AI Slop Is The New MFA, And We All Need To Fight It | AdExchanger

"Low-quality, AI-generated content - or AI slop - is flooding the open web. The entire digital ecosystem is adapting to the challenges that generative AI's exponential growth presents. As someone who spends a lot of time thinking about media waste and ROAS, I've seen how easy it is for bad actors to spin up thousands of low-value websites with a few clicks. These sites exist for one reason: to capture ad dollars. And generative AI makes it easier than ever to create slop at scale."

"Budgets get wasted, consumers are misled, and legitimate publishers lose revenue. However, many publishers are experimenting responsibly, using AI to enhance reporting or streamline workflows while still applying human oversight. The real challenge is drawing a clear line between the AI-generated content that adds value and the kind that erodes trust and leads to significantly lower ad effectiveness. Telling the difference Advertisers should focus on stopping the bad while preserving what works."

"The good stuff comes from reputable publishers who disclose their use of AI, apply fact-checking and prioritize relevance and accuracy. Source credibility, content accuracy, article depth and visual quality are all signals to help differentiate quality from slop. Meanwhile, low-quality AI slop sites tend to resemble MFA, which should stand for Made for Arbitrage . They are characterized by a high ad-to-content ratio, repetitive or shallow articles and vague disclosures on the use of AI."

Low-quality AI-generated content is proliferating across the open web and driving the creation of thousands of low-value sites aimed at capturing ad revenue. Advertisers face wasted budgets, misled consumers, and revenue losses for legitimate publishers. Some reputable publishers use AI responsibly, combining disclosure, fact-checking, and human oversight to improve reporting and efficiency. The main challenge is distinguishing value-adding AI content from content designed to game ad systems. Signals of quality include source credibility, content accuracy, article depth, and visual quality. Low-quality sites often exhibit high ad-to-content ratios, repetitive shallow articles, plagiarism, and vague AI disclosures.

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