The artificial intelligence (AI) revolution: How important for scientific work and its reliable sharing

Jutel, Marek; Zemelka‐Wiącek, Magdalena; Ordak, Michał; Pfaar, Oliver; Eiwegger, Thomas; Rechenmacher, Maximilian; Akdiş, Cezmi A.

doi:10.1111/all.15778

Cited by 11 publications

(7 citation statements)

References 4 publications

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“…As Marek J. Magdalena Z. (2023) mentioned, AI-generated images are created by training models on vast amounts of data and using that data to generate novel visual content [1]. As Brownlee J.…”

Section: Participantmentioning

confidence: 99%

AIGC (Artificial Intelligence Generated Content) infringes the copyright of human artists

Zhuang

2024

ACE

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With the rapid development of artificial intelligence technology, content generated by artificial intelligence has been rapidly applied to people's lives. At the same time, it is also accompanied by many infringement lawsuits, whether AIGC has really caused different degrees of infringement to human artists. Through the analysis of the existing literature on copyright issues and the walkthrough of Stable Diffusion, an AI-generated image platform, this article digs into the main factors that the AI-generated platform causes infringements on human artists. Provide references for using AI by enterprises and related media, and let more scholars pay attention to this issue. The study found that in the workflow of the AI generation platform, taking Stable Diffusion as an example, the two processes of model training and image generation may cause copyright infringement to a certain extent. Based on this, the AI generation platform has unauthorized use of copyright works, excessive plagiarism and adaptation of copyright works, and the generated images are not marked with watermarks or sources, which damages the copyright owner's rights.

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Section: Participantmentioning

confidence: 99%

AIGC (Artificial Intelligence Generated Content) infringes the copyright of human artists

Zhuang

2024

ACE

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“…2 Some studies reported that among children with AD, Black children were more prone to develop AA, whereas White children were more likely to develop AR. 3,4 However, prior studies on racial differences in the Atopic march have focused primarily on child genetic and environmental factors but have not considered prenatal and maternal factors, which are known to affect child's immune system. 5 In this study, we sought to examine multiple early-life factors in relation to AD and the Atopic march in 1998 mother-child pairs from the Boston Birth Cohort (BBC), a long-term prospective cohort of high-risk (37.6% AD incidence), primarily urban, low-income, and racial/ethnic minority (80.9% Black and Hispanic) populations who have been historically underrepresented in atopic disease research (Figure S1).…”

Section: Early Life Risk Factors Of Atopic March In a High-risk Minor...mentioning

confidence: 99%

“…Linping Shu 1,2,3 Qunshan He 4 Bing Yan 1,2,3 Di Wu 1 Menglin Wang 1,2,3 Chengshuo Wang 1,2,3 Luo Zhang 1,2,3,5…”

Section: Ack N Owled G M Entsmentioning

confidence: 99%

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Human‐in‐the‐loop: Human involvement in enhancing medical inquiry performance in large language models

Shu,

He,

Yan

et al. 2023

Allergy

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“…An article published in June 2023 in Allergy pointed out that ChatGPT can generate reliable but incorrect and meaningless responses. For this reason, it is essential to keep expert supervision in mind when publishing this type of material [ 3 ]. A number of articles have been published in recent months assessing the accuracy of ChatGPT’s answers.…”

Section: Introductionmentioning

confidence: 99%

ChatGPT’s Skills in Statistical Analysis Using the Example of Allergology: Do We Have Reason for Concern?

Ordak

2023

Healthcare

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Background: Content generated by artificial intelligence is sometimes not truthful. To date, there have been a number of medical studies related to the validity of ChatGPT’s responses; however, there is a lack of studies addressing various aspects of statistical analysis. The aim of this study was to assess the validity of the answers provided by ChatGPT in relation to statistical analysis, as well as to identify recommendations to be implemented in the future in connection with the results obtained. Methods: The study was divided into four parts and was based on the exemplary medical field of allergology. The first part consisted of asking ChatGPT 30 different questions related to statistical analysis. The next five questions included a request for ChatGPT to perform the relevant statistical analyses, and another five requested ChatGPT to indicate which statistical test should be applied to articles accepted for publication in Allergy. The final part of the survey involved asking ChatGPT the same statistical question three times. Results: Out of the 40 general questions asked that related to broad statistical analysis, ChatGPT did not fully answer half of them. Assumptions necessary for the application of specific statistical tests were not included. ChatGPT also gave completely divergent answers to one question about which test should be used. Conclusion: The answers provided by ChatGPT to various statistical questions may give rise to the use of inappropriate statistical tests and, consequently, the subsequent misinterpretation of the research results obtained. Questions asked in this regard need to be framed more precisely.

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The artificial intelligence (AI) revolution: How important for scientific work and its reliable sharing

Cited by 11 publications

References 4 publications

AIGC (Artificial Intelligence Generated Content) infringes the copyright of human artists

AIGC (Artificial Intelligence Generated Content) infringes the copyright of human artists

Human‐in‐the‐loop: Human involvement in enhancing medical inquiry performance in large language models

ChatGPT’s Skills in Statistical Analysis Using the Example of Allergology: Do We Have Reason for Concern?

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