AINov 18, 2023

Best uses of ChatGPT and Generative AI for computer science research

arXiv:2311.11175v14 citationsh-index: 12
Originality Synthesis-oriented
AI Analysis

It addresses the problem of improving research efficiency for computer scientists, but it is incremental as it reviews existing uses rather than introducing new methods.

This paper explores how ChatGPT and generative AI can enhance computer science research productivity, focusing on applications like brainstorming, drafting papers, and synthesizing literature, while also noting limitations and non-recommended uses.

Generative Artificial Intelligence (AI), particularly tools like OpenAI's popular ChatGPT, is reshaping the landscape of computer science research. Used wisely, these tools can boost the productivity of a computer research scientist. This paper provides an exploration of the diverse applications of ChatGPT and other generative AI technologies in computer science academic research, making recommendations about the use of Generative AI to make more productive the role of the computer research scientist, with the focus of writing new research papers. We highlight innovative uses such as brainstorming research ideas, aiding in the drafting and styling of academic papers and assisting in the synthesis of state-of-the-art section. Further, we delve into using these technologies in understanding interdisciplinary approaches, making complex texts simpler, and recommending suitable academic journals for publication. Significant focus is placed on generative AI's contributions to synthetic data creation, research methodology, and mentorship, as well as in task organization and article quality assessment. The paper also addresses the utility of AI in article review, adapting texts to length constraints, constructing counterarguments, and survey development. Moreover, we explore the capabilities of these tools in disseminating ideas, generating images and audio, text transcription, and engaging with editors. We also describe some non-recommended uses of generative AI for computer science research, mainly because of the limitations of this technology.

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