Dis-automatizing classes

This post will list some of the Stieglerian techniques I used in some of my courses this year to attempt to dis-automatize thought.

 What is dis-automatization    top

Dis-automatization techniques are ways to cope with the “great transformation” (cf. Polanyi) of the Anthropocene. This transformation comprises massive interconnected systems on a global scale that standardize such as by making any differences the same by concretizing them all as technical facts that serve systems. Where these systems become closed such as through extractive practices, entropy and structural insolvency can ensue. Further, where knowledge turns into non-knowledge by being automatized, such as where data mined from individuals is aggregated and returned to us in algorithmic processes that function four million times faster than the human nervous system, it becomes toxic.

By contrast, individual and collective acts of dis-automatization can ex-press and exteriorize new symbols (not constrained in closed systems where symbols can only be consumed). This can further cultivate knowledge through the learning that can take place through the exteriorization of memory. Memory can be exteriorized through tools like pen-and-paper or computer screens.

Key to dis-automatization are local deliberations comprising local networks. A network could be a class comprising groups that come together to complete projects and/or share (project) work. Work in such a network is discussed, annotated, and interpreted.

Cultivating knowledge is critical: the design of the work/projects must seek to avoid automatic memorization, which transformative technologies such as GPT can now do better than humans anyway. And by knowledge is meant Platonic, maieutic implications at the root of the word educate: ‘to educe’ means ‘to evoke’ knowledge from within a person (cf. Nachmanovitch), who further internalizes not just subject matter but learning processes. One learning process key to the production of knowledge is interpretation, especially as it directly points to the code of interpretation that structures social understanding (cf. Ricoeur).

Interpretation is what can bring into question what in cultural studies is called the assumptions that embed cultural artefacts (cf. Williams), which are taken for granted. Interpretation is also what can bring into question the ideologies that go without question although they are the codification of society in which people think but not conceptions that they pose. Bringing this back to Stiegler, thinking through the automatizing tool without questionning it can be a form of poison, not cure, (φάρμακον) as it can lead to forgetting – not just how to do a given task but to live, in general. To give some banal examples, not everyone remembers how to bathe without running water, to make sources of light without electricity, to forage for edible foods in the forest.

Further, forgetting to question even systems of thought can make these systems become systems of belief (cf. Ellul in Ricoeur). Stiegler explains this problem in his own way:

all knowledge contains the possibility of being dis-automatized through the act of knowing, where this knowing internalizes the automatisms in which this knowledge also consists, but which through being automatized becomes anti-knowledge, that is, a dogma that can be dogmatic only by concealing from itself its dogmatic character, or in other words, its automatic character.

Note: while it is true that knowledge exteriorization needs to be somewhat stable for it to be transmitted, such as through schematization, idealization, and rhetoric (thereby becoming dogmatic in character), the massive, global scale of automatization taking place today through aggregation of the digital traces that humans leave calls for the re-presencing of these traces so that there remains social cohesion. As Ricoeur has explained, the average cultural level of a group can be surpassed, in which case it no longer remains coherent. It cannot be coherent if the culture is no longer self-explanatory, which will happen if too much knowledge is lost.

Therefore, what are some of the ways in which the act of knowing is promoted?

 Prompts for the act of knowing    top

Wiki structures
Explicit emphasis on how knowledge is being classified, sorted, and hierarchized. Wikis can help with this through tagging, categories, and link-log pages, for example. Inspiration can also be drawn from P2s used in professional contexts, which also gives students work-relevant experience.
A class charter
What is the purpose of a class? Through participatory syllabus techniques, this can be discussed and decided on as a class through a class charter.
Annotated archives
Just as data is aggregated from us, we, too, can get experience in collecting and sorting information, which can become knowledge through annotation and discussion. The content in the archives can form material for project work.
Reflective components can be added throughout, not just through annotation or interpretation (by students alongside teachers) but also through question prompts, chat comments, discussion threads, etc.
Mind maps
Mind maps – done by hand – can be practiced as course material was presented. This is quite literal dis-automatization as no digital technology is used.
Classifications for course design
It is fun to think of different ways for course material to be organized from semester to semester. This is also dis-automatization, especially for the teacher.
Glossaries, blogs, [site] resource pages, etc. can be used in various ways. For example, students can practice technical writing and review the digital tools used in class, or resource pages can point to how to post images according to Creative Commons best practices. Students can also critique the digital tools that are used or not used in a course to prompt thinking about the computational processes behind the tools and not automatic use of the tools themselves. Seth Kenlon explains the importance of this approach.

 References    top