You will get to know the group, get details on the schedule and general house-keeping information.

The tracks will discuss the texts they have collectively chosen and discuss a more specific focus of their collective work over the next days. We recommend a mix of discussions in the group and time for everyone to write down themes and questions they find particularly interesting.

You will continue the work of the last session and prepare a short introduction to your track themes for the presentation in the afternoon. You can also prepare questions you have for the whole group. Plan for a presentation of 5-10 minutes where you share your main interests, track theme and questions you would like to pursue. Slides are not required, but can be helpful.

Each of the six tracks will have 20 minutes including presentation and discussion. The aim is to learn from each other's ideas and also find potential overlaps between the track themes. We all know this is work-in-progress! You can also briefly include what you expect from the different methodological approaches.

Abstract:

We arguably live in a new age of planetary design. From the training of large language models on billions of users to the rise of synthetic biology and bio-materials, life is becoming a medium for experimenting with technology at every scale. This talk traces a history of the planetary experiment and investigates how the new logics of AI governance both extend and challenge earlier histories of globalization, colonialism, and modernity in science and design. I will also discuss the ways concepts of data, representation, and evidence are being transformed in our present.

The effort to experiment at scale is not new. We might, for example, consider colonial terraforming projects, Fascist ideas of the ‘new man’, Communist collectivization, and cybernetic ideas of spaceship earth, among many other practices and imaginaries of social planning, experimentation, and design. This talk argues , however, that while contemporary technical practices and corporations may borrow from these pasts, the contemporary ideas and practices of design grounded in AI and notions of planetarity are radically new, and mark a separation from these legacies.

I argue generative AI reflects and advances a new idea of planetarity and design grounded above all in the concept of a planet whose survival demands increased computational power. Contemporary planetary design imagines the planet in a state of crisis, to which AI is the answer. I will trace four loci to track the emergence of this new ethos of generativity: 1) transforming practices (from creativity to generativity and prompting, and from ideals of risk management to resilience), 2) new forms of computational territory (the zone and the spaceship), 3) emerging forms of rationality and perception (situational awareness rather than distraction or attention) and 4) new ideas of synthetic data and materials that transform separations between organic and inorganic at multiple scales and are producing new economies of knowledge and money (such as biomaterials, nanotech, and synthetic biologies, and the emergence of new economic models such as smart infrastructure as service).

Based on the text "Reading Datasets" by Lindsay Poirier, we will engage with datasets both literally and critically through different readings: Denotative, Connotative, and Deconstructive. The denotative reading aims at a literal reading of the metadata of the dataset and asks what counts according to the data producer; the connotative reading explores the dataset’s cultural grammar and historicity; and the deconstructive discusses what is made absent/residual and thus aims at politicizing the dataset and its meaning.

Reading means that the tracks will search for information about the dataset and its context and discuss and interpret it within the group. You find a set of analytic questions that can guide the three readings in the method input document. If many new questions come up in the process, all the better. The aim is not just to generate some answers, but to discover different perspectives.

It might be helpful to do the first reading together, create the dataset profile and engage with the denotative reading in the track. For the connotative and deconstructive readings, participants will need some time for individual research online. Overall, a back and forth between individual time for research and gathering information and group time for synthesizing and discussing the information seems suitable to make the most of the time.

Please remember to document your work and e.g. note what information is difficult to find and include this in the discussions.

It might be helpful to decide on a more detailed timing for the two sessions at the beginning of the first session. You should also use a shared document to note down your (different) readings (e.g. set up a document in the Hessen Box or set up an etherpad).

Continue with the readings you have begun in the first session. Don't forget to document your readings in the shared document. As for all methodological exercises, we ask each track to also document their learning experiences and reflections on the coloured cards we distributed.

And please keep in mind that there will be a presentation at the end of the week. Writing down the most important results and reflections will help with the preparation!

Based on Powell's "Data Walkshop" text and the organizers' experiences, data walks will be introduced as a method that enables experiences of datafication processes (and its limits), allows for criticall engaging with data and exploring data (infrastructures) in practice. For our second methodological exercise in the summer school, organizers will provide a recipe that offers some guidance on how to conduct the data walk.

Tracks meet to agree on a topic for their data walk and prepare it for the following day. See "Method Input 2 - Datawalk".

1. Exchange ideas and agree on
   • how data related to your topic can be collected or generated
   • the recording (capturing) devices you find helpful and/or would like to use
   • what forms for visualisation could be suitable
2. Decide on the 'where' of the walk and the route

Please pick up your lunch box at the hotel reception at 8am!

Tracks meet up to carry out their respective data walks. For checking-in before the walk and debriefing after the walk see "Method Input 2 - Datawalk". It is up to the tracks how they structure the day in time: There is plenty of time for taking things slowly, for strolling and resting.

Brief joint recap of the data walk experiences, data/materials generated and and thoughts on whether to use it for the following visualisation exercise.

This input will prepare you for the data visulization exercise.

Data review phase (15 minutes) - briefly discuss and document:

• What dataset(s) will you be using for your visualization?
• What uncertainties do you have about the content and scope of the dataset?
• What are some distinctive features of the data that you are already curious about?
• What themes from your track discussions and previous exercises should be incorporated into your visualization?
• What special skills for data visualization can you draw on in your group?

Conceptualization phase (45 minutes) - discuss and document:

• Find three or more existing visualizations that you find interesting or relevant.
  • What do you like about them? What could be improved?
  • How could they be adapted for your project?
• Make two or more fast and rough sketches – by hand, on paper – of visualizations that you would like to pursue:
  • The data itself isn’t important, just make up metrics on the fly.
  • Focus on the type of visualization instead: structure, variables, axes, shapes, …
  • Keep it as minimalist as possible. Beware of “feature creep”.
• Briefly discuss each sketch:
  • How can we simplify it (even more)?
  • Is it feasible with the data you have?
    • If it isn’t, skip to the next sketch.
    • If you are out of sketches, prepare more.
  • What do you expect the data may show? Why is that interesting?
  • What expectations and habits does it cater to? How could you subvert them? Why would you want to?
• Decide on one approach:
  • Which sketched visualization will you carry out?
  • What tools will you be using?
  • Explicitly assign specialized roles that require technical expertise.

Preparation phase (30 minutes)

• Prepare the data. Depending on your approach and the dataset, this may involve data import or entry, cleaning and summarizing data, joining different sources, or shaping data.
• This may not be a good task for a large group. Here are some tasks that other track members can do in the meantime:
  • Organize the notes taken so far.
  • Refine the sketch.
  • Curate a mood board with inspirations and relevant aesthetics.
  • Discuss:
    • What are some features you would like to add to the map if you have the time? Why?
    • What are some (easy) alternatives for metrics, shapes, colors etc. that you may want to try in future iterations.

Visualization phase (60 minutes)

• Prepare a minimalist version of the visualization. Save this version for future reference.
• Critique it.
• Iterate by adding, changing, subtracting.
• Document the process.

Continue visualization phase (60 minutes)

Finalization phase (30 minutes)

• Write up a brief accompanying text drawing on your documentation of the process.

Abstract:

Digital fish, AI-designed enzymes, voice biomarkers, epidemiological risk scores – these are just some of the digital formations that proliferate with ubiquitous datafication. Emergent data critters thrive in the life sciences and beyond; they populate research proposals, science and technology policies, public debates and are imbued with anticipation. While some data critters may be transitory and disappear again, they leave traces, modify their surroundings, are being worked upon, or seep into infrastructure. Data sets mobilized in recent AI aspirations contain legacy infrastructures that cannot be fully disentangled; rather they need to be treated as mixtures and unpurified archives from the outset. Asking for what remains unaccounted for in this current digital reassembling can help render visible the orderings and politics in pertinent data ecologies. This talk will introduce a small subset of data critters and propose the format of a partial inventory as a method to engage with things digital.

Tracks prepare their final presentations- based on the documentation and reflection of their activities during the week.

Presentation of Tracks 1-3 - each track has 20 minutes in total (max 10 minutes for their presentation and rest for discussion)

Concluding discussion - based on the experiences gained during the week and the methodological reflection card questions.