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Artificial Intelligence (AI) has been increasingly integrated into clinical and neuroscientific research methods over the last decade, expanding on methods and results while raising ethical concerns. Concerns about patient privacy, scientific and clinical validity, neuro-discrimination, and anthropomorphism have been evaluated in the literature (Salles, et al., 2020, Ienca and Ignatiadis, 2020, Timmons, et al., 2022). A literature review was conducted to evaluate the potential benefits as well as the potential concerns associated with recent AI developments over the last 5 years in the fields of neuroscience and psychology. 30 articles were reviewed using Google Scholar and PubMed. Search terms included AI and neuroscience, deep learning neuroscience, AI and neuroscience ethics, AI phenomenology, AI psychological diagnosis, and AI deep learning concerns. Key findings include enhanced speed of diagnosis in medical cases and the accuracy of neuroimaging due to assistance from Deep Learning (DL) algorithms. Using DL, scientists have utilized AI to decrease artifacts and noise in imaging (Zhu, et al., 2019). In terms of research, researchers have utilized AI to conduct novel studies, including using AI to decode semantic thought (Tang, et al., 2023). Additionally, DL AI has been able to evaluate neuroimaging scans and, in some cases, diagnose medical disorders earlier than would otherwise be possible (Ahila, et al., 2022, Shaver, et al. 2019). Some of these studies suggest the possibility of using DL AI for diagnosing psychological disorders in the future. However, reservations remain regarding equivalent success or application in psychology. Concerns include misrepresentation of the phenomenological experience of patients and bias in diagnoses derived from limited and biased data in the learning process (Timmons, et al., 2022, Monteith et al., 2022). Further research and analysis of ethical implications of AI are needed to establish appropriate regulations of universal use in psychology.



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