A model is a thing that projects a resemblance, which permits it to be accepted as an analogue of something else. Think for instance of a toy airplane or the scale model of a building. Yet models, especially as their scale approaches that which they are imitating, may sometimes also have an air of the uncanny about them. Is it because they are doppelgängers that live somewhere between physical reality and something dreamlike? They make it difficult for us to define the boundaries of their thingness, a dissonance all too familiar from our childhood, from a time when abstraction played a lesser role and we tended to interpret the world by appearance and immediate experience.

Or was this possibly a precognition of sorts, a hunch that reality can flow both ways? Is the model engaging with the world in a way much less passive than we commonly think?

Imitating appearance is the most basic way of modeling. Almost anything can be deconstructed into its aspects, in order for its perceived essence to be reflected in another thing. James Watt’s steam engine, for instance, was explicitly modeled to be a functional analogue of a horse. Although vastly different in its physical manifestation, it succeeded in bridging body and machine through the quantification of physical work embodied in the unit of horsepower. A generation later, Charles Babbage created an engine that ran on numbers alone, which has since enabled us to model and simulate what can be deconstructed and quantified. And, starting with the earliest days of computing, the Earth itself has been the prime thing to have its data collected, its reality sought to be grasped and its future to be predicted.


One has to appreciate the vast difference that lies between an estimated 1.33 x 1050 atoms that constitute the world, the data we are able to collect about it, the computing power available, and the uncertainties that arise from the very equations that constitute the model itself. But when the visual likeness of a storm emerges on a computer screen from comparatively sparse data collected by weather stations and a few basic rules alone, as philosopher Manuel DeLanda describes in his book on the subject, the simulation becomes a thing in its own right.1 One whose thingness is of a different order, its reality inside the machine hinging on our theoretical grasp of the very world we are trying to understand.

It could be argued that simulation modeling is a new and highly speculative mode of erkenntnis, one that cannot be easily dismissed as long as its computerized experiments succeed in “reveal[ing] information about actual, possible, or impossible worlds,” as R.I.G. Hughes puts it.2 More importantly, ‘synthetic reason’ is by far our best hope at ever bridging the cognitive gap between our own reasoning and things that are as vast and dynamic as a planet. It is an epistemic lens through which we regard the world, and like all such tools it will have flaws and introduce distortions, perhaps even make us see mirages.

Crucially, such reasoning has agency within the world and it does so through us. Not necessarily by improving our understanding of nature, but through the conclusions drawn from the results of simulations run and the action that we feel they afford. Climate science is the prime example, since it rests largely on running simulations of Earth’s futures whose results have an immediate influence on global policy­-making.

Here it is, then, where the flow of reality reverses, and the model forces its own thingness onto the world in an otherwise impossible feedback loop. Through a complex flow of human and synthetic reasoning and agency, it shapes the future of its target system. It is not only a “nether land that is at once nowhere and everywhere” on the map, as historian of science Peter Galison says—it is the map and the territory at the same time.3

Maybe it was this that we unwittingly anticipated when we imagined the toy airplane could fly.


About the Images:

In Elsewheres: The Miracle of 540 W 21st Street, computer simulation becomes a medium for creating a site-specific, procedural installation that is changing over the course of the exhibition.

The space of Eyebeam as well as all objects present were weighed, measured, and have been recreated in the form of a 3D environment. A virtual stage, in which physical interactions are being simulated according to mathematical models, forming a chain of inherently unpredictable events.

Once an event, such as a collision between two objects, has concluded, the resulting changes to the objects are manually introduced into the space. People become agents of the virtual, re-arranging the physical world according to machinic speculation.

(Elsewheres was co-produced by: STUK Kunstencentrum, Leuven and Eyebeam, New York)

  1. DeLanda, Manuel. Philosophy and Simulation: The Emergence of Synthetic Reason. London: Continuum, 2011.

  2. Winsberg, Eric. Science in the Age of Computer Simulation. Chicago: University of Chicago Press, 2010.

  3. Galison, Peter. The Disunity of Science: Boundaries, Contexts, and Power. California: Stanford University Press, 1996.

All photos courtesy Sascha Pohflepp & Chris Woebken.