In the pre-internet era, a small number of executives and critics decided what art was produced and celebrated. Today, social media algorithms allow the audience to decide what is 'good' by rewarding it with attention, enabling talent that would have been overlooked by the old system to thrive.

AI's ability to generate Hollywood-quality films or other complex media for an individual user will lead to extreme market fragmentation. This hyper-personalization won't just transform creative industries like film; it could completely erase them by dissolving the shared cultural experiences that underpin them.

As AI drives the cost of content creation to zero, the world floods with 'average' material. In this environment, the most valuable and scarce skill becomes 'taste'—the ability to identify, curate, and champion high-quality, commercially viable work. This elevates the role of human curators over pure creators.

While AI can create personalized films, humans fundamentally crave shared experiences that act as social 'Schelling points' for discussion. The value of watching the same movie or attending the same concert as others will limit the appeal of infinitely customized content, which offers no common ground for connection.

In tech, data is often the final arbiter in decision-making. In creative industries like entertainment, data starts the conversation, but the final call comes down to artistic taste, quality, and user delight. Tech could create better products by adopting this 'end with delight' principle.

While seemingly beneficial, algorithms that perfectly cater to existing preferences (e.g., in music or news) can trap users in narrow cultural silos. This "calcification" of taste prevents personal development and creates a balkanized cultural landscape, hindering shared experience and discovery.

Since AI learns from and replicates existing data, human creators can stay ahead by intentionally breaking those patterns. AR Rahman suggests that the future of creativity lies in making unconventional choices that a predictive model would not anticipate.

The greatest danger of AI content isn't job loss or bad SEO, but a societal one. Since we consume more brand content than educational material, an internet flooded with AI's 'predictive text' based on what's common could relegate collective human knowledge and creativity to a permanent base level.

Great ideas like deep learning were not immediately recognized. Their value emerged over time as others built upon them. This suggests an idea's fruitfulness is a product of its context and cultural adoption, not just its isolated brilliance, making it difficult for an AI to evaluate its ultimate impact.