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FAQ Künstliche Intelligenz und gute wissenschaftliche Praxis - Version 2

FAQ Artificial Intelligence and Research Integrity - Version 2
Authors: Frisch, Katrin;

FAQ Künstliche Intelligenz und gute wissenschaftliche Praxis - Version 2

Abstract

Diese FAQ versammeln Fragen, die uns häufig im Zusammenhang mit künstlicher Intelligenz (KI) und guter wissenschaftlicher Praxis (GWP) erreichen. Die vorliegende Version 2 enthält Updates und Erweiterungen der ursprünglichen Fassung vom November 2024. Die FAQ beschränken sich dabei auf generative KI, insbesondere Large Language Models (LLM), die Forschenden seit der Markteinführung von ChatGPT im November 2022 in verschiedensten Tools zur Verfügung stehen. Die Antworten sollen bei der Orientierung in einem schnelllebigen Thema helfen, ohne dabei präskriptiv zu sein. Sie stellen keine offizielle Positionierung des Ombudsgremiums für die wissenschaftliche Integrität in Deutschland (OWID) dar, sondern beschreiben den Status Quo und ordnen bereits bestehende Empfehlungen aus Sicht der GWP ein, identifizieren Lücken und verweisen auf weiterführende Literatur. Diese FAQ richten sich primär an Forschende sowie an Ombudspersonen, die Forschende in Bezug auf Fragen zur KI beraten. Für die Nutzung von KI in der Lehre und in studentischen (Qualifikations-)Arbeiten sind i.d.R. universitäre KI-Richtlinien, angepasste Prüfungsordnungen und Selbstständigkeitserklärungen sowie Entscheidungen individueller Lehrpersonen maßgeblich. Daher werden eventuelle Besonderheiten von KI in der Lehre und in Prüfungsangelegenheiten in diesen FAQ nicht besprochen.

This FAQ compiles a set of questions that we frequently receive regarding artificial intelligence (AI) and research integrity (RI). This version 2 is an updated and extended version of the original FAQ document, published in November 2024. The scope of the FAQ is limited to generative AI, especially Large Language Models (LLMs) that are the basis of many tools available to researchers since the launch of ChatGPT in November 2022. The aim is to offer guidance in a fast-paced debate without being prescriptive. This FAQ does not constitute an official statement on the use of AI by the Ombuds Committee for Research Integrity in Germany (OWID). Instead, it describes the status quo, contextualises existing recommendations, identifies gaps and provides further literature. The intended audience are researchers as well as research integrity advisors. The FAQ does not cover questions concerning student use of AI, since this is usually regulated by university policies, examination regulations (Prüfungsordnungen), declarations of originality (Selbstständigkeitserklärungen) as well as individual decisions made by lecturers.

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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.
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    influence
    This indicator 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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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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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!
1
Average
Average
Average
Green