Each generation has its own idyll year. For my great-grandparents, 1927 was a good one: Lucky Lindy crossed the Atlantic, and his baby hadn’t yet been abducted in the dark of the night by nefarious German immigrant Richard Hauptmann (who insisted on his innocence until his execution by electric chair in 1936). My grandparents reveled in the post-war boom of the Truman years, probably getting the most out of 1947’s interbellum with idk, sock hops and soda fountains or whatever. For my parents’ generation, the Summer of Love in ’67 was the apotheosis by which the nadir of the entire decade of the 1970s was contrasted. For me though, the best year of my youth was 1985. Continue reading “Assimilation vs Integration”
In pre-modern, small scale societies, trust was multi-lateral: Everyone knew everyone. This was robust to any one individual being untrustworthy, but had real trouble scaling. If someone new came to town she would have to earn the trust of every node in the network—a problem that grew in proportion to the population.
So in the modern era (and long before it as well—the modern era is just when we mastered it) we replaced multi-lateral networks of trust with bi-lateral trusted intermediaries. This was an incredible innovation from the perspective of scaling cooperation. Persons A and B could trade and borrow from one and other while being total strangers, given their mutual, bi-lateral trust of C.
Who or what is C? C has represented many different things throughout history. The state. Markets. Banks. MasterCard. Uber. With the help of lots and lots of Cs we were able to scale from simple gift economies to the complex and deeply integrated society we have today.
This change occurred must faster than our brains could adapt. As apes evolved for smaller scale society we have therefore not extricated our craving for microcosms of multi-lateral trust: family, friends, community, and so forth. This seems to be what social scientists are measuring when they report some countries as “higher trust” than others. These are societies that have, to varying degrees, decentralized the bilateral institutions in order to promote greater multilateralism. In doing so, these societies trade-off some scale efficiency and assimilative capacity in exchange for greater robustness and, presumably, reduced feelings of social-alienation.
Yet if this is right it is incredibly misleading to call such societies “high trust” as if the others are not. Rather, they are high in a particular kind of trust. It’s only the bilateral model that lets two complete strangers engage in a multi-phase, high stakes project without having to trust each another one bit. Instead, each trusts the underwriting of the intermediary institutions. There is the same amount of effective trust, as manifest in productive cooperation, but it comes with much less cognitive burden. You don’t have to keep mental track of your colleague’s reputation, or whether their ideological and cultural preferences match yours. Nor do you have to worry about collecting debts or punishing bad behavior. That’s all been offloaded and outsourced. The trust, in other words, still exists, but is embodied in the environment and institutions, rather than in our heads.
Even in so-called high trust societies, this latter sort of trust is still doing most of the work in the background. We just don’t notice it by design. Conversely, many societies measured as low trust may in fact be quite high in multilateral trust, but in a way that is localized to pockets without the bilateral institutions needed for effective interfacing.
Thus when a country is described as low trust I stop and ask myself “what sort of trust?” There may be a lot of virtue in an, as measured, low trust society if it better facilitates the rapid integration of newcomers, a greater diversity of lifestyles, and larger scale cooperation. After all, impersonal interactions are not a bad thing. They’re the stuff of civilization.
Absolute zero is difficult to imagine. As far as we know, it is only a theoretical possibility, measured as 0° kelvin, at which temperature all molecular movement stops, the absolute absence of heat. Its existence would theoretically be found at the very reaches of the universe, where the energy of the Big Bang has somehow completely dissipated; in other words, absolute zero cannot be achieved, but you can come close.
As far as wrongness is concerned, Adam Gurri has come as close to absolute as is possible. In his post Rhetoric and Due Diligence, Adam posits that scientists have a responsibility to gauge the rhetorical effect of their work. This request, brought forward in the cloak of the humanities, will have the unintended effect of returning us to the childhood of man, wherein we looked to a priestly religious caste to protect us from The Truth. The world has now grown up and is populated by adults, particularly the white, European variety, which has for centuries eschewed superstition and has dispassionately pursued The Truth.
Adam is particularly mistaken in his view of Scientists, egregiously assigning to them fallibility, not only in result, but also (and here, I think, is the reason we should start piling faggots around a large stake) in their motives. It is incontrovertible that Scientists, especially Social Scientists, are dispassionate, guided only by the Scientific Method, which is the cornerstone of The Truth, revealed to us by the Universe itself. Truth, then, is like a coal seam, and Scientists are only coal miners, trudging to their labor, lords of the underworld, to tirelessly mine Facts.
In the same way that a single coal seam can appear in many different parts of the world, e.g., Spain to Wales to Pennsylvania, and many methods can be applied in those various parts of the world for its extraction, so also Scientists, especially Social Scientists, are merely extracting Facts and Data in many and various ways, which they then haul to the surface for dispassionate examination and then application to The Truth, to which all Facts and Data eventually snap, be the Scientist at hand clever enough. If he is not clever enough, then another Scientist, undoubtedly, again, guided gently along the paths created by the Scientific Method, will eventually dispassionately discover how the Fact snaps to The Truth.
It may sound like a chicken-crosses-the-road joke, but the profoundly serious directive of Science is at stake: why do Scientists mine data? For the same reason miners mine coal: they are impelled to do so. It doesn’t matter who’s hurt or offended in the process; any such consequences are only the growing pains of a human civilization going through the inexorable process of cohering as one around The Truth. Some sloughing off is to be expected. Therefore, Adam’s homily on rhetoric clanks to the floor like so many iron manacles employed by the unfortunate and thoroughly representative Christian Spanish Inquisition: the humanities are not only not necessary, they are a hindrance to establishing The Truth.
Should it ever be discovered that a Scientist, especially a Social Scientist, has lost his dispassion, or has even willfully departed from the Scientific Method, anywhere along the process, beginning with descending into the Data mine, extracting Facts, examining the Facts, and then snapping the Facts to The Truth, then let the dispassionate peers of that Scientist immediately banish him from Science and force him to become ordained into the nearest amenable religious order at hand. So when Adam Gurri cries out in the wilderness, “We must acknowledge the rhetoric of scientific inquiry,” I say to him, “Save your preaching for Sundays, Friar Tuck.”
Every political change must be accepted by the populace, either tacitly or explicitly. On a more granular level, different types of political change require different levels of acceptance from different networks of people. Therefore, types of political change can be categorized by the intensity with which they affect networks of people. Given my interest in free cities, cities with a degree of legal autonomy, I thought I would take Adam Gurri’s kind invitation to discuss the discourse on free cities.
My interest in free cities stems largely from my understanding of political change. Politics is highly path dependent. Free cities offer a way to break that, potentially accelerating institutional improvements. However, there remains a great deal of hostility to free cities.
First, there are three groups with interest in free cities, libertarians, Silicon Valley, and developers. Libertarians largely have the ideas right. Some focus on outlandish Rothbardian ideas of property rights unlikely to work. However, a strand of libertarians has focused on best practices for institutions and how to recreate them in the developing world. Paul Romer largely fits this description, though I expect he would deny the association with libertarians. Unfortunately, while libertarians have the ideas, they lack the influence and money to build free cities. Hopefully Honduras can break this generalization.
The second group is Silicon Valley. They have some overlap with libertarians, but are distinct enough to justify a second category. Initially led by Peter Thiel and Patri Friedman, Silicon Valley focuses more on achieving the best institutions, rather than improving those in the developing world. Y Combinator is a welcome recent addition to Silicon Valley discussions about cities. Silicon Valley largely has the ideas, as well as some of the money, but lacks the influence to implement free cities.
Much of the difficulty that libertarians and Silicon Valley have faced in their quest to build free cities is their aversion to politics. A free city is seen as opting out of politics, rather than an inherently political act. They want a blank slate on which to build a city, but don’t fully understand how to achieve the autonomy required for a blank slate. Luckily, they have also been realizing this over the past several years, and will hopefully have more luck in the future.
The third group is international developers, a group which should be interested in free cities, but isn’t yet. The New Cities Foundation has an annual forum, Cityquest, which brings together developers building new cities. These are multi-billion dollar projects, but they, by and large, conceive of cities as construction projects, not realizing the value of legal institutions. Luckily, again, based on conversations with development groups, they are slowly realizing the value of legal institutions.
The last relevant question is, what prevents the emergence of free cities? Of course, countries are still reluctant to allow such high levels of autonomy, but what are the particulars? My current understanding is that the primary barriers are McKinsey and World Bank types. They are often presidential advisors in countries that could host free cities. However, they are unimaginative and risk averse. When presented with free cities, their response is to suggest a special economic zone with slightly lower taxes.
Building free cities means changing the mind of McKinsey and World Bank types. Free cities have to be normalized. As such they can no longer be fevered dreams to create a libertarian utopia or a techno-futurist city. Instead, free cities must be seen as adopting the best practices of governance, as an addition to the existing world order, not an attempt to opt out from it. Institutional change requires the ruling elite. Advocates of free cities should heed that lesson.
Part of what I do professionally involves attempting to identify groups of people who act a certain way, so that businesses can meet their specific needs. The marketing term for this is “customer segmentation,” and it’s a powerful set of tools for setting marketing strategies.
One problem with customer segmentation, however, is that when we carve out a particular segment of customers because they exhibit Behavior X on average, we accidentally include a bunch of customers who do not exhibit Behavior X, because they diverge from the average. Sometimes they even exhibit precisely the opposite behaviors. Just because you own a smart phone and an Xbox and happen to be a male aged 27 years doesn’t mean you’re going to watch the Super Bowl this year, even though most people who are like you on paper probably will.
Or, to put it pictorially:
If you run a business, then you don’t actually care who gives you money (for the most part), you just want them to give it to you. Finding out what your key customer segments are is a means by which you attempt to identify people who have a high probability of giving you money, subject to the assumption that demographic data is predictive of a person’s giving you money. It also helps give you a language with which to communicate to them.
But that’s all it is. Your prediction may very well be wrong.
In business, this means that a lot of the people who get your direct-mail-or-whatever will completely ignore it and not give you any money. That’s because, despite your smart phone and Xbox ownership, your sex, and your age, you might not want to watch the Super Bowl; or, despite your looking a lot like the average childless male gunfighter, you might actually be a female customer service rep who is raising her grandchild; or, etc., etc.
Notice: It is quite often the case that many individual members of the nebulous group of people we believe to have a certain set of characteristics do not actually have any of those characteristics at all. Our customer segment includes both groups of people.
The error a lot of marketeers make occurs when they observe the multitude of behaviors exhibited by a particular segment that do not seem to cohere in a way that can be exploited through marketing strategies. They first think that they didn’t get the marketing message right, so they invest a lot more money into getting it right. When that doesn’t work, they decide that they got their segmentation wrong, and then go looking for “the real segment.” (When they find it, the process starts over again.)
Either way, for a long time, they’re stuck in their segmentation paradigm. Whatever else they choose to change, they don’t change the paradigm. The problem here is that, at a certain point, the marketeers have conflated their customer segment with what they really want to know. They don’t really want to know “Who is in Segment A?” Instead, they want to know, “Who is going to give me more money?” Segmentation is just a means to an end. It’s just a paradigm.
So it goes with all forms of segmentation. It’s tempting to describe the world – and especially human interaction – in terms of “people segments,” subsets of the population who we believe, on average, to behave a certain way. As I stated before, though – and I don’t want to belabor the point, but it bears repeating just one more time – any time you choose to create a segment, you include large swaths of people who behave very differently than the segment itself is said to behave. What this means is that, when you aim to talk about a segment – even your own – you wind up being terribly wrong about a good number of people in that segment.
So, what good is a segment?
Segmentation can be useful as a sort of mental model: If all individual behavior more or less corresponded to the behavior we wish to assign to a group, then what does the world look like? Once we’ve answered that question and come up with a rudimentary view of the world, we can then think about relaxing some of our assumptions, making the “segments” a little fuzzier, and assessing what that does to our basic world view.
This only works, however, if we agree to at least two rules.
First, we shouldn’t make the mistake of conflating our segment-oriented mental model with the actual state of the real, physical world. It might be useful to pare things down a little bit to gain some grasp over the broadest strokes, but the simple fact of the matter is that the real world is more complex than our mental models.
Second, as we relax our assumptions – and we must relax them – we must also agree to test how relaxing them impacts not only the behavior of our model, but also its credibility. If your model of how Purple People related to Blue People only explains, say, 30% of the interactions between Purples and Blues, and only does so if we agree to use the loosest language possible, then perhaps its time to reconsider whether Purple-versus-Blue is the right cut of the data. Maybe it’s Purple-versus-Green. Maybe it’s Triangles and Circles instead. Purple-versus-Blue might be the story with the most emotional power, it might be the story that wins you the highest number of friends or blog followers, it might be the story that wins the largest quantity of grant money, and it might be the one that everybody wants to hear about.
But it might still be wrong nonetheless. As one who puts people into boxes, it’s your responsibility to ensure that your boxes are worth anything.
If you hated this post, boy, are you going to hate these:
Featured image is Lord Byron On His Death-Bed, by Joseph-Denis Odevaere.
I’m not looking forward to the process of dying. Whatever one’s beliefs about the afterlife, my thoughts will inevitably turn to the course of my life – my accomplishments and failures, regrets and reprisals, triumphs and shortcomings. It’s the final act of accounting for oneself – for every good deed and praiseworthy act I can think of, it’s guaranteed that there was an equal and opposite instance of personal or moral failure. We all want to make peace, and allow ourselves to rest, in hope that our final thoughts will be positive, happy. The harder we think about life, though, the less sure we are that we are good people. No one wants to die a failure.
This line of thinking inspires a great deal of humility. No matter how right you think you are, how much good you think you’ve done, if you were twenty minutes from dying you might worry that you weren’t right enough, or good enough, to die at peace with yourself.
This kind of humility is, in my opinion, important and positive. Taken to the extreme, though, it is paralyzing, and the one thing worse than dying in a state of philosophical uncertainty is living in one. Continue reading “Certainly”
Featured image is Saint Jerome in His Study, by Marinus van Reymerswaele.
It is easy to think that a paper or a conversation, or even an academic convention, happen in relative isolation. After all, if a paper gets hundreds of citations, it is considered wildly successful. Meanwhile, the biggest websites measure their link counts in the tens or hundreds of millions. An academic field provides a relatively small audience even for its rockstars, and specialized sub-fields are yet smaller.
But the consensus of these fields has implications for all of us. We have nuclear power but also nuclear weapons, vaccines and antibiotics but also chemical and biological weapons, sophisticated tools for financing businesses and college educations and home buying…but also the volatile and bewilderingly complex financial system. Academic conversation played a role, to varying degrees, in each of these cases.
In the human sciences, the academic conversation concerns the very question of what it means to be human. And the conclusions which are drawn there, again, do not occur in a vacuum. The approach that a legislator or an agency rule-maker takes depends to no small degree on just what sort of animal they—or their social scientist advisers—believe human beings to be.
The architects of the American administrative state believed that individual humans were nothing more than organs or cells which added up to a body politic, with the state as the head. They believed that individual rights were a relic of historic superstitions, and in any case were articulated before the Industrial Revolution, which changed everything. All that mattered was the health of the body politic—and so undesirable individuals became mere polluting elements, threatening the short or long term health of the body. These illiberal reformers thus set to work drafting immigration restrictions, as well as forcible sterilization laws, to name but two of the legacy of their honored stewardship of the American project.