that blessing is an obligation to create a world that is dialogue-first for everyone. It’s on you to stand by dialogue-first ethics and also remain compassionate, humble, and cool in the boiling pot of politics-first exchange. You have to hold yourself to the high standards of both.

Step 1 is actually the only step. The second step is “wait.” Not because it’s all you have to do, but it’s all you can do. You can’t make someone assume good faith, so you need to have the capacity to maintain dialogue-first presence, model its value, and absorb political blows until others finally let their guard down and it becomes true.

Considerations

Because of all the patience and compromise involved, it is easier for pragmatists than ideologues to be first-movers. You often have to choose between saying things bluntly (“being right”) and saying things tactfully (“being effective”). You have to lead with your shortcomings and abolish pride. And you don’t just avoid behavior that actually alienates others, but behavior that comes off as potentially alienating, in the way that public figures work to avoid both impropriety and the appearance of impropriety. Overall, integrity in first-movers is maintaining the standards to thrive in both spaces.

If you do have capacity, you should get over that time you were called out unfairly, and become part of the solution. And if you can’t manage patience and waiting, then you might be more in the politics-first headspace than you realize. If your approach to defending rationality, reason, discussion, open-mindedness, freedom of expression, and other good stuff involves being defensive, dismissive, combative, sarcastic, or otherwise closed to the concerns of those who question consensus, then there’s a good chance that you’re just an agent provocateur, claiming you support dialogue-first spaces while covertly undermining them with bad faith politics-first tools. The tension between the spaces is an opportunity, not a warzone, and making war of it is a fundamental betrayal of enlightenment values. You should consider getting out of the way, until you get the help of a first-mover yourself.

It is sometimes easy to support people back into dialogue from a politics mindset, but there are failure modes. One failure is to move toward dialogue prematurely, while a community is still suffering from deeply rooted bad behavior or bad faith. So in addition to capacity, good first-movers need empathy and sensitivity, and they have to be up-to-date on a space’s current drama. They also need the integrity to not be creeps themselves, which can be hard if they have the blindspots that come from identifying as an ally. Another failure is that if someone has become powerful in a politics-first space, it might not be in their interest to change (a lot of radical Twitter), or they might only engage with people they identify with. That’s why a good first-mover is someone who is already a legitimate insider in their target identity group, which can be rare. Your identity shouldn’t matter, but in politics space it does. A third failure is if you encounter the immune response of a politics-first space. Politics-first constructs like tone-policing can be weaponized to discredit the whole idea of dialogue-first relationships. If that happens, this might not be the right time, or you might not be the right person. The last failure isn’t a failure at all. Again, on the very edge of social change and activism, political tools are the right tools. Some spaces are inherently politics-first, and some people specialize in that toolkit and thrive in that setting. If you step in where dialogue doesn’t make sense, you’ll just invite ridicule. Alinsky’s Rules for Radicals are built on exploiting the vulnerability of dialogue exchange for political wins.

This is a model. It succeeds at explaining a lot of the contradictions faced by people who are both sympathetic and wary about social justice. It explains why a lot of things that seem ugly about social justice rhetoric are adaptive in context, and what a space needs to be ready for civility discourse. It also gives a strategy for moving forward. And it gives rationalists who have been hurt something to aspire to. Hopefully this makes it easier for you to understand what’s going on with society right now, and articulate your place in change.

More notes

I’m still developing and editing this. On the one hand, there’s a lot to say, on the other, I’m trying to keep it short. Here are more dimensions as I come up with them, to maybe incorporate.

• Audience for this piece is people with capacity and commitment to dialogue-first space.
• Breaking consensus isn’t pointing out that there are politics. There are always politics. Consensus is the agreement that the politics aren’t bad enough for anytone to abandon dialogue-first values.
  Breaking consensus is announcing that the latent politics have become bad enough that your community’s shared commitment to dialogue-first values is causing too much harm
• Just like there’s always politics, there’s always power. Dialogue-first spaces can be compatible with power asymmetries (e.g. prof <-> student). What’s important is mutual assumption of good faith, and common belief in mutual assumption of good faith.
• “Good faith” can be made more specific: good faith commitment to community’s mission (in a university, intellectually learning/growing together)
• During social change, the pendulum overswings. Remembering that makes it easier to feel OK when it looks like the world is abandoning your values.
• There are more than two spaces. Political spaces, violent or not, don’t put violence first. That’s the space of actual war, which makes politics civil by comparison

In 1997, physicist and futurist Michio Kaku wrote this picture of daily life in 2020. He did pretty well. .Not all predictors of the future do. What I enjoy the most is how magical the present becomes when it’s described as far-fetched visionary fare.

A gentle ring wakes you up in the morning. A wall-sized picture of the seashore hanging silently on the wall suddenly springs to life, replaced by a warm, friendly face you have named Molly, who cheerily announces: ‘It’s time to wake up!’
As you walk into the kitchen, the appliances sense your presence. The coffeepot turns itself on. Bread is toasted to the setting you prefer. Your favorite music gently fills the air. The intelligent house is coming to life.
On the coffee table, Molly has printed out a personalized edition of the newspaper by scanning the Net. As you leave the kitchen, the refridgerator scans its contents and announces:’You’re out of milk. And the yogurt is sour.’ Molly adds: ‘We’re low on computers. Pick up a dozen more at the market while you’re at it.’
Most of your friends have bought ‘intelligent agent’ programs without faces or personalities. Some claim they get in the way; others prefer not to speak to their appliances. But you like the convenience of voice commands.
Before you leave, you instruct the robot vacuum cleaner to vacuum the carpet. It springs to life and, sening the wire tracks hidden beneath the carpet, begins its job.
As you drive off to work in your elecric/hybrid car, Molly has tapped into the Global Positioning System satellite orbiting overhead. ‘There is a major delay due to construction on Highway 1,’ she informs you. ‘Here is an alternate route.’ A map appears ghostlike on the windshield.
As you start driving along the smart highway, the traffic lights, sensing no other cars on this highway, all turn green. You whiz by the toll booths, which register your vehicle PIN number with their laser sensors and electronically charge your account. Molly’s radar quietly monitors the cars aroung you. Her computer, suddenly detecting danger, blurts out, ‘Watch out! There’s a car behind you!’ You narrowly miss a car in your blind spot. Once again, Molly may have saved your life. (Next time, you remind yourself, you will consider taking mass transit.)
At your office at Computer Genetics, a giant firm specializing in personalized DNA sequencing, you scan some video mail. A few bills. You insert your smart wallet card in the computer in the wall. A laser beam checks the iris of your eye for identification, and the transaction is done. Then at ten o’clock two staff members ‘meet’ with you via the wall screen.

Copied without permission from The Faber Book of Utopias, Ed. John Carey, who copied with permission from Kaku’s 1997 book Visions.

Being surrounded by smart people makes you think about intelligence. After all, they’re all so different from each other, so how could intelligence be one thing? And what does it mean with it changes!? I have been around long enough, and changed enough times in enough ways, to watch my own intelligence wax and wane in minor ways with changes in personality, circumstance, social environment. I’ve evolved a picture of intelligence that’s in line with prominent theories like the Cattell–Horn–Carroll theory, in which general intelligence has many dimensions, turned all the way up to 11. Where many of us imagine that IQ is a single knob in the brain that is just cranked way up or down for different people, I’ve come to think of it something with tens or hundreds of indeterminate overlapping facets that can be tweaked by nearly everything.

In that way, intelligence is a lot like nutrition. Above the usual macronutrients of carbohydrate, fat, and protein, our bodies rely on many many trace chemicals. The way the micronutrients work is that if you only need your trace amount of each them to be generally fine. Getting more than the necessary amount doesn’t tend to provide a benefit. Megadoses of this or that vitamin, while trendy, are usually pointless, and sometimes dangerous. So the name of the nutrition game isn’t so much about getting as much as possible of a few things, but getting the right amount of lots of things, not too little, and maybe not too much. Maybe “you’re only as healthy as your weakest nutrient.” Or “the roof is only as high as the shortest column.” In this way, nutrition is limited by a lot of potential bottlenecks.

I think intelligence is the same way. It requires a lot of traits, and its level isn’t determined by the strongest of them, but the weakest of them. Qualities that support intelligence, and hold it back, include creativity and curiosity, but also attention, self-consciousness, self-control, arousal, and even memory, risk tolerance, and coping style. Within memory, long-term, short-term, episodic, visual, and muscle memory are probably each potential bottlenecks on general intelligence. It can probably be held back by one’s limits to think visually, and to think verbally. Processing skills like subitization are probably excellent prereqs to strong visual reasoning. Certainly nutrition, life stability, and other aspects of nurture, like your exposure to logic and the wide variety of other tools of thought.

This doesn’t mean that traits can’t fill in for each other. Some traits can really make up for others (memory, and maybe fortitude), and can really be cranked quite high before they stop helping. But under this picture, there are limits to that kind of coping, for at least some traits, which makes them bottlenecks.

This has all borne out for me in different ways. I’ve observed myself behave with less intelligence when I’m not alert. And more interestingly, I got to observe myself become smarter after my personality changed to make me less anxious about loss and risk. Having known incredibly intelligent people with excellent memories, and watched a decline in my memory, I think my long-term memory may be my biggest bottleneck. A lot of my younger school age success was due to the fact that, once upon a time, I only had to read things once to remember them indefinitely. It isn’t like that any more. I’ve also never been much of a visual reasoner, and I’m a sorry subitizer.

This “bottleneck-driven” or “nutrition-like” picture of intelligence accounts for a lot. It seems compatible at first with theories of “multiple intelligences,” but it’s ultimately grounded in the idea of a general intelligence. General intelligence is just the idea that intelligence is general: that being smart isn’t being smart in one thing. I buy it because of something you see in education science: when you do interventions in classrooms, there is a type of student that will just do really well on every educational intervention you give them, no matter what it tests. Distributions of student performance on these kinds of assessments can be normal bell-curves, or close, with several students clustered tightly at the top of the performance range, and others distributed widely across the rest of the range. The hypothesis is that students off of the performance ceiling have one or more bottlenecks keeping them back, and they are all different in which quality is playing the role of bottleneck.

This theory has other implications as well for how we interpret learning accommodations. Rather than saying that exams miss measuring intelligence by testing only your memory and ability to sit still and concentrate, this theory more precisely says that exams test your intelligence in part by testing your memory and ability to sit still and concentrate, and that they miss intelligence by failing to measure the facets they don’t measure like creativity and curiosity. It also reinterprets what aids do. From this view, attention aids like drugs or exercises are intelligence aids for those people whose intelligence is limited by their ability to control their attention.

Going one step away from direct supporters of intelligence, there might also be traits that are only bottlenecks in certain cultures or environments. In a typical classroom setting, obedience is probably an important predictor of how effectively education feeds intelligence, and students without it may either need to develop it or seek a learning environment that doesn’t allow a trait like obedience to become an intelligence bottleneck. Conversely, it might be that among students in unstable social or cultural environments, the hyperfocus that you find with ADHD is adaptive. And obviously, in domains where knowledge is stored primarily in written words, impediments to reading, or a lack of alternatives to reading, will be indirect impediments as well.

There are obviously many things the theory misses. It’s great if there is just one way to be intelligent and lots of ways that intelligence can be limited. But if there are many kinds of intelligence, the theory only needs a couple tweaks from the nutrition model. Rather than bunching each personality or other trait that influences intelligence into the bottlenecks category, driven by the minimum, you’d call other max driven. In the more complicated picture, you’d say that the height of the ceiling depends on the shortest of some columns and the tallest of others.

But being no specialist in education science, I can’t seriously say that this is anything more than idle theorizing based off of personal anecdote. And any theory of such an elitist idea as intelligence is inherently going to be a little offensive. Allowing that, I imagine that this picture of it is overall less offensive than most others. All things considered, I think being such a holistic theory of intelligence makes it pretty humane, open, and empowering. It’s certainly makes a lot of predictions, and is actionable. In my case, if I personally buy this theory, I should probably become a better memorizer.

Cybernetics was an important part of my intellectual development, my first hint indication that there was a rigorous, systematic way of approaching complex things. I eventually got over cybernetics specifically, as much too general to contribute to the observation side of science. I was also disappointed that all of its legacy in science seemed to be obscured, with many senior academics I knew privately acknowledging its importance, but publicly revealing no hints. However, I’ve slowly learned that the influence of cybernetics was much more substantial than I’ve appreciated. I’ve collected anecdotes on its development in anthropology, and one of it’s services to big tobacco, and I knew it was the path to Allende’s technoutopia, with help from cyberneticist Stafford Beer. But apparently it was also influential in Jerry Brown’s first governorships, and less directly, in the first applications of graphic or interface design to computers.

Here are various quotes I pulled from the Jerry Brown article, which weaves together UC Berkeley’s full design talent, US politics, early environmentalism, and even the Dead Kennedys.

“Learn to distinguish between unity and uniformity—between God and hell.” That abouts summs [sic] up the 20th Century problem.

Eschewing the industrial iconography of steel and glass, the Bateson Building made do with concrete and wood … in order to maximize thermal performance and economy in the blazing Sacramento summer sun. The building’s understatement, which bordered on a functionalist antiaesthetic and surely contributed to its disappearance from the canon, was central to its broadly ecological mission. That mission seems to have had three main aspects: energy efficiency, interaction, and an attentiveness to systems. In pronouncing that mission, the Bateson Building represented the state’s pursuit of interdependence, adaptability, and self-reliance.

For Van der Ryn, such an integration of the greater sociopsycho-ecological whole was the central purpose of design. “The process of institution building and institutional innovation becomes more than a technical problem,” he wrote in 1968 with his then assistant, the political economist Robert Reich, who later served as secretary of labor under President Bill Clinton. “It becomes part of an overall design. It becomes utopian.” 63

The New Age state addressed a skepticism about government that ran even deeper than the culture wars. Its cybernetics and ecology countered pessimism about whether a selfless politics was even possible,

“Going into Space is an investment . . . and through the creation of new wealth we make possible the redistribution of more wealth to those who don’t have it. . . . As long as there is a safety valve of unexplored frontiers, then the creative, the aggressive, the exploitive urges of human beings can be channeled into long term possibilities and benefits. But if those frontiers close down and people begin to turn in upon themselves, that jeopardizes the democratic fabric.”

I would love to be optimistic about the future. In fact, I’m actively trying. There is hope in stunning technological advances, the existence and development of progressivism, and all the license we have to abide by some lessons of history (that human potential overall gets higher) and potentially ignore others (the inevitability of resource conflict). We can imagine ignoring dark lessons of history because modern humanity has demonstrated its ability to change how it is. We’ve changed in the last 100, 50, 10, or even 5 years more than we did over thousands of our earliest years. Maybe scarcity is a solvable problem. For example, I’ve been following with awe and wonder the rapid, exciting progress of the Wendelstein 7-X experimental fusion reactor in Greifswald, Germany. The limitless energy of hot fusion, and several other emerging technologies, means that we can think about energy intensive technological solutions to otherwise forbidding problems, toward the availability of costly fresh water from sea or waste water, the availability of sufficient food and wood from ever higher input agriculture, the possibility of manually repairing the climate, undoing material waste by mining landfills and the ocean’s trash fleets, and accessing the infinite possibilities permitted by space. These things could all be in hand in the next few decades, no matter how destructive we are in the meantime. Allowing these possibilities means very actively suppressing my cynicism and critical abilities, but I think it’s a very healthy thing to be able to suppress them, and so I try.

But every argument I come up with for this rosiest view backfires into an argument against postscarcity. Here’s an unhopeful argument that I came up with recently, while trying to go the other direction. It has a few steps. Start by imagining the state of humanity on Earth as a bowling ball rolling down the lane of time. Depending which pins it hits, humanity does great, awful, or manages something in between. There are at least two gutters, representing states that you can’t come back from. They foreclose entire kinds of future path. Outside of the gutters, virtually any outcome for humanity is on the table, from limitless post-humanity to the extinction of all cellular life on earth. In a gutter, a path has been chosen, and available options are only variations on the theme that that gutter defines. The most obvious gutter is grim: if we too rapidly and eagerly misspend the resources that open our possible paths, we foreclose promising futures and end up getting to choose only among grimmer ones. A majority of climate scientists assert that we are already in a gutter of high global temperature and sea levels. There is also a hope gutter, in which technology and the progressive expansion of consciousness will get us to an upside of no return, in which only the rosiest futures are available, and species-level disaster— existential risk— is no longer feasibly on the table.

The doom gutter is the easier to imagine of the two, and therefore it is easier to overweight. It’s too easy to say that it is more likely. “You can’t envision what you can’t imagine.” The question to answer, in convincing ourselves that everything is going to be fine, is how to end up in the hope gutter, and show that it’s closer than anyone suspects. That’s what I was trying to do when I accidentally made myself more convinced of the opposite.

The first in my thinking is to simplify the problem. One thing that makes this all harder to think through is technology. How people use technology to imagine the future depends a lot on their personality and prior beliefs. And those things are all over the place. From what I can tell, comparable numbers of reasonable people insist that technology will be our destruction and salvation. So my first step in thinking this all through was to take technology out: humanity is rolling down the gutter of time with nothing beyond the technology of 1990, 2000, or 2020, whatever. Which gutter are we mostly like to find now? Removing technology may actually change the answer a lot, depending where you come from. I think many tech utopians, as part of their faith that technology will save us, also believe that we’re doomed without it. I’ve found tech optimists to be humanity pessimists, in the sense that, if brave individuals step up to invent things that save us, it will be despite the ticking time bomb of the vast mass of humanity.

I, despite being a bit of a tech pessimist, am a humanity optimist. I think if technology were frozen, if that path was cut off from us we’d have a fair chance of getting our senses and negotiating a path toward a beautiful, just, empowering future. Especially if we all suddenly knew that technology was off the table, and that nothing would save us but ourselves. I don’t think we’d be looking at a postscarcity future, there is no postscarcity without seemingly magical levels of technological advancement, but one of the futures provided by the hope gutter. Even without technological progress, changes in collective consciousness and awareness and increases in the space of thinkable ideas can and have had a huge influence on where humanity goes. Even without the deus ex machina of technology, it is still possible to have dreams about wild and wonderful possible futures. This isn’t such a fringe idea either. Some of my favorite science fiction, like Le Guinn’s “Always Coming Home,” takes technology out of the equation entirely, and still imagines strange and wonderful perfect worlds.

So without technology, I actually see humanity’s path down the bowling lane of time being a lot like the path with technology: we have a wide range of futures available to us, some in the doom gutter, some in the hope gutter. That’s a very equivocal answer, indisputable to the point of being meaningless, but it’s still useful for the next step of my argument.

I do not think technology is not good. It is not bad. It doesn’t create better futures or worse ones. It overall just makes things bigger and more complicated. One quip I use a lot is that Photoshop (an advanced design technology) made good design better and bad design worse. Nuclear science created a revolution in energy, and also exposed us to whole new kinds of bitter end. Genetic engineering will do the same. Even medicine, possibly, if it ends up being able to serve the authoritarian ends of psychology-level social control. So unlike most people, I don’t think technological advances will bias humanity into one gutter or the other. I think technology will expand the number of ways for us to get into one gutter or the other. And it will get us into whichever gutter faster. That’s step two.

Step three of the argument starts with my assumption that the doom gutter is closer than the hope gutter. It is without technology, and it is with technology. I started off by saying that we should avoid saying that because it’s easy to say. But even then, I still think so. That’s just my belief, but this is all beliefs. One of the few clean takeaways of the study of history is that it is easier to destroy things than create them. But doom, in the model I’ve built, isn’t more likely because of technology, only because it is more likely overall. That doesn’t mean that technology will have no effect. It will bring us more quickly to whichever gutter it is going to bring us to. If at the end we’re doomed or saved because of technology, that end is less likely to happen slowly, and less likely to be imaginable.

p.s. I’d love to believe something different, that technology will save us. I’ll keep trying. We’ll see.

“Classical mechanics” is the name of the simplest physics. It is the physics of pool tables, physics before electricity, magnetism, relativity, and quantum effects. Nevertheless, we’re still learning new things about it. And those discoveries lead to some pretty deep toys.

Four tops

• Reverse-rotating top (magically turns around to spin the other way)
• Axis-reversing top (magically twists around itself spinning the same way)
• Self-inverting top (magically flips upside down)
• Negative-space top (magically turn any shape into a top)

Two dice

• Six-sided spherical die (magically not infinite-sided)
• One-sided die (actually a pretty big deal; great if you don’t like games of chance)

Digging up videos of these led me to other great things, like oloids, sphericons, solids of constant width, and tops in space

Society is not immutable, and it was not drawn randomly from the space of possible societies. People incrementally change the social systems that they participate in toward satisfying their own needs. This process can be conceptualized as a trajectory through the space of societies, whose “attractor” societies represent the systems that participants have selected.

I wrote a paper that implements this idea in simulation and demonstrates some simple results that fall out of it. This work explores the trajectories produced by selfish simulated agents exploring abstract spaces of economic games. It shows that the attractors produced by these artificially selfish agents can be unexpectedly fair, suggesting that the process of institutional evolution can be a mechanism for emergent cooperation.

Frey, S. and Atkisson C. (2020) A dynamic over games drives selfish agents to win–win outcomes Proc. R. Soc. B.28720202630. https://doi.org/fnq2

This paper took me almost 10 years to finish, so I’m very proud to have it out, especially in a venue as fancy as Proc B.

Short URL’s are useful in their own right. But they are in demand, prohibitively expensive, and also hard to find. You have to know some tricks to find unused URLs without raising the eyebrows of hucksters, but with the explosion of top-level domains (the end part of a URL, like .com), it’s actually possible. Using this price sheet, you can find all kinds of stuff: prices are going below the standard $15/year for .com, and also well above, like over $8000/year for a .makeup link. Rooting around, with .za not available yet, .uk comes out as the cheapest 2 letter domain per year. In .com, two, three, and four character domain names are allg gone, and super valuable. How about in .uk? Are there any two, three, or four level domains? I wanted to find out, so I wrote the following shell script

#Low profile search for the cheapest, shortest domain on the Internet
for i in {0..9}; for j in {0..9}; do whois $i$j.uk | grep "No match"; done;
for i in {a..z}; for j in {0..9}; do whois $i$j.uk | grep "No match"; done;
for i in {0..9}; for j in {a..z}; do whois $i$j.uk | grep "No match"; done;
for i in {a..z}; for j in {a..z}; do whois $i$j.uk | grep "No match"; done;

The key part is whois, which takes a URL and queries an official database of registered URLs. grep pulls out all error messages returned by whois, indicating URLs that have never been registered. It returned exactly one value, meaning that out of (10+26)^2=1296 possible URLs, only one had never been registered. So here you are, talking to the proud owner of the least desirable possible 2-letter URL: 0w.uk. And rather than paying thousands or millions, I pay less than $10, less than one pays for .com or .org.

What’s so undesirable about 0w.uk? It wasn’t clear at first, but here’s what I’ve come to: Two ‘w’s are desirable because of the invocation of the World Wide Wieb’s “www” convention. But a single w doesn’t do that. All it does is give so many syllables that the url takes longer to pronounce character-by-character than some five-letter URLs. And the 0, being easily confused with o, makes it so that the most available possible word-level pronunciations (“ow!” or “ow-wuck”) are positively misleading.

Still, it’s got some charm for being the runt of its litter. I expect to put it to good use.

Grad student

Postdoc

How many times have you been to court in your life? Once? Five times? Something wild, like 10 times? Donald Trump has been to court over 4095 times.

With 330M Americans, that amounts to a 1/100,000 chance he’ll end up in court against you. Remote enough, but way more likely than winning the lottery.

1 in 100,000 is about the same as your chances of dying by assault from a sharp object, and more likely than death by poisoning, peripheral vascular disease, or “animal contact”.

So … how’s this case gonna go, and what can you do to be prepared? For starters, are you more likely to be on the offense or defense?

According to the numbers, you’ve got pretty much equal chances of being the plaintiff or the defendant. Except! Close to half of all of his lawsuits involve him being the plaintiff in a casino-related case …

… so if you’re not in court with him about a casino-related matter, chances are 4:1 you’ve got him on the defense. We’ll see that that’s the wrong place to be.

And how likely are you to win? Turns out, almost any way you slice it, and no matter what other areas of life you might think he’s a loser, Donald Trump is a winner in court. Whether on defense or offense, Trump has won almost 9 times for every case he’s lost.

Of course, that’s unambiguous wins and losses, and those account for maybe only a third of cases. What about his “wins” (adding cases closed or dismissed as defendant or settled as plaintiff) and “losses” (cases closed or dismissed as plaintiff or settled as defendant)? That’s sure to change things.

Even including cases that ended settled, closed, or dismissed, Trump still comes out on top. He “wins” about 2.5 cases for every case he “loses”. Maybe it’s because he’s always right. Maybe he picks his battles. Maybe it’s that orange teflon coating. Maybe it’s just the triumph of wealth.

Or maybe, I don’t know, what if we compare his “wins” and “losses” as defendant vs plaintiff? Is he more or less effective on the offense vs defense? Turns out that that doesn’t make a difference either. On either side of the room, he wins almost 2.5 cases for each he loses.

There is one exception. I said above that most of his suits are as plaintiff in a casino case. Same for his “wins”. A major chunk of his “wins” are real offensive wins in casino cases. If we subtract those, the in the remaining cases that he’s the plaintiff you get almost perfectly even odds.

To be clear, that’s still not a winning bet. Win or lose, that’s one very costly coin flip on average, and perhaps more likely to be lose/lose than anything. But it’s the best it gets. As defendant in a non-casino case, which happen 5x more often, he’s still 2.5x more likely to come out on top somehow.

Slicing tinier and tinier adds more and more doubt, but there may be one exception to the exception. If you can get him to sue you specifically for a branding or trademark matter, the odds finally start to lean in your favor, with a 2.5 chance that *you’ll* win. That number is only based on a dozen or so cases. Go ahead, try your luck.

So the takeaway: If you must end up in court against Donald Trump, which is much more likely to happen than you think, you want to be the defendant in a case that’s not about casinos. You want him to sue you.

If Donald Trump sues you in a non-casino case, he’s about as likely to close the case prematurely, have it dismissed by the judge, or straight up lose as he is to win the case or get you to settle. This is ultimately not a winning scenario for you, just the least bad.

If you really want to find a way to win things against Donald Trump, become a fact checker. Of non-partisan Politifact’s 820 or so fact checks of Trump statements, 70% have been rated Mostly False or worse and only 4% have been rated True (https://www.politifact.com/personalities/donald-trump/).

… Or become Joe Biden who, as of mid-Summer 2020, is sitting on a 10 point major landslide of a lead.

Credit, disclaimers, and future directions:
Credit: I put this together from USA TODAY’s rolling analysis of Trump’s suits over the decades:
https://www.usatoday.com/pages/interactives/trump-lawsuits/
Death comparisons: https://en.wikipedia.org/wiki/List_of_causes_of_death_by_rate

Disclaimer 1: I’m not a lawyer.

Disclaimer 2: Of his 4000 suits, USA TODAY only has outcome data for 1500. That’s not a random 1500. It might over- or undercount his settlements or prematurely closed cases, as defendant or plaintiff. It may over-count recent cases in either role. Since the outcome data covers less than half of his cases, there’s a fair chance that all of these numbers are completely wrong. Welcome to working with data about humans.

Future directions:
1. It would be great to figure out the missing data. 2. Trump’s casino-related cases have died down a lot in recent years. Other kinds of cases have ramped way up. Rerunning this analysis on only the last 5-10 years could tell a much different story. 3. Also different, of course, are cases again his administration. His record there may be worse. 4. Are you more or less likely to get sued if you’re liberal or conservative? I’d guess no difference. 5. This would all be more clear if I had made figures.

The Takeaway again: If you must end up in court against Donald Trump, which is much more likely to happen than you think, you want to be the defendant in a case that’s not about casinos. You want him to sue you.

After several years of evidence of the volatility, insecurity, and overall reality of cryptocurrency, the conversation around cryptocurrency is evolving further away from the strict ideal of an immutable governance machine that runs itself without politics. Part of this is due to seeing the pure market do one of the many things that pure markets do: get captured by monopolists and oligopolists. It became a reality very quickly that both wealth in the network and control of its infrastructure concentrated very quickly in the hands of a few powerful actors. While some libertarians embrace market power as legitimate power because it emerges, the fall of these currencies, Bitcoin in particular, into the hands of the few has meant the end of the honeymoon for many in the crypto space. The narrative that has evolved is that we had high hopes, but we’ve learned our lesson, and with our eyes wide open are now looking at more types of mechanisms and more complex governance to create a new type of system that’s not just a market and such and such.

The simple critique of that narrative is that market capture caught no one by surprise who has done their homework. Market concentration, the emergent accumulation of capital in the hands of the few, is as reliable a property of markets as equilibrium, nearly as old and distinguished. We don’t hear about it as much, usually because of a mix of rug sweeping (“Inequality isn’t cool. Efficiency; that’s cool.”, “¿Monopoly, what monopoly?”), gaslighting (“But The State!”) or rationalization (“Is a Pareto distribution really that unequal?”, “Inequality is inevitable no matter what”, “Corporate capture of regulators is the fault of the existence of regulators”, “theoretically a natural monopolist will act as if they have competitors so no problem”, “the market’s autocrats are bad but less bad than those of The State”). Really, it should have caught no one by surprise that BitCoin and coins like it fell very quickly to those who probably don’t need more money.

But to the naïve surprise at protocol capture in crypto economies, there’s a much deeper critique. The original Bitcoin whitepaper, Nakamoto (2008), which was focused on demonstrating the security of the distributed ledger scheme, actually imposes a capture process by assumption, as part of its security arguments. The first security concern that Nakamoto tackles is the double spending problem, that an attacker who builds out a false ledger faster than the original secure ledger can undermine the currency by rewriting it to enrich themselves. This attack has proven to be more than theoretical. To prove against it, Nakamote defined a stochastic process, a random walk. He theorized to 1-D random walk agents (the original and the attacker) and estimated the size of the difference in their positions, given an initial headstart by the original. A basic result of probability theory is that, for an unbiased random walk, the probability of reaching every point, whether walking in 1 or 2 dimensions, approaches 1 as time extends toward infinity. By extension, no difference between two random walkers should be insurmountable. But Nakamoto doesn’t assume an unbiased walk. He assumes that the probability of the original chain to advance is greater than the probability of the false chain. This asymmetry breaks the result and guarantees that the original chain’s probability of success will diverge exponentially as their initial advantage increases. This was the security result.

But take a look. An assumption required by the security result is that the original chain has a structural advantage.

If a majority of CPU power is controlled by honest nodes, the honest chain will grow the fastest and outpace any competing chains. To modify a past block, an attacker would have to redo the proof-of-work of the block and all blocks after it and then catch up with and surpass the work of the honest nodes.
…
If a greedy attacker is able to
assemble more CPU power than all the honest nodes, he would have to choose between using it
to defraud people by stealing back his payments, or using it to generate new coins. He ought to
find it more profitable to play by the rules, such rules that favour him with more new coins than
everyone else combined, than to undermine the system and the validity of his own wealth.

The assumption is being used to examine one type of attack, but assuming it for this case has consequences that are much greater. It is the assumption that miner dynamics are driven by a rich-get-richer dynamic that implies oligopoly. Nakamoto gives some attention to this problem assuming that any nodes who accumulate enough power to cheat will have a greater incentive to stay honest. Whether that holds is another question: the point is that structural advantage and rich get richer dynamics were built into Bitcoin. having an imbalance of CPU power gives an agent the power to influence the very legitimacy of the system. Power within the system confers power over it. This was just the first example of many in the crypto space, of a few agents gaining the power to write the rules they follow. This can’t be framed as an embarrassing surprise, or an unfortunate lesson learned. It’s a foundation of the viability of the system. It was baked in; Bitcoin was vulnerable to capture from Day 1.

There’s a sort of battle for the soul of Internet going on right now, among those who see it as some combination of tool and microcosm of the future of society.

On the one hand you’ve got your decentralization utopians. They’ve been bolstered by the burgeoning of crypto. You might hear libertarian bywords like “maximizing human potential.” They see antiauthoritarianism as straightforwardly anti-state, and do what they can to create weed-y technologies that can’t be tamped down: that can’t be kept out of use by “the people,” which may or may not mean entrepreneurs. They see technology as making new forms of government possible.

On the other you’ve got your democratic utopians. They’re a bit more old school: some of the original dreamers into the potential of the Internet. They’re fairly pluralistic, as you can tell by the fact that every major democracy on the Internet is completely different from every other. They see technology as a complement, and not even a too necessary complement, to culture and community as the key to success in self-governance. They are more comfortable with bureaucracy and even some hierarchy: they’re pragmatic. Or not: I think they are because that what I think. I’m definitely a democracy fetishist, and not a decentralization fetishist.

A person can be both kind of utopian. Where they differ, the decentralized types might criticize democracy as faulty, unworkable, and too bureaucratic. The democracy types might criticize the decentralization types as too focused on technology and markets, and naive about the importance of culture and the social side.

The big threat to democratic experiments online: it requires a lot of upkeep to be performed by a lot of people. Members need training or skill or experience to be good stewards of a democracy. If you fall off on training, democracy devolves into forms like demagoguery. It seems to work best when members are invested enough that they think it’s worth all the time. To really be a viable model for the future, it’s not going to be enough to have a theory of institution engineering. Where going a theory of culture engineering.

The big threat decentralization experiments online, especially these days, is their vulnerability to co-optation. They rely heavily on reputation schemes, which can be thought of as a token representation of a person’s quality. A lot of effort is going now into mechanisms that quantify ineffables like that. But by making these qualities into ownable goods, you make them easier to distribute in a market economy, and whatever your ideals for your tool, the tool itself is liable to get picked up by institutions with lots of money if it can help them make more. This is because markets only work on excludable, subtractable goods. When we use technology to gives qualities the properties of a token, it becomes legible to markets, and they can step in and do what they’re good at.

There’s also a big threat to both. Somehow, the weaknesses of each get amplified at scale. Neither grows well. Neither is robust to capture at scale.

I love cybernetics, a funny body of work from the 50s-70s that attempted to give us a general theory of complex systems in the form of systems of differential equations. I love it so much that it took me years to realize that its metaphors, while offering wonderful links across the disciplines, are just metaphors, and would be incapable of leading me, the young scientist, towards new discoveries. Because in every discipline you find ideas that are just like those offered by cybernetics, except that they are specific, nuanced, grounded in data, and generative of insights. Cybernetics, for me, is a great illustration of how metaphors let science down, even when they are science-y. But there are exceptions.

James Hutton is the father of modern Geology, and in many ways he’s the Darwin of geology, although it might be more fair to say that Darwin is the Hutton of biology, as Hutton preceded Darwin by a generation, and his geology was the solid ground that the biologist’s biology ultimately grew on. Like Darwin, Hutton challenged the tacit dominance of the Bible in his field. The understanding, never properly questioned before him, had always been that the Earth was only a few thousand years old and had formed its mountains and hills and continents over several days of catastrophes. The theory that preceded Hutton is actually termed catastrophism, in contrast to the theory he introduced, that the earth is mind-bogglingly old, and its mountains and hills the result of the drip drip drip of water, sand, and wind.

How did he come up with that? Writer Loren Eisley gives us one theory: Hutton was trained as a physician. His thesis was on the circulatory system: “Inaugural Physico-Medical Dissertation on the Blood and the Circulation of the Microcosm”. Microcosm? That’s in there Hutton subscribed to the antiquated belief that humans were like the Universe in miniature. He observed that the dramatic differences between our young and old are the result of a long timeline of incremental changes, occurring in the tension between the constant growth and death of our skin, hair, nails, and bones. If humans are the result of a drip drip drip, and they are a copy of the universe, then incremental processes must account for other things as well. And there you have it, a shaky metaphor planting the seed for a fundamental transformation not only in how humanity views the earth, but how it views time. Hutton invented deep time by imagining the Earth to be like the body. Eisley called it “Hutton’s secret”: the Earth is an organism, and it’s there underneath us now, alive with change.

So big shaky metaphors can serve science? Really? What if Hutton was a one-off, lucky. Except he’s not alone. Pasteur’s germ theory of disease came out of a metaphor baked deep into his elitism and nationalism: as unlikely as it seems, tiny things can kill big things, the same way the awful teeming masses threaten the greatness of Mother France and her brilliant nobles. So there’s two. And the third is a big one. No grand metaphor has been more important to the last few hundred years of science than “the universe is a clockwork”, especially to physics and astronomy. This silly idea, which had its biggest impact in the 18th and 19th centuries, made thoughts thinkable that most of classical mechanics needs to make any sense at all.

I’m still not sure how bad metaphors lead to big advances. All I can figure is that committing 100% might force a person out of the ruts of received wisdom, and can make them receptive to the hints that other views pass over. Grand, ungrounded, wildly unfounded metaphors have a place in science, and not just any place. We can credit them with at least two of humanity’s most important discoveries from the last 250 years.

Long ago I ended up in a sort of leadership position for a member-owned, volunteer-run, consensus-based, youth-heavy multi-house housing cooperative. It has everything great and bad about democracy. Over five years I made tons of mistakes and lots of friends and lots of not friends and learned a lot about myself and how to get things done. At some point I wrote some of them down.

• Don’t bring a proposal to a membership meeting unless you know it’s going to pass. That means doing the legwork and building support behind the scenes, and also having a feel for the temperature in the room.
• You can’t keep all the balls in the air. Be intentional and maybe even public about which balls you are letting drop. Focus on existential threats. Accept that your org is and will always be a leaky boat.
• Hardest biggest lesson: I am full of self-doubt by nature and profession (scientist). But I learned to stick to the course of action I thought was right, against the noise of people thinking I was wrong, without having to convince myself they were wrong and I the brave harried hero.
• When you propose a rule, don’t write it to fix the thing that went wrong, write it to prevent anything like it from ever happening again. The difference is how much thought you put into how it happened and what has to fail for it to happen again.
• You have to be able to deal with people not liking you without getting resentful yourself. It was hard. I never would have learned except I had to. And even then I failed a lot.
• People respond to you genuinely publicly suffering to meet their needs. I was vulnerable a lot and begging a bunch.
• Need to bring people together? Being the common enemy works in a pinch. This is the corollary to letting balls drop. You can use this to get everyone to take on the job of keeping those less important but still nice and now unifying balls in the air.
• You can’t ever assume things are fine and not currently about to blow up.
• Can’t communicate enough with the membership. It’s amazing how fast bad vibes can start to build up in secret if you aren’t constantly rehumanizing yourself.
• Neat trick for the horse trading that is a part of getting things done: One nice right of your authority position is the power to create symbols of value out of thin air (titles, the name of a thing, the signature on an important contract). They cost you nothing to create and others value them. So create them and trade them away in exchange for things that matter. I signed four houses to my coop, and had a pet name for each one, and never got to name a single one. I always had to trade the name off in exchange for support on closing the deal.
• Power exists and you should use it to do what you think is right for the org, even if you might be wrong, as long as you are always double checking and striving to be less wrong. Democracy is inherently political/nonideal, in the sense that it is the sum of a bunch of people doing more and less undemocratic things within the broader constraints of a democratic accountability framework. So acts of power and working behind the scenes and managing information strategically aren’t undemocratic, they are a part of it, and you should do them when you need to, and you shouldn’t do them too much or its your head. That’s the way of things: admitting the existence of power and the necessity of occasionally wielding it despite your ideals. Running a system by occasionally violating its tenets isn’t bad, it’s beautiful. In an internally inconsistent world, what else but an internally inconsistent organization can survive?

Things I never figured out:

• How to guess who will be reliable before investing a bunch and being wrong.
• How to inspire. The few times it happened were totally unreproducible flukes. So I did a lot on my own.
• How to build an org that learns from its mistakes
• How to build a culture with really widespread engagement, not just a good core group

I have a paper that will be coming out in the upcoming Big Data special issue of Behavior Research Methods, a top methods journal in psychology. It’s called “The rippling dynamics of valenced messages in naturalistic youth chat” and it is out in an online preview version here:
https://link.springer.com/article/10.3758%2Fs13428-018-1140-6

The paper looked at hundreds of millions of chat in an online virtual world for youth. The popular pitch for the piece is about your words coming back to haunt you on social media. That’s one takeaway you might draw out from the work we did. We looked at social influence: how my words or actions affect you. Of course, a lot of people look at social influence. Some papers look at those influence over minutes, and that’s good to do because it might help us understand behavior in, say, online political discussion. Others look at social influence over years, and that’s also good to do because it tells us how our peers change us in the long term. But say you wanted the God’s eye view of specifically what kinds of small daily interactions have the smallest or largest effect on long-term influence. That would really get at the mechanisms of the emergence of identity and, in some sense, social change. But the same things that make that kind of conclusion exciting also make it hard to reach. Short-term social influence is a tangle of interactions, and long-scale influence is a tangle of tangles. We were able to untie the know just a bit. Specifically, we reconstructed the flow of time for chat messages as they rippled through a chat room and, reciprocally, as they rippled back to the original speaker. The finding was that, when I say something, that thing elicits responses in two seconds (predictably), and keeps eliciting responses for a minute, getting stronger in its effects quickly, and then slowly tapering off. The effect of the single chat event is to produce a wave of chat events stretched out over time. And each of those itself causes ripples that effect everyone else further, including the speaker. Putting it all together, your words’ effect on other ripples back to affect you, in a wave that starts around 8 seconds, and continues for several minutes, almost ten in you were being negative. We are able to count the amount of chat that occurred as a consequence of the original event, that wouldn’t have occurred if the chat hadn’t happened. By isolating your effect on yourself through others, and mapping that wave’s effects from 2 seconds to thirty minutes, we’re able to put a quantitative description on something we’ve always known but have rarely been able to study directly: the feedback, self-activating nature of conversation and influence. If chat rooms are echo chambers, we were able to capture not just others’ echoes of you, but your own echoes of yourself in the past.

Social scientists are very ecological in their understanding of causes and effects. If you stay close to the data, you are bound to see the world in terms of everything affecting everything. It’s what makes social science so hard to do. It’s also what makes virtual worlds so exciting. They are artificial places composed of real people. Stripped down, the social interactions they host can be seen more clearly, and you can pick tangles apart in a way you couldn’t do any other way. For this study, we were able to use a unique property of online youth chat to pry open an insight into how people’s words affect each other over time. To really do that, you’d have to piece out all the ways I affect myself: I heard myself say words, and that changes me. I anticipate others responding to my words and that changes me. Others actually respond and their responses change me. Those are all different ways that I can change me, and it seems impossible to separate them. The accomplishment of this project is that we were able to use the artificiality of the virtual world separate the third kind of change from the other two, to really zoom in on one specific channel for self influence.

This world is designed for kids, and kids need protection, so the system has a safety filter built in. The way the filter works is that if it finds something it doesn’t like, it won’t send it, but it also won’t tell you that it didn’t send. The result is that you think you sent a chat, but no one ever saw it. That situation never occurs in real life, but because it occurs online, we are able to look at the effect of turning off the effects of others hearing your words, without changing either your ability to hear your own words or your belief that others heard you. With this and other features of the system, we were able to compare similar messages that differed only on whether they were sent or were only thought to have been sent. By seeing how you are different a few seconds after, a few minutes after, when you did and didn’t actually reach others, we’re able to capture the rippling of influence over time.

This is a contribution to theory and method because we assumed for decades that this kind of rippling and tangling of overlapping influences is what drives conversation, but we’ve never been able to watch it in action, and actually see how influence over seconds translates into influence over minutes or tens of minutes. That’s a little academic for a popular audience, but there’s a popular angle as well. It turns out that these patterns are much different if the thing you said was positive or negative. That has implications for personally familiar online phenomena like rants and sniping. The feedback of your actions onto yourself through others corresponds to your rants and rages negatively affecting you through you effects on those you affected, and we’re able to show precisely how quickly your words can come back to haunt you.

I was following up on the lit around Bullshit Receptivity (or “BSR”; http://journal.sjdm.org/vol10.6.html) and stumbled on this master’s thesis using it to evaluate modern art perceptions. Title quote is from the abstract
https://uwspace.uwaterloo.ca/handle/10012/13746
(Can’t vouch for the research though; didn’t actually read the thesis).

As someone who always cringes reading artist statements, and whose English-degree-holding proud pedantic jerk wife failed critical theory twice out of spite, this was pretty gratifying.

Just one comment from the pedantic jerk: “Did they mean profundity?”

I stumbled on this in a used bookstore. Books about science by scientists are already my thing, and anthropologist Jacob Bronowski already stands out in my mind as a distinguished big-picture popular scientist because I’ve youtubed his The Ascent of Man, a 1980’s BBC series about human natural history that was commissioned by David Attenborough.

The book has its unity, even though its most easily described in terms of its parts: a sketch of the history of Western thought as a history of science. The emphasis he places on human error, accident, and historical contingency help reinforce an overall message that science is a human social endeavor. He succeeds in showing that the things that make it vulnerable and flawed are precisely what make it accessible, and he positions the book as an argument against a popular fear and suspicion of science that emerged in the 20th century.

What struck me in the beginning of the book was how much his account of the rise of science-like thinking mirrored Foucault’s in The Order of Things: for centuries humans understood the signature of order in nature to be similarity (walnuts prescribed for headaches because they look like brains—one of Foucault’s examples) , until intellectual developments in the 17th and 18th centuries reinterpreted similarity as occurring in minds, and not beyond them, and created a new way of ordering things in terms of causes and mechanisms.

And what struck me about the end of the book was how forcefully presents the rare picture of science that I most often fight for myself, as something less about steel-cold logic, and more about a world so complicated as to permit only tinkering, and yield only to luck and experience.

Most times that you hear a scientist resisting a picture of science, they’re pushing back against what they imagine the man-on-the-street thinks: “We’re not out-of-touch eggheads in the ivory tower? We matter!”. But there is a picture of science that I wrench as often out of the heads of scientists as any other type of person. It’s the idea that the goal of science is to find the logical system that explains everything. It’s an attractive picture because it has an end, and also because, at moments in the past, it hasn’t seemed so far off. Newton found a system that explains both billiard balls and the solar system. 20th century biologists of the modern evolutionary synthesis connected genetics to evolution to, eventually, cellular biology. But for most sciences, especially the natural and social sciences, well, there might be a system, but its going to be beyond the ability of the human mind to encapsulate. In such an environment, you have to step back from finding the system that explains everything, to finding a system that explains as much as it can without getting too complicated. In this picture, a big constraint on theory building is the human capacity to understand theories. It’s a special view of science because it’s harshly critical of many of the archetypes that we usually see as unimpeachable core scientists. Those great minds that imposed mathematical rigor on human behavior, and were so dazzled by it that they dismissed evidence when it threatened to haze the luster.

The sweep and finality of his system, which like the Goddess of Wisdom seemed to his contemporaries to step fully formed from a single brain was a visible example. From a puzzle of loose observations and working rules he had produced a single system ordered only by mathematics and a few axioms: ordered, it seemed, by a single divine edict, the law of inverse squares. Here was the traditional problem of the trader nations since Bible times; its solution meant something to every educated man. And its solution was so remarkably simple: everyone could grasp the law of inverse squares. From the moments that it was seen that this lightning flash of clarity was sufficient—God said “Let Newton be” and there was light—from this moment it was felt that here plainly was the order of God. And plainly therefore the mathematical method was the method of nature.
…
A science which orders its thoughts too early is stifled. For example, the ideas of the Epicureans about atoms two thousand years ago were quite reasonable; but they did only harm to a physics which could not yet measure temperature and pressure and learn the simpler laws which relate them. Or again the hope of the medieval alchemists that the elements might be changed was not as fanciful as we once thought. But it was merely damaging to a chemistry which did not yet understand the compositions of water and common salt.

The ambitions of the 18th century systematizers was to impose a mathematical finality on history and biology and geology and mining and spinning. It was a mistaken ambition and very damaging. (p44–45)

I’m especially happy about his digs at economics.

There is no sense at all in which science can be called a mere description of facts. It is in no sense, as humanists sometimes pretend, a neutral record of what happens in an endless mechanical encyclopedia. This mistaken view goes back to the eighteenth century. It pictures scientists as utilitarians still crying “Let be!” and still believing that the world runs best with no other regulating principles natural gravitation and human self-interest.

But this picture of the world of Mandeville and Bentham and Dickens’s Hard Times was never science. For science is not the blank record of facts, but the search for order with in the facts. And the truth of science is not truth to fact, which can never be more than approximate, but the truth of the laws which we see within the facts (130p)

It took five years, but it’s out, and I’m thrilled:

https://onlinelibrary.wiley.com/doi/full/10.1111/cogs.12632

You can get an accessible version here

I’m happy to answer questions.

These are a few of my favorite doodles from the “A Mammals Notebook” collection of Erik Satie’s whimsical (i.e. silly) writings and drawings and ditties. Who knew he also wrote and joked and drew? I scanned many many more:

SatieDoodles

“Pavlov’s CAT!!!! GET IT?”

Here are 20 more or less professional cartoonists who had precisely that original thought. Guess how many of them managed to make it funny. I’m posting this because I’m surprised at how much failure there is on this. Is the idea of Pavlov’s Cat inherently, objectively unfunny?

Bonus, slightly fewer people made it to Schrödinger’s dog. Somehow, a few of these are kind of funny. Why is Schrodinger’s Dog less hackneyed than Pavlov’s Cat? What does it mean about humor or semantics. Also notice the different roles of the dog compared to those of the cat.

And what does not original plus not original equal? Still not original.

OK, fine, the last one is funny.

I read
Advice for a young investigator
by Santiago Ramon y Cajal (1897)

Here is a good bit:

Once a hypothesis is clearly formulated, it must be submitted
to the ratification of testing. For this, we must choose
experiments or observations that are precise, complete, and
conclusive. One of the characteristic attributes of a great
intellect is the ability to design appropriate experiments.
They immediately ªnd ways of solving problems that
average scholars only clarify with long and exhausting
investigation.
If the hypothesis does not fit the data, it must be rejected
mercilessly and another explanation beyond reproach
drawn up. Let us subject ourselves to harsh self-criticism
that is based on a distrust of ourselves. During the course
of proof, we must be just as diligent in seeking data contrary
to our hypothesis as we are in ferreting out data that may
support it. Let us avoid excessive attachment to our own
ideas, which we need to treat as prosecutor, not defense
attorney. Even though a tumor is ours, it must be removed.
It is far better to correct ourselves than to endure correction
by others. Personally, I do not feel the slightest embarrassment
in giving up my ideas because I believe that to fall and
to rise alone demonstrates strength, whereas to fall and wait
for a helping hand indicates weakness.
Furthermore, we must admit our own absurdities whenever
someone points them out, and we should act accordingly.
Proving that we are driven only by a love of truth, we
shall win for our views the consideration and esteem of our
superiors.
Excessive self-esteem and pride deprive us of the supreme
pleasure of sculpting our own lives; of the incomparable
gratification of having improved and conquered ourselves;
of refining and perfecting our cerebral machinery—the legacy
of heredity. If conceit is ever excusable, it is when the
will remodels or re-creates us, acting as it were as a supreme
critic.
If our pride resists improvement, let us bear in mind that,
whether we like it or not, none of our tricks can slow the
triumph of truth, which will probably happen during our
lifetime. And the livelier the protestations of self-esteem
have been, the more lamentable the situation will be. Some
disagreeable character, perhaps even with bad intentions,
will undoubtedly arrive on the scene and point out our
inconsistency to us. And he will inevitably become enraged
if we readily correct ourselves because we will have deprived
him of an easy victory at our expense. However, we
should reply to him that the duty of the scientist is to adapt
continuously to new scientific methods, not become paralyzed
by mistakes; that cerebral vigor lies in mobilizing
oneself, not in reaching a state of ossiªcation; and that in
man’s intellectual life, as in the mental life of animals, the
harmful thing is not change, but regression and atavism.
Change automatically suggests vigor, plasticity, and youth.
In contrast, rigidity is synonymous with rest, cerebral lassitude,
and paralysis of thought; in other words, fatal inertia—certain
harbinger of decrepitude and death. With
winning sincerity, a certain scientist once remarked: “I
change because I study.” It would be even more self-effacing
and modest to point out: “I change because others study,
and I am fortunate to renew myself.” (pp 122–123)

Of course, he also said things like this:

To sum things up: As a general rule, we advise the man inclined toward science to seek in the one whom his heart has chosen a compatible psychological profile rather than beauty and wealth. In other words, he should seek feelings, tastes, and tendencies that are to a certain extent complementary to his own. He will not simply choose a woman, but a woman who belongs to him, whose best dowry will be a sensitive compliance with his wishes, and a warm and full-hearted acceptance of her husband’s view of life.
(pp 103–104)

Unlike teachers of history and literature, unaccustomed to assigning writing that mixes nuggets of wisdom and bald sexism. I’m thinking of being explicit with my students that they have several options, to
read and think in a manner divorced from emotion, to take the good and leave the bad, or to dismiss it all as rot. That’s got problems, but so does everything else I can think of. Working on it.

I want all of my interactions with students to be about the transmission of wondrous ideas. All the other bullshit should be defined out of my life as an educator.

But life happens, and students can flake on you and on their classmates, and if you don’t discourage it, it gets worse. So now the transmission of wonder is being crowded out by discussion about your late policy. And late policies are a trap.

For a softy like me, any policy that is strong enough to actually discourage tardy work is too harsh to be credible. To say NO LATE WORK WILL BE ACCEPTED is all well and good until you hit the exceptions: personal tragedies you don’t want to know about, the student who thoughtfully gave you three weeks advance notice by email, your own possible mistakes. Suddenly you’re penalizing thoughtfulness, incentivizing students to dishonestly inflate their excuse into an unspeakable tragedy, and setting yourself up to be the stern looker-past-of-quivering-chins. And what’s the alternative? 10% off for each day late? I don’t want to be rooting through month-past late-night emails from stressed students, looking up old deadlines, counting hours since submission, or calculating 10% decrements for this person and 30% for that one, especially not when such soft alternatives actually incentivize students to do the math and decide that 10% is worth another 24 hours. Plus, with all of these schemes, you’re pretending you care about a 10:02 submission on a 10:00 deadline—or even worse, you’re forgetting reality and convincing yourself that you actually do care.

My late policy should be flagrantly generous and utterly fearsome. It should be easy to compute and clear and reasonable. It should most certainly not increase the amount of late work, especially because that increases the work on me. It should be so fair that no one who challenges it has a leg to stand on, and so tough that all students are very strongly incentivized to get their work in on time. It should softly encourage students to be good to themselves, while allowing students flexibility in their lives, while not being so arbitrarily flexible that you’re always being challenged and prodded for more flexibility.

What I wanted was a low effort, utterly fair policy that nevertheless had my students in constant anxiety for every unexcused minute that they were late.

Is that even possible? Meet the Gamble Protocol. It’s based around one idea: because humans are risk averse, you can define systems that students simultaneously experience as rationally generous and emotionally terrifying. All you have to do is create a very friendly policy with small, steadily increasing probabilities of awful outcomes.

The Gamble Protocol is a lot like the well-known “10% off for every day late.” In fact, in the limit of infinite assignments, they’re statistically indistinguishable. Under the Protocol, a student who gets an assignment in before the deadline has a 100% chance of fair assessment of their work. After the deadline, they have a steadily increasing chance of getting 0% credit for all of their hard work. No partial credit: either a fair grade or nothing at all. On average, a student who submits 100 perfect assignments at 90% probability gets an A-, not because all submissions got 90%, but because ten got 0%. A bonus, for my purposes, is that I teach a lot of statistical reasoning, so the Protocol has extra legitimacy as an exercise in experiential learning.

After experimenting a bit, and feeling out my own feelings, I settled on the following: for each assignment, I draw a single number that applies to everyone (rather than recalculating for every late student). I draw it whenever I like, and I always tell students what number got drawn, and how many students got caught. The full details go in the syllabus:

Deadline. If the schedule says something is due for a class, it is due the night before that class at 10:00PM. There is no partial credit for unexcused lateness; late assignments are worth 0%. However, assignments submitted after the deadline will get a backup deadline subject to the Gamble Protocol.
The Gamble Protocol. I will randomly generate a backup deadline between 0 and 36 hours after the main deadline, following a specific pattern. Under this scheme:

• an assignment that is less than 2 hours late (before midnight), has a 99% chance of earning credit,
• an assignment turned in before 2:00AM has a 98% chance of earning credit,
• an assignment turned in 12 hours late, by 10AM, has a 90% chance of earning credit,
• that jumps suddenly down to 80% between 12–14 hours, getting worse faster,
• an assignment turned in 24 hours late, before the next 10:00PM, has a 60% chance of earning credit,
• and an assignment turned in more than 36 hours late is guaranteed to earn zero credit.

I will not calculate the backup deadline until well after its assignment was due.

Calculating is easy. For each assignment,

• you can put the following numbers in a hat and draw:
  
0 2 4 5 6 7 8 9 10 11 12 12 12 12 12 12
12 12 12 12 14 15 16 17 18 19 20 21 22 23 14 15
16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31
32 33 34 35 24 25 26 27 28 29 30 31 32 33 34 35
24 25 26 27 28 29 30 31 32 33 34 35 24 25 26 27
28 29 30 31 32 33 34 35 24 25 26 27 28 29 30 31
32 33 34 35

• or you can open any online R console and paste this code:
  deadline <- c( 0,2, c(4,5,6,7,8,9,10,11), rep(12, 10), rep(14:23,2), rep(24:35,5) ) sample(deadline)[1]

I'm keeping data from classes that did and did not use this policy to see if it reduces late work. I still haven't chugged any of it, but I will if requested. For future classes, I was thinking of extending from 36 hours to a few days, so that it really is directly equivalent to 10% for a day's tardiness.

Trying to get my students interested in how the Internet works, I ended up getting my family interested as well. We made this:

Here is how to install it:

• Download this file, containing the homepage and puppy image in a folder
• Move the file where you want it installed and unzip it
• Drag the Google.html file to your browser
• Copy the address of the file from your location bar, and have it handy
• Copy that file name into your browser’s box for replacing or overriding the new tab page. Or, if you are on another browser, wherever in their options where new tab pages get customized.
  • On Chrome, you’ll have to install this extension
  • On Firefox, you’ll have to install this extension
  • In addition to changing the new tab page, you can more easily change the default home page to the same address.
• If you want to change the appearance of this page in any way, you can edit the Google.html file as you like. The easiest thing to do is search/replace text that you want to be different.

My wife, a librarian and self-described pedantic jerk, got a tough question at the library the other day: “What’s a pee-dant?” Her first thought? “This has got to be a setup.”

My momma is from a part of Jordan where women had a tradition of getting tattoos all over. After many years of searching, and finally help from my librarian wife, I found a book published by Jordan’s national press by Taha Habahbeh and Hana Sadiq, an Iraqi fashion designer living in Jordan. I don’t think either speaks English, and the book is only in Arabic, but the pictures are good, if grainy.

(None of these are my great-grandma. These are all pictures from the book. It has a lot more. Full scan here.)

So yeah, face tattoos. And while we’re on the subject of things you in the Middle East do without fully thinking through the consequences, here’s a political service announcement about US foreign policy: After an extended period of secularization through the mid-20th century, in which my mom wore miniskirts and short hair, fundamentalist Islam started its revival in Jordan in the 1980s. The reversal is almost entirely attributable to the fallout from USA’s hysterically anticommunist foreign policy. That violent silliness drove US funding and training of the Afghani groups that became Al Qaeda, the initiation of a nuclear program in Iran to keep it from leaning on Russia, the smuggling of arms to Iran to fund anti-Communist massacres in Nicaragua, and the destructive consequences of the US’s uncompromising support for the Israeli occupation of Palestine. More recently, with US-caused conflicts in Iraq spreading war to Syria, Jordan continues to be the largest refugee camp in the world. Jordanians may always be a minority in their country.

Hypnotic flythrough of CT Scans of polymer climbing rope

From Wikimedia Commons

I love seeing visions of the future and of the past. I also love things that make super-human spans of time apprehensible. So, naturally I’m sold on this concluding vision of 2001 from a January 1901 special issue of Collier’s Weekly that focused on life since 1801.

I got this from the collections of Dartmouth College’s Rauner Library, which lets everybody in to ask for anything, and which hosted a personal showing of proto-sci-fi and early astronomy books.

The nature of reality doesn’t come up so often in general conversation. It only just occurred to me that that’s amazing, since pretty much everyone I know who has thought about it thinks something different. I know Platonists, relativists, nihilists, positivists, constructivists, and objectivists. Given the very deep differences between their beliefs about the nature of their own existences, it’s really a miracle that they can even have conversations. Regardless of the fact of the matter, what you think about these things affects what language means, what words means, and what it means to talk to other people.

And not only can you complete sentences with these people, you can do science with them, and science can build on a slow, steady accretion of facts and insights, even if each nugget was contributed by someone with a totally different, and utterly irreconcilable conception of the nature and limits of human knowledge. How?

I think of science as an abstraction layer. That’s sad, probably for a lot of reasons, but most immediately because it means that the only easy metaphor I was able to find is the computer programming language Java. Java was important to the software industry because it made it possible to write one program that could run on multiple different operating systems with no extra work. Java took the complexities and peculiarities of Unix and Windows and Moc and Linux and Solaris and built a layer on top of each that could make them all look the same to a Java program. I think of the tools of thought provided by science as an abstraction layer on different epistemologies that makes it possible for people with different views to get ideas back and forth to each other, despite all their differences.

Here is an excellent illustration.