First, some shameless self-promotion: I made an album, and you can listen to it (and buy it!) here:
There’s a well known Borges story called“On Exactitude in Science”, in which the desire for a perfectly accurate map eventually results in “a Map of the Empire whose size was that of the Empire, and which coincided point for point with it”; this map is, of course, “useless.” The purpose of any map is precisely to scale a large area down and make it possible to see all at once, with emphasis on whatever information is most important for a particular use. In doing that, some details are removed or de-emphasized, which is not a failing of the map but part of its purpose. All maps are, in this sense, incomplete, but each is incomplete in its own way, according to its intended function. The danger comes from forgetting what is left out— mistaking the map for the territory.
“Colonial Cartography”, by Apoorva Tadepalli, is in a way about this problem. Any map or model, insofar as it is the lens through which we see the world— by which the world is made visually comprehensible— also shapes our sense of what the world looks like. In general, we see most of the world, most of the time, only through maps, and our vision is constrained by what those maps include and what they leave out. As Tadepalli says,
Maps are productive rather than simply informative creatures; they start dialogues and create identities.
A map is, in a sense, making a claim about reality, about what is there and what matters, what can/em> be known and what is important to know about a place. Quoting historian Thongchai Winichakul talking about maps of colonial Siam, Tadepalli says that the colonial map:
“anticipated spacial reality,” rather than the other way around; the map “was a model for, rather than a model of, what it purported to represent…
The image of Siam as a unified chunk of territory, with definite borders— borders fixed mostly without reference to the existing cultural, economic, or political realities on the ground— is an assertion of colonial claims as much as a reflection of them, a way of establishing “facts on the ground” as much as a record of them. With official backing, the map becomes evidence that can be used in disputes over territory, jurisdiction, or resources. Once it is publicized, the map becomes part of the reality, the context, in which colonial claims are advanced, disputed, and reconciled.
Teju Cole’s most recent column (which is apparently his last [?!]) makes a related point about the colonial use of photography:
This was one of the repeated interactions between imperial powers and the populations that they sought to control: The dominant power decided that everything had to be seen and cataloged, a task for which photography was perfectly suited. Under the giant umbrella of colonialism, nothing would be allowed to remain hidden from the imperial authorities.
But, of course, at the same time as the camera is described as providing a complete, objective picture of reality in its entirety, the view it offers of a colony’s peoples and societies is highly selective, in ways that reflect colonial perspectives and purposes.
Tadepalli extends her argument about colonial maps to current ways of using maps and location data as a means of expressing identity— showing others who we are by showing them where we have been, and what we did there. She suggests that such use in effect generates an idea of a place (specifically, what one should do and see there, and the kind of person who is there doing and seeing these things). That idea then shapes what that space means for others and, eventually, what it looks like as well. Much as the kind of puzzle-piece iconography of the colonial map generated a sense of unity and singularity within arbitrarily drawn borders, the social media map of a place makes a claim about what it is and what it means.
The personalized ways in which locations are used on social media make a city both more disconnected and more legible to the outsider at the same time: less and less relevant as navigational information, but increasingly efficient at communicating personalities, lives, individual narrations, identities.
The idea here, as I read it, is that by having a map that is always with us, and that changes to suit our immediate needs (not only tracking our location, but adjusting scale, identifying points of interest, and so on), we become able to navigate without really acquiring any knowledge of the landscape through which we move— potentially, without even needing to look at it, in between destinations chosen on the basis of received representations. The map becomes our>/em> map, not only in the sense that it is tailored to present needs, but in the sense that it reflects our sense of who we are and provides another means by which we can present ourselves to the world.
In this case, though, the issue is complicated by the role of large technology companies like Google, who are the ones actually producing the maps onto which people pin themselves. These maps allow only certain, specific ways of using location data; only certain, predetermined kinds of links between the map and the photo or hashtag or filter are allowed. And as in the colonial map, the image thus produced reflects and supports the interests of the mapmakers. In particular, because location-tagged posts become data points that will be used to sell advertising or other services, users participate in transforming places into products. In Tadepalli’s specific example, “Brooklyn” has become a product that you consume by visiting it, moving through it— and tagging your posts.
I think I still find the parallel here a little overdrawn; social media tagging, and even the gentrification of Brooklyn, are not quite like colonialism. What I’m interested in is the idea of a map as a kind of tool or resource for making claims about the world— an argument about how things should be, rather than simply a depiction of how things are.
Any model, maybe, can be seen in this way. Models are made to be useful, to help explain or understand complex realities, but people become invested (in multiple senses) in the utility of particular models. The belief in the utility of a model is also a belief in the version of the world that it reflects. “How Beauty Is Making Scientists Rethink Evolution”, by Ferris Jabr, is partly about a dispute over models. Specifically, he is writing about the place of beauty in theories of evolution. Darwin himself argued for a process of “sexual selection” that operated alongside natural selection: he suggested that each species had its own “standard of beauty” by which females judged males, and the most successful males would be those who evolved toward that standard. In this account, the things which make an individual beautiful don’t have any particular, direct value in terms of survival; they lead to success in procreation simply because they are, for whatever reason, attractive or appealing to potential mates.
Later scientists more or less rejected this idea, arguing instead that the features that make an individual creature beautiful also indicate something about its fitness; a male bird with full and lustrous plumage, for example, must be successful in finding sufficient food to support its growth, and must therefore also be intelligent, healthy, etc. Beauty, to that way of thinking, is just a visible index of more utilitarian attractions.
This has been the dominant way of thinking about beauty in the natural world for decades, but things may be starting to change.
Now, nearly 150 years later, a new generation of biologists is reviving Darwin’s neglected brainchild. Beauty, they say, does not have to be a proxy for health or advantageous genes. Sometimes beauty is the glorious but meaningless flowering of arbitrary preference. Animals simply find certain features — a blush of red, a feathered flourish — to be appealing. And that innate sense of beauty itself can become an engine of evolution, pushing animals toward aesthetic extremes. In other cases, certain environmental or physiological constraints steer an animal toward an aesthetic preference that has nothing to do with survival whatsoever.
There’s a lot in this piece, and many different ways of thinking about beauty and evolution. For instance, the idea of “sensory bias” allows for the possibility that, due to either evolution or to characteristics of the environment, certain aesthetic traits might be favored simply because they make an animal more noticeable to mates, without conveying any meaningful information about their actual fitness, but also without appealing to any kind of aesthetic preferences.
One thing that becomes clear in reading about this debate, though, is the way that different models can fundamentally alter one’s understanding of the world; a model determines the range of possibilities a person is likely to perceive or consider. Thinking about beauty outside of a strict natural selection framework can dramatically increase the complexity of evolutionary models, but opens up a range of new possible ways of thinking about what is going on in natural systems.
It’s not enough to consider how an animal’s habitat and lifestyle determine the size and keenness of its eyes or the number and complexity of its neural circuits; we must also question how an animal’s eyes and brain shape its perceptions of reality and how its unique way of experiencing the world can, over time, profoundly alter both its physical form and its behavior. There are really two environments governing the evolution of sentient creatures: an external one, which they inhabit, and an internal one, which they construct. To solve the enigma of beauty, to fully understand evolution, we must uncover the hidden links between those two worlds.
There is something beautiful, and even awe-inspiring, about this idea. One argument often made for the importance of reading fiction is that it is a kind of lesson in empathy; putting ourselves into the head of a fictional character can make us better at seeing things from the perspective of other people in the real world. Fiction, in other words, is a reminder that every human being we encounter is in essence a complex world in themselves, a world to which our access is only ever partial and imperfect. The perspective on evolution Jabr is describing requires us, in essence, to think of animals this way as well. In doing that, we confront the sheer, unfathomable complexity of a world full of millions of living, moving beings, each one of whom is in itself an entire world both alien to us and complex beyond our comprehension.
The environment constrains a creature’s anatomy, which determines how it experiences the world, which generates adaptive and arbitrary preferences, which loop back to alter its biology, sometimes in maladaptive ways. Beauty reveals that evolution is neither an iterative chiseling of living organisms by a domineering landscape nor a frenzied collision of chance events. Rather, evolution is an intricate clockwork of physics, biology and perception in which every moving part influences another in both subtle and profound ways. Its gears are so innumerable and dynamic — so susceptible to serendipity and mishap — that even a single outcome of its ceaseless ticking can confound science for centuries.
In the evolutionary debate, the models are deliberately built by scientists, who publish and argue for them. But we must all operate in the world using various kinds of models all the time, and we are often unaware of them.
When I was in junior high, computer class was mostly about basic computer skills— typing, formatting a text document, sometimes a little simple programming with “Model Metropolis”, by Kevin T. Baker, suggests that the assumptions on which the game was modeled might also be part of the answer. Developer Will Wright, looking for a way to bring life to model cities that he began making for a different game, discovered a book called Urban Dynamics, by Jay Forrester, an early pioneer in computer simulation. In the late 1960s, Forrester began to look at the array of problems in American cities that would come to be referred to as the “Urban Crisis,” and eventually claimed that he had successfully “reduced the problems of the city to a series of 150 equations and 200 parameters,” with which he could plausibly simulate the outcomes of a various possible policy solutions.
The results of Forrester’s models “proved popular among conservative and libertarian writers, Nixon Administration officials, and other critics of the Great Society,” because they suggested “that cities should take a less interventionist approach to the problems of urban poverty and blight, and instead encourage revitalization indirectly through incentives for businesses and for the professional class.” This approach arguably still dominates the outlook of urban governments today, as seen in the controversy over Amazon’s new headquarters.
The problem is that, like all models, Forrester’s made simple simplifying assumptions; in his case, those assumptions both left out vital aspects of urban life and smuggled in a great deal of ideological baggage.
The city inside Forrester’s model was a highly abstracted one. There were no neighborhoods, no parks, no roads, no suburbs, and no racial or ethnic conflicts. (In fact, the people inside the model didn’t belong to racial, ethnic, or gender categories at all.) Economic and political life in the outside world had no effect on the simulated city. To the extent that the world outside the model existed, it served only as a source for migrants into the city, and a place for them to flee to if the city became inhospitable.
The residents of Forrester’s simulated city belonged to one of three class categories, “managerial-professional,” “worker,” and “underemployed.” As one moved down the class ladder in the urban dynamics model, classist assumptions about the urban poor piled up: birth rates were higher, tax contributions were lower, and the use of public expenditures increased. This meant that the urban poor served as a massive drag on the health of the simulated city: they did not add to its economic life, they had large families which strained public services, and they contributed only paltry amounts to the city’s coffers.
Some of these assumptions, in turn, got imported into SimCity, in particular the assumption that the lowest possible taxes will always produce the fastest growth— and more generally the assumption that growth is always the overriding goal.
The consequences in this case are probably fairly trivial; Baker says that “Within a few years of its release, instructors at universities across the country began to integrate SimCity into their urban planning and political science curriculums,” but— at least in the version I was playing— the game is surely too obviously simplified for many people to have taken it as any kind of instruction manual for city planning. This is, though, an instance of a more general problem with the models we live by. Making a model of any kind involves making assumptions— taking certain things for granted, or treating them as fixed rather than variable— in order to reduce complexity. When those models are implemented in the real world, though, the assumptions come with them, creating blind spots that we may not be aware of. The danger of mistaking the model for reality— the map for the territory— is always there.
Almost three years ago now, I wrote about the story of a farm in Kansas whose residents were plagued by visits from people—including law enforcement— convinced that the house was sheltering any number of nefarious activities, from theft and kidnapping to murder and drug running. The reason for this was that, in a widely-used online database used to tie IP addresses to geographic locations, hundreds of millions of addresses seemed to point to this farm. That, in turn, was because IP mapping is very imprecise; often, all you can learn from an IP address is the city, county, or even state in which the device using that address is located. When the address is mapped to a such wide area, databases, by default, pin it to the center of the area— which just happened to be the location of the Kansas farm.
Now, Kashmir Hill, the author of that article, has a kind of follow-up piece about a house in Johannesburg that has suffered from the same problem. In “How Cartographers for the U.S. Military Inadvertently Created a House of Horrors in South Africa”, though, there is the added wrinkle of a U.S. government agency, which is the ultimate source of the satellite mapping data used by the companies who offer IP mapping services.
One way of thinking about all of this is that people who are using these databases are in effect paying for the use of a model built by somebody else— and getting all of the assumptions and simplifications that go along with it, whether they are aware of them or not. This is a much more general problem; we all make use of all kinds of models that we did not create ourselves as we move through the world, whether they are philosophical or religious beliefs, scientific ideas, or the more obviously constructed models of services like Google maps. It isn’t really possible to live without doing this; nor, probably, can we realistically make a systematic inventory of all of the assumptions made in the models we use. (In the case of the services provided by large corporations, that information probably isn’t available to us in any case). But maybe it still pays to be conscious of the fact that those assumptions and simplifications must be there, as well as the fact that every model is an argument about the world as much as a representation of it.
Some other recent things of interest:
“In Praise of the Humble Knot”, by Jody Rosen
Rosen considers the knot as a technology, one so ubiquitous as to be effectively invisible. He also interviews Des Pawson, who runs a knot museum in a shed in his backyard.
“The Five Families of Feces”, by David Gauvey Herbert
Competition for the porta-potty market in New York City is fierce, and the stakes are surprisingly high.
“Flying Squirrels That Glow Pink in the Dark”, by Veronique Greenwood
Some species of flying squirrel have fur that glows under UV light. As yet nobody knows what purpose this serves, if any, or even whether the squirrels themselves can see it.
“How Iran’s Greatest Director Makes Art of Moral Ambiguity”, by Giles Harvey.
A nice profile of Ashgar Farhadi, which I think conveys a sense of what I love about his movies; he says, “I believe that every character in my films has reasons for their wrongdoings, and that if we gave them time they’d be able to explain those reasons to the rest of us.” Which is to say: they are human.
“What is Glitter?”, by Caity Weaver
Glitter, it turns out, is a remarkably complex product, with a lot of science involved in making it. Refraction indices.
“This Land is Meant Only for Saffron”, by Sharanya Deepak
Kashmir has long been known as the source for the highest-quality saffron, but climate change and continual military conflict have reduced production to a fraction of what it was a couple of decades ago, threatening both an economic system and a culture.