My Associations with AI

When you hear the term 'AI', which software, platform or service do you immediately think of? In order to start a more systematic and less affirmative discussion about AI, we need to set aside current trends in the media and public opinion. This approach helps us to start the debate and analysis of the broad field of AI applications in our society, moving beyond image and chatbots. First, the possibilities of sociometric constellations are explored. Next, questions relating to the various fields of AI application are examined in greater depth.

Goals

Understand the breadth of AI applications in society and reflect on the social relevance and impact of technology.
Strengthen analytical skills

Steps

1. Sociometry

When you hear AI – what software, platform, or service do you immediately think of?

Participants are asked to share their associations aloud. Example: Participant 1: 'ChatGPT.' Anyone else who thought of ChatGPT is asked to stand beside them.

Gradually, a sociometric cluster of familiar applications or forms of AI emerges.

Sociometry

A method to visualize social information spatially by creating living infographics with the participants' bodies.

Sociometry

2. Landscape of AI systems

At present, many people would probably answer "ChatGPT" or "image-generating AI". However, to discuss AI regulation, we need to broaden our perspective. The facilitator places cards on the floor, each representing a different kind of AI system. If participants are not familiar with them, the facilitator briefly describes each one.

Examples for AI systems in the society

Curating the newsfeed in social media
Social media monitoring
Creditworthiness and reputation scoring
Job applications
Managing platform workers
Monitoring performance during work
Mood tracking (in example in schools)
Camera surveillance of elderly people at risk of falling at home
Camera systems in shopping centres
Electricity and heating meters
License plate recognition, e.g., on highways
Control of smartphone cameras
…

A trainer then asks what other systems the participants can think of and adds new cards.

3. Transfer

We tend to first think of AI that we experience directly as users. But most of the largest and most powerful systems operate in the background. We do not perceive them as users, but we are affected by their consequences.

Some parents, for example, have not received credit from a bank because their creditworthiness was poorly assessed by a system. Or the camera in a shopping centre focuses on young people because, unlike the majority, they move around less purposefully and often in groups. When we think of a smartphone camera, we often don’t realise that it is largely controlled by AI (and works differently from earlier digital cameras).

Extension

Young people position themselves in relation to specific systems they would like to discuss in more depth or learn more about. Then work on exploration of these systems in smaller groups.

Handbook: More than Go with the Flow

A handbook on Digital Citizenship Education, created in the frame of the project DIYW-ROAD/Competendo. Digital Youth Work - rights-sensitive, open, accessible, democratic.
Unless otherwise stated, authors and editors of the methods published in the project are Elisa Rapetti, Markus José Plasencia Kanzler, and Nils-Eyk Zimmermann