arXiv AI By Rida Qadri, Remi Denton, Michael Madaio, Mahima Pushkarna, Leslie Lai, Sherry Moore, Michelle Chen Huebscher, Andrew Butcher, Ritom Sen, Hsiao-Yu Tung, Shaan Mathur, Yimeng Liu, Shibl Mourad, Noah Fiedel, Edward Grefenstette, Michael Terry

Working with Agentic `Teammates': When a New Organizational Actor Collides with the Human Ecosystem of Work

Read the original on arXiv AI →

The paper reports an in‑situ qualitative study of a persistent, proactive AI teammate deployed across multiple teams in a large technology company. It finds that the human‑agent workplace is in flux, with breakdowns and negotiations emerging around tacit workflow rules, the relational boundaries of the non‑human actor, and the redistribution of trust and human agency. These micro‑negotiations are used to propose a new research, design, and organizational agenda that seeks to preserve human agency when sharing workspaces with non‑human actors.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

arXiv AI
Aug 18

Position: AI Agents in Scientific Teams Should Be Studied as Human-Agent Systems

arXiv:2608. 14667v1 Announce Type: new Abstract: Large language model-based agents are increasingly deployed as collaborators in scientific discovery yet most current work focuses on the autonomous capabilities of "AI Scientists".

By Patrick Emami, Sameera Horawalavithana, Truc Nguyen, Gihan Panapitiya, Bruno Jacob, Siddhisanket Raskar, Saumya Sinha, Jared D. Willard, Andrew Glaws, Nithin Somasekharan, Ling Yue, Brian Lu, Shaowu Pan, Jason Eisner
arXiv AI
Sep 11

Pairit: A Platform for Live Experiments on Human-AI Collaboration

Pairit is an online platform that enables researchers to design, test, and deploy live experiments on human-AI collaboration. Using a single YAML configuration file, users can specify an executable experiment graph—including pages, routing, randomization, matchmaking, chat, shared workspaces, server-hosted agents, surveys, timers, and custom HTML components—and combine any number of humans and AI agents in real-time sessions. The platform has been validated through multiple live deployments, including peer-reviewed studies, and captures high-resolution process traces of communication, negotiation, and collaborative work in human-AI dyads.

By Harang Ju, Sinan Aral
arXiv AI
1d ago

Human-AI Collaboration: From Paradoxes to Patterns

The paper demonstrates that humans and AI systems achieve better performance when collaborating rather than working alone. It investigates how two design dimensions—autonomy and initiative—shape collaboration patterns, using a paradox perspective to uncover internal tensions and map underlying paradoxes. From this analysis, the authors derive four distinct human‑AI collaboration patterns: Instruction, Delegation, Assistance, and Co‑creation.

By Michael Weiss