Is AI scaling wealth and opportunity gaps into a permanent divide? The asymmetry in how the law is applied is staggering. Mark Zuckerberg’s Meta reportedly downloaded at least 81.7 terabytes of data from shadow libraries such as LibGen and Anna’s Archive to train its Llama models—amounting to a massive unauthorized transfer of copyrighted material. By contrast, in 2010–2011 Aaron Swartz downloaded roughly 70 GB of academic articles from JSTOR via MIT’s network—a tiny fraction of Meta’s scrape. For attempting to liberate scholarly knowledge, federal prosecutors pursued charges carrying a maximum penalty of a $1 million fine and 35 years in prison. We are witnessing a massive consolidation of power in which a handful of incumbents have captured the entire AI stack. Today’s founders face a harsh reality: to build anything meaningful, they often must rent compute, data, and infrastructure from the very giants they hope to challenge. We lost Aaron Swartz—the Reddit co-founder and one of our generation’s most brilliant architects—in 2013. The system seemed optimized to protect legacy institutions rather than nurture the open, decentralized future he championed. The world wasn’t ready for that vision, and we are now living with the consequences in today’s increasingly closed AI economy.