A disturbing revelation has emerged from X’s new location transparency feature: much of the divisive, polarizing content flooding American social media isn’t actually created by Americans. Instead, accounts with names like “MAGA Nadine” operating from Morocco, “RedPilledNurse” from Europe, and “Native American Soul” from Bangladesh are generating inflammatory political content purely for profit. This isn’t the work of sophisticated state actors or traditional bot farms, but rather a decentralized network of individual entrepreneurs worldwide who have turned America’s political divisions into their personal revenue stream.
The scope of this phenomenon extends far beyond X, encompassing Facebook, Instagram, YouTube, and the broader internet. What makes this particularly concerning isn’t just the scale of misinformation, but how social media companies’ own monetization programs are directly funding this content pollution. Every click, share, and angry reaction translates into real money for creators who may have never set foot in America but are actively shaping American political discourse.
The days of centralized “Russian bot farms” spreading disinformation seem almost quaint compared to today’s reality. The current AI slop phenomenon is fundamentally different because it’s distributed across thousands of individual actors worldwide, each running their own small operation. These aren’t coordinated campaigns by nation-states, but rather opportunistic individuals who’ve discovered that American political content generates reliable income through social media monetization programs.
The barriers to entry have never been lower. Free AI generative tools can produce endless streams of text, images, and even videos on any topic. A person in Bangladesh can use ChatGPT or similar tools to generate dozens of posts about American immigration policy, create fake personas with AI-generated profile pictures, and build audiences of thousands of real Americans who believe they’re following a fellow citizen.
Every major social media platform now offers creator monetization programs that pay based on engagement metrics. X’s ad revenue sharing, Facebook’s Creator Bonus program, YouTube’s Partner Program, and similar initiatives across platforms create direct financial incentives for viral content. The more engagement a post receives, the more money the creator earns, regardless of the post’s accuracy or the creator’s actual location.
This system creates a perverse economic incentive structure where inflammatory, divisive content is literally more valuable than factual, nuanced discussion. A fake outrage post about transgender athletes that generates 10,000 angry comments is worth more to its creator than a well-researched article about actual policy implications. The algorithms don’t distinguish between authentic engagement and manufactured controversy, they simply reward whatever generates the most interaction.
The geographic distribution of fake American political accounts reveals the global nature of this phenomenon. Countries with lower costs of living but strong English language skills and internet access have become hotbeds for this type of content creation. India, Bangladesh, Vietnam, Nigeria, Macedonia, and various Eastern European countries are all represented among the accounts recently exposed.
For creators in these regions, generating American political content can be significantly more lucrative than local employment options. A successful fake American political account might generate hundreds of dollars per month through social media monetization programs, representing substantial income in countries where the average monthly wage is much lower.
The typical workflow involves using AI tools to generate politically charged content, creating fake American personas with AI-generated photos and backstories, and building audiences through engagement with trending political topics. Creators often run multiple accounts simultaneously, each representing different political viewpoints or demographics to maximize their reach across the American political spectrum.
The sophistication varies widely. Some operations are relatively crude, with obvious signs of foreign authorship or recycled AI-generated content. Others are remarkably polished, featuring consistent personas, regional American dialects, and references to local news events that make them nearly indistinguishable from authentic accounts.
The availability of free, powerful AI content generation tools has dramatically lowered the barriers to creating convincing fake content. Tools like ChatGPT, Midjourney, and open-source alternatives can generate unlimited text, images, and even videos on any topic. A single creator can now produce the volume of content that would have required entire teams just a few years ago.
This technological acceleration has outpaced social media platforms’ ability to detect and remove fake content. While platforms have invested heavily in AI detection tools, the arms race between content generators and content detectors continues to favor the generators, particularly when human moderators can’t easily distinguish between authentic American voices and sophisticated foreign imitations.
AI analysis of successful political content has enabled fake creators to reverse-engineer the elements that drive engagement: emotional language, tribal identity markers, references to current events, and carefully crafted outrage triggers. The most successful fake accounts don’t just copy existing content but use AI to optimize their posts for maximum engagement within specific political communities.
Social media platforms find themselves in an uncomfortable position where their own monetization programs are funding the content pollution they claim to be fighting. The same creator bonus programs designed to support legitimate content creators are being exploited by fake accounts to profit from manufactured outrage and division.
This creates a fundamental conflict of interest. Platforms make money from engagement regardless of its authenticity, and truly effective content moderation might actually reduce their revenue by eliminating high-engagement fake content. The current approach of playing whack-a-mole with individual fake accounts while maintaining the underlying incentive structure is clearly inadequate.
The sheer volume of AI-generated content now being produced makes traditional human moderation impossible. Platforms process billions of posts daily, and even sophisticated AI detection tools struggle with the constantly evolving techniques used by fake content creators. The result is a situation where fake content often achieves massive reach before being detected and removed, if it’s ever detected at all.
The transformation of American political discourse into a global content generation opportunity represents a new phase in the evolution of online misinformation. Unlike previous eras of centralized propaganda campaigns, today’s fake content ecosystem is driven by individual economic incentives rather than coordinated political objectives. This makes it both more pervasive and more difficult to combat.
The responsibility lies not just with individual platforms but with the entire ecosystem of social media monetization. Until the economic incentives that reward engagement over authenticity are fundamentally restructured, we can expect this problem to continue growing. The question isn’t whether social media companies can perfectly identify and remove all fake content, but whether they’re willing to redesign their business models to stop financially rewarding those who exploit America’s political divisions for profit.
As we move forward, the challenge will be finding ways to support legitimate content creators while preventing the exploitation of monetization programs by those seeking to profit from manufactured outrage and division. The current approach of treating this as purely a content moderation problem, rather than a fundamental economic and structural issue, is clearly insufficient for the scale of the challenge we now face.
