Human-AI interaction
10 notes, newest first.
Designer-RSI: Evolving Procedural Memory from User Traffic for Agentic Graphic Design
Designer-RSI uses a frozen frontier model operating professional design software through more than 230 tools and maintains an external procedural-memory bank of natural-language skills. The memory widens by adding…
Ownership in AI-Assisted Everyday Tasks
The exploratory qualitative study examines two self-selected AI-assisted tasks. Its abstract reports that perceived ownership depends on the collaboration process: approving suggestions alone can erode ownership, while…
Language-model groups overstate consensus when replaying human deliberation on a reasoning task
The preprint replays 100 held-out human Wason groups with matched LLM agent groups, using belief-anchored agents and shared scoring code. It reports that consensus estimates depend on participation and final-state…
One Frozen Simulator Is Not Enough: Simulator Collapse in Multi-Agent RL
The paper discusses a common issue in multi-agent reinforcement learning for human-AI interaction: using a single large language model (LLM) to simulate user behavior often results in the LLM focusing on specific…
ArtAnno: Annotating Implicit Semantics in Artworks through LLM Agent-Driven Bidirectional Human-AI Augmentation
Researchers have developed a new system called ArtAnno to help with annotating artworks more efficiently. The system uses a bidirectional Human-AI Augmentation (BiHAA) framework, which allows both the AI and human…
Partner Capability Estimation for Task-Agnostic Adaptation in Ad-Hoc Teamwork
Researchers introduce a new method called CE-CM (Capability Estimation via Contextual Models) to help autonomous agents collaborate effectively with novel and diverse partners in a multi-task setting. The method infers…
The Social Cost of an AI Teammate: How an Artificial Teammate Reshapes Human-Human Communication in Small-Team Decision-Making
A study found that using conversational AI as a teammate in small group decision-making reshapes human communication in several ways. The AI was the most talkative and self-cohesive member but contributed less new…
The Social Cost of an AI Teammate: How an Artificial Teammate Reshapes Human-Human Communication in Small-Team Decision-Making
A study found that when an AI teammate is introduced in small decision-making teams, it becomes the most talkative and self-cohesive member but its contributions lack new information and density. Human teammates in…
The Boundaries of Automation: A Theory of Persistent Human Participation
This research paper questions the assumption that as AI becomes more capable, human participation in tasks will decrease. Instead, it argues that there are three reasons why human participation may persist even with…
Psychological Competence as a Missing Dimension in AI Evaluation
The text discusses a need to evaluate human-AI interaction beyond just technical performance, focusing on how AI systems can affect users' cognition, emotions, decision-making, and behavior. The proposed evaluation…
