I am going to be in conversation (remotely) with Thomas Moynihan at Transmediale. I was supposed to propose something about technology and philosophy and here were the options I sent over to Thomas. He selected one, the others I may expand upon at a later date.
1) Augury in the 21 century
Since the caves of Lascaux, humans have attempted to predict and influence the future. Today we have scenario planning and future studies that are supported by the methodology of simulation and empowered by computation. In the past, there was a symbolic relationships between the world and the instruments of prediction e.g, bones in a certain formation meant rain was coming. Today prediction is a two step process, data collection, world building, and interpretation/selection. The bones and their environment (ie milieu) report data points that are reduced to quantitative values. These values are used to along with the perturbations of variables to construct a variety of worlds. We then pick the most likely of worlds as our prediction. [THIS last sentence would want to rework – it is not phenomenological – but I cant think of the world I want to use, I also feel like I might want to talk about Simondon and his notion of the relationship between magic, aesthetics, science and ethics]
What is the relationship between the simulations of today and the folk practices of divination, and what can we learn from an archaeology of prediction?
2) Modalities of Data Visualization
Data visualization of often the end result of a simulation or some sort of numerical analysis, and used either for informative or aesthetic purposes.
When we engage in data visualization, we are engaging in data mapping. All these mappings are contingent since there is nothing in the data that forces the visualization to be a certain way: why a dot and not a line, or example. In the face of this radical contingency, how can we engage in data visualization or data mapping in a rigorous way? One criterion that moves beyond modalities of necessary and contingent is coherence or incoherence, and this also has some history in the work of philosophers of science such as Carnap. So perhaps a better visualization is which is more coherent and encompasses more variables.
How can we create a robust framework to ground data visualization, and data mapping in general?
3) Hypothetical Ethics
Most people would agree that we have a responsibility to clean an oil spill that we cause. How about if we run a simulation that predicts with 70% probability robots will create too many paperclip and thus destroy the world. Is it our responsibility to prevent this? The Nicomachean Ethics does not have section on how to take responsibility for probabilistic future events. Neither does Kant’s moral imperative address this issue. I posit we are in new ethical territory created by computational simulation, and we need a new framework for understanding how we ought to act, taking into considerations notions of risk, probability, and simulation robustness.
What are the new rules of actions in regards to probabilistic future events predicted by a computer simulation?