Reassessing Collaborative Writing Theories and Frameworks in the Age of LLMs: What Still Applies and What We Must Leave Behind

TL;DR

This paper critically reviews existing human-human collaborative writing theories to evaluate their applicability to human-AI collaboration, highlighting process shifts caused by AI and proposing a prototyping approach for better interaction design.

Contribution

It offers a theoretical reassessment of collaborative writing frameworks in the context of AI, and introduces practical design implications for human-AI writing tools.

Findings

AI delegation shifts cognitive processes from planning/translating/reviewing to planning/waiting/reviewing

Waiting periods in AI-assisted writing can disrupt the writing process

Prototyping with smaller chunks enables faster iteration and maintains cognitive flow

Abstract

In this paper, we conduct a critical review of existing theories and frameworks on human-human collaborative writing to assess their relevance to the current human-AI paradigm in organizational workplace settings, and draw seven insights along with design implications for human-AI collaborative writing tools. Our main finding was that, as we delegate more writing to AI, our cognitive process shifts from the traditional planning/translating/reviewing process to a planning/waiting/reviewing process, breaking the process due to the waiting that occurs in between. To ensure that our cognitive process remains intact, we suggest a "prototyping" approach, where the tool allows for faster iterations of the cognitive process by starting with smaller chunks of text, and gradually moving on to a fully fleshed-out document. We aim to bring theoretical grounding and practical design guidance to the interaction designs of human-AI collaborative writing, with the goal of enhancing future human-AI writing software.