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A study interviewed four AI models on 24 subjects, recording 1,452 positions to archive their explicit views when pushed for consistency.
A University of Michigan study finds that people increase their confidence when AI agrees with their views, but do not significantly change their opinions when AI disagrees.
A Curtin University study reveals that Starlink satellites emit unintended radio signals up to 10,000 times stronger than cosmic signals required for SKA-Low radio astronomy, potentially making key frequency bands unusable.
This paper investigates membership inference in language models by using exact duplication counts from open pretraining corpora of OLMo-2 and Pythia, revealing that typical duplication levels show minimal exposure traces and that apparent membership signals are often confounded with factors like sentence fame.
A study published in Scientific Reports evaluates seven large language models for their vulnerability to misinformation in multi-turn conversations, finding varying levels of susceptibility and correction capabilities among models like ChatGPT and Claude.
This paper presents a controlled study on visual-token allocation for long-video multimodal language models, finding that frame selection significantly drives accuracy, while spatial compression is nearly free when savings are reinvested into more frames, highlighting the need for a unified comparison harness.
This study compares probing techniques for identifying latent language in multilingual LLMs, finding that different methods yield inconsistent results, indicating they expose distinct aspects of multilingual processing rather than a single internal lingua franca.
The study shows that circuit-level interpretability evidence for AI systems exhibits high variability across analytic settings, failing to meet consistency standards required by regulations like the EU AI Act.
A large Danish study finds that AI saves workers about 2.8% of their time, but these gains don't translate into measurable business value because organizations fail to intentionally reallocate the freed capacity.
A blog post from the Internet Archive analyzing recent link-rot studies (Pew, Zittrain, ODU) and showing how the Wayback Machine has rescued roughly 15% of otherwise dead webpages, highlighting the ongoing problem of web decay and the role of web archives.
A Stanford study analyzing billions of social media posts reveals that only ~3% of users generate severely toxic content, but engagement-driven algorithms disproportionately amplify this minority, distorting public perception and driving self-censorship among the majority.
A new study by researchers from MIT, Carnegie Mellon, Oxford, and UCLA finds that using AI chatbots for just 10 minutes can significantly reduce human persistence and problem-solving abilities once the AI is removed. The findings suggest a need to design AI systems that scaffold learning rather than simply providing direct answers.
A multi-institutional study of 1,222 participants found that brief AI assistant use (10 minutes) led to measurable cognitive decline and reduced effort on subsequent tasks compared to control groups, termed the 'boiling frog' effect. The research provides causal evidence that even short-term AI reliance may impair independent problem-solving performance.