# NCAD AI for Artists Workshop

**Format:** Optional 4-hour Wednesday drop-in workshop, 15 weeks
**Audience:** NCAD students, mostly under 23, across motion design, illustration, UX, animation, graphic design, 3D, and video
**Core promise:** Learn how AI actually applies to creative work — without sacrificing artistic integrity.

---

## What This Course Is

This is **not** an "AI makes art for you" class.

It is a professional creative survival and leverage workshop. Students learn what AI tools genuinely do inside creative industries, where they fail, what they cost ethically, and how to use them (or deliberately refuse them) from a position of knowledge instead of fear.

**One-line version for posters and emails:**
> You don't have to like AI. You do have to understand the machine your industry is already using.

### Students WILL learn to use AI for

- **Research acceleration** — summarizing, comparing, mapping unfamiliar territory, finding the right questions.
- **Ideation width** — generating many directions fast, then exercising human taste to reject most of them.
- **Critique and simulation** — using a model as a hostile client, confused user, or extra pair of eyes.
- **Production planning** — briefs, shot lists, asset lists, schedules, specs, QA checklists.
- **Repetitive admin** — file naming, alt text, captions, transcripts, export checklists, versioning.
- **Portfolio and career support** — case-study drafting, CV tailoring, interview prep, outreach systems.
- **Tiny creative tools** — small coded utilities, generators, and site builds with AI coding assistants.
- **Agentic workflows** — multi-step automated processes with human checkpoints.

### Students will NOT be encouraged to

- Copy living artists' styles without consent.
- Hide AI use where disclosure matters (clients, competitions, assessment, portfolios).
- Submit raw model output as finished craft.
- Replace fundamentals (drawing, typography, motion principles, UX research, 3D craft) with shortcuts.
- Treat AI output as factual or authoritative without verification.

---

## Teaching Thesis

AI is becoming part of the creative industry stack the same way Photoshop, After Effects, and Figma did — except faster, messier, and with real ethical baggage attached.

The students who understand its **limits, ethics, and workflows** will have an advantage over students who either worship it or refuse to learn it.

**The message to skeptical artists:**
You do not need to let AI make your art. You do need to understand the machine that clients, studios, agencies, and competitors are already using — so that your choices about it are informed choices, not fearful ones.

**The message to enthusiastic students:**
Speed is not the skill. Taste, judgment, and accountability are the skill. AI raises the floor; your job is to raise the ceiling.

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## Who Shows Up (and How We Teach Them)

| Student | Arrives feeling | What the course gives them |
|---|---|---|
| The skeptic | Hostile, protective of craft | Honest treatment of ethics, consent, and labor; permission to refuse generation while still learning the landscape |
| The anxious | "Will I have a job?" | Concrete evidence of what AI can't do, plus leverage skills that compound their existing craft |
| The enthusiast | Already generating everything | Standards, taste training, disclosure habits, and the gap between output and authorship |
| The overwhelmed | Curious but lost | One structure, repeated 15 times: context → demo → lab → reflection. Chunked handouts they can revisit |

Every week works for all four. Nobody is ever required to generate images to participate — planning, critique, and documentation tracks always exist.

---

## Learning Outcomes

By the end of the 15 weeks, a participating student can:

1. **Explain** what LLMs, diffusion models, and agents actually are, in plain language, including their characteristic failure modes (hallucination, genericness, bias, continuity breaks).
2. **Brief** an AI system the way a creative director briefs a junior: context, references, constraints, output format, critique criteria.
3. **Operate** an iteration loop — generate, reject, select, refine — while documenting the human decisions that shaped the result.
4. **Apply** AI to their own discipline's pipeline (motion, illustration, UX, animation, graphic design, 3D, video) at the planning, production-support, and post stages.
5. **Build** at least one tiny tool or automated workflow that removes friction from their real practice.
6. **Judge** when AI use requires disclosure, and write honest, specific disclosure language for portfolios, clients, and competitions.
7. **Defend** an articulated personal boundary: what they will use AI for, what they won't, and why.

---

## The 15-Week Arc

The arc moves from literacy → craft-specific application → systems → synthesis.

| Wk | Title | Phase |
|---|---|---|
| 1 | AI Without the Ick: Literacy, Integrity, and Creative Control | Literacy |
| 2 | Prompting Like an Art Director: Briefs, References, and Critique Loops | Literacy |
| 3 | Research, Moodboards, and Concept Development Without Copying | Literacy |
| 4 | Image Generation and Editing for Illustration, Design, and Previs | Craft |
| 5 | Motion Design: Boards, Style Frames, Scripts, and Production Assistants | Craft |
| 6 | Animation and Story: Characters, Worlds, Continuity, and Previsualization | Craft |
| 7 | Graphic Design and Branding: Systems, Layouts, Copy, and Production | Craft |
| 8 | UX and Product Design: Research, Flows, Wireframes, and Prototypes | Craft |
| 9 | 3D Workflows: Modeling Support, Materials, Scenes, and Render Planning | Craft |
| 10 | Audio, Voice, Video, and Multimodal Critique | Craft |
| 11 | Coding for Artists: Websites, Tools, and Tiny Apps with Codex/Claude Code | Systems |
| 12 | Agentic Workflows: Automating the Boring Parts Without Losing Control | Systems |
| 13 | Jobs, Portfolios, Freelance, and Creative Career Leverage | Synthesis |
| 14 | Capstone Sprint: Build a Personal AI-Enhanced Creative Workflow | Synthesis |
| 15 | Demo Day, Future-Proofing, and the Artist's AI Operating System | Synthesis |

**Drop-in rule:** every week stands alone. Weeks 1–3 build the shared vocabulary, but each later session opens with a 5-minute integrity-framework recap so a first-timer can participate fully.

---

## Class Rhythm (every week)

1. **Context** (50 min) — what the technology is and why it matters to working artists.
2. **Demo** (45 min) — instructor shows a real workflow, including the failures.
3. **Lab** (70 min) — students try a constrained activity with per-track variants.
4. **Reflection** (45 min) — share, critique, and document: what AI did, what the human did, where integrity lives.

Breaks every ~50 minutes. Full timing in `TEACHING_GUIDE_MASTER.md`.

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## Weekly Deliverables (the artifact trail)

Each session ends with a concrete artifact a student keeps even if they never return:

| Wk | Deliverable |
|---|---|
| 1 | Personal AI Use Manifesto v1 (8–12 bullets) |
| 2 | AI-ready creative brief + track-specific critique rubric |
| 3 | Mini concept board, source list, 150-word direction statement |
| 4 | Process board: 6+ iterations with written selection notes |
| 5 | 15-second motion treatment pack |
| 6 | One-scene animation packet |
| 7 | Mini brand sheet: positioning, voice, type/colour rationale, asset checklist |
| 8 | Task flow + low-fi wireframe + critique checklist |
| 9 | 3D scene plan + one AI-assisted script/checklist |
| 10 | Captioned clip/still critique packet + prioritized edit list |
| 11 | Tiny tool spec: user, problem, inputs, outputs, UI sketch, build prompt |
| 12 | Agent workflow spec with steps, tools, risks, human checkpoints |
| 13 | Improved case-study/CV section + job-search prompt pack |
| 14 | Capstone draft + 1-page process explanation |
| 15 | Final capstone + AI Use Manifesto v2 + personal tool tracker |

Together these become a **process portfolio**: evidence of skill that survives any individual tool dying.

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## Access and Equity

**Recommended:** ChatGPT Plus or Claude Pro (~€20+VAT/month tier). One paid frontier-model account covers most weeks.
**Optional:** Claude Code or Codex access for students interested in Weeks 11–12 coding/agentic content.

**Nobody is excluded for not paying:**

- Free tiers of ChatGPT, Claude, and Gemini handle most lab activities (with rate limits).
- Labs are designed for pair/team work — one account per pair is enough.
- Instructor demos cover paid-tool-only features; students watch, then apply the pattern in free tools.
- Every lab has a **zero-generation track**: planning, critique, and documentation workflows that need only a text model or paper.
- When generation limits hit mid-lab, students switch to the critique/documentation track — which is half the lesson anyway.

Details in `TOOLS_AND_ACCESS_JUNE_2026.md`.

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## Integrity Framework (course spine)

The full pact is in `STUDENT_AI_INTEGRITY_PACT.md`. The short version, repeated weekly:

- **AI for friction, humans for meaning.** Use AI on the parts that aren't your art: summaries, variants, checklists, scaffolds.
- **Raw output is raw material.** Nothing ships unedited.
- **Disclose where it matters.** Portfolios, clients, competitions, assessment.
- **Verify before you trust.** Models are confident, not correct.
- **Consent matters.** No cloning living artists, classmates, or anyone's voice/face without permission.

**The question students learn to ask:** *Am I using this to deepen my work, or to avoid doing the work?*

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## Assessment (drop-in mode vs. credited class)

**Drop-in mode (current):** no grading. The deliverable artifact + reflection is the proof of learning. Attendance any week is rewarding on its own.

**If run as a credited class (future):** see `ADMIN_OBSERVATION_BRIEF.md` for the proposed assessment scheme — process portfolio (40%), capstone (35%), critique participation (15%), integrity/disclosure practice (10%). No grade ever depends on the aesthetic quality of raw AI output.

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## Document Map (for instructors and admins)

| Document | What it's for |
|---|---|
| `COURSE_OVERVIEW.md` | This file — course position, arc, outcomes |
| `TEACHING_GUIDE_MASTER.md` | How to run any session: voice, timing, facilitation, accessibility, substitute orientation |
| `TOOLS_AND_ACCESS_JUNE_2026.md` | Current tool landscape, accounts, fallbacks, classroom policy |
| `STUDENT_AI_INTEGRITY_PACT.md` | Student-facing ethics agreement + disclosure templates |
| `GLOSSARY.md` | Course-wide glossary, creative-practice definitions |
| `DEMOS_AND_VISUAL_AIDS.md` | Every weekly demo: exact prompts, what to show, what to notice |
| `ADMIN_OBSERVATION_BRIEF.md` | Dean/admin-facing: rationale, outcomes, assessment, observation guide |
| `PREP_WITH_CODEX_AND_CLAUDE_CODE.md` | Instructor prep backlog for building demo artifacts |
| `PRODUCTION_NOTES.md` | Build status, PDF regeneration, link verification |
| `weekly/week-XX/` | Per-week handout, instructor guide, slide source |
| `site/` | Student-facing reference site + HTML slide decks |
| `templates/` | Reusable briefs, specs, disclosure language |