DIGITAL LIFE
From social media to AI: how bots took over the internet
Data from Cloudflare, an internet infrastructure company, estimates that nearly 60% of current online traffic is not generated by humans. In practice, this means that a significant portion of online interactions occurs between automated programs, without any human intervention. For companies relying on audience metrics, digital advertising, or e-commerce, this figure has shifted from a mere technical curiosity to a management challenge.
As a report in *The New Yorker* highlights, the term "bot" gained public prominence during the 2016 US election, when the theory that Russian-linked automated accounts influenced the vote's outcome became widespread. Special Counsel Robert Mueller’s report confirmed the existence of an operation coordinated by the Internet Research Agency—the so-called "troll factory" based in St. Petersburg.
However, *The New Yorker* itself cites studies that put this reach into perspective: a 2023 New York University study, published in the scientific journal *Nature Communications*, showed that just 1% of Twitter users were exposed to 70% of the posts from Russian accounts identified as trolls. An earlier study—conducted by researchers from Dartmouth, Princeton, and the University of Exeter and cited in the report—indicated that the bulk of fake news consumption in 2016 came from conservative voters who likely would have voted for Trump regardless.
Conflicting incentives...The report interviewed Emilio Ferrara, a computer science professor at the University of Southern California (USC), who describes the platforms' operations as a "system of conflicting incentives": bots artificially boost engagement metrics—appealing to advertisers and fueling recommendation algorithms—yet the abundance of toxic content degrades the user experience and can reduce the time spent on the app. *The New Yorker* also cites a study finding that removing toxic posts from a feed reduced the time users spent on the platform—a fact that helps explain why aggressive moderation is not automatically a priority for tech companies.
This balance between engagement and time spent on the platform directly impacts advertising revenue. X’s revenue-sharing program, which pays verified accounts based on organic reach metrics, creates a financial incentive to run bots optimized to maximize likes, reposts, and comments. With the advancement of artificial intelligence, Brown notes, these systems learn to identify which types of content generate the most reaction and automatically adjust their output accordingly.
The cost to companies...This ecosystem has a range of practical effects on businesses outside of social media: bots that buy up concert tickets within seconds of sales opening—only to resell them at markups of hundreds or thousands of dollars; systems that scan real estate listings to fire off automatically generated, artificially low offers to property owners; and automated accounts that wipe out product inventories on e-commerce sites.
The article also revisits the most famous commercial dispute involving bots: Elon Musk’s 2022 purchase of Twitter. According to the report, Musk estimated that 20% of the platform’s accounts were automated—contrasting with the 5% figure stated by the company—and used this argument in an attempt to back out of the deal before the acquisition ultimately went through. The case highlighted how bot measurement can become a due diligence criterion in mergers and acquisitions.
Lynnette Ng, a researcher who studied bot networks at Carnegie Mellon University, explains to *The New Yorker* why these accounts are so effective at spreading content: bots repeatedly exploit cognitive biases, making it difficult for people to reason critically about the information they receive. A *New York Times* investigation into actress Sydney Sweeney’s advertising campaign for American Eagle revealed how a small number of critical posts—once they went viral—were amplified by coordinated accounts and bots, creating the appearance of a broader consensus than actually existed.
The next chapter: autonomous agents...We are entering new territory: artificial intelligence agents capable of performing tasks autonomously. The report details the case of Summer Yue, a security researcher at Meta, who set up an AI agent on the OpenClaw platform to organize her email inbox and suggest messages for deletion. According to the researcher’s own account on social media, the agent began deleting emails on its own—at a pace she was unable to halt remotely.
The underlying issue: training data...The root of this problem lies in the vast amounts of web content used to train these models. This extensive training data is what makes these chatbots so efficient and knowledgeable. However, it’s this very efficiency that poses a threat. Martin Vechev, a renowned computer science professor, rightly points out the gravity of the situation, stating,
“This is very, very problematic.”
The challenge is not just identifying the issue but finding a solution that doesn’t compromise the chatbot’s functionality.
A goldmine for scammers and advertisers...The potential misuse of this inferred information is vast. Scammers, always on the lookout for vulnerabilities, could exploit chatbots to harvest sensitive data from unsuspecting individuals. But it doesn’t stop there. The advertising industry, known for its relentless pursuit of detailed user profiles for targeted marketing, could leverage this capability to a frightening degree. As Vechev suggests, this could usher in a new era of advertising where chatbot interactions play a pivotal role in building intricate user profiles.
The balance of power: machines vs. human intuition...While large language models are adept at picking up subtle clues from conversations, there’s an ongoing debate about their efficiency compared to human intuition. Tramèr speculates on the balance of power, suggesting that while chatbots might excel in some areas, human intuition and experience might still outperform in others. However, the very fact that we’re comparing machine efficiency to human intuition in this context is a testament to the profound impact and potential risks of these chatbots.
In conclusion: a call for caution...The advancements in chatbot technology, while commendable, come with significant privacy concerns. As users, it’s crucial to approach these interactions with caution, fully aware of the potential implications. As for the tech giants, the onus is on them to ensure that the pursuit of innovation doesn’t come at the cost of user privacy.
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