  Academic writing is an indispensable yet laborious part of the research
enterprise. This Perspective maps out principles and methods for using
generative artificial intelligence (AI), specifically large language models
(LLMs), to elevate the quality and efficiency of academic writing. We introduce
a human-AI collaborative framework that delineates the rationale (why), process
(how), and nature (what) of AI engagement in writing. The framework pinpoints
both short-term and long-term reasons for engagement and their underlying
mechanisms (e.g., cognitive offloading and imaginative stimulation). It reveals
the role of AI throughout the writing process, conceptualized through a
two-stage model for human-AI collaborative writing, and the nature of AI
assistance in writing, represented through a model of writing-assistance types
and levels. Building on this framework, we describe effective prompting
techniques for incorporating AI into the writing routine (outlining, drafting,
and editing) as well as strategies for maintaining rigorous scholarship,
adhering to varied journal policies, and avoiding overreliance on AI.
Ultimately, the prudent integration of AI into academic writing can ease the
communication burden, empower authors, accelerate discovery, and promote
diversity in science.
