Contextual stories about Algolit

From Algolit

Why contextual stories?

During the monthly meetings of Algolit, we study manuals and experiment with machine learning tools for text processing. And we also share many, many stories. With the publication of these stories we hope to recreate some of that atmosphere. The stories also exist as a podcast that can be downloaded from

For outsiders, algorithms only become visible in the media when they achieve an outstanding performance, like Alpha Go, or when they break down in fantastically terrifying ways. Humans working in the field though, create their own culture on and offline. They share the best stories and experiences during live meetings, research conferences and annual competitions like Kaggle. These stories that contextualize the tools and practices can be funny, sad, shocking, interesting.

A lot of them are experiential learning cases. The implementations of algorithms in society generate new conditions of labour, storage, exchange, behaviour, copy and paste. In that sense, the contextual stories capture a momentum in a larger anthropo-machinic story that is being written at full speed and by many voices.

We create 'algoliterary' works

The term 'algoliterary' comes from the name of our research group Algolit. We have existed since 2012 as a project of Constant, a Brussels-based organization for media and the arts. We are artists, writers, designers and programmers. Once a month we meet to study and experiment together. Our work can be copied, studied, changed, and redistributed under the same free license. You can find all the information on:

The main goal of Algolit is to explore the viewpoint of the algorithmic storyteller. What new forms of storytelling do we make possible in dialogue with these machinic agencies? Narrative viewpoints are inherent to world views and ideologies. Don Quixote, for example, was written from an omniscient third-person point of view, showing Cervantes’ relation to oral traditions. Most contemporary novels use the first-person point of view. Algolit is interested in speaking through algorithms, and in showing you the reasoning underlying one of the most hidden groups on our planet.

To write in or through code is to create new forms of literature that are shaping human language in unexpected ways. But machine Learning techniques are only accessible to those who can read, write and execute code. Fiction is a way of bridging the gap between the stories that exist in scientific papers and technical manuals, and the stories spread by the media, often limited to superficial reporting and myth-making. By creating algoliterary works, we offer humans an introduction to techniques that co-shape their daily lives.

What is literature?

Algolit understands the notion of literature in the way a lot of other experimental authors do: it includes all linguistic production, from the dictionary to the Bible, from Virginia Woolf's entire work to all versions of the Terms of Service published by Google since its existence. In this sense, programming code can also be literature. The collective Oulipo is a great source of inspiration for Algolit. Oulipo stands for Ouvroir de litterature potentielle (Workspace for Potential Literature). Oulipo was created in Paris by the French writers Raymond Queneau and François Le Lionnais. They rooted their practice in the European avant-garde of the twentieth century and in the experimental tradition of the 1960s. For Oulipo, the creation of rules becomes the condition to generate new texts, or what they call potential literature. Later, in 1981, they also created [ ALAMO, Atelier de littérature assistée par la mathématique et les ordinateurs (Workspace for literature assisted by maths and computers).

An important difference

While the European avant-garde of the twentieth century pursued the objective of breaking with conventions, members of Algolit seek to make conventions visible.

'I write: I live in my paper, I invest it, I walk through it.' This quote from Georges Perec in Espèces d'espaces could be taken up by Algolit. (Espèces d'espaces. Journal d'un usager de l'espace, Galilée, Paris, 1974)

We're not talking about the conventions of the blank page and the literary market, as Georges Perec was. We're referring to the conventions that often remain hidden behind interfaces and patents. How are technologies made, implemented and used, as much in academia as in business infrastructures? We propose stories that reveal the complex hybridized system that makes machine learning possible. We talk about the tools, the logics and the ideologies behind the interfaces. We also look at who produces the tools, who implements them, and who creates and accesses the large amounts of data needed to develop prediction machines. One could say, with the wink of an eye, that we are collaborators of this new tribe of human-robot hybrids.