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  1. 8
      content/Section 3 - Bots/1-introduction.md
  2. 10
      content/Section 3 - Bots/10-theoretical-perspectives-on-bots.md
  3. 2
      content/Section 3 - Bots/2-examples.md
  4. 2
      content/Section 3 - Bots/4-bots-and-infrastructures.md
  5. 23
      content/Section 4 - Bot Logic/1-introduction.md
  6. 35
      content/Section 4 - Bot Logic/2-bot-logic.md
  7. 16
      content/Section 4 - Bot Logic/3-bot-behaviour.md

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content/Section 3 - Bots/1-introduction.md

@ -3,3 +3,11 @@ Slug: 01-s3-introduction
Date: 2020-11-01 12:00
Summary:
## What are bots?
When we say bots, we refer to software agents which automatise certain actions and can run autonomously or semi-autonomously. The particular bots we are interested in for this online module are those that act as an interface between the digital platform and human users, or what Hepp calls communicative robots[^hepp], robots that "are defined as autonomously operating systems designed for the purpose of quasi-communication with human beings to enable further algorithmic-based functionalities – often but not always on the basis of artificial intelligence."
In this section, we will introduce Darius Kazemi, computer programmer and artist, and Andreas Hepp, professor of media and communications.
[^hepp]: Artificial companions, social bots and work bots: communicative robots as research objects of media and communication studies, <https://journals.sagepub.com/doi/full/10.1177/0163443720916412>

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content/Section 3 - Bots/10-theoretical-perspectives-on-bots.md

@ -1,13 +1,3 @@
Title: Theoretical perspectives on Bots
Slug: 10-s3-communicative-bots
Date: 2020-11-01 12:10
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content/Section 3 - Bots/2-examples.md

@ -2,3 +2,5 @@ Title: Some Examples of Bots
Slug: 02-s3-examples
Date: 2020-11-01 12:02
Summary: <Short summary here>
Some examples of bots are

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content/Section 3 - Bots/4-bots-and-infrastructures.md

@ -2,3 +2,5 @@ Title: Bots and Infrastructures
Slug: 04-s3-bots-and-infrastructures
Date: 2020-11-01 12:04
Summary: <Short summary here>
How do bots relate to digital infrastructures? Let's take two examples of communication platforms that

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content/Section 4 - Bot Logic/1-introduction.md

@ -5,29 +5,8 @@ Summary:
## Bots as infrapunctures
Infrapuncture is a comely term at a moment in time when there is a lot of discussion around the political roles of automated agents in digital infrastructures. Before we move any further, perhaps a short definition of bots is necessary. When we say bots, we refer to code that automatises certain behaviours and which often acts as an interface between platform and human users.
Infrapuncture is a helpful term at a time when there is a lot of discussion around the political roles of automated agents in digital infrastructures.
Many online communities engage with bots, for example the editor community of English Wikipedia, which consists of both humans and bots. The interactions between them go beyond the maintenance of Wikipedia. Instead, affective relations are formed wherein the bots are anthropomorphised. So writing a bot implies not only to understand the API (Application Programming Inferface) of the platform, what determines the possibilities of interaction, but also the social norms established within the community of editors and users of Wikipedia.
And that's of course just one example. Bots act differently depending on the platform on which they are running.
## Bot logic
What kind of puncturing logics might bots enable in digital platforms?
Bot logic is phrased as a response to platform logic, which Jonas Andersson Schwarz describes as "digital platforms enacting a twofold logic of micro-level technocentric control and macro-level geopolitical domination, while at the same time having a range of generative outcomes, arising between these two levels".
'Bot logic' refers to the situational effect of bots upon a socio-technical ecology and their potential to infiltrate and co-exist with server-side conditions. Perhaps we can move our attention to these few points. When referring to platform logic in the points below, we refer to commercial infrastructures, not federated and free software platforms such as those present in the Fediverse, which have a different kind of dynamics[^theses].
* Where platform logic accumulates, bot logic disperses
* On commercial platforms, the engagement of users equals economic value that is translated through data capture and organisation. Metadata is extracted from users that then through pattern matching can be used to target users for advertisements. While bots can and do participate in this economy, they can also enable its sabotage. In the case of buying bot followers, this can be a means to generate noise in the collected dataset and blur the perception of the user as a set of behaviours that the platform has.
* Where platform logic centralises, bot logic fragments
* Platforms such as Twitter or Facebook use a centralised system, in the sense that the servers on which our information is stored are owned by their company. Bots, on the other hand, do not require a lot of computational power in order to run. They can be simply run from the computers of the persons who wrote the code themselves. In fact, bots really point to the materiality of the structures on which they run, as researcher Stuart Geiger also points out when he talks about 'bespoke code' as code that extends or transforms the operations of software platforms, but "runs on top of or alongside existing systems instead of being more directly integrated into and run on software-side codebases".
* Where platform logic creates distance between user and infrastructure, bot logic develops an intimate knowledge of the platform
* If we consider means of communication as means of production (Williams, 2005), there is a certain alienation that happens on commercial centralised platforms, where the user has no stake in the development of the material conditions of the platform on which they communicate. From this point of view, the making of bots implies a closeness to the platform that is indicated through the understanding of both the sociological and technical systems that determine the usership of a platform. In order to code a bot, you need to know what kind of actions are allowed and how the bot would be received by the community.
* Where platform logic reinforces habitual behaviour, bot logic encourages new habit formation
* If we think about a commercial platform as a structure or surface on which actions can take place, these actions are often predefined by the affordances of the platform. However, as was mentioned in the beginning, bots are the automation of certain actions and behaviours. To be able to define these behaviours as a user can mean an alteration of the socialities embedded in a platform.
All of these points were written with commercial platforms in mind, however, exciting developments are happening in federated platforms such as Mastodon, where users are part of defining features and possibilities of interaction. There, the norms of the platform and the way they are codified into the technical structure are more often revised and reformulated together with the user base. This in itself creates a different space for bots, which are still active contributors in the way sociality is imagined on these platforms. However, on platforms like Mastodon, bots don't only comply to the terms of services of the API but also to the code of conduct, for example.

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content/Section 4 - Bot Logic/2-bot-logic.md

@ -0,0 +1,35 @@
Title: Bot Logic
Slug: 01-s4-bot-logic
Date: 2020-11-01 12:01
Summary:
## Bot logic
What kind of puncturing logics might bots enable in digital platforms?
Bot logic is phrased as a response to platform logic, which Jonas Andersson Schwarz describes as "digital platforms enacting a twofold logic of micro-level technocentric control and macro-level geopolitical domination, while at the same time having a range of generative outcomes, arising between these two levels".
'Bot logic' refers to the situational effect of bots upon a socio-technical ecology and their potential to infiltrate and co-exist with server-side conditions. Perhaps we can move our attention to these few points. When referring to platform logic in the points below, we refer to commercial infrastructures, not federated and free software platforms such as those present in the Fediverse, which have a different kind of dynamics[^theses].
* Where platform logic accumulates, bot logic disperses
* On commercial platforms, the engagement of users equals economic value that is translated through data capture and organisation. Metadata is extracted from users that then through pattern matching can be used to target users for advertisements. While bots can and do participate in this economy, they can also enable its sabotage. In the case of buying bot followers, this can be a means to generate noise in the collected dataset and blur the perception of the user as a set of behaviours that the platform has.
* Where platform logic centralises, bot logic fragments
* Platforms such as Twitter or Facebook use a centralised system, in the sense that the servers on which our information is stored are owned by their company. Bots, on the other hand, do not require a lot of computational power in order to run. They can be simply run from the computers of the persons who wrote the code themselves. In fact, bots really point to the materiality of the structures on which they run, as researcher Stuart Geiger also points out when he talks about 'bespoke code' as code that extends or transforms the operations of software platforms, but "runs on top of or alongside existing systems instead of being more directly integrated into and run on software-side codebases".
* Where platform logic creates distance between user and infrastructure, bot logic develops an intimate knowledge of the platform
* If we consider means of communication as means of production (Williams, 2005), there is a certain alienation that happens on commercial centralised platforms, where the user has no stake in the development of the material conditions of the platform on which they communicate. From this point of view, the making of bots implies a closeness to the platform that is indicated through the understanding of both the sociological and technical systems that determine the usership of a platform. In order to code a bot, you need to know what kind of actions are allowed and how the bot would be received by the community.
* Where platform logic reinforces habitual behaviour, bot logic encourages new habit formation
* If we think about a commercial platform as a structure or surface on which actions can take place, these actions are often predefined by the affordances of the platform. However, as was mentioned in the beginning, bots are the automation of certain actions and behaviours. To be able to define these behaviours as a user can mean an alteration of the socialities embedded in a platform.
All of these points were written with commercial platforms in mind, however, exciting developments are happening in federated platforms such as Mastodon, where users are part of defining features and possibilities of interaction. There, the norms of the platform and the way they are codified into the technical structure are more often revised and reformulated together with the user base. This in itself creates a different space for bots, which are still active contributors in the way sociality is imagined on these platforms. However, on platforms like Mastodon, bots don't only comply to the terms of services of the API but also to the code of conduct, for example.
API, Stuart Geiger

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content/Section 4 - Bot Logic/3-bot-behaviour.md

@ -0,0 +1,16 @@
Title: Bot behaviour
Slug: 01-s4-bot-behaviour
Date: 2020-11-01 12:02
Summary:
As programmable objects, bots have particular action modes. Below some examples (although this is a non-exhaustive list)
- repetition: bot code can be run repeatedly
- condition: bot code often is written in response to a particular condition
- iteration: bot code can be run multiple times
- memory: bots can rely on a database
- tempo: bots can operate at a specific time frame as described by the programmer
Of course, these action modes can also be "executed" by humans. It is by no means surprising that many Twitter users are mistaken for bots, or that the term itself has attained a derogatory meaning. However, an interesting phenomenon can be observed on platforms such as Twitter, where human users have adopted a type of bot behaviour to create networks of dissent and to push activist counter-narratives. Such a moment happened recently on Dutch Twitter. In response to the Black Lives Matter protests, extreme right wing politician Geert Wilders posted an image on Twitter on June 5th 2020 using the hashtag #ZwartePietMatters.[^zwartepiet] Following this post, a wave of from the k-pop community
[^zwartepiet]: Zwarte Piet is a ...
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