A large-scale study covering 208,000 participants and 26 million responses shows that the very training that turns language models into helpful chatbots weakens their ability to replicate human behavior. The effect gets worse with each new model generation. Even the popular persona trick, feeding models demographic profiles, brings practically no benefit for individual predictions.<br /> The article Making AI chatbots helpful weakens their ability to simulate human behavior, large-scale study finds appeared first on The Decoder. [...]
We all have anecdotal evidence of chatbots blowing smoke up our butts, but now we have science to back it up. Researchers at Stanford, Harvard and other institutions just published a study in Nature a [...]
Artificial intelligence agents powered by the world's most advanced language models routinely fail to complete even straightforward professional tasks on their own, according to groundbreaking re [...]
Despite growing chatter about a future when much human work is automated by AI, one of the ironies of this current tech boom is how stubbornly reliant on human beings it remains, specifically the proc [...]
For more than two decades, digital businesses have relied on a simple assumption: When someone interacts with a website, that activity reflects a human making a conscious choice. Clicks are treated as [...]
A new research paper quietly published last week outlines a breakthrough method that allows large language models (LLMs) to simulate human consumer behavior with startling accuracy, a development that [...]
A growing number of developers and AI power users are taking to social media to accuse Anthropic of degrading the performance of Claude Opus 4.6 and Claude Code — intentionally or as an outcome of c [...]
San Francisco-based AI lab Arcee made waves last year for being one of the only U.S. companies to train large language models (LLMs) from scratch and release them under open or partially open source l [...]