GenAI & MT Acknowledgement

This page documents how I used Generative AI and Machine Translation (MT) to support my A2 Design Research, how I ensured personal authorship, and what I learned. It follows the course’s Responsible Use Framework.

1) Transparency Log

Where and how GenAI/MT helped in my workflow:

  • Idea scaffolding: brainstorming page section headings (Accessibility, Ethics, GenAI) and card-based layouts.
  • Code review (front-end): checking navbar accessibility (ARIA states, keyboard activation, Escape to close) and focus styles.
  • Copy clarity checks: simplifying sentences to ~Year 8–9 reading level and removing jargon.
  • Prompted summaries: turning lecture/brief points into concise bullets I then edited for accuracy and tone.
  • MT: light EN↔ES phrasing checks for my notes; all public page text is authored/edited by me in English.

2) My Authorship & Decision-Making

What is mine vs. what was tool-assisted:

Area
My Contributions
Tool Assistance
Final Ownership
HTML structure
Page hierarchy, sections, headings, content flow
Got examples for card/grid patterns
I authored and edited all code
CSS components
Variables, focus states, responsive tweaks
Requested suggestions for small polish
I implemented and tested
Navbar JS
Chose ARIA behavior and keyboard support
Reviewed sample patterns for edge cases
I reviewed and integrated
Ethics content
Identified harms, mapped to ACS values, chose options
Prompted for structure ideas (cards/table)
I wrote final copy and rationale

3) Responsible Use Guardrails

  • Accuracy & integrity: I verified AI suggestions against the client brief, lectures, and WCAG references; I rewrote anything off-target.
  • Privacy: No personal or sensitive data entered into tools; all examples are generic or anonymised.
  • Learning focus: I used AI to accelerate ideation and checks, not to replace my own reasoning, coding, or decisions.
  • Attribution: This page documents all tool assistance; code/comments retain my authorship.

4) Effectiveness

  • Helpful: catching small accessibility gaps (skip link, focus states), structuring content into simple cards, and editing for plain language.
  • Less helpful: generic WCAG or ethics statements without context; I replaced these with specifics from my design.
  • Time: quicker first drafts, but I still needed review cycles to ensure accuracy and fit for the brief.

5) Limitations & Next Steps

  • Limitations: AI can be over-confident and context-blind; it won’t know course-specific expectations unless I restate them.
  • Next steps: add automated checks (e.g., linting) and manual keyboard testing; keep a small prompt library tailored to A2/A3.
  • Reflection plan: note where AI helped or hindered in my reflection log to improve prompts and reduce rework.

6) Acknowledgement Statement

I used Generative AI to brainstorm structure, review accessibility patterns, and clarify wording. I verified all outputs against course materials and the client brief, and I authored the final code and content. This submission reflects my learning, judgement, and design decisions.