A research paper written by OpenAI’s GPT-o3:
The advent of advanced AI systems capable of generating academic text — including “chain-of-thought” large language models with test-time web access — is poised to significantly influence scholarly writing and publishing. This review discusses how academia, particularly in quantitative social science, should adjust over the next decade to AI-assisted or AI-written articles. We summarize the current capabilities of AI in academic writing (from drafting and citation support to idea generation), highlight emerging trends, and weigh advantages against risks such as misinformation, plagiarism, and ethical dilemmas. We then offer speculative predictions for the coming ten years, grounded in literature and present data on AI’s impact to date. An empirical analysis compiles real-world data illustrating AI’s growing footprint in research output. Finally, we provide policy and workflow recommendations for journals, peer reviewers, editors, and scholars, presented in an exhaustive table. Our aim is to inform a balanced approach to harnessing AI’s benefits in academic writing while safeguarding integrity
and transparency.
More here.
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