In this room installation, I bring together artefacts from the past that I have found in the cellar and in my memory: An art print that once hung above my parents’ marital bed, framed by a floral tabete; a stuffed animal head, a stylised sculpture of a deer, a television. A long corridor with no entrance or exit. They all find their place in a space that is both real and fictitious, but which we wander through again and again in time. Like prisoners of a time loop.
If you could define ‘oblivion’ or ‘eternity’ as a mathematical formulae – what would they be? Can an AI find a logical answer to this?
Probability of ‘forgetting’ (AI-generated)
Explanation of the variables:
P(F): Probability of forgetting. This lies between 0 and 1
M: Memory strength. It describes how well the information is anchored in the memory. A high value for M reduces the probability of forgetting.
R: Relevance. The more relevant information is, the more it is remembered and the less likely it is to be forgotten.
P: Perception. Describes the intensity with which the information is absorbed. A high intensity of perception reduces forgetting.
SM: Mental State. This value influences the ability to perceive and retain information. A high value means a stable mental state and reduces forgetting.
t: Time – Time. The probability of forgetting increases with increasing time.
Interpretation:
This formula is based on an exponential decay model, similar to the model of radioactive decay or other forms of memory loss over time. When memory strength, relevance, perception and psychological state are all high, the value in the exponent is very large, and P of F approaches 0, which means that the probability of forgetting is low. However, as time t increases, the exponent becomes smaller, bringing P(F) closer to 1 – forgetting becomes more likely.
