The company’s A.I.-generated answers look authoritative, but they draw on an array of sources, from trustworthy sites to Facebook posts.
Google’s AI Overviews Can Scam You. Here’s How to Stay Safe
Beyond mistakes or nonsense, deliberately bad information being injected into AI search summaries is leading people down potentially harmful paths.
Landmark German ruling declares Google's AI Overviews are Google's own words and makes it liable for false answers
A German regional court has ruled that Google is directly liable for the content of its AI search overviews. According to the court, previous limited liability protections for search engine operators don't apply to AI overviews. In this case, Google's AI had falsely linked two publishers to fraud and made claims that didn't appear in any of the linked sources. The ruling could set a precedent for AI-generated content liability worldwide.
How Google and AI Nearly Made a Seasoned Reporter Spiral — ProPublica
I thought I had missed something major in my reporting. Turns out I had stumbled into an AI-fueled feedback loop that involved a real LLC’s fictional website and a search engine that’s thrusting unreliable answers on users.
AI-Summarized News Articles: Readers Want Clear, Reliable Sources
A survey in Japan found that readers of AI-summarized articles on an app felt that having clearly cited sources was the most important factor in assessing reliability.
On Google declaring war on the Web
In Yesterday’s IO Keynote Google declared war on the remnants of the Web. (See longer description on their website.) TL;DR: They are pushing Search more into the “here’s your processed answer” direction that “AI Overviews” have established (you know, those AI snippets in current Search that are wrong about 10% of the time). So they […]
Zero-Click Readership: Are AI Overviews Changing the Way We Discover Research - The Scholarly Kitchen
Today's post asks: If research is increasingly accessed through AI-generated summaries rather than via primary sources, then what does it mean to “engage with research” at all?
Do people click on links in Google AI summaries?
In a March 2025 analysis, Google users who encountered an AI summary were less likely to click on links to other websites than users who did not see one.
You Should Still Fact-Check the 'Expert Advice' in Google's AI Summaries
Google's AI responses will now show expert advice pulled from online forums like Reddit with specific quotes and links to discussions related to search queries.
The Age of PageRank is Over
When Sergey Brin and Larry Page came up with the concept of PageRank in their seminal paper The Anatomy of a Large-Scale Hypertextual Web Search Engine (Sergey Brin and Lawrence Page, Stanford University, 1998) they profoundly...
The State of the Web at Google I/O 2018
The web is a global treasure, and has many strengths we all enjoy. It is a distribution platform like no other, providing people around the ...
AI use in American newspapers is widespread, uneven, and rarely disclosed
AI is rapidly transforming journalism, but the extent of its use in published newspaper articles remains unclear. We address this gap by auditing a large-scale dataset of 186K articles from online editions of 1.5K American newspapers published in the summer of 2025. Using Pangram, a state-of-the-art AI detector, we discover that approximately 9% of newly-published articles are either partially or fully AI-generated. This AI use is unevenly distributed, appearing more frequently in smaller, local outlets, in specific topics such as weather and technology, and within certain ownership groups. We also analyze 45K opinion pieces from Washington Post, New York Times, and Wall Street Journal, finding that they are 6.4 times more likely to contain AI-generated content than news articles from the same publications, with many AI-flagged op-eds authored by prominent public figures. Despite this prevalence, we find that AI use is rarely disclosed: a manual audit of 100 AI-flagged articles found only five disclosures of AI use. Overall, our audit highlights the immediate need for greater transparency and updated editorial standards regarding the use of AI in journalism to maintain public trust.
AI use in American newspapers is widespread, uneven, and rarely disclosed
AI is rapidly transforming journalism, but the extent of its use in published newspaper articles remains unclear. We address this gap by auditing a large-scale dataset of 186K articles from online editions of 1.5K American newspapers published in the summer of 2025. Using Pangram, a state-of-the-art AI detector, we discover that approximately 9% of newly-published articles are either partially or fully AI-generated. This AI use is unevenly distributed, appearing more frequently in smaller, local outlets, in specific topics such as weather and technology, and within certain ownership groups. We also analyze 45K opinion pieces from Washington Post, New York Times, and Wall Street Journal, finding that they are 6.4 times more likely to contain AI-generated content than news articles from the same publications, with many AI-flagged op-eds authored by prominent public figures. Despite this prevalence, we find that AI use is rarely disclosed: a manual audit of 100 AI-flagged articles found only five disclosures of AI use. Overall, our audit highlights the immediate need for greater transparency and updated editorial standards regarding the use of AI in journalism to maintain public trust.
Category:WikiProject lists of reliable sources
The following 61 pages are in this category, out of 61 total. This list may not reflect recent changes.
Google Search's guidance about AI-generated content | Google Search Central Blog | Google for Developers
In this post, we'll share more about how AI-generated content fits into our long-standing approach to show helpful content to people on Search.
Do our social media algorithms correctly reflect our values? Our new article published today in @pnas.org shows that the answer is often not, and that the content that gets promoted into their ranked feeds is often actively counter to our values.
Do our social media algorithms correctly reflect our values? Our new article published today in @pnas.org shows that the answer is often not, and that the content that gets promoted into their ranked feeds is often actively counter to our values.
