Company Offering ‘100% Human-Written, Never AI’ Medical Research Is Entirely AI

Research Gold's team of human methodologists are either AI generated or using the identity of real people without their permission

Près de 40 % des Français visitent chaque mois des sites d’info générés par IA

Le premier observatoire français de l’audience des sites GenAI, établi par Médiamétrie en octobre 2025, avait établi que près de 25 % des Français y…

Un quart des Français visitent les sites d’infos générées par IA recommandés par Google

14 à 16 millions d’internautes français consultent chaque mois l’un des 251 sites d’infos GenAI les plus recommandés par Google et identifiés par Next,…

The unintended consequences of large language models as a labor-augmenting technology in science

As a labor-augmenting technology, large language models (LLMs) have the potential to accelerate scientific activity across the research pipeline. But even if LLMs perform on par with human experts at selected tasks, their use will bring unintended consequences as they alter the balance of frictions and inducements that steer the allocation of research effort across projects. Here we develop a simple mathematical model to illustrate. In fields where LLMs are useful primarily as tools for discovering promising projects, researchers will become more selective about what they publish; where they facilitate the process of publishing existing data, researchers will become less selective. By allowing scientists to work more quickly, LLMs raise the opportunity cost of researcher time, creating incentives to refine papers less thoroughly before moving on. Enticing as it is to imagine that, by saving us time on mundane tasks, LLMs will provide us with more time to think deeply and develop projects completely, our results temper such hopes.

AI Comes for Academics. Can We Rely on It?

By now, the fact that artificial intelligence can hallucinate is, I hope, well known. There are countless examples of platforms like ChatGPT giving the wrong answer to a straightforward question or

Content Independence Day, one year on- building the business model for the agentic Internet

One year after declaring Content Independence Day, a dynamic market for monetized content has officially emerged. In this report, we examine how the rise of autonomous AI agents is upending traditional search referrals and detail the new infrastructure required to support a sustainable web economy.

Google Is Building an A.I. Fence Around the Internet It Once Championed

As Google incorporates more artificial intelligence into search, people are spending more time on Google. Some website operators are crying foul.

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.

Once Unimaginable, Publishers Are Preparing to Opt Out of Google Search

The nuclear option is gaining traction as web traffic collapses and Google refuses to negotiate with content creators

Your Search Results Are Getting Sloptimized

How companies are gaming the chatbot internet

Why Google’s New AI-Saturated Search Page Will Be A Disaster

Google didn’t invent full-text search of the Internet – that honor belongs to early pioneers such as WebCrawler, Lycos and AltaVista. But for the last 25 years or so, Google has…

Google検索の「AIによる概要」が虚偽の情報を記載したことにGoogleが直接的な責任を負うとの画期的判決が下る

Google検索の検索結果ページの一番上に表示される「AIによる概要」はAIが情報をまとめてくれるため利便性が高い一方で、1時間に何千万件もウソをついているという調査結果があるように、その不正確さが問題視されることがあります。AIによる概要が企業について誤った情報を提示した上で修正要請にも対応しなかったとして、Googleに責任を求める判決がドイツの裁判所で下されました。

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.

Nobody needs AI to search the Internet, court says in ruling against Google

Google AI Overview court loss in Germany could spell doom for AI search industry.

AI Just Isn’t Right

Can AI do fact-checking? A WIRED fact-checker fact-checks.

DuckDuckGo sees iPhone installs spike in the US following AI announcements at Google I/O

Following Google I/O, DuckDuckGo says it has seen a notable and sustained surge in U.S. users, including a sharp jump in iPhone app installs.

When Science Goes Agentic

In a couple of years, we will inspect AI-generated source code about as often as we inspect the assembly output of a compiler. Which is to say, far less often—outside of high-stakes and adversarial settings. The trajectory is clear: vibe coding is not a fad but a transition, a stepping stone. Debugging AI-generated code will shrink dramatically for a lot of everyday software—not because the code will be flawless, but because the feedback loops between generation, testing, and correction will tighten until human inspection becomes the bottleneck rather than the safeguard. In this respect, requiring the co-generation, with code, of mechanically verifiable formal attestations can also improve the process.