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The integration and implications of artificial intelligence in forensic science

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Abstract

This commentary explores the integration of artificial intelligence (AI) in forensic science and its potential implications. The applications of AI in forensic disciplines such as medicine, forensic anthropology, digital forensics, and taphonomy have enhanced the accuracy and efficiency of identification processes and the analysis of digital evidence. However, this rapid advancement prompts critical considerations in privacy, data protection, bias and fairness, and the accuracy and reliability of AI systems. The inherent challenges of the “black box” nature of AI algorithms call for transparency and accountability to maintain trust and uphold the integrity of forensic investigations. Ethical use, legal compliance, interdisciplinary collaboration, education, data integrity, standardization, human oversight, and societal impact, along with sustainability are identified as pivotal areas requiring urgent attention. The discussion underscores the need for rigorous scrutiny, standardized operating procedures, and proactive dialogue to ensure the responsible advancement of AI in forensic science.

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Acknowledgements

The author would like to acknowledge the use of ChatGPT in the planning stages of this manuscript.

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Correspondence to Paige Tynan.

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Tynan, P. The integration and implications of artificial intelligence in forensic science. Forensic Sci Med Pathol (2024). https://doi.org/10.1007/s12024-023-00772-6

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