AI Feedback Loop
The term AI Feedback Loop coined in 2025 by dbw.
The AI Feedback Loop describes a self-reinforcing cycle of misinformation in digital ecosystems. Flawed or false information from sources like biased articles, Reddit threads, or Wikipedia enters large language models during training or retrieval. These models then output the errors as factual responses. Users, journalists, or content creators copy this AI-generated text into new articles, posts, or pages. As the same falsehood appears across multiple sites, search engines and future AI updates treat it as more credible due to repetition rather than accuracy. This amplification turns isolated mistakes into widespread "truths," making AI systems progressively less reliable and contaminating online knowledge over time.
The AI Feedback Loop captures a real and growing problem in information ecosystems. It refers to a cycle where flawed or false data from online sources gets ingested by large language models, regurgitated as fact, and then amplified through new content creation. This reinforcement makes errors seem more credible over time due to increased prevalence across sources.
The spread of AI-driven misinformation has surged, with documented campaigns rising 400-600% since 2023 and projected to hit 500-800% by late 2025. AI incidents overall climbed 56% in 2024 alone. Meanwhile, mitigation tools like detection algorithms lag, with predictions that disinformation tech will outpace defenses by 2026-2027. This imbalance stems from AI's rapid scaling and easy access, while fixes demand coordinated policy, tech upgrades, and education that move slower. Some studies note trusted news sources help counter the trend without total breakdown, but the gap widens as loops reinforce errors across platforms.
Examples include political misinformation from outlets like The New York Times being echoed by AI, then reused in other publications, creating a self-perpetuating echo chamber. In journalism, AI tools have been noted to accelerate this by rephrasing and republishing untruths, as seen in reports on disinformation campaigns. Studies also highlight how generative AI acts as an amplifier for anti-white or self hate speech and fake news, turning isolated lies into widespread narratives.