thesis/chapters/00. Coding Contingencies.md

Notes for the intro

-   with a clear structure the simulation can be more heterogeneous
-   aggregate materials and references

-   intro as a readme file
-   Could be interesting to read What the Dormouse Said

Simulation overview

This introduction is not a written as a text, but runs a simulation.

Coding Contingencies (CC) is a procedural take on how different characters deal with code.

How did they choose a particular programming language, a coding paradigm, a development environment, an infrastructure where to run the code, and so on? These are not just technical choices, but rather coding contingencies.

Personal decisions, trending technologies, curiosity and boredom, to name a few. A talk on esolangs as form of frugality, a collegue passionate about live coding that drags you to an algorave night, a crypto-boyfriend, the tech stack of a company, a drastic turn of events, etc. etc.

These contingencies are situated in contexts. Programming then is not just sharing code, but sharing context. It's providing a point of view and a perspective to look at the world, before attempting to get some grip onto it with a script.

Using the simulation as a writing machine we can articulate these CC with some benefits:

• 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) One character could decide one morning to write their own operative system from scratch using Red Stone circuits in Minecraft, and it would be fine. 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

  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

  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

  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. By design, the simulation articulates software as a mean to orientate, as well as being oriented by, these trajectories.
  How does certain programming languages facilitate certain ways of thinking, and totally block some others?

The simulation is structured as a series of stages:

1. Requirements

   Where to decide and define the elements involved in the simulation.

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

   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.

   0  do loop
   1   for each world
   2    for each participant
   3     ask for updates
   

   The structure of the simulation resembles a nested loop: for each world visit each participant, and ask for updates. Actually, we can save resources simulating just the combinations we want to explore, and not all the worlds of the initial dataset. The more iterations, the deeper the simulation gets.

   Being a writing machine more than a piece of software, the process could be thought as a slow simulation. One that benefits the understanding of such a device and the quality of the different stages, instead of the quantity of iterations and generated data. A way to witness code and non-code entities (Mackenzie, 2006) coming together and shaping each other.

   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

   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?

   These emerging issues will articulate the main questions of this research: could software documentation be a surface to situate code in the world? Could it be a device to foster entry points for a more diverse participation? Could it be a way to orientate technologies with our set of values?

Requirements

The first step is to decide on the participants of the simulation.

Although we could sink into a well of details to describe actors in the most accurate way, in a simulation just a detail it's enough to start.

Who and what are they? When and where are they coding? And what do they do when they are not in front of a computer? These and other questions will be unpacked during the simulation.

Instead, let's trace some categories: programmers, programming languages and use cases.

These categories are a way to deal both with the software and hardware circumstances of code (Marino, 2020), but also their relations with non-code entities (Mackenzie, 2006). A more-than-human and more-than-technical set of elements.

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.

Programmers are actors that deal with code. They will be grounded into our present and recent history, where people are often defined by what do they do in order to pay the bills. Thank you capitalism™️ for this detrimental reductionism! They are usually human (or groups of), situated within a professional context. Not all of them code for a living, but some live for coding.

Programmer

- developer
- engineer
- teacher
- musician
- artist
- designer
- researcher
- class
- student
- sailor

Software are objects made of code. Here we will refer to a particular subset of software, namely programming languages. In order to explore different worlds within the simulation we will chose languages coming from different contexts: from the present and from the past, high and low level, commercial and esoteric.

Software

- lisp
- cobol
- javascript
- python
- haskel
- assembly
- redstone

Use cases are fields or objectives one could use code for. This could seem a bit loose, but in the scope of the simulation, it orientates actors in certain directions. Their effect is more like a magnetic force, than the call of destiny. This writing machine is not an hard coded teleological device, but rather a sandbox to generate narratives around software.

Use case

- business
- work
- accessibility
- survival
- publishing
- play
- writing
- modding
- research

Setup

Notes:

• possible references to build the dataset

  • Weathering Software Winter (100R)
  • Close to the Machine, Life in Code (Ulman) ch. Close to the mainframe?
  • Pattern of Software, (Gabriel) ch. into the ground?
  • Red Stone Focus? Mods, Essay, Virtual machines
  • P5js accessibility issues?
  • Paged.js?
  • Screenless Office
  • SI16

---

then we need to combine thigs from the three categories

• developer, cobol, work
• sailor, assembly, survival
• teacher, lisp, business
• artist, javascript, accessibility
• designer, javascript, publishing
• class, python, publishing
• engineer, python, art
• artist, red stone, writing
• student, red stone, modding
• engineer, red stone, research

ITERATE

Notes:

• Explore a combination

• Visit each element and elaborate on it

• Highlight aspects of simulation

• Repeat

• Repeat with other combination

• Need to understand how to format this!

• Meaning: One after the other or all in parallel?

• TBD

• Different ways to approach the relation betwen software and context

• Discrete Temporality

  1. Temporality could also be a way to explore events of the past not every simulation must be set in the present

     ie: Ulman account on childish developers culture (Close to the machine, Life in code) ie: Richard Gabriel timeline for example (Pattern of software)

  2. Temporality could also be non uniform! ie: updating using commits in a version control system, gradually fading away when a project stops being maintained

• Suspension of Judgement

  1. exploration of margins uncommon or absurd setup why are they absurd? what is the norm?

  2. proxy exploration exploring thing we dont understand software as unknown?

     ie: esolangs

  3. a way to investigate and build on disproportion of means: ie: contemporary infrastracture to code a TODOs app ie: quest for frugality in permacomputing projects

• Partiality that could also be read as multiplicity

  1. Focus on the same actor in different contexts:

     ie redstone circuits used to develop a virtual minecraft into minecraft itself but also cited by hito steyerl refering to the overflowing of internet into real life, as well as the sinking of real life into internet (steyerl) but also expanded by modders to build different red stone dialects, forking the original one

     ie reclaimed technology tech deployed for military purposes recontextualized for medical uses (find exact references maybe in ways of being) (bridle)

• Orientation

• level of details

1. zoom out to outline trends

   ie coding language hype how languages get popular and then forgotten trending on yt, threads on twitter, conferences, investors! sponsor! etc.

   less about single characters more about their surroundings online communities!

• When things are vivid enough go on

---

now that the setup is done, the simulation can start.

to build something meaningful out of these random combinations we can balance between what is defined and what is not. leveraging on the unknown of the simulation gives room for narrations.

so for example we have #04

a musician what is their background?
which kind of music do they play?
where are they based?

using pure data an open source visual programming language
works in real-time
focus on interaction and sound design

for work which kind of occupation?
is it for interactive installations?
to teach sound design?
for live gigs?

see how there are a lot of open questions in the first and third fields, while the programming language is slightly more defined and fixed. this is a good starting point. obviously a programming language is vast and complex and with dozen of features one could be interested in, but for the sake of our system it is useful to leave these things unsaid.

we can use the software as a pivot to orientate the relation between the actor and their intentions.

from where they are coming and where do they want to go? who took them there? what do they need? which particular aspect of pure data resonates with their view of the world? is it the open source nature and the licensing of the source code? the welcoming community thriving around the programming language? or the visual paradigm that facilitates the thinking about and connecting abstractions together?

INSERT DOCUMENTATION AS ELEMENT

Notes:

• introduce documentation as new element in each simulation
• look what it does, how it ripples through the system
• which other element relates with documentation?
• who has to write, who get to write, who is addressed, how is sustained, etc
• articulate critical points

---

WRAP UP

Notes:

• software as a mean to orientate narratives

• narratives as a mean to orientate software

• documentation as a surface to explore

• how to situate our use of code in the world

• which context ? situated software

• why it matters for me!!!!!