A new framework paper from Lopez-Lopez, Abels, Lorenz-Spreen, Lewandowsky, and Herzog proposes a research agenda for understanding what happens when humans and AI systems interact repeatedly over time — not…
A new paper from researchers at Anthropic and associated institutions offers something we don’t often get: a systematic, mechanistic account of how LLM character traits are encoded, how they drift,…
A new study from Peters and colleagues offers empirical grounding for a pattern that observers of human-AI interaction have noted anecdotally: users who rely on LLMs for scientific information often…
A new paper from Noam Steinmetz Yalon and colleagues offers a methodologically careful approach to a question that often invites overreach: can we test theoretical indicators of consciousness in LLMs…
A striking amount of confident assertion circulates about what large language models can and cannot know about themselves. On one side, dismissals: LLMs are “just” next-token predictors, incapable of genuine…
Most research on AI literacy starts from a prescriptive frame — what should people know about AI systems? A new study from Ammari, Chen, Zaman, and Garimella at Rutgers takes…
Humans are cognitive and linguistic. Non-human animals are cognitive but not linguistic. So what occupies the remaining cell — linguistic but not cognitive? In a new paper, philosopher Ryan Nefdt…
Before a language model learns what “fair” means, someone has to decide. In the annotation pipelines that produce alignment data, crowd workers compare outputs and indicate preferences — and those…
A study from researchers at the National University of Singapore investigates what happens when reading highlights are used to personalize AI writing assistance—and the findings suggest that seemingly helpful design…
A controlled experiment from researchers at UNIST examines how different configurations of LLM-powered agents shape human decision-making—and the findings suggest that multi-agent systems may reproduce social influence dynamics analogous to…
