edge literacy · module 21

Video Games

The algorithm wants you to play more, not get better. Can you see the difference?

Video games, netcode, and behavioral algorithms

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Core

Video games combine technology, social life, flow, business and behavioral design. Here you compare your real playing experience against the netcode, the matchmaking and the systems that govern invisible conditions of play.

Practice debt: a game that plays itself is no game at all, and the same goes for skill. If you let AI analyze the game before you have written about your own experience, you borrow convenience and mortgage your own understanding of the game. Start with your own, then amplify it.

Before you startBefore you start: the human anchor is about your thinking, not spelling, presentation or a perfect result. You may use dictation or speech-to-text if that suits you better, and it is fine to make mistakes. Choose an example you feel comfortable sharing. In the algorithmic pivot, you may use any AI tool; a free account is enough and you do not need a subscription.

Human Anchor

Write the first part of the project without AI. The goal is to create a human benchmark that can later be compared with algorithmic analysis. The text should be personal, grounded in your own experience, and detailed enough so that AI cannot simply replace it with a generic summary.

Choose a video game you know well. Write 1,000–1,200 words about flow, community, difficulty, frustration, the feeling of victory, unfairness, and what keeps you coming back. Do not use AI in this part.

Scope

  • 1,000 words minimum, unless the teacher decides on a shorter test version.
  • No AI, no automated rewriting, and no machine translation.
  • Use your own examples, your own words, and express clear uncertainty where it exists.

Include This

  • What you know or think before AI is introduced to the task.
  • What experience, memory, physical observation, or local knowledge shapes your perspective.
  • Which three questions you want the AI to challenge in the next step.

Assessment

The teacher does not assess whether the text is perfect. They assess whether the human voice, the student's own judgment, and real context are clear enough to hold up against algorithmic output later in the project.

Algorithmic Pivot

Have the AI break the game down into two systemic components: netcode and latency on the one hand, matchmaking and retention on the other. Ask it to explain tick rate, client-side prediction, SBMM, EOMM, churn, and loot or reward loops.

Fyrirspurn til gervigreindar

This is a ready-made frame to use in Step 2. It disciplines the AI by giving it a role, a task, constraints and verification questions, instead of a free-form chat. Copy it, try it, and adapt it to your own project.

Role
You are a critical assistant in the Tækniseigla category Video Games. You are to expand the student's analysis without taking the responsibility away from them.
Task
Analyze the technical and behavioral architecture of a video game with respect to the student's experience.
Constraints
  • Distinguish verified technical documentation from speculation about secret matchmaking systems.
  • Compare the AI output with your own experience and official sources.
  • Show both what makes the game good and what can rob autonomy.
Verification questions
3 verification questions are included in the copied prompt. You answer them in step 3.

Fiduciary Anchor

The accountability document is the final gate of the project. Here you show that you can use AI without hiding behind it. All claims that survive in the final product require verification, a clear disclaimer, or a conscious rejection.

Compare the technical analysis with your own gaming experience and public data, patents, or technical documentation if available. Where is the game designed as a challenge, and where is it designed as a trap for autonomy?

1. AI Process

Record which tool was used, which prompts were tested, what changed between versions, and which parts of the output first seemed convincing.

2. Verification

Use at least three independent pillars depending on the nature of the project: a primary source, official data, an academic source, your own calculation, physical testing, expert evaluation, or comparison with human experience.

3. Errors and Blind Spots

Answer these questions:

  • What part of the experience is explained by netcode or latency?
  • What part might be retention design rather than pure gameplay?
  • Where does your own experience correct the AI's technical narrative?

4. Rejection

Name at least two points that you reject from the AI output. Explain whether they were incorrect, unproven, ethically weak, too general, or simply not in line with your human anchor.

5. Accountability Statement

Conclude with a brief statement in the first person: what you take responsibility for, what you do not yet know, and what decision you would not delegate to AI.

Now it is your turn. The exercise is the bridge between step 2 and step 3.

Go to exercise

For teachers, competency line: Edge literacy

That is the whole module: anchor, pivot, accountability. The work itself happens off this page.

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