What's So Human about Human-AI Collaboration, Anyway? Generative AI and Human-Computer Interaction

TL;DR

This paper surveys the ACM 'acmart' LaTeX document class and its features for preparing ACM publications. It explains how the template consolidates diverse ACM/SIG formatting conventions into a single framework and how to select template styles and parameters to target different venues, including journals and conferences. It discusses built‑in accessibility and metadata extraction, as well as requirements for fonts, rights management, and metadata like CCS concepts and user-defined keywords. The practical outcome is a detailed guide enabling authors to produce camera-ready and submission-ready documents with correct formatting and rich metadata, improving consistency and discoverability in ACM digital libraries.

Abstract

While human-AI collaboration has been a longstanding goal and topic of study for computational research, the emergence of increasingly naturalistic generative AI language models has greatly inflected the trajectory of such research. In this paper we identify how, given the language capabilities of generative AI, common features of human-human collaboration derived from the social sciences can be applied to the study of human-computer interaction. We provide insights drawn from interviews with industry personnel working on building human-AI collaboration systems, as well as our collaborations with end-users to build a multimodal AI assistant for task support.