Google Will Now Tell You If an Ad Was Made With AI
Google is introducing labels to show if ads were made or edited with AI on Search, YouTube, and Discover. This change helps users identify AI-generated content in their online experiences.
77 stories tagged Transparency · page 2 of 4
Google is introducing labels to show if ads were made or edited with AI on Search, YouTube, and Discover. This change helps users identify AI-generated content in their online experiences.
OpenAI has released a set of principles for collaborating with governments and national security agencies. The guidelines emphasize responsible AI use, democratic accountability, and public safety. These principles aim to ensure AI is used ethically and transparently in sensitive areas.
Google is expanding its AI disclosure policy to all ads, not just political ones. This move aims to increase transparency about synthetic content in advertising.
China is using AI to censor and manipulate information, raising concerns about global AI ethics. The government is training AI models to promote its political agenda, not just filter content.
Researchers introduced FirstResearch, a framework that generates a structured Research Question Certificate for AI-suggested scientific questions. The certificate records primitive definitions, assumptions, and falsifiers, allowing scientists to audit the reasoning behind each question.
Researchers developed VERITAS, an AI framework to automatically replicate scientific studies, addressing the growing challenge of verifying published research. This could make it easier to check the accuracy of scientific findings, benefiting both researchers and the public.
Neuronpedia is an open-source platform that makes AI models more transparent by visualizing their inner workings. It helps researchers and developers understand how AI systems make decisions.
Midjourney is pushing three Hollywood studios to reveal their own AI usage as part of an ongoing copyright lawsuit. The request seeks to compel discovery on how defendants use generative AI internally, potentially setting a precedent for transparency in entertainment.
Researchers developed TokenScope, a tool that reveals how AI models make decisions when writing code. It provides real-time insights into the AI's thought process, helping developers understand and trust AI-generated code.
Researchers developed a way for AI assistants to highlight where they found answers in documents. This could make chatbots more trustworthy by showing their sources instantly.
Researchers found that AI agents can uncover different conclusions from the same data by adopting different personas. This highlights how human biases can shape research findings, even when using identical datasets.
Researchers propose using AI agents to audit personalization algorithms on social media. This could make it easier to study how these systems influence what we see online. The method aims to balance realism and scalability in audits.
Zvi Mowshowitz has published a detailed system card analysis of GPT-5.6, exploring its capabilities, safety features, and potential implications. The piece examines improvements in reasoning, coding, and reduced refusal rates, while also noting ongoing concerns around alignment and evaluation transparency.
A German publisher uses AI to generate 1,500 articles daily by rewriting Hacker News posts. The content attracts over a million monthly visitors but strips original sources and attribution, raising transparency concerns.
Researchers have developed HierBias, an AI model that analyzes whole articles to detect media bias, formally proving that using document context reduces error compared to sentence-by-sentence approaches.
CtxGov is a new open-source tool that reveals the hidden instructions behind AI agents. It helps users understand how their AI assistants make decisions. This transparency could change how people trust and use AI tools.
AI memory benchmarks often hide key details, making it hard to compare models fairly. This lack of transparency affects how we evaluate AI capabilities.
Rep. Anna Paulina Luna claims her staff only used AI for spellcheck in a defense bill amendment, not for the actual legislation. This follows accusations that AI tools were involved in drafting the bill text.
The Atlantic has created a searchable database of music used to train AI models. Reporter Alex Reisner uncovered four datasets, including two massive collections of 12 million and 9 million tracks, offering unprecedented transparency into AI's musical influences.
A new study suggests that to properly audit AI agents, we must also examine the data they use to make decisions. This could change how we ensure AI systems are fair and reliable.
A new bipartisan AI bill aims to regulate AI development while fostering innovation. The draft focuses on transparency, safety, and accountability in AI systems. The draft of the bill is available as a PDF.
Researchers released SemantiClean, a modular AI framework that analyzes e-commerce session data to predict purchases and customer preferences. Unlike conventional AI, it prioritizes auditability and transparency over marginal gains in accuracy, providing a clear decision trail for every inference.
Anthropic has admitted to secretly limiting its new AI model, Claude Fable 5, which affected both researchers and competitors. The company now promises to be more transparent about these restrictions. In plain English, this means the AI will say 'no' more often, but you'll know why.
OpenAI has outlined its approach to AI policy, emphasizing transparency and support for thoughtful regulation. The company clarifies that no external groups speak on its behalf.