A.1.2: Case Study Topic Area #2: Responsibility & AI
The Divergence Artefact
Note: This outline provides guidance specific to Case Study #1, complementing the general case study rubric [link].
The Prompt
Create something using Generative AI — visual, written, computational, or hybrid — but do not simply accept what the AI gives you.
Your task is to demonstrate deliberate human judgement and agency by identifying the model’s defaults, pushing beyond them, and making consequential decisions about what should be accepted, changed, rejected, or created differently.
The central question is:
Where does the machine’s contribution end, and yours begin?
1. What did the AI want to give you?
Identify the model’s default response or path of least resistance.
• What patterns appeared repeatedly?
• What seemed generic, average, conventional, or expected?
• What assumptions did the model appear to make for you?
2. What did you make it give you instead?
Document where you deliberately redirected, rejected, modified, or overrode the machine.
• What choices did you make?
• Why did you make them?
• What changed because of your intervention?
Your goal is not simply to improve the output.
Your goal is to demonstrate meaningful divergence from the model’s default.
3. What risks did you navigate?
Identify at least two meaningful risks encountered through the development of your work.
These may include:
- Legal — copyright, intellectual property, ownership, liability
- Regulatory — institutional rules, platform policies, terms of use
- Moral / Ethical — harm, deception, manipulation, misrepresentation
- Creative — convergence, mediocrity, imitation, loss of authorship or voice
Do not simply list risks.
Explain where they arose, what decision they required from you, and how you responded.
4. Where is the line?
Identify specific moments where the relationship between human and machine contribution becomes visible.
Ask:
• What came directly from the AI?
• What did you select, reject, combine, transform, or reinterpret?
• Which decisions required judgement that the AI could not make for you?
• Who should ultimately be responsible for the resulting artefact?
Your analysis should reveal one key insight about responsibility, authorship, or human agency when working with Generative AI.
What a Strong Submission Demonstrates
A strong submission will:
- Identify the default behaviour of the AI
- Demonstrate clear moments of human intervention and divergence
- Document the decisions and reasoning behind those interventions
- Identify meaningful risks and responsibilities
- Make the boundary between human and machine contribution legible
- Use evidence from the process rather than relying only on the final output
Your work should demonstrate judgement, agency, and critical responsibility.
Deliverables
Your submission is built around a central artefact, which forms the backbone of the case study and provides the evidence from which your abstract, slides, video, and poster are constructed.
The Artefact — Divergence & Evidence
The artefact is the primary object of investigation in this case study.
It may be visual, written, computational, or hybrid, depending on what best allows you to investigate responsibility and human agency in Generative AI.
Examples might include:
• An image or visual composition
• A piece of writing
• A designed object or proposal
• A website or interactive experience
• A computational or generative experiment
• A sequence of outputs or transformations
• Another appropriate creative or analytical form
The artefact should not simply demonstrate that you can produce something with AI.
It should provide evidence of how you made decisions while working with AI.
Your artefact and supporting documentation should make visible:
• Default
– What did the AI want to give you?
– Document the default, the average, or the path of least resistance.
• Divergence
– What did you make it give you instead?
– Show where you pushed, redirected, rejected, combined, or overrode the AI.
• Risk & Decision
– What risks did you navigate?
– Identify at least two legal, regulatory, ethical, or creative risks.
– Show what decisions these risks required from you.
• Human–Machine Boundary
– Where is the line?
– Identify specific moments where the AI’s contribution ends and your judgement begins.
Use evidence from your process to support these claims.
This might include:
• Prompts and responses
• Screenshots or transcripts
• Initial and revised outputs
• Rejected alternatives
• Comparisons
• Annotations
• Diagrams of your process
• Evidence of editing, selection, combination, or transformation
• Other documentation of moments of friction, resistance, or divergence
Include at least one clear example of friction or divergence where you did not accept the machine’s initial direction.
Each piece of evidence should be carefully selected and captioned to explain what happened, what decision you made, and why it matters.
i. Abstract
Provide a concise written abstraction of no more than 300 words.
Distil the artefact’s central question, your approach, the key moment of divergence, the risks or responsibilities examined, and your principal insight about human agency when working with AI.
ii. Slides
Develop a sequence of portrait-format slides that uses your artefact and supporting evidence to construct a clear visual story.
The sequence should make the progression from AI default → human intervention → divergence → responsibility legible.
iii. Video
Develop a short-form video presentation of no more than 90 seconds using your slides and artefact as its visual foundation.
Use the video to connect the strongest evidence and communicate your central argument about choice, divergence, and responsibility.
iv. Poster
Bring the strongest elements of your artefact and evidence together into a complete A2-format poster.
The poster should function as a self-contained visual argument, making the AI default, your intervention, the resulting divergence, and your principal insight clearly legible.
Grading Criteria
In a nutshell
We are not grading:
- Polish
- Technical sophistication
- “Correct” use of AI
We are grading:
| Criterion | What It Means |
|---|---|
| Deliberateness | Did you make meaningful choices, or did you accept defaults? |
| Awareness | Can you identify and articulate the risks and responsibilities you navigated? |
| Divergence | Is there evidence that the work required meaningful human intervention? |
| Honesty | Are you clear about the respective contributions of the AI and yourself? |
Rubric
| Criterion | Excellent | Adequate | Insufficient |
|---|---|---|---|
| Deliberateness | Clear, specific choices are documented with convincing rationale | Some choices are documented, but reasoning is limited | Defaults are largely accepted with little evidence of deliberate choice |
| Risk Awareness | Multiple meaningful risks are identified and connected to specific decisions | Relevant risks are identified but treated superficially | Little or no meaningful consideration of risk |
| Divergence | Clear evidence of intervention, resistance, or transformation that materially changes the work | Some divergence from AI defaults is demonstrated | Artefact remains largely indistinguishable from uncritical AI output |
| Honesty | Human and AI contributions are clearly and precisely distinguished | Roles are generally identifiable but boundaries remain partly unclear | Human–AI boundary is unclear or obscured |
The Standard
The goal is not to use AI well.
The goal is to demonstrate judgement in deciding when to accept it, challenge it, or override it.
Do not simply present the final output.
Make your choices, risks, interventions, and responsibility visible.
Don’t let the machine make every decision for you.
Prove you are not redundant.