arXiv AI

Human-AI Agent Interaction in a Business Context

arXiv:2606. 18716v1 Announce Type: cross Abstract: As AI agents are increasingly integrated into core business processes, understanding and designing effective interaction patterns between humans and AI agents becomes crucial for value creation.

arXiv AI
Jun 10

Human-AI Coordination Zones: A Framework for Designing Human-in-the-Loop Experiences with Agentic AI

arXiv:2606. 09848v1 Announce Type: cross Abstract: As generative and agentic AI becomes embedded in everyday products, practitioners face a persistent challenge: how to design human-AI coordination -- the ongoing mutual adjustment between users and AI systems as mediate through interfaces-that supports usability, trust, and safety.

By James Pierce, Vaiva Kalnikait\.e, Siddharth Gupta, Brian Granger
arXiv Machine Learning
Aug 4

From Information to Delegation: Mapping Human-AI Financial Decision Making

arXiv:2608. 02100v1 Announce Type: cross Abstract: As AI increasingly participates in human decision making, understanding how decision-making authority is distributed between humans and AI has become a fundamental behavioural question.

By Iman Munire Bilal, Yingcan Carol Wang, Ajan Raj, Filippo Giovagnini, Pranav Tewari, Yuwei Zhang, Mei-Chen Zoe Liou, Qamar Zaman
arXiv AI
Jun 10

How can we assess human-agent interactions? Case studies in software agent design

arXiv:2510. 09801v3 Announce Type: replace Abstract: While benchmarks measure the accuracy of LLM-powered agents, they mostly assume full automation, failing to represent the collaborative nature of real-world use cases.

By Valerie Chen, Rohit Malhotra, Xingyao Wang, Juan Michelini, Xuhui Zhou, Aditya Bharat Soni, Hoang H. Tran, Calvin Smith, Ameet Talwalkar, Graham Neubig