One month before I submitted the final edits for the last chapter of this book, I received an email from my literary agent.

The Creativity Leap, my very first solely authored book, had been identified as one of the works scraped by Anthropic in the class action lawsuit Bartz v. Anthropic. My ideas, the frameworks I spent years developing, the writing I had poured into those pages, had been ingested into a commercial AI system. Without my knowledge, my consent or without compensation.

I submitted a claim form. And then I kept writing.

I want to be clear about why. Not because the situation didn’t bother me, but because my response to it is not to reject AI as a tool. Rather, it is to insist on a distinction that I think is at the center of the most important conversation we are not quite having: the difference between using AI as a partner in creative expansion and using it as a mechanism for creative extraction. The former is alchemy, and the latter is exploitation. The difference between them is entirely a question of ethics, intention, and to what we are accountable.

I call this the ethics of ease.

THE PART NOBODY WANTS TO SAY OUT LOUD

Technological ease is genuinely seductive. The conversation about AI ethics has a tendency to flatten into either uncritical enthusiasm or reflexive alarm, and neither of those positions is useful.

AI tools are extraordinary. With just a few keystrokes, I can synthesize a research summary that once would have taken me days. I can generate a first draft based on a verbal download on my Otter app, visualize a new framework, or prototype a course structure based on a chapter in one of my books in the time it used to take me to clear my desk and make a cup of tea! I use these tools regularly. I am not interested in performing ambivalence about them.

But here is the thing we must remember: every leap in technological convenience carries an ethical echo. The question is not only what we can make with AI, but also how we make it, and at whose expense. When we pursue ease without asking that second question, we quietly hollow out the conditions that make creative work meaningful and fair.

This is where the WonderRigor™ model I write about throughout The Creativity Leap becomes something more than an innovation framework. Applied to AI ethics, it asks two questions simultaneously. Wonder asks: what could this make possible? Rigor asks: at what cost? You cannot skip either question. Wonder without rigor becomes exploitation. And rigor without wonder becomes paralysis. The creative sweet spot, the alchemy, is what happens when you hold both in the balance.

WHAT THE REGULATORS ARE SEEING

The legal and policy community is arriving at similar conclusions, and more quickly than you might expect.

The US Copyright Office’s 2025 report on copyright and AI draws a direct line: the largescale commercial use of copyrighted creative works to produce competing content goes beyond what established fair use protections allow. The report calls for licensing frameworks, for structures that make it possible to innovate and to compensate the people whose work makes that innovation possible. This is rigor at work, the necessary discipline that keeps creative acceleration from becoming creative appropriation.

The Harvard Law Review published an essay in 2025 that named something I think many creators feel but struggle to articulate: the creative double bind. There is a simultaneous desire to embrace what AI makes possible and a fear of being replaced by it, a fear made more acute by the knowledge that your own creative work may already be training the systems you are being asked to compete with. That is not paranoia, it’s a structurally accurate description of how many writers, designers, musicians, and thinkers are currently positioned.

And then there was the Christie’s art auction, which became a genuine flashpoint. When the auction house announced an AI-driven sale, artists called it mass theft. A spokesperson responded by saying that in most cases the algorithms had been trained on the artists’ own inputs. If you want to understand why that response deepened rather than resolved the outrage, sit with it for a moment. The implicit argument was: we used your creative work to build a system that now competes with you, and that should be fine because it was your work we used. That is not a reassurance, it’s actually the problem.

THE TRAINING DATA ARE HUMAN BEINGS

I keep coming back to a statement from artist Elly Mambounou, writing for the Copyright Alliance in 2025: that “the irreplaceable value of human creativity cannot be automated.”

What strikes me about that sentence is the word irreplaceable. It’s easy to lose sight of what’s unique in a moment when AI can produce something that looks, at a glance, like creative work. The something it produces has been assembled from the patterns of human creative work. For example, the novels someone wrote through a decade of early mornings; or the photographs a person spent a lifetime learning to see.

So the call for licensing, transparency, and consent is not, as some critics frame it, a demand to slow innovation, it’s a demand to sustain dignity. The creative economy has human beings at its foundation, and that any framework for AI development that ignores those people is building on an unstable and ethically indefensible base.

This matters for business leaders, not just artists and advocates. The organizations that will be trusted in the years ahead are not the ones that moved fastest. They are the ones that moved with integrity. Coca-Cola CEO James Quincey made this point when he observed at the 2025 Adobe summit I attended that consumers want to be the protagonists of their own stories. What he was really saying is that authenticity is not a marketing strategy. It is a prerequisite for trust. In an era where AI-generated content is everywhere. Trust is the scarcest and most valuable thing a brand can possess.

WHAT I TRY TO ASK MYSELF

I want to share the test I apply to my own use of AI, because I think it is practical and it might be useful.

When I am using an AI tool, I try to ask: is this accelerating my thinking, or replacing it? Is it helping me develop and organize ideas I have already generated, or is it generating ideas that I am then adopting as my own? Is it serving my creative judgment, or have I quietly allowed it to substitute for my own discernment?

The distinction is not always clean. There is genuine ambiguity in a lot of AI-assisted creative work, and I think that ambiguity is worth sitting with rather than resolving too quickly in either direction. What I try to stay alert to are the moments when I cannot answer those questions, because those are usually the moments when I need to slow down and pay closer attention.

For organizations, I think the equivalent practice is having an explicit conversation about where the human line sits: which decisions require human discernment, not because AI cannot produce an output, but because the stakes, the relational complexity, or the ethical weight demand a human being in the loop? That conversation is not a bureaucratic exercise. It is a creative one. It requires imagining what good work actually looks like, and then having the discipline to protect that standard even when a faster option is available.

It also means building the reciprocal structures this moment requires: Licensing frameworks for creators whose work trains AI systems; Attribution practices that acknowledge human origins; Transparency about when and how AI has been used. These are not obstacles to innovation, they are the conditions under which innovation becomes sustainable and trustworthy.

EASE CAN BE EARNED

I want to end where I started, with my own book sitting inside a class action lawsuit, and with the fact that I kept writing anyway.

I kept writing because I believe in the alchemy that is possible when human creativity and AI collaborate honestly and ethically. I kept writing because the answer to extraction is accountability and the insistence that wonder—the wild, expansive, generative capacity to imagine what could be—must always be paired with rigor, the discipline to ask at what cost, for whom, and toward what end.

Technology’s promise is efficiency. Creativity’s purpose is meaning. When those two things come apart, we do not just lose the ethical plot, we lose the thing that made the work worth doing in the first place.

Ease can be elegant, but only when it is earned. And in this moment, earning it means being willing to train with rigor and learn the fundamentals; to ask the harder questions; to slow down with wonder at the moments when speed is most tempting, and to treat the humans whose imagination made all of this possible not as training data but as the ultimate point.

About the Author

Natalie Nixon is a creativity strategist and president of Figure 8 Thinking. She advises and emboldens leaders to transform their businesses through creativity and foresight. She is a regular contributor to Inc., Fast Company, Katie Couric Media, and SHE Media and the editor of the book Strategic Design Thinking. Nixon’s global speaking roster includes TEDxPhilly, the Fast Company Innovation Festival, and the Mayo Clinic’s Transform conference, and her corporate clients include Kraft Heinz and Paycor. She holds a doctorate in design management, a master’s in global textile marketing, and a bachelor’s (cum laude) in anthropology and Africana studies. In 2024, she received the Architecture of Innovation award and was named one of the Thinkers50 Radar.