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ZENODO
Report . 2023
License: CC BY
Data sources: ZENODO
ZENODO
Report . 2023
License: CC BY
Data sources: Datacite
ZENODO
Report . 2023
License: CC BY
Data sources: Datacite
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Research Integrity and Generative AI

Authors: Duckham, Matt; Scholer, Falk; Barr, Daniel; Blades, David; Cheng, Chi-Tsun (Ben); Falzon, Brian; Forsyth, Anthony; +14 Authors

Research Integrity and Generative AI

Abstract

This White Paper explores the implications for research integrity of recent advances in generative artificial intelligence (AI). Our objective is to support researchers in safely and responsibly understanding and managing the issues that may arise for research activities that involve generative AI tools. Our scope includes generative AI technologies that facilitate generation of text, computer code, images, artwork, and other media, and particularly those that involve generation from a linguistic (user-specified) prompt. The White Paper covers five main topics: A summary of the characteristics and capabilities of generative AI tools. A review of the enduring role of established Research Integrity principles, which continue to guide the conduct of all research, whether or not it involves the use of AI tools at any stage. The identification of seven key areas of elevated risk for research integrity in misuse of generative AI, including research falsification, misinformation, transparency, reproducibility, and bias. The identification of emerging opportunities for progress in the responsible conduct of research using generative AI with potential benefits to research, researchers, and wider society. The suggestion of selected actions to assist in maintaining or enhancing research standards and integrity in the face of both positive and negative disruptions that generative AI tools, such as ChatGPT, may cause to research activities.

Related Organizations
Keywords

generative AI, research integrity, large language models, artificial intelligence

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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Average
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green
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