@ -25,7 +25,7 @@ It's providing a point of view and a perspective to look at the world, before at
Using the simulation as a writing machine we can articulate these CC with some benefits:
- Suspension of judgment
- **Suspension of judgment**
Within the scope of the simulation it's not necessary to label good or bad choices.
_(That would have been the case for a machine learning writing device, for example)_
@ -33,21 +33,21 @@ Using the simulation as a writing machine we can articulate these CC with some b
Due to the nature of the process, even the most absurd starting point it's a valid and powerful narrative device.
In this way it becomes easier to explore marginal cases, improbabilities, and non-conform situations.
- Discrete temporality
- **Discrete temporality**
A simulation does not happen all at once, instead it is a process that evolves through time.
This happens in both discrete steps and long-term iterations.
Discrete steps can be further subdivided or grouped together, with the possibility of magnifying details, and the ability of zooming in and out a story.
Long-term iterations are a way to keep asking _what's next? what's next?_ to the machine. At every cycle, the simulation reaches out to each partecipant and asks for an update. In this way all the actors and relations develop in parallel.
- Partiality
- **Partiality**
Participants are defined gradually, and do not come as a monolithic block.
They start as details, a label, a profession, an ideal, and then begin to entangle gradually.
They can be imagined as lines: merging together and branching away, tying and loosening knots. (Ingold)
This leads to multi-facets and situated (Haraway) subjects, where not all the elements needs to interact with each other all the time. Their interfaces can be loose, they don't need to be one hundred percent compatible to come together.
- Orientation
- **Orientation**
Zooming in and out from the particular, we get a glimpse of a more gradual and diffuse process.
A subtle sense of direction emerge from the initial randomness.
@ -56,17 +56,17 @@ Using the simulation as a writing machine we can articulate these CC with some b
The simulation is structured as a series of stages:
1. Requirements
1. **Requirements**
Where to decide and define the elements involved in the simulation.
2. Setup
2. **Setup**
Where we join these actors together in small combinations.
These will be the starting worlds of the simulation.
To keep things simple, each world will be a closed ecosystem, and there won't be explicit interaction between different ones.
3. Worlds simulation
3. **Worlds simulation**
At this point each world will be really dry and synthetic, defined just by some labels that state that an actor is a musician, the name of a programming language, etc.
@ -85,7 +85,7 @@ The simulation is structured as a series of stages:
This procedure helps us to think about software as cultural object. Something "deeply woven into contemporary life –economically, culturally, creatively, politically– in manners both obvious and nearly invisible." (Software Studies, 2009), and not just as technical tool existing in a vacuum.
4. Insert documentation element
4. **Insert documentation element**
Through some iterations, each world will grow a network of actors to play with. Once reached a sufficient mature state, we will introduce a new element: documentation. Throwing a pebble in the puddle to watch how it will ripple through. Which other elements will relate with it, and which one will not? Which transformation it will trigger in the dynamics of access, of power, and representation that are sprouting around software in each simulation?
@ -108,7 +108,7 @@ These categories are a way to deal both with the software and hardware circumsta
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In a grey zone where Actor Network Theory (Latour) and Object Oriented Onthology (Harman) overlap, we can think to every element in these categories as an actor, or an object. Hence we can afford, on one hand, to delegate the identity of an actor to its relations with others. Here every iteration and every update of the simulation is an event, an exchange between actants. On the other hand, the unknowable nature of the object leaves room for the simulation to dig deeper, to keep renegotiating the object' state exposing different qualities from time to time.
