human-ai-interaction

topic7 events

papersTODAY 04:00 UTC

Paper Proposes Self-Play Method for Training AI Assistants When to Ask Clarifying Questions

A new arXiv preprint introduces a method that teaches AI assistants how to handle ambiguous or underspecified user requests. The approach uses collaborative self-play to learn a steerable policy that decides between answering directly, listing several possible interpretations, or asking the user for clarification. The goal is to improve how systems manage uncertainty in dialogue rather than guessing wrong.

research/agents/self-play/dialogue

papersTODAY 04:00 UTC

arXiv Paper Explores Generative AI Co-Design for Personal Health Interfaces

A new arXiv preprint examines how generative AI can be used in co-design processes to tailor personal health interfaces to individual preferences. The authors argue that standard wellbeing dashboards often fail to match how people interpret and act on their own data, and that customizing them typically demands design and technical skills many users lack. The work positions generative AI as a way to lower that barrier by involving users directly in shaping what they see.

generative-ai/health/co-design/arxiv

papersTODAY 04:00 UTC

Multi-Method Study Tests Whether Existing Design Guidance Fits AI Companions

A new arXiv paper examines how well established design recommendations apply to AI companions, conversational agents built on large language models that aim to foster emotional bonds rather than complete practical tasks. Using several research methods, the authors assess where conventional design guidance holds up and where it falls short for this emotionally oriented class of systems. The work is posted as a cross-listing on arXiv cs.AI.

ai-companions/hci/design/llm

papersTODAY 04:00 UTC

Study maps how people treat LLMs as authorities on personal dilemmas

A new arXiv paper examines the trend of users consulting large language models as all-knowing authorities on subjective personal questions. The authors propose a typology of this behavior and LLM-based measurement methods, citing concerns about user autonomy and well-being. The work is categorized as a cross-listing on arXiv cs.AI.

research/safety/user-behavior/llm-reliance

papersTODAY 04:00 UTC

arXiv Paper Examines How Users Mistreat Conversational AI Systems

A new arXiv preprint studies how users direct hostility, coercion, and adversarial pressure at conversational AI models, an area the authors say is often overlooked in favor of research on model-generated harms. The paper argues that understanding when and why such mistreatment happens is needed to correctly interpret model behavior and alignment drift. It appears under the cs.AI category as a new submission.

safety/alignment/conversational-ai/user-behavior

papersSEP 12 04:00 UTC

arXiv paper proposes interaction contracts for agents embedded in existing software

A new arXiv preprint examines the coordination challenges that arise when an AI agent is embedded inside an existing application, where users may change goals or edit shared objects while the agent is still acting on earlier instructions. The authors argue that reliable integration depends on explicit interaction contracts plus ongoing verification of the agent's behavior during execution. The work frames this as a continuous assurance problem rather than a one-time setup step.

agents/software-engineering/safety/arxiv

papersSEP 10 04:00 UTC

Pairit Introduces a Platform for Live Experiments on Human-AI Collaboration

Researchers have unveiled Pairit, a programmable platform for running live experiments in which human participants and AI systems coordinate, delegate tasks, and make decisions together. The tool is aimed at studying organizational design questions as AI becomes part of real-time group work, supporting sessions that mix human-to-human and human-AI interaction.

human-ai-collaboration/research-tools/platform/experiments