The Coffee Bank and the Speed of Change (collabfund.com)

OpenAI’s new video model Sora—able to generate cinematic footage from a text prompt—has reignited a familiar tension: innovation moving faster than the rules that govern it. The piece uses Starbucks and Uber as analogies—Starbucks’ app-driven prepaid balances (nearly $2 billion in customer funds) quietly turned it into a bank by design, while Uber deliberately tested regulatory edges by launching first and letting scale create legitimacy. Sora’s leap is technically impressive but ethically and legally fraught: the model learned movement, lighting and storytelling from vast libraries of films, animation and photography it likely ingested without creators’ consent, exposing a mismatch between current copyright frameworks (built for copying physical works) and models that “ingest” distributed cultural output. For the AI/ML community this matters both practically and strategically. Practically, data provenance, licensing, and compensation are now core technical and product design problems—how you source, document, and filter training data will shape legitimacy and risk. Strategically, the story underscores how fast iteration cycles (days) outpace regulatory responses (years), shifting governance toward informal mechanisms—reputation, public trust, platform controls—which are faster but fragile. The piece argues for builders who test limits responsibly: transparency, consent, and accountability should be treated as design constraints, not afterthoughts, if AI progress is to avoid becoming extraction rather than empowerment.