Profiting from Noise: How Misinformation and AI Imagery on X Are Turning Users into Earners

As the US elections approach, X users are reportedly generating substantial income through the dissemination of election misinformation and AI-generated images, raising concerns about the impact on political discourse in the lead-up to the election.

Pervasive activity on X reveals a troubling trend where users reported earning thousands of dollars by sharing a mix of factual and misleading election-related content. Investigations found clusters of accounts systematically amplifying each other's posts, thereby maximizing reach and monetization. Users described an environment wherein collaboration occurred in private forums and group chats—a cycle of mutual support to share sensationalized narratives, both true and fabricated. They spoke candidly about their income, stating figures ranging from hundreds to thousands of dollars, aligning with observed engagement metrics.

The recent change in X's payment structure, favoring engagement metrics from premium users over traditional advertising revenue, has fueled this surge in profit potential. This policy shift raises alarms among observers concerned about whether financial incentives are encouraging more incendiary posts at a politically sensitive time in the US electoral landscape. The platform does not currently impose stringent guidelines to combat misinformation, contrasting with many other social media channels that regulate such content.

Among the users, individuals both supportive of President Trump and Vice President Harris are prominent, with earnings tied to their engagement strategies and audience interactions. User “Freedom Uncut” elaborated tactics that include posting AI artwork designed to provoke discussions, stating he views his work as art rather than deception, despite the content's controversial nature.

In stark contrast, users like “Brown Eyed Susan,” a supporter of Harris, reported harnessing their large followings to promote narratives that riot against the opposition. Susan noted that while she stumbled into monetization, she embraces the distribution of both policy discussions and unfounded theories, claiming these engage her audience. The tendency to propagate questionable stories highlights how users can transform polarizing content into profitable ventures.

An illustrative incident involved a manipulated image of Kamala Harris that went viral after being mistakenly attributed to her supporters. This misrepresentation ignited discussion about authenticity and accountability in the dissemination of political imagery. Users like Blake, who have engaged in creating doctored posts, admitted they prioritize engagement over truth, reflecting a broader truth in social media dynamics: narratives are often shared because they resonate emotionally, irrespective of factual basis.

X’s approach to misinformation includes efforts to label manipulated media, yet critics argue that its lack of decisive action during election cycles complicates the integrity of the political discourse. The platform’s response—or lack thereof—might well influence the trajectory of US politics as voters gear up for the crucial elections. As the lines between fact and fiction increasingly blur, the question remains: how will these emerging patterns of misinformation-backed profits affect democratic processes?

The contributions of AI and user-generated content in this evolving narrative illustrate the capacity for social media, particularly X, to shape political campaigns significantly. As scrutiny builds around these practices, the impact on political outcomes and public understanding necessitates a thorough examination of the consequences for both voters and candidates alike.