Learning objectives
After this exercise, you will be able to:
- identify the AI systems in your own everyday life, including the invisible ones;
- classify them as mechanical, thinking, or feeling AI;
- locate them in the AI value chain and estimate which company or national ecosystem they depend on;
- reflect on how dependent you are on these tools, and how much you actually know about them.
What you need to know
| Tool | Categories |
| Type of AI (Huang & Rust, 2021) | Mechanical: routine, repetitive tasks. Thinking: processing data to decide or personalize. Feeling: recognizing and responding to emotions. Many systems blend types. |
| AI value chain ecosystem | Upstream: chips, data centers, cloud (e.g., Nvidia, TSMC). Midstream: foundation models (e.g., OpenAI, Google DeepMind, Anthropic, DeepSeek, Alibaba’s Qwen). Downstream: apps and services you use. Ecosystem: US, China, European or unknown |
| Confidence | Know: you have evidence (e.g., the app names its AI provider). Guess: an informed inference. Unknown: you cannot tell. |
| Dependency on AI tools | How hard would this activity be without AI? Low, Medium, or High. |
Roles (groups of four)
- Facilitator: keeps the group moving and makes sure everyone contributes.
- Recorder: fills in the group table (Answer Sheet, Part B).
- Timekeeper: watches the clock (about one minute per item).
- Reporter: presents the group’s results if called on (up to 5 minutes).
Steps and timing (60 minutes)
| Time | Step | What to do |
| 10 min | 1. Individual inventory | Alone, list every point of contact with an AI-driven system in the past 48 hours — or the AI products and services you used, each with its main function. Aim for at least eight items (Part A). Think of: keyboard and autocorrect, recommendations, navigation, customer-service chats, photo/voice/face recognition, writing or translation tools, spam filters, chatbots. |
| 20 min | 2. Group coding | In groups of four, combine your lists into at least 16 items. Code each item in Part B: type, value-chain layer, ecosystem, confidence, and dependency. Then choose one item that surprised you and one that concerns you (privacy, labor, bias, dependency, or another reason). |
| 20 min | 3. Plenary | Three groups report (up to 5 minutes each): one surprising item, one concerning item, and your pattern of know/guess/unknown. |
| 10 min | 4. Synthesis and reflection | Discuss the case questions (Handout 1) as a class; then write your individual reflection sentence (Part D). |
Deliverable
Each group hands in its completed answer sheet (Parts B and C; minimum 16 coded items). Each student keeps their reflection sentence (Part D) for Session 2.
Discussion questions
- Which areas of your daily life are most AI-saturated?
- Which companies or countries’ ecosystems recur most often — and how sure are you?
- Where is your dependency on AI tools highest, and does that concern you?