The Creative Professional's Housewife Intellectual Guide to AI
A four-course certificate where foundational AI concepts meet creative practice, critical equity frameworks, and the messy, real work of building something worth keeping, all without a technical prerequisite.
Colab · p5.js · Teachable Machine · Computational Creativity · New Media · AI Ethics · Your Creative Career
"This certificate integrates foundational AI literacy for creative professionals with critical equity scholarship and hands-on creative practice. Whether you're a faculty developer, a creative entrepreneur, or both, it meets you where you are."
Running Thread Across All Four Courses
Building Your Personal AI System
Each course deposits one layer of your permanent, evolving toolkit for working with AI in creative and professional contexts.
Course 1 Deposit
Your Creative AI Toolkit
What You BuildA curated set of AI tools tested against your own creative practice, with documented use cases, known limitations, and personal workflows. Your "go-to stack" for generating text, visuals, and sound.
Course 2 Deposit
Your Critical Evaluation Framework
What You BuildA personal rubric for assessing any new AI tool: Who built this? Who benefits? Whose data trained it? What does it misrepresent? A framework that travels with you as tools change.
Course 3 Deposit
Your Ethical Design Practice
What You BuildA documented design methodology for AI-assisted projects, including stakeholder empathy processes, ethics checkpoints, and a template for communicating the business and social value of your work.
Course 4 Deposit
Your Staying-Current Protocol
What You BuildA personal system for monitoring the AI landscape: curated sources, a tool-assessment checklist, a community of practice, and a decision tree for when to adopt, wait, or reject a new tool.
The Full Curriculum
Four Courses. One Arc.
Zero Generic Syllabi.
Course One · Getting Creative
Getting Creative With AI
Computational creativity, paper coils, and why expert systems are not as smart as they sound.
Creative Professional Integration
This course opens with the foundational question from the integrated creative professional curriculum: What does it mean to be a creative when AI is competing for your work? Before touching a single tool, students examine their own creative practice as a baseline and define what AI can and cannot replicate about it.
You already know that making something by hand is a form of thinking. Every coil you fold for allmyquills.com is a decision-tree, a spatial algorithm, a meditation in iteration. This course asks: what happens when you let AI do the looping?
Course One builds your foundational AI toolkit through creative experimentation. No prerequisites, no gatekeeping. You will use Google Colab to generate text and images, p5.js to code generative visuals that mirror the mathematics of spiraling paper, and Teachable Machine to train models on things you can actually see and touch.
Every tool you touch gets interrogated through two questions: What is this actually doing? and What is this worth to my creative work or organization?
Estimated Course Cost: $0–25. Colab, p5.js, and Teachable Machine are free.
Weekly Breakdown
Week 1
What Is AI, Actually? And What Does It Want From You?
Distinguish between expert systems and machine learning. Trace computational creativity from the 1950s to now. Inventory your own creative practice.
Try This: Map your quilling process as a decision tree. Where would an expert system fail? Where might machine learning succeed?
Week 2
Your AI Origin Story: First Experiments in Colab
Run your first text generation notebook in Google Colab. Ask the model to write about paper quilling, then critique what it gets wrong. Understand prompting as a creative and technical skill.
Try This: Generate 10 descriptions of your signature quilling style. Keep the one that's weirdly accurate. Analyze why the others missed.
Week 3
The Coil as Code: p5.js for Visual Thinkers
Fibonacci spirals, Archimedean coils, and the mathematics of quilling all translate to p5.js. Write short sketches that generate the visual patterns you already make by hand.
Try This: Recreate your most complex quilling piece as a generative sketch and write a 200-word artist's note on what the code cannot do.
Week 4
Teachable Machine: You Are the Training Data
Train a custom image classifier using images you provide. Explore what the model learns and what it misses entirely. Reflect on yourself as both designer and data.
Try This: Train a model on two categories of your own work, then test it on work you've never shown it. Document the failure modes.
Week 5
Sound, Text, and the Multimodal Creative Experiment
Use AI to generate audio, text, and visuals. Combine all three in a short experimental new media piece. What counts as yours?
Try This: Prompt an AI to write a "Spilled and Studied" post. Annotate every place it sounds nothing like you. That list is your brand differentiation document.
Week 6
Assessing Opportunity: The Business Case for Your AI Toolkit
Evaluate the tools you've tried through a business and creative career lens. Which tools save you time without costing you voice? Build the first version of your Personal AI Toolkit document.
Try This: Write a one-page "AI Business Case" for allmyquills.com: where would AI add value, where would it undermine your premium positioning?
✦ Signature Assignment
"The Quill-Gorithm" Portfolio + Toolkit v1
Create a three-part creative portfolio: (1) a p5.js sketch inspired by your signature quilling form with an artistic research statement; (2) a Teachable Machine model trained on your own images with a written analysis of its accuracy and gaps; and (3) a short multimodal new media piece combining AI-generated text, visuals, and audio. Alongside these, submit Toolkit v1: a two-page personal document cataloging the AI tools you tested, their real costs, their creative and business applications, and your honest assessment of each.
Course Two · Power & Problems
Creating With Generative AI: Power and Problems
Multidisciplinary history, manufactured authenticity, and the receipts buried in the training data.
Creative Professional Integration
AI did not emerge from one field, one country, or one tradition. Understanding that history is not academic nicety: it is the foundation for making smart decisions about which tools to trust with your creative work and your organization.
Your Fulbright research examined how hip hop and digital culture support global citizenship. That lens is exactly what this course needs. Generative AI was built on scraped internet data, which means it was built on every bias, every erasure, every overrepresentation that already existed online.
This course interrogates opportunities and limitations of AI for creative work with honest specificity. Not "AI is great" or "AI is dangerous" but: for this kind of creative work, in this context, here is what AI can and cannot be trusted to do.
The "Spilled and Studied" framework gets formalized here: manufactured personas on reality television mirror the manufactured authenticity of large language models in ways that are analytically useful and deeply personal.
Estimated Course Cost: $0. All auditing work uses free tool tiers.
Weekly Breakdown
Week 1
Before the Bot: A Multidisciplinary History of AI
From the Jacquard loom to ELIZA to GPT-4, trace how AI development drew from mathematics, philosophy, linguistics, art, and the military. Read Safiya Umoja Noble alongside the timeline.
Try This: Find one AI origin story that centers a non-Western innovator or creative practitioner. What did that research require of you?
Week 2
The Training Data Problem (It's Political, and It's About Your Work)
Where does AI training data come from, who it includes, and how it shapes what AI can imagine as creative work. Use a bias audit framework to test an image generator.
Try This: Prompt an image AI to generate "a professional artist," "a creative director," and "a designer." Analyze the implicit aesthetic and demographic assumptions.
Week 3
Opportunities and Limitations: An Honest Accounting
For three specific creative use cases (copywriting, illustration, and sound design), map what AI genuinely accelerates, what it flattens, and what it cannot do.
Try This: Interview one creative professional about their actual AI experience. Separate the marketing language from the operational reality.
Week 4
Spilled and Studied: Pop Culture as Critical AI Lens
Formalize your intellectual framework. Manufactured personas on reality TV and manufactured outputs of LLMs share a structure. Workshop the "Spilled and Studied" analytical method as a publishable intellectual contribution.
Try This: Write a tight 600-word Substack post connecting a specific Real Housewives moment to a specific AI limitation.
Week 5
Hip Hop, Remix Culture, and the Debt Generative AI Owes
Generative AI is a remix engine built on content it did not pay for. Hip hop negotiated authorship, sampling, and credit for decades before this debate existed.
Try This: Map hip hop's legal battles over sampling to current AI copyright lawsuits. Identify the structural parallels and the key legal gaps.
Week 6
From Critique to Framework: Your Critical Evaluation Rubric
Synthesize your critical analyses into a personal evaluation framework you can apply to any new AI tool. Address: historical accountability, representational equity, creative opportunity, organizational risk. This becomes Toolkit v2.
Try This: Apply your completed framework to one AI tool you currently use. Write a one-page brief as if recommending (or not) its adoption to your organization.
✦ Signature Assignment
"The Spilled and Studied AI Audit" + Toolkit v2
Choose one generative AI tool and conduct a 1,200-word equity and opportunity audit informed by at least two critical frameworks. Include historical context, bias documentation, creative opportunity, and limitations. Publish as a "Spilled and Studied" Substack post. Submit Toolkit v2: your personal AI critical evaluation framework as a reusable one-page template.
Course Three · Ethical Design
Co-Creating With AI: Ethical Tools for Design Innovation
Design Thinking, CliftonStrengths, and the business of communicating the value of work that matters.
Creative Professional Integration
Design Thinking is the methodology, but the real skill being built is persuasion: how do you help a client, a dean, or a community understand what your AI-assisted work is worth, why your judgment matters, and why the ethical commitments embedded in your process are a feature, not a constraint?
You've been building the Luddy AI Teaching Lab, designing Teach and Learn sessions, creating facilitation guides for faculty who are terrified of their students' AI fluency. This course hands you the formal scaffolding for what you've already been doing intuitively.
Design Thinking maps beautifully onto your CliftonStrengths coaching practice. Empathy interviews mirror strengths-based coaching conversations. Prototyping mirrors iterative curriculum design.
The ethical innovation lens asks: what does it mean to build with AI when the people you're designing for didn't get to vote on AI entering their organizations?
Estimated Course Cost: $25–50. Prototyping may involve one paid tool subscription.
Weekly Breakdown
Week 1
Empathize: Whose Problem Are We Actually Solving?
Conduct three empathy interviews with real stakeholders about their AI experiences. Notice how CliftonStrengths coaching conversations and empathy interviews use the same muscle.
Try This: Interview a Luddy faculty member skeptical of AI in teaching. Map their concern using both design thinking language and Fink's Significant Learning framework.
Week 2
Define: The Problem Worth Solving (and the Business Case)
From your interview data, synthesize a "How Might We" question. Then write the business case: why does solving this problem matter to the organization, the client, or the community?
Try This: Write three HMW statements for your AI curriculum integration challenge at Luddy. For each, write one sentence of ethical justification and one of institutional value.
Week 3
Ideate: AI-Assisted Brainstorming, With Appropriate Skepticism
Use AI tools to expand your ideation canvas, then critically evaluate what the AI included, excluded, and defaulted to. Practice using AI as a thought partner that needs supervision.
Try This: Ask an AI to brainstorm solutions to your HMW question. Identify the three ideas that feel most culturally grounded. Ask why the AI didn't center those without prompting.
Week 4
Prototype: Build Something You Can Actually Test
Build a low-fidelity prototype of your AI-assisted design. The constraint: it must include at least one AI component and at least one explicit ethics checkpoint users encounter during use.
Try This: Prototype the opening session of your Luddy AI Teaching Lab. Map what a participant does, thinks, and feels in the first 20 minutes.
Week 5
Test, Iterate, and Document: Feedback Is Data
Run your prototype with real users and gather structured feedback. Treat critique as data. Iterate at least twice. Document what changed and why.
Try This: Run your prototype with one enthusiastic and one skeptical participant. Map where their experiences diverged. Use the divergence to make your design more robust.
Week 6
Communicate Value: Presenting Ethical AI Design to the People Who Hold the Budget
Translate your design process into a persuasive presentation for a non-technical audience. How do you communicate that your ethical commitments increase, not decrease, the value of your work?
Try This: Write a 200-word executive summary as if pitching to the Dean of Luddy. No jargon. One clear recommendation. One value proposition. One sentence on why the ethical framing is a competitive advantage.
✦ Signature Assignment
"The Luddy Lab Prototype" + Business Value Brief + Toolkit v3
Design, prototype, test, and iterate an ethical AI-assisted intervention for a real stakeholder community. Deliverables include an empathy research summary, design process journal, working prototype, user testing documentation, 1,500-word design rationale, and a one-page Business Value Brief. Present to a live audience of at least three people. Submit Toolkit v3: a reusable ethical design process template with embedded ethics checkpoints.
Course Four · Synthetic Identities
Developing and Detecting Synthetic Identities With Generative AI
Staying current, detecting the artificial, and building the system that keeps you ahead of a landscape that never stops changing.
Creative Professional Integration
This course treats staying current as a system design problem. By the end, you will have a repeatable, personal protocol for staying informed, evaluating new tools, and making decisions that protect your creative practice, your clients, and the people who trust your work.
This is the capstone course, designed for someone who has been thinking about performed authenticity since their first episode of Real Housewives. You've been studying synthetic identity for years. You just didn't call it that.
Course Four is where the critical framework from Course Two, the creative tools from Course One, and the design practice from Course Three converge into your most sophisticated, most public, and most durable work.
The capstone project sits at the intersection of your Substack brand, your scholarly identity, and your role at Luddy. It asks: in a world where the line between real and synthetic is increasingly a design choice, what is your system for navigating it?
Estimated Course Cost: $25–50. Total certificate cost stays within $75–100.
Weekly Breakdown
Week 1
What Even Is a Synthetic Identity?
Define "synthetic identity" across three registers: legal (fraud), technical (AI generation), and cultural (performed persona). Use Real Housewives as your primary case study.
Try This: Apply all three synthetic identity definitions to one Housewife's arc across multiple seasons. Write a 400-word analysis. This is publishable. Treat it that way.
Week 2
The Detection Toolkit: Seeing What the Machine Made
Survey text detectors, image forensics tools, and video analysis frameworks. Test them rigorously and document their failure modes.
Try This: Run the same text through five different AI detectors. What does the variance tell you about the epistemological reliability of these tools as institutional gatekeepers?
Week 3
Deepfakes, Docu-fakes, and the Ethics of Synthetic Storytelling
Examine synthetic media in documentary journalism, creative campaigns, and political communication. Where does creative license end and harmful deception begin?
Try This: Find three examples of synthetic media in storytelling: one clearly creative, one ambiguous, one clearly harmful. Write the principles you used to categorize them.
Week 4
Social Trust and the Epistemics of AI Content
When you cannot reliably tell what is real, how do you make decisions? Explore the epistemological stakes for democratic discourse, academic integrity, and creative industry trust.
Try This: Design a one-question instrument that measures a student's epistemic confidence about AI-generated content. Test it on three people.
Week 5
Creating Synthetic Media Ethically: A Practice, Not a Paradox
Develop a personal set of ethical principles for creating synthetic media. Then actually create something: a clearly-labeled synthetic persona with full transparency documentation.
Try This: Create a clearly-labeled AI persona that could guest-post on your "Spilled and Studied" Substack. Write the transparency disclosure. Make it as interesting as the content.
Week 6
Staying Current: Building the Protocol That Outlasts This Course
Design your personal system for monitoring the AI landscape after the certificate ends. Curate sources, build your tool-assessment checklist, identify your community of practice.
Try This: Set up your staying-current infrastructure today: one newsletter, one community, one weekly check-in practice, one person you'll call when something confusing happens.
Week 7–8
Capstone: Advocacy, Authorship, and the Integrated AI System
Produce your capstone deliverables. Compile your complete Personal AI Toolkit. Write your capstone essay and Substack companion. Present to a live audience.
Try This: Write the abstract for a conference paper connecting synthetic identity detection to authentic assessment in computing education. Submit it somewhere real.
✦ Capstone Assignment
"Real or Not Real" + Complete Personal AI System
Two-part capstone. Part 1: a 2,000-word scholarly-accessible essay connecting synthetic identity theory to computing education practice, with a companion "Spilled and Studied" Substack post and a detection appendix of at least three annotated examples. Part 2: your complete Personal AI System, compiled from all four Toolkit versions into a single polished professional document. This is the document you hand to a collaborator, a hiring committee, or a grant reviewer.
Integrated Certificate Learning Outcomes
What You'll Walk Away With
Both tracks, fully integrated. The scholarly depth of the certificate and the practical fluency of the creative professional curriculum, inseparable by design.
AI Literacy and Creative Practice
Fluency in foundational AI concepts, including expert systems, machine learning, and generative AI, explained in plain language through your own creative practice.
A working portfolio of AI creative experiments: a p5.js generative sketch, a custom Teachable Machine model, and a multimodal new media piece rooted in artistic research methods.
A multidisciplinary understanding of AI's history across fields including mathematics, cognitive science, creative arts, and global cultural contexts.
Hands-on experience with AI detection tools, synthetic media analysis, and a nuanced understanding of why detection is always a moving target.
A capstone essay and public Substack companion piece that bridge your scholarly identity and your Housewife Intellectual brand at the highest level of your voice.
Conference-ready materials connecting synthetic identity detection to authentic assessment in computing education, grounded in your SIGCSE grant research.
Creative Career and Professional Development
A tested, iterated prototype of an ethical AI-assisted intervention for a real stakeholder community, with full documentation and a business value brief ready for institutional audiences.
A published equity audit using your "Spilled and Studied" framework, documenting both bias and genuine opportunity in a real generative AI system.
The ability to evaluate and communicate the business and organizational value of AI-assisted creative work to non-technical decision-makers, clients, and funders.
A complete Personal AI System: four integrated toolkit documents covering your creative toolkit, critical evaluation framework, ethical design practice, and staying-current protocol.
A repeatable system for monitoring the AI landscape, evaluating new tools against your own frameworks, and making informed adoption decisions as the field continues to change.
The confidence and the receipts to walk into any room at Luddy, any creative industry context, or any public intellectual space and speak to AI with nuance, rigor, and your signature flair.