16. AI for Creative People

Course Positioning

This course treats AI as a creative collaborator, not a replacement for taste or voice. It covers idea generation, writing, image/video/audio workflows, character and worldbuilding, editing, content repurposing, creative direction, and IP/ethics.

Learning outcomes

Use AI to brainstorm, structure, draft, revise, and produce creative work across media.
Maintain a distinctive human voice while using AI for iteration and production support.
Create multimodal creative workflows involving text, images, video, audio, and social formats.
Understand copyright, consent, attribution, style imitation, and platform risks.
Build a personal creative AI system with prompt libraries and production checklists.

Expanded Topic-by-Topic Coverage

Module 1. AI as creative collaborator

Module focus: Ideation, divergent thinking, remixing, critique, iteration, creative control. Primary live activity or lab: Generate 20 ideas, then select and refine three using human criteria. Expected take-home output: Idea bank.

Topics and coverage

Ideation

What it means: define Ideation clearly and connect it to the module focus: Ideation, divergent thinking, remixing, critique, iteration, creative control.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

divergent thinking

What it means: define divergent thinking clearly and connect it to the module focus: Ideation, divergent thinking, remixing, critique, iteration, creative control.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

remixing

What it means: define remixing clearly and connect it to the module focus: Ideation, divergent thinking, remixing, critique, iteration, creative control.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

critique

What it means: define critique clearly and connect it to the module focus: Ideation, divergent thinking, remixing, critique, iteration, creative control.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

iteration

What it means: define iteration clearly and connect it to the module focus: Ideation, divergent thinking, remixing, critique, iteration, creative control.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

creative control

What it means: show where creative control appears in the learner's real workflow and which parts are judgment-heavy versus draftable.
What to cover: current workflow, pain points, AI-assisted steps, human review checkpoints, quality standard, and ownership of the final decision.
Demonstration: convert one messy real-world input into a structured brief, draft, analysis, checklist, or next action.
Evidence of learning: learners produce a reusable template or playbook entry that can be used after the course.

Practice and evidence of learning

Learners complete or discuss: Generate 20 ideas, then select and refine three using human criteria.
Learners produce: Idea bank.
Instructor checks for accuracy, practical usefulness, clear assumptions, appropriate human review, and fit with the course audience.
Learners revise once after feedback so the module contributes to the final project, portfolio, or playbook.

Minimum coverage before moving on

Learners can explain the module vocabulary without relying on tool-generated text.
Learners have seen one worked example, one hands-on application, and one limitation or failure case.
Learners know what must be verified, what data must be protected, and who remains accountable for the output.

Module 2. Voice, taste, and originality

Module focus: Personal style, reference boundaries, avoiding generic output, creative constraints. Primary live activity or lab: Create a personal style guide from original writing or creative examples. Expected take-home output: Creative voice guide.

Topics and coverage

Personal style

What it means: define Personal style clearly and connect it to the module focus: Personal style, reference boundaries, avoiding generic output, creative constraints.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

reference boundaries

What it means: define reference boundaries clearly and connect it to the module focus: Personal style, reference boundaries, avoiding generic output, creative constraints.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

avoiding generic output

What it means: define avoiding generic output clearly and connect it to the module focus: Personal style, reference boundaries, avoiding generic output, creative constraints.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

creative constraints

What it means: show where creative constraints appears in the learner's real workflow and which parts are judgment-heavy versus draftable.
What to cover: current workflow, pain points, AI-assisted steps, human review checkpoints, quality standard, and ownership of the final decision.
Demonstration: convert one messy real-world input into a structured brief, draft, analysis, checklist, or next action.
Evidence of learning: learners produce a reusable template or playbook entry that can be used after the course.

Practice and evidence of learning

Learners complete or discuss: Create a personal style guide from original writing or creative examples.
Learners produce: Creative voice guide.
Instructor checks for accuracy, practical usefulness, clear assumptions, appropriate human review, and fit with the course audience.
Learners revise once after feedback so the module contributes to the final project, portfolio, or playbook.

Minimum coverage before moving on

Learners can explain the module vocabulary without relying on tool-generated text.
Learners have seen one worked example, one hands-on application, and one limitation or failure case.
Learners know what must be verified, what data must be protected, and who remains accountable for the output.

Module 3. Writing workflows

Module focus: Hooks, outlines, scenes, dialogue, essays, scripts, newsletters, revisions. Primary live activity or lab: Develop a short script or essay through outline, draft, critique, revision. Expected take-home output: Writing artifact.

Topics and coverage

Hooks

What it means: define Hooks clearly and connect it to the module focus: Hooks, outlines, scenes, dialogue, essays, scripts, newsletters, revisions.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

outlines

What it means: define outlines clearly and connect it to the module focus: Hooks, outlines, scenes, dialogue, essays, scripts, newsletters, revisions.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

scenes

What it means: define scenes clearly and connect it to the module focus: Hooks, outlines, scenes, dialogue, essays, scripts, newsletters, revisions.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

dialogue

What it means: define dialogue clearly and connect it to the module focus: Hooks, outlines, scenes, dialogue, essays, scripts, newsletters, revisions.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

essays

What it means: define essays clearly and connect it to the module focus: Hooks, outlines, scenes, dialogue, essays, scripts, newsletters, revisions.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

scripts

What it means: define scripts clearly and connect it to the module focus: Hooks, outlines, scenes, dialogue, essays, scripts, newsletters, revisions.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

newsletters

What it means: define newsletters clearly and connect it to the module focus: Hooks, outlines, scenes, dialogue, essays, scripts, newsletters, revisions.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

revisions

What it means: define revisions clearly and connect it to the module focus: Hooks, outlines, scenes, dialogue, essays, scripts, newsletters, revisions.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

Practice and evidence of learning

Learners complete or discuss: Develop a short script or essay through outline, draft, critique, revision.
Learners produce: Writing artifact.
Instructor checks for accuracy, practical usefulness, clear assumptions, appropriate human review, and fit with the course audience.
Learners revise once after feedback so the module contributes to the final project, portfolio, or playbook.

Minimum coverage before moving on

Learners can explain the module vocabulary without relying on tool-generated text.
Learners have seen one worked example, one hands-on application, and one limitation or failure case.
Learners know what must be verified, what data must be protected, and who remains accountable for the output.

Module 4. Visual generation and art direction

Module focus: Prompting images, composition, characters, consistency, aspect ratios, editing, moodboards. Primary live activity or lab: Create a visual concept board for a story or campaign. Expected take-home output: Visual board.

Topics and coverage

Prompting images

What it means: explain how Prompting images changes the interaction between human intent, model behavior, external information, and final output.
What to cover: inputs, constraints, examples, output format, grounding, iteration, failure modes, and when a human must intervene.
Demonstration: show a weak attempt, a stronger structured attempt, and a reviewed final version with explicit checks.
Evidence of learning: learners create a reusable prompt, schema, retrieval note, or workflow pattern and test it on at least two examples.

composition

What it means: define composition clearly and connect it to the module focus: Prompting images, composition, characters, consistency, aspect ratios, editing, moodboards.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

characters

What it means: define characters clearly and connect it to the module focus: Prompting images, composition, characters, consistency, aspect ratios, editing, moodboards.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

consistency

What it means: define consistency clearly and connect it to the module focus: Prompting images, composition, characters, consistency, aspect ratios, editing, moodboards.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

aspect ratios

What it means: define aspect ratios clearly and connect it to the module focus: Prompting images, composition, characters, consistency, aspect ratios, editing, moodboards.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

editing

What it means: define editing clearly and connect it to the module focus: Prompting images, composition, characters, consistency, aspect ratios, editing, moodboards.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

moodboards

What it means: define moodboards clearly and connect it to the module focus: Prompting images, composition, characters, consistency, aspect ratios, editing, moodboards.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

Practice and evidence of learning

Learners complete or discuss: Create a visual concept board for a story or campaign.
Learners produce: Visual board.
Instructor checks for accuracy, practical usefulness, clear assumptions, appropriate human review, and fit with the course audience.
Learners revise once after feedback so the module contributes to the final project, portfolio, or playbook.

Minimum coverage before moving on

Learners can explain the module vocabulary without relying on tool-generated text.
Learners have seen one worked example, one hands-on application, and one limitation or failure case.
Learners know what must be verified, what data must be protected, and who remains accountable for the output.

Module 5. Video and audio workflows

Module focus: Shot lists, voiceover scripts, music briefs, editing plans, storyboards, synthetic media caveats. Primary live activity or lab: Create a 30-second video plan with prompts and storyboard. Expected take-home output: Video production plan.

Topics and coverage

Shot lists

What it means: define Shot lists clearly and connect it to the module focus: Shot lists, voiceover scripts, music briefs, editing plans, storyboards, synthetic media caveats.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

voiceover scripts

What it means: define voiceover scripts clearly and connect it to the module focus: Shot lists, voiceover scripts, music briefs, editing plans, storyboards, synthetic media caveats.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

music briefs

What it means: define music briefs clearly and connect it to the module focus: Shot lists, voiceover scripts, music briefs, editing plans, storyboards, synthetic media caveats.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

editing plans

What it means: define editing plans clearly and connect it to the module focus: Shot lists, voiceover scripts, music briefs, editing plans, storyboards, synthetic media caveats.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

storyboards

What it means: define storyboards clearly and connect it to the module focus: Shot lists, voiceover scripts, music briefs, editing plans, storyboards, synthetic media caveats.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

synthetic media caveats

What it means: define synthetic media caveats clearly and connect it to the module focus: Shot lists, voiceover scripts, music briefs, editing plans, storyboards, synthetic media caveats.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

Practice and evidence of learning

Learners complete or discuss: Create a 30-second video plan with prompts and storyboard.
Learners produce: Video production plan.
Instructor checks for accuracy, practical usefulness, clear assumptions, appropriate human review, and fit with the course audience.
Learners revise once after feedback so the module contributes to the final project, portfolio, or playbook.

Minimum coverage before moving on

Learners can explain the module vocabulary without relying on tool-generated text.
Learners have seen one worked example, one hands-on application, and one limitation or failure case.
Learners know what must be verified, what data must be protected, and who remains accountable for the output.

Module 6. Content repurposing

Module focus: Long-to-short, carousel, reels, newsletters, threads, scripts, community posts. Primary live activity or lab: Turn one idea into five formats. Expected take-home output: Repurposing pack.

Topics and coverage

Long-to-short

What it means: define Long-to-short clearly and connect it to the module focus: Long-to-short, carousel, reels, newsletters, threads, scripts, community posts.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

carousel

What it means: define carousel clearly and connect it to the module focus: Long-to-short, carousel, reels, newsletters, threads, scripts, community posts.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

reels

What it means: define reels clearly and connect it to the module focus: Long-to-short, carousel, reels, newsletters, threads, scripts, community posts.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

newsletters

What it means: define newsletters clearly and connect it to the module focus: Long-to-short, carousel, reels, newsletters, threads, scripts, community posts.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

threads

What it means: show where threads appears in the learner's real workflow and which parts are judgment-heavy versus draftable.
What to cover: current workflow, pain points, AI-assisted steps, human review checkpoints, quality standard, and ownership of the final decision.
Demonstration: convert one messy real-world input into a structured brief, draft, analysis, checklist, or next action.
Evidence of learning: learners produce a reusable template or playbook entry that can be used after the course.

scripts

What it means: define scripts clearly and connect it to the module focus: Long-to-short, carousel, reels, newsletters, threads, scripts, community posts.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

community posts

What it means: define community posts clearly and connect it to the module focus: Long-to-short, carousel, reels, newsletters, threads, scripts, community posts.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

Practice and evidence of learning

Learners complete or discuss: Turn one idea into five formats.
Learners produce: Repurposing pack.
Instructor checks for accuracy, practical usefulness, clear assumptions, appropriate human review, and fit with the course audience.
Learners revise once after feedback so the module contributes to the final project, portfolio, or playbook.

Minimum coverage before moving on

Learners can explain the module vocabulary without relying on tool-generated text.
Learners have seen one worked example, one hands-on application, and one limitation or failure case.
Learners know what must be verified, what data must be protected, and who remains accountable for the output.

Module 7. Creative critique and editing

Module focus: Feedback prompts, originality checks, emotional impact, pacing, clarity, audience fit. Primary live activity or lab: Use AI as editor, then accept/reject suggestions. Expected take-home output: Revision log.

Topics and coverage

Feedback prompts

What it means: explain how Feedback prompts changes the interaction between human intent, model behavior, external information, and final output.
What to cover: inputs, constraints, examples, output format, grounding, iteration, failure modes, and when a human must intervene.
Demonstration: show a weak attempt, a stronger structured attempt, and a reviewed final version with explicit checks.
Evidence of learning: learners create a reusable prompt, schema, retrieval note, or workflow pattern and test it on at least two examples.

originality checks

What it means: define originality checks clearly and connect it to the module focus: Feedback prompts, originality checks, emotional impact, pacing, clarity, audience fit.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

emotional impact

What it means: define emotional impact clearly and connect it to the module focus: Feedback prompts, originality checks, emotional impact, pacing, clarity, audience fit.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

pacing

What it means: define pacing clearly and connect it to the module focus: Feedback prompts, originality checks, emotional impact, pacing, clarity, audience fit.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

clarity

What it means: define clarity clearly and connect it to the module focus: Feedback prompts, originality checks, emotional impact, pacing, clarity, audience fit.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

audience fit

What it means: define audience fit clearly and connect it to the module focus: Feedback prompts, originality checks, emotional impact, pacing, clarity, audience fit.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

Practice and evidence of learning

Learners complete or discuss: Use AI as editor, then accept/reject suggestions.
Learners produce: Revision log.
Instructor checks for accuracy, practical usefulness, clear assumptions, appropriate human review, and fit with the course audience.
Learners revise once after feedback so the module contributes to the final project, portfolio, or playbook.

Minimum coverage before moving on

Learners can explain the module vocabulary without relying on tool-generated text.
Learners have seen one worked example, one hands-on application, and one limitation or failure case.
Learners know what must be verified, what data must be protected, and who remains accountable for the output.

Module 8. Rights, ethics, and monetization

Module focus: Copyright, likeness, voice cloning, fan art, derivative styles, disclosure, portfolios, client work. Primary live activity or lab: Create a personal AI ethics and usage statement. Expected take-home output: Creative AI policy.

Topics and coverage

Copyright

What it means: define Copyright clearly and connect it to the module focus: Copyright, likeness, voice cloning, fan art, derivative styles, disclosure, portfolios, client work.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

likeness

What it means: define likeness clearly and connect it to the module focus: Copyright, likeness, voice cloning, fan art, derivative styles, disclosure, portfolios, client work.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

voice cloning

What it means: define voice cloning clearly and connect it to the module focus: Copyright, likeness, voice cloning, fan art, derivative styles, disclosure, portfolios, client work.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

fan art

What it means: define fan art clearly and connect it to the module focus: Copyright, likeness, voice cloning, fan art, derivative styles, disclosure, portfolios, client work.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

derivative styles

What it means: define derivative styles clearly and connect it to the module focus: Copyright, likeness, voice cloning, fan art, derivative styles, disclosure, portfolios, client work.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

disclosure

What it means: define disclosure clearly and connect it to the module focus: Copyright, likeness, voice cloning, fan art, derivative styles, disclosure, portfolios, client work.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

portfolios

What it means: connect portfolios to the data lifecycle from source and structure through analysis, interpretation, and decision-making.
What to cover: source reliability, missing or biased data, leakage, assumptions, calculations, and the difference between correlation and decision-ready evidence.
Demonstration: walk through a small dataset or example table and mark the checks required before trusting the result.
Evidence of learning: learners produce a short analysis note that includes assumptions, limitations, and verification steps.

client work

What it means: define client work clearly and connect it to the module focus: Copyright, likeness, voice cloning, fan art, derivative styles, disclosure, portfolios, client work.
What to cover: the core concept, why it matters, what good usage looks like, and where learners are likely to misunderstand it.
Demonstration: give one simple example, one realistic example, and one failure or limitation example.
Evidence of learning: learners explain the topic in their own words and apply it to a small artifact or decision.

Practice and evidence of learning

Learners complete or discuss: Create a personal AI ethics and usage statement.
Learners produce: Creative AI policy.
Instructor checks for accuracy, practical usefulness, clear assumptions, appropriate human review, and fit with the course audience.
Learners revise once after feedback so the module contributes to the final project, portfolio, or playbook.

Minimum coverage before moving on

Learners can explain the module vocabulary without relying on tool-generated text.
Learners have seen one worked example, one hands-on application, and one limitation or failure case.
Learners know what must be verified, what data must be protected, and who remains accountable for the output.

Labs, projects, and assessments

Lab 1: Build a personal creative voice guide.
Lab 2: Produce a multimodal concept package: synopsis, moodboard, script, storyboard, and caption set.
Lab 3: Repurpose one long-form idea into five platform-specific outputs.
Capstone: Complete a small creative project with process notes showing human choices, AI assistance, revisions, and final rationale.

Evaluation approach

25% creative process journal.
25% multimodal concept package.
20% revision and critique quality.
30% final creative capstone.

Recommended tools and materials

AI assistant, image/video/audio generation tools, Canva/Figma, editing software, notes app, social scheduling tools.
Optional: voice tools, storyboard tools, music tools, scriptwriting software.

Safety, ethics, and governance emphasis

Avoid cloning real people's voices or likenesses without permission.
Be careful with living artists' distinctive styles and copyrighted characters.
Do not use AI to fabricate endorsements, testimonials, news footage, or deceptive personal stories.

Delivery notes

Use studio-style critique sessions.
The course should celebrate taste, constraints, and editing rather than one-click generation.

Instructor Build Checklist

Prepare one short demo for each module and one learner activity that creates a saved artifact.
Prepare examples that match the audience, local context, and likely tools learners can access.
Add a verification step to every AI-generated output: factual check, source check, data sensitivity check, and quality review.
Keep a running portfolio folder so each module contributes to the final project or learner playbook.
Reserve time for reflection on what the learner did, what AI did, what was checked, and what remains uncertain.