Current developments of Psychological Research and the use of AI

Abstract

AI systems learn statistical regularities from large datasets to generate, classify, or transform information, producing outputs that are fluent and often difficult to distinguish from human-generated content.In research contexts, they can assist with idea development and study design, literature review and synthesis, data handling and analysis, writing and editing, publication support, communication, and ethical compliance (Khalifa & Albadawy, 2024).However, because such generative systems optimize for plausibility rather than truth, they may fabricate references, distort findings, obscure analytic assumptions, and reproduce embedded biases (Lund et al., 2023).Our aim is to use this editorial to show the journal's seriousness concerning AI and to maintain the trust of the journal's readers in our work.To do so, we think that now more than ever, rigorous peer review is important.The more expert the reviewer is on the topic, especially those with published papers on the subject and cited in the submission, the higher the quality of the peer reviews the journal receives (Resnik & Elmore, 2016).In many instances where we have identified papers that challenge scientific integrity (e.g., fabricated papers or plagiarism), the reviewers had papers on that topic and were also cited in the reference list.This perspective on the importance of expert reviewers who are highly active in relevant research fields is consistent with the general strategy of the publisher of this journal.Despite the potential benefit of AI, Springer Nature also stresses that it is more important than ever to have the involvement of a human in all steps of the publication process ( h t t p s : / / l i n k .s p r i n g e r .c o m / b r a n d s / s p r i n g e r / j o u r n a l -p o l i c i e s).Another risk of AI is that papers do not contain reliable findings.To reduce this risk, we aim to more actively invite and encourage replication studies and apply, among others, Psychological Research's new article type "Registered Replications" (Strobach & Estudillo, 2025), because replications are also more important than ever.In cases where results may be fabricated (something that is often impossible to detect during peer review), the value of replication becomes critical.Emphasizing and favoring well-designed replication studies would strengthen the journal's as well as

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