Procedure

This task consists of five parts.

In the first part, there is a short input from the moderator to get participants excited about the topic and give them a basic understanding. Topics for this can be found in training material 2.

In the second part, participants acquire basic knowledge about how the internet, algorithms, artificial intelligence, and machine learning work by completing a series of stations. Participants visit different knowledge stations (work materials 1–4) individually and at their own pace. Each knowledge station consists of a text or video explaining the topic and a task. Once they have completed the task, they should enter a keyword that comes to mind into a collaborative word cloud tool. Alternatively (or in parallel), they can write the word on a piece of paper, fold it, and place it in a pot at the knowledge station – the moderator will later enter the words into a corresponding tool for visualization.

In the third part, the participants should discuss the topics they have just been working on together. They can do this using the theses from training material 1. Alternatively, the participants can line up according to their position and be asked for their opinion. During the discussion, the moderator can, for example, create word clouds or prepare the station learning for the next part.

In the fourth part, participants work in pairs with a sheet of paper and walk through a small chamber of wonders of artificial intelligence. These are various stations or exhibits (working materials 5–11) where they can click through websites or tools of AI-based programs and marvel at what is already possible. In between, they should work on their own fictional AI on their sheet of paper and draw it or describe it with functions they have thought up themselves.

In the fifth part, the participants hang up the AIs they came up with in the fourth part in the room and look at each other’s work. Afterwards, the participants go through the reflection questions in training material 1 alone or together with the moderator.

Preparation

• The input in part 1 must be prepared by the moderator. Stories and sources can be found in training material 2.
• The individual knowledge stations (working materials 1–4) and later the exhibits (working materials 5–11) must be printed out, some of them cut out and, ideally, set up with sufficient space between them.
• For working materials 3 and 4 for the second part, flipcharts must be laid out for the tasks to be carried out.
• The tools in working materials 5–11 should be checked for availability/usability.
• For some exhibits, it is worth providing a device on which the relevant website is already open. The Lobe app (work material 11), in particular, is only available for desktop computers.

Notes on moderation

• The scope and presentation of the input can be adapted or omitted.
• The keywords to be collected at each station in the second part are optional and therefore not noted in work materials 1–4.
• The fourth part of the task is based on the Renaissance concept of the “Wunderkammer” (cabinet of curiosities). This was a type of exhibition in which people were supposed to develop an overall understanding of the world (at that time) through exhibits from science, art, and nature. In this task, the same can be transferred to the digital world–participants can learn through amazement, curiosities, and wonder. The individual stations can also be designed or decorated as small digital exhibitions.
• Some of the tools selected here are in English. However, they can be understood and tested even with little knowledge of English. The station “more AI stuff” (working material 11) is a collection of tools that require a little more knowledge of English. To avoid language barriers in the fourth part of the task, any potential language barriers should be announced and taken into account when dividing the groups.

Overview of knowledge stations (part 2)

• Station 1: What is the internet?
• Station 2: What are algorithms?
• Station 3: What is artificial intelligence?
• Station 4: How does machine learning work?

Overview of exhibits (part 4)

• Exhibit 1: Make a wish
• Exhibit 2: Beethoven’s unfinished symphony completed?
• Exhibit 3: Ghostwriting made easy
• Exhibit 4: That’s impossible
• Exhibit 5: Learn any language
• Exhibit 6: Image magnifier
• Exhibit 7: [en] More AI Stuff

Interesting sources

• [en] Vox has compiled 40 maps about the internet, which are not only useful examples for “Knowledge Station 1: What is the internet?” but also provide an understanding of the internet and its history. Some of the maps or the stories behind them can also be incorporated into the first part of the task, under “Thematic input.”
• https://www.vox.com/a/internet-maps
• The book “Atlas of AI” by Kate Crawford is particularly well suited for understanding how the manufacturing, operation, and maintenance processes of artificial intelligence work. It also provides clear information about the human labor and resource and environmental costs of these processes.