Models (of the World)

Models are everywhere. They appear as mathematical equations and physical prototypes, maps and diagrams, architectural maquettes and scientific simulations. A model can be a person posing in a drawing class, an organism standing in for a species, an example to follow, or an artificial intelligence trained on vast amounts of data. Despite these very different meanings, models share a peculiar relationship with something beyond themselves: they stand for, simplify, embody, test, predict, or propose something else.

Models are fundamental tools of both scientific inquiry and artistic practice. We build them because the world is too complex, too large, too small, too distant – or sometimes simply not yet there – to be approached directly. Models isolate relationships, test assumptions, communicate ideas and explore possibilities. Their power lies in selection and reduction: in deciding what matters and what can, at least temporarily, be left aside.

Modelling is therefore an active and consequential process. Something becomes a model because someone decides what should be represented, which relationships are significant and which can be ignored. Who makes a model, for whom and for what purpose? What enters it, what disappears, and what might emerge unexpectedly in the process?

These questions also complicate the relationship between model and world. An architectural model may refer to a building that does not yet exist. A climate model describes processes that can never be encountered as a single object. A mathematical model may have no obvious material original at all, while fictional and speculative models can construct possible worlds of their own. Modelling can move from an existing phenomenon towards abstraction, but also from an idea, hypothesis or fiction towards something that might eventually become real.

Scientific and artistic practices both work within this productive distance. Models can make inaccessible phenomena available for observation and experiment; sketches, maquettes, scores, diagrams, simulations and fictional scenarios allow relationships to be rearranged and possibilities tested. In doing so, models can reveal structures that were not apparent before. They do not simply show what is already known. They can make something visible, thinkable or knowable in the first place.

And models can act back upon the world. Maps organise territories, economic and climate models inform decisions, architectural models anticipate environments that may subsequently be built. Digital technologies intensify this feedback. A digital twin can become part of the system it was designed to describe. Machine-learning models classify, generate, recommend, decide and communicate. What does model mean when a model no longer only represents something, but begins to act within the world – and even talks back to us?

The gaps, omissions and failures of models are equally revealing. Models can be inaccurate, biased, outdated, deceptive or simply confronted with something they were never designed to accommodate. Yet the discrepancy between a model and the world can itself produce knowledge. It may expose hidden assumptions, reveal what has been excluded, or open possibilities that a supposedly accurate representation would not.

Models have always participated in changing ways of understanding the world. Globes, anatomical figures, perspective drawings, maps and mathematical abstractions do more than preserve particular worldviews. By selecting and arranging relationships, they help establish what can be seen as evidence, what can be known and what can be imagined as real. Sometimes models describe worlds; sometimes they anticipate them; and sometimes the world begins to resemble its models.

This year’s topic invites students to approach modelling as an experimental practice across art and science: to investigate existing models and their assumptions, to test their limits, take them apart, misuse or reinvent them, and to imagine models for things that have so far resisted representation.

What other models might we need to understand a world that is changing around us? What happens if we model relationships, uncertainties, transformations or possible futures? Can we invent models that do more than explain what already exists – models that allow us to think differently, perceive differently, and imagine worlds that have not yet taken shape?

The challenge is not only to understand the models we already have, but to discover what else a model could be – and what other worlds it might enable us to think.