00000nam a22000008i 4500 UP-8027390931311452396 Buklod 20241206141530.0 a ||| u ta 241206s2024 njuda gr b 001 0deng 9781119813323(hardbound) 23124343 DLC DLAW rda eng HV 8078.7 A78 2024 Artificial intelligence (AI) in forensic sciences edited by Katrin Franke, Zeno Geradts. New Jersey JW-Wiley 2024. xii, 242 pages 24 cm text rdacontent unmediated rdamedia volume rdacarrier Forensic science in focus Includes bibliographical references and index. Introduction-- AI-based forensic evaluation in court: the desirability of explanation and the necessity of validation-- Machine learning for evidence in criminal proceedings: techno-legal challenge for reliability assurance-- Formalising representation and interpretation of digital evidence to reinforce reasoning and automated analysis—Servicing digital investigations with artificial intelligence-- On the feasibility of social network analysis methods for investigating large-scale criminal networks-- Mapping NLP techniques to investigation and investigative interviews-- The influence of compression on the detection of deepfake videos-- Event log analysis and correlation: a digital forensic perspective-- (Hyper-)graph analysis and its application in forensics-- Conclusions-- Index. "This book is in the AAFS Reference Series Library and serves a guide on using AI in forensic science. In Zeno's year of Presidency of the AAFS, one of the topics was Artificial Intelligence and the impact it can have on forensic science. In many forensic products Artificial Intelligence and Deep Learning is already included without the user being aware of it. Examples are software for facial and speaker comparison, many digital forensic packages for searching on for instance firearms. Furthermore, it is upcoming in chemometrics and many other fields. Also, the use of AI can impact forensic science, for instance on easier to make deepfakes, so spoofing evidence becomes easier. Different jurisdictions will handle the use of AI differently, depending on the laws. Examples are provided of good use of artificial intelligence, where the expert should be in the loop. The expert as well as the courts also needs to know the limitations of the approach. The book is composed out of chapters which can be used in a course, and will finalize with the newest research in developing approaches with graph neural networks. The book first does an introduction in the field as such, then it will go deeper in the legal issues with AI and the need for developing standard. Many examples of using AI are discussed and presented, such as smart cities, IoT in Hansken and at the end Also, the use of AI for making deepfakes will be discussed as well as how to detect it. The field develops rapidly, and much awareness is also being made by the European Commission on regulation of AI in practical use. In the United States NIST is working on standards on using Artificial Intelligence. New legislation is expected in many states, for example Colorado has legislation on use of facial recognition services and Vermont has legislation enacted on ethical use of artificial intelligence. One of the most significant applications of AI in forensic science is in the analysis of DNA evidence. DNA sequencing technology has advanced significantly in recent years, allowing scientists to analyze large amounts of genetic data quickly and accurately. However, the sheer volume of data generated by these techniques can be overwhelming for human analysts. AI algorithms can be used to quickly and accurately identify genetic markers that are associated with specific individuals or groups, making it easier for forensic scientists to identify suspects or eliminate suspects from an investigation"-- Provided by publisher. Artificial intelligence. Digital forensic science. Electronic evidence. Forensic sciences Data processing. Franke, Katrin editor. Geradts, Zeno J. editor. John Wiley & Sons publisher. Forensic science in focus. FO UPD DLAW HV 8078.7 A78 2024 Book