Purpose: Deliver a long, analytical blog post on Jon M. Chu’s WIRED Big Interview remarks about Wicked, creativity, representation, marketing, and artificial intelligence — showing what makes art beautiful in the AI era and asking the right questions to move the conversation forward.
Interrupt — Engage: Stop scrolling. Think about a single human wink that changed a film. Why did that wink matter? That small, unscripted moment says more about cinema’s value than a room full of algorithms ever will. How will you defend the human creative moments that make art beautiful? How will we measure value when tools can fake likeness but not lived truth?
Why Jon M. Chu’s take matters
Jon M. Chu has steered major films and culture-shifting projects for years. His work on Wicked did not arrive overnight; it was the product of more than five years of work, complex choices, and real consequences. He links the film to his family’s immigrant story, and that link is not decorative. It shapes how he frames representation and why certain details matter on screen. When Chu speaks about craft, commerce, or technology, listen. He brings both the filmmaker’s toolbox and the immigrant’s vantage point — practical know-how plus moral clarity.
Marketing: the story begins before release and keeps going
Chu is blunt about how modern blockbusters run: the story circulates long before the premiere and keeps evolving after opening weekend. Viral moments, influencer traction, podcasts, and carefully staged press appearances are now as much part of the film’s lifecycle as the editing room. He’s watched this play out since early social platforms such as MySpace and Twitter changed audience connection points. The practical lesson: promotion is not a sideline. It’s part of the creative architecture.
Ask yourself: where does storytelling end and promotion begin? How do you hold on to craft while you fight for attention across platforms? Chu’s method is to treat both tasks as creative problems to solve, not compromises to accept.
Why casting and human chemistry beat tick-box optics
Chu faced backlash: split the film into two parts and you’re a “money grabber”; cast Ariana Grande and Cynthia Erivo and you’ll split fandoms. He heard it all. Yet he made choices in the audition room and trusted what he saw. The emotional intensity between Grande and Erivo on tour comes from a rare production condition: both films shot together. The cast lived the entire arc — joy, fallout, grief — before anyone saw it. That shared process created authentic bonds and spontaneous moments. Those spontaneous moments — a wink, an unscripted beat, a look — are the human creative moments Chu keeps pointing to. They are unpredictable. They are not reproducible by a generative model.
Mirroring that idea: unpredictable human moments. Unpredictable human moments. Those are the difference-makers that make art beautiful.
Representation: show, don’t argue
Chu chose concrete action over endless debate. He cast people who bring lived reality to roles: Cynthia Erivo as Elphaba, Michelle Yeoh as Madame Morrible, the first wheelchair user as Nessarose, Latino artists across the world of the film. He framed representation as a production decision, not a press-release talking point. When the film works at the box office, the market evidence speaks. That’s social proof by design: make diverse stories and the audience will show up. If audiences reject the choice, that’s useful data. If they accept it, the debate ends.
Ask: how do you turn moral conviction about representation into production choices that prove the point in the marketplace?
AI in filmmaking: a nuanced stance, not a manifesto
Chu refuses a headline-ready stance that simply applauds or rejects AI. He says the label “AI” is too broad to carry meaningful debate. He separates tools: autocorrect, recommendation algorithms, and generative systems that can fabricate images, voices, or scripts. He warns about unethical mining of images and stories without permission or compensation. That’s a rights issue and a values issue. He’s open to tools that help craft a film, while protecting the unexpected human creative moments that give a film its soul.
Consider this: a generative model can stitch a frame, but it cannot invent the accidental wink on a crowded set, or the split-second improvisation that shifts an actor’s performance. Those human creative moments are emergent, social, and embodied. They arise when hundreds of people react in real time to each other on a set. Can a model simulate that? It can mimic, but mimicry is not the same as origin.
Ethics, rights, and the market test
Chu asks the right political question: what will society value? He suggests artists and audiences will choose. But the profession must shape those choices with clear rules: consent, fair compensation, and attribution. If an algorithm uses someone’s face or a creator’s art without permission, that’s theft dressed up as progress. Say “No” to unchecked mining of creators’ work. Say “Yes” to tools that assist a craft under fair rules.
Try this thought experiment: which costs more — a generative replacement that captures a likeness, or a living performer bringing a real, risky, unreproducible moment? Box office and cultural traction provide one metric. Moral legitimacy and long-term trust provide another. Which currency do you want to spend?
Concrete examples from Wicked: why small moments matter
Chu tells a simple story: Cynthia Erivo winks while putting on a cape. That wink travels beyond the frame. It becomes shorthand for character, for rebellion, for connection. That wink was not planned; it happened because a living actor made a tiny choice. Replicating that decision with a synthetic tool misses the provenance. The audience senses authenticity. Authenticity breeds attachment. Attachment drives cultural conversation and box office returns. That’s the causal chain Chu keeps returning to.
Negotiation moves applied to filmmaking decisions
Let’s borrow a negotiation trick from Chris Voss and apply it to studio decisions: ask calibrated, open-ended questions. “How can we use AI to cut costs without losing the human creative moments audiences care about?” That question forces the studio to think in constraints rather than slogans. Use mirroring when stakeholders push for blanket automation: repeat back their phrase — “cut costs” — and ask, “cut costs how?” That invites specificity and keeps the conversation grounded.
Also, preserve the power of “No.” A director or producer saying “No” to a technology that erases performers’ agency protects leverage. Saying “No” isn’t obstruction; it’s a bargaining chip that clarifies priorities. Who will bear the moral and economic fallout if a tool erases human voice? That question sets boundaries.
Chu’s approach to representation as strategy and proof
Chu’s method is simple and effective: make the film, measure the market, and let profits and cultural response produce the evidence. He does not engage in endless social-media debates. He builds. That is a commitment-and-consistency play: once you back diversity with production choices repeatedly, you create expectations. Audiences begin to anticipate and demand it. Studios see the receipts. That loop is how change sticks.
What this means for artists, studios, and audiences
For artists: protect your authorship. Ask hard questions about consent and compensation when a tool asks for your work as training data. For studios: set clear rules about acceptable use, and invest in projects that prove diversity sells. For audiences: reward work that brings truth and risk to the screen. Box office is feedback. Cultural conversation is another.
Practical takeaways — what you can do now
1) Treat promotion as part of the art. Plan for storytelling arcs that begin before release and continue after. 2) Insist on consent and payment when any tool uses a creator’s work. 3) Protect the human creative moments on set; block attempts to replace them with synthetic shortcuts. 4) Use calibrated questions when evaluating new tools: “How will this affect authorship?” and “Who benefits economically?” 5) Build representation into casting decisions as a production variable, not a PR stunt. Show the market with concrete examples.
Questions to push the conversation forward
What does your organization say “No” to in order to protect creative integrity? How will you measure the value of human creative moments versus the cost savings of automation? If you had a seat at the studio table, what rules would you propose for fair use of training data?
I’ll pause here. Let those questions sit. …
Final thought: keep the human element central
Chu doesn’t reject tools; he names a border. He grew up in Silicon Valley and knows the upside of technology. He also knows what happens when we confuse replication with creation. The beauty of art in the AI era will be decided by both market signals and moral choices. If we protect those unpredictable, living moments — the wink, the breath, the shared silence on set — then cinema will remain a place where human risk and human generosity show us something true about ourselves.
#Wicked #JonMChu #AIinFilm #Representation #HumanCreativity #Filmmaking #Cinema
Featured Image courtesy of Unsplash and Sandy Millar (YAs18IHJY5Q)