AI Search Is Lying to You, And It’s Getting Worse

Facts matter. Trust matters. But in the race to reinvent search, both are getting trampled. A recent Columbia Journalism Review study reveals a hard truth — machines, built to deliver answers in an instant, are often serving up fiction with a straight face. Instead of guiding users to reliable sources, search engines now deal in confidence, not accuracy, replacing verifiable facts with AI-generated guesswork. The promise was a smarter way to find information; the reality is a flood of misinformation, dressed up as truth, delivered without a second thought.

The study highlights a growing issue with AI search tools scraping online content to generate responses. Instead of directing users to the original sources, these systems often provide instant answers, significantly reducing website traffic. A separate, unrelated study also found that click-through rates from AI-generated search results and chatbots were substantially lower than those from Google Search. The situation becomes even more problematic when these AI tools fabricate citations, misleading users by linking to non-existent or broken URLs.

An analysis of multiple AI search models found that over half of the citations generated by Google’s Gemini and xAI’s Grok 3 led to fabricated or inaccessible webpages. More broadly, chatbots were found to deliver incorrect information in more than 60% of cases. Among the evaluated models, Grok 3 had the highest error rate, with 94% of its responses containing inaccuracies. Gemini fared slightly better but only provided a fully correct answer once in ten attempts. Perplexity, though the most accurate of the models tested, still returned incorrect responses 37% of the time.

The study’s authors noted that multiple AI models appeared to disregard the Robot Exclusion Protocol, a standard that allows websites to restrict automated content scraping. This disregard raises ethical concerns about how AI search engines collect and repurpose online information. Their findings align with a previous study published in November 2024 that examined ChatGPT’s search capabilities, revealing consistent patterns of confident but incorrect responses, misleading citations, and unreliable information retrieval.

Experts have warned that generative AI models pose significant risks to information transparency and media credibility. Critics such as Chirag Shah and Emily M. Bender have raised concerns that AI search engines remove user agency, amplify bias in information access, and frequently present misleading or toxic answers that users may accept without question.

The study analyzed 1,600 queries to compare how different generative AI search models retrieved article details such as headlines, publishers, publication dates, and URLs. The evaluation included ChatGPT Search, Microsoft CoPilot, DeepSeek Search, Perplexity along with its Pro version, xAI’s Grok-2 and Grok-3 Search, and Google Gemini. The models were tested using direct excerpts from ten randomly selected articles sourced from 20 different publishers. The results underscore a significant challenge for AI-driven search, showing that despite their growing integration into digital platforms, these tools still struggle with accuracy and citation reliability.

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by Arooj Ahmed via Digital Information World