The 2010s have been a very interesting decade for the creation and generation of images of reality and beyond. The discovery of the Higgs boson particle (2012) and the capturing of the shadow of a black hole (2019) are two of the most prominent examples of science and imagination colliding, shattering the lines of what was previously understood as universal reality. It's been a decade during which it became common knowledge that standard models need extensions, fields of knowledge continuously scale up and down and AI is used pervasively to predict not only the future, but also to see beyond the unseeable. What was once deemed impossible, has become possible.
In 2019 I won the Collide at CERN/Barcelona award with my proposal “Shadow Knowledge”, a project about the fringes of what is enlightened (or: not in the dark). Subsequently, I was awarded a two month residency at CERN, with an additional month in its partnering city of science, Barcelona. In my research proposal, I used the shadow as a metaphor: “In the shadows, things lack definition. The shadows offer shady outlines that can function either as a vector of progress or as a paint by numbers.” I proposed research about what can just be seen or sensed, and about how these new and other techniques can be deployed to derive knowledge about objects of unsupported scale and dimension.
In September that year I finally made it to the largest experiment in the world. But upon arrival at CERN I quickly encountered multiple linguistic clashes. Where I, as an artist, like to use poetic phrases such as Shadow Knowledge, communicating this way with members of the scientific community remained difficult. Our use of language did not jive. Pretty quickly, it became clear I had to cross over to a scientific use of language and find a way to communicate that made sense to the scientists there. A challenge compounded due to differences in language between scientific disciplines, methods, and even experiments.
To consider this challenge I sat down with my two scientific partners: Jeremi Niedziela and Rolf Landua.
With their generous help I reframed my research into a single question:
Imagine you could obtain an 'impossible' image
of any object or phenomenon that you think is important,
with no limits on spatial, temporal, energy, signal/noise or cost resolutions.
What image would you create?
(The answer can be a hypothetical image of course!)
During the three months of my residency I asked every scientist I met this question. Not only for them to consider what images are possible or impossible, but also to probe and isolate the mechanics at work whenever a certain type of image (or rendering) is or becomes ‘impossible,’ or similarly, when a method of rendering gets compromised (deleted, discarded or obsolete). This new method of inquiry worked really well; I rapidly collected countless im/possible images in dialogues with scientists, via email, and through an online form set up for this purpose.
