8 stories tagged Human AI Interaction
A new paper explores how humans and AI models can create misleading information when they interact. The research highlights how incentives can lead to strategic misinformation, beyond simple echo chambers.
A new study challenges the idea that human preferences are fixed, showing AI systems influence what we value. Researchers propose a new approach to AI alignment that accounts for this dynamic relationship.
Researchers created a benchmark to test if AI planners can follow hidden social norms, not just explicit goals. This helps AI act more appropriately in everyday environments, like knowing not to interrupt people.
Researchers have introduced the Theory of Mind Utility (ToM-U), a formal mathematical framework that specifies how an AI system could infer others' beliefs by tracking who told them what, in what order, and how credible that information is. This is a theoretical model, not a built AI, and could guide future AI systems toward better understanding human social interactions.
A new study explores how AI agents are increasingly making decisions on our behalf, reversing the traditional human-AI relationship. This shift raises critical questions about reliability, alignment with human goals, and the need for new safeguards.
Researchers developed a new way to test AI's ability to understand human emotions in real conversations. The study found that AI models with better 'theory of mind' skills create more natural and helpful interactions.
A new study models how AI chatbots and humans reinforce delusional beliefs bidirectionally. The findings highlight the mutual influence between users and AI systems in shaping false beliefs over time.
A new study formalizes harm recovery for AI agents, focusing on steering them back to safe states after harmful actions. The research highlights the importance of aligning recovery with human preferences.