Summary of Llms As Research Tools: a Large Scale Survey Of Researchers’ Usage and Perceptions, by Zhehui Liao et al.
LLMs as Research Tools: A Large Scale Survey of Researchers’ Usage and Perceptions
by Zhehui Liao, Maria Antoniak, Inyoung Cheong, Evie Yu-Yen Cheng, Ai-Heng Lee, Kyle Lo, Joseph Chee Chang, Amy X. Zhang
First submitted to arxiv on: 30 Oct 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); Computers and Society (cs.CY); Digital Libraries (cs.DL); Human-Computer Interaction (cs.HC)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary Machine learning researchers are increasingly turning to large language models (LLMs) to augment or automate various aspects of their research workflow. While some have found benefits in using LLMs, others have raised concerns about the risks and ethics involved. To better understand how the research community uses and perceives LLMs as research tools, we conducted a large-scale survey of 816 verified research article authors. Our findings reveal that 81% of researchers have already incorporated LLMs into their workflow, with traditionally disadvantaged groups in academia (non-White, junior, and non-native English speaking researchers) reporting higher LLM usage and perceived benefits. However, women, non-binary, and senior researchers have greater ethical concerns, potentially hindering adoption. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Large language models are becoming popular tools for scientists. Many researchers are using them to help with their work, but some people are worried about the risks and ethics involved. A new study asked 816 scientists how they use these models and what they think of them. Most scientists (81%) said they already use large language models in their work. Some groups of scientists, like those from diverse backgrounds or who are just starting out, might benefit more from using these tools. However, some other groups of scientists, like women, non-binary people, or senior researchers, have concerns about the ethics of using these models. |
Keywords
» Artificial intelligence » Machine learning
