{"title":"The dual edge of AI: advancing and endangering scientific integrity in chemistry","authors":"Erdal Yabalak","doi":"10.1007/s43681-025-00829-y","DOIUrl":null,"url":null,"abstract":"<div><p>The integration of artificial intelligence (AI) into environmental and analytical chemistry presents both transformative opportunities and serious risks to scientific integrity. AI offers increasingly advanced capabilities in data interpretation, process automation, and predictive modeling, while its uncritical use—particularly in generating scientific texts—raises concerns about bias, error propagation, and ethical accountability. This article is a conceptual and critical analysis, not an experimental report. It critically examines the dual impact of AI on scientific research, highlighting potential threats to rigor, transparency, and authorship. The article also discusses the transformative benefits of AI in enhancing analytical efficiency, real-time monitoring, and predictive modeling in chemical research. The article emphasizes the need for robust oversight, ethical frameworks, and the preservation of human expertise in AI-assisted studies. By exploring AI-generated outputs and evaluating their implications through expert critique, this work aims to foster responsible and informed integration of AI in chemistry. Recommendations are provided for researchers, editors, and institutions to safeguard the credibility and trustworthiness of scientific communication in the era of AI.</p><h3>Graphical abstract</h3><div><figure><div><div><picture><source><img></source></picture></div></div></figure></div></div>","PeriodicalId":72137,"journal":{"name":"AI and ethics","volume":"5 5","pages":"4635 - 4643"},"PeriodicalIF":0.0000,"publicationDate":"2025-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"AI and ethics","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.1007/s43681-025-00829-y","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The integration of artificial intelligence (AI) into environmental and analytical chemistry presents both transformative opportunities and serious risks to scientific integrity. AI offers increasingly advanced capabilities in data interpretation, process automation, and predictive modeling, while its uncritical use—particularly in generating scientific texts—raises concerns about bias, error propagation, and ethical accountability. This article is a conceptual and critical analysis, not an experimental report. It critically examines the dual impact of AI on scientific research, highlighting potential threats to rigor, transparency, and authorship. The article also discusses the transformative benefits of AI in enhancing analytical efficiency, real-time monitoring, and predictive modeling in chemical research. The article emphasizes the need for robust oversight, ethical frameworks, and the preservation of human expertise in AI-assisted studies. By exploring AI-generated outputs and evaluating their implications through expert critique, this work aims to foster responsible and informed integration of AI in chemistry. Recommendations are provided for researchers, editors, and institutions to safeguard the credibility and trustworthiness of scientific communication in the era of AI.
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