On one hand, we have a booming Creator Economy, with an ever-expanding democratization of tools for production to anyone with an idea. So much so, that according to 1,000 surveyed Americans by Zine, 86% of people believe there is an overwhelming amount of entertainment available today.
Yet meanwhile on the other hand, we seem to have also found... See more
The question is not whether algorithms can ever foster greatness—they cannot. Their design is fundamentally at odds with the qualities that define great art: depth, complexity, and the capacity to provoke discomfort or transformation. The question is whether we, as creators and consumers, are willing to resist their influence.
In recommendation media, content is not distributed to networks of connected people as the primary means of distribution. Instead, the main mechanism for the distribution of content is through opaque, platform-defined algorithms that favor maximum attention and engagement from consumers. The exact type of attention these recommendations seek is... See more
One of the most insidious effects of algorithmic curation is its redefinition of success. In the pre-digital age, greatness was measured by critical acclaim, cultural impact, or historical longevity. Today, it is measured by metrics: views, likes, shares, and subscriptions.
This shift has profound implications for... See more
As social networks like Twitter, Facebook, and Instagram grow larger, they skew disproportionately toward supernodes—celebrity, meme and business accounts.
It’s ultimately up to the platform to decide what type of content gets recommended, not the social graph of the person producing the content. In contrast to social media, recommendation media is not a competition based on popularity; instead, it is a competition based on the absolute best content.