In May 2023, the Writers Guild of America went on strike — the biggest Hollywood work stoppage in 15 years. One of the central demands was protection from AI tools like ChatGPT being used to generate or revise scripts. Studios wanted the right to use AI drafts and pay human writers only to "polish" them. Writers said that would destroy the profession. The strike lasted 148 days and ended in September 2023 with new contract language that restricted AI use — the first labor agreement in any major industry to directly address generative AI.
The WGA strike wasn't about robots writing movies on their own. It was about economics: if a studio can pay AI to produce a first draft and hire one writer instead of five, fewer writers earn a living. This is the real question behind "will AI replace jobs?" — not whether AI is as good as a human, but whether it is good enough to reduce how many humans get paid.
The answer depends on the job. Some creative roles are already being reshaped. Getty Images reported in 2023 that sales of stock photography declined significantly as AI image generators became widely available. Shutterstock and Adobe Stock both introduced AI generation tools directly into their platforms, acknowledging the shift. Meanwhile, game studios, film VFX houses, and advertising agencies all began publicly experimenting with AI pipelines.
But new roles are also appearing. Prompt engineers, AI art directors, and AI music supervisors are job titles that did not exist five years ago. The McKinsey Global Institute's 2023 report on generative AI estimated that while certain creative tasks face automation pressure, the demand for workers who can direct, evaluate, and refine AI outputs is growing.
This is not the first time a new tool disrupted creative work. When photography was invented in 1839, painters feared extinction. What actually happened: portrait painting declined, but landscape painting, abstract art, and fine art photography all expanded. The total number of people making a living from visual creativity grew. When digital audio workstations arrived in the 1990s, record labels predicted chaos. Instead, independent music production exploded — millions of artists now release music who could never have afforded a recording studio.
The pattern is consistent: new tools lower barriers, change who can participate, and shift which specific skills are valued — but rarely eliminate the underlying human desire to create and to experience creative work made by other humans.
What does change, and change permanently, is the shape of the workforce. Skills that were once rare (like hand-retouching a photograph) become less valuable. Skills that were once inaccessible (like composing orchestral music) become learnable. The people who thrive are those who learn the new tools quickly while keeping the distinctly human skills that AI struggles with: original perspective, cultural context, emotional nuance, and ethical judgment.
If you are 14 years old today, you will enter the workforce around 2030. That is close enough that the AI tools being built right now will absolutely affect your career — but far enough away that the landscape will look quite different from today. Learning to work with AI creatively is not optional for your generation. The question is whether you approach it with curiosity and skill, or let it catch you unprepared.
You are going to have a real conversation about what creative careers might look like when you're ready to enter the workforce. Think about a creative field you're genuinely interested in — music, writing, film, game design, visual art, fashion, architecture, or anything else — and explore how AI might change it.
This lab is designed for students ages 12–18. The AI will speak plainly, use real examples, and help you think critically — not tell you what to think.
In February 2023, the US Copyright Office issued a ruling on Zarya of the Dawn, a graphic novel by Kristina Kashtanova. The Office had originally granted copyright for the entire work. After review, it partially withdrew that protection — the text and the arrangement of images remained copyrighted, but the individual AI-generated images (made with Midjourney) were not protected by copyright. The ruling stated that copyright requires "human authorship" and that works produced by AI without human creative control do not qualify. This was the first major US government ruling on AI art and copyright.
The US Copyright Office's position as of 2024 is that AI-generated content by itself cannot be copyrighted. But content where a human made significant creative choices — selecting, arranging, editing, or substantially directing the AI — can receive some protection. The line between "significant creative control" and "pushing a button" is still being argued in courts and regulatory hearings around the world.
In the UK, the law actually goes further in one direction: computer-generated works can be copyrighted, with the copyright going to "the person who makes the arrangements" for the generation — which would often be the company that built the AI, not the user. Japan has signaled it may not protect AI-generated works at all. The result is a patchwork of rules that is still being written.
For young creators, this matters because every platform you publish on has its own policies built on top of these laws. Spotify, YouTube, Instagram, and Wattpad all have terms of service around AI-generated content, and those terms change frequently. A song or story that's allowed today may be flagged or removed tomorrow as policies tighten.
There's a second dimension to the ownership question: the training data. AI image generators like Midjourney, Stable Diffusion, and DALL-E were trained on billions of images scraped from the internet — including copyrighted work by professional artists, photographers, and illustrators, most of whom were not asked permission and received no compensation.
In January 2023, a class-action lawsuit was filed in California by artists including Sarah Andersen, Kelly McKernan, and Karla Ortiz against Stability AI, Midjourney, and DeviantArt, alleging copyright infringement through training data scraping. Getty Images filed a separate suit against Stability AI in both US and UK courts. As of 2024, these cases were still working through the legal system — their outcomes will shape how AI companies are allowed to train future models.
Some companies have responded proactively. Adobe Firefly was trained exclusively on Adobe Stock images, licensed content, and public domain works — and Adobe pays contributors whose work was included. Shutterstock has created a contributor compensation fund for artists whose images were used in training. These models show that ethical training is possible; the question is whether it becomes standard or remains the exception.
Beyond law, there's an ethical question: when AI assists heavily in making something, should the creator disclose that? Many platforms are now requiring disclosure (YouTube, for example, mandates labeling of AI-generated content in news, electoral, and certain entertainment contexts). The creative community is divided — some see full disclosure as always necessary for honesty; others argue that all art uses tools, and the level of AI involvement exists on a spectrum, not a binary.
Creative ownership gets complicated fast when AI is involved. In this lab you'll talk through real-feeling scenarios with the AI and develop your own reasoned position — not just repeat back what you were told.
These scenarios are designed to be genuinely difficult, like real creative and legal situations are. There are often no perfect answers, just better and worse reasoning.
In April 2023, a track called "Heart on My Sleeve" went viral on TikTok and Spotify — it used AI-cloned voices of Drake and The Weeknd to create a convincingly real-sounding song that neither artist had anything to do with. Universal Music Group had it removed and sent a letter to streaming platforms demanding action against AI voice cloning. The incident reignited debate: if AI can clone a voice perfectly, what does a singer actually offer that is irreplaceable? The answer that emerged from musicians, psychologists, and audiences was surprisingly consistent: lived experience, authenticity, and presence — knowing that a real person felt these things, made these choices, and put themselves into the work.
This is not a feel-good claim. There are specific, documented ways that AI creative tools fall short — things that matter to audiences and clients:
Original perspective from lived experience. AI generates content by recombining existing patterns. It has no childhood, no heartbreak, no specific cultural neighborhood, no particular body. The aspects of creative work that resonate most deeply are usually the ones that feel specific and true — and that specificity comes from actual human experience. Photographer Nan Goldin's 1986 photo book The Ballad of Sexual Dependency documents her own circle of friends and her own trauma. That specificity is unreplicable by AI because the experience itself was irreplaceable.
Accountability and stakes. When a human creator puts their name on something, they take a risk. That risk creates a relationship with the audience. When AI produces something offensive, confusing, or harmful, there's no one to hold responsible in the same way. Audiences understand this distinction intuitively, which is partly why AI-generated news, medical information, and public statements feel different from human-authored ones.
Cultural participation and community. Art is not just a product — it's participation in a community and a conversation. When Kendrick Lamar released "Not Like Us" in 2024, the meaning came from knowing who was involved in the dispute, what it meant culturally, and who was responding to whom. AI cannot be in a community, cannot have genuine disputes, cannot participate in history as a subject. It can only describe it.
Ethical judgment in context. AI models can follow rules, but they don't have genuine values. When a human director decides not to make a war scene graphically violent because of how it might affect audiences who have experienced real violence, that is a moral judgment rooted in empathy. AI cannot make that judgment — it requires a human to set the parameters and take responsibility.
Research by the National Endowment for the Arts and by education scholars studying AI's impact on creative learning points to a consistent set of skills that remain distinctly human and are worth developing deliberately:
Specificity of observation. The ability to notice precise, true details about the world — what a room actually smells like, how a specific person moves, what a particular afternoon in a specific city in a particular decade felt like. AI averages. Humans who observe specifically stand out.
Ethical reasoning under ambiguity. Creative decisions constantly involve tradeoffs — what to show, what to omit, who might be hurt, who might be helped. Developing the habit of thinking through these questions carefully is not just good ethics; it's a professional skill that clients and employers increasingly value as AI takes on more production work.
Collaboration and communication. AI tools are increasingly team members in creative workflows. Knowing how to direct them, evaluate their outputs, communicate your vision to human collaborators, and navigate disagreement is crucial. These are skills you develop through practice — in school projects, in clubs, in any creative work done with other people.
Taste and curation. The flood of AI-generated content makes the ability to choose well more valuable, not less. An editor who can identify the one outstanding piece in ten thousand mediocre ones, a music supervisor who knows exactly which song belongs in a scene — these curatorial skills are premium skills in an age of abundance.
You are building your creative identity at exactly the moment when it matters most to be intentional about it. The experiences you have now — the music you make in your bedroom, the stories you write for yourself, the photos you take of your actual life — are building the specific perspective that no AI can replicate. Don't shortcut that process. Use AI as a tool, but don't outsource the experience of being yourself.
This lab is a guided self-reflection. You'll work with the AI to identify the specific experiences, observations, and perspectives that make your creative voice distinctly yours — things that AI could never generate because they're about your actual life.
This isn't about being better than AI. It's about knowing what you bring to the table that no tool can replace.
In 2023, Adobe partnered with the College Board to integrate AI literacy into AP Art and Design curricula across American high schools — the first time a major standardized curriculum explicitly addressed AI tools as part of creative education. In parallel, organizations like Khan Academy launched Khanmigo, an AI tutor, while the MIT Media Lab released free AI creative tools specifically designed for middle and high school students. The message from major educational institutions was clear: AI fluency is now considered a foundational creative skill, not an advanced specialty.
AI fluency is not the same as knowing how to code. For creative careers, it means being able to use AI tools as part of a creative workflow, evaluate their outputs critically, understand their limitations, and make decisions about when and how to use them. The analogy is to photo editing: a professional photographer today doesn't need to understand the code behind Lightroom, but they absolutely need to know how to use it and — crucially — when not to use a particular filter.
Adobe's 2023 State of Creativity report found that 83% of creative professionals expected to use generative AI tools regularly within two years. Among creative directors (the people who hire), the top skills they said they would prioritize were: AI tool proficiency, critical evaluation of AI outputs, and the ability to brief AI effectively — a skill that looks a lot like writing, directing, and communication.
The practical implication: if you can write a precise, evocative creative brief, you can direct an AI. If you can evaluate a piece of writing or art with genuine critical thinking, you can evaluate AI output. These are skills you can develop right now, in school, in creative projects, and in clubs.
Make things without AI first. The most important thing you can do in the next few years is build a deep library of creative work made primarily from your own imagination, observation, and skill. This is not about purity — it's about building a foundation. Composers who understand music theory can use AI tools in more sophisticated ways than those who skip straight to generation. Writers who have wrestled with structure and voice can direct AI text tools with clarity and judgment.
Document your process, not just your output. In 2024, many art schools and universities began requiring process documentation for portfolios — showing your thinking, your drafts, your decisions — partly in response to AI. A portfolio that shows how you think is impossible to fake and impossible for AI to produce on your behalf. Build that habit now.
Stay curious about the tools without being captured by them. Explore AI tools, experiment, see what they can and can't do. But notice when you're using them to avoid the hard, slow work of developing your own skills. AI can produce a passable first draft of almost anything instantly — which means it can also stop you from doing the thing that actually builds your capability.
Find your community. The creative careers that survive and thrive in an AI world will be the ones embedded in real human communities — the local scene, the specific subculture, the particular audience. Communities can't be automated. Build yours now.
Nobody knows exactly what creative careers will look like in 2035. Anyone who says they do is overconfident. What we can say honestly: the need for human creativity, perspective, and community will not disappear. The tools will keep changing. The people who do well will be those who stayed curious, kept making things, kept developing their own voice, and learned to use new tools without losing themselves in them. That's not a new challenge — it's the challenge every generation of creators has faced.
This is the final lab of the entire course. You're going to work with the AI to build a specific, actionable plan for your creative development over the next 3–5 years — one that takes AI seriously as a tool you'll use, while putting your own voice, skills, and community at the center.
The AI will ask you real questions, push you to be specific, and help you think through tradeoffs. This is not a school assignment exercise — it's meant to produce something you could actually use.