AI in Forensic Science, Data Management and Law

The book provides a complete overview of forensic science, AI, and data management in law and business. It reviews the applications of AI and advanced data management methods across various legal and forensic domains. Topics discussed include digital forensics, predictive modelling, automatic classification, anomaly detection, cold case analysis, metadata analysis, and pattern recognition using blockchain technology.

The book explores the cutting-edge intersection of fields such as ethical AI in legal systems, forensic science, data privacy, and forensic accounting laws. It examines the ethical implications of integrating computational intelligence including AI and machine learning into legal and judicial systems. The challenges and opportunities of applying AI to decision-making in human rights contexts are analysed, with emphasis on transparency, accountability, and fairness in algorithmic decision-making within legal frameworks.

Further, it evaluates the intersection of data privacy and human rights with respect to biometric data collection, discussing the implications of mass surveillance, data harvesting, and profiling on individual privacy and civil liberties. The book also investigates how computational intelligence can be used to analyse large-scale datasets and enhance legal research and decision-making within the framework of human rights and the rule of law.

Key Features:

• Studies the use of AI in criminal scene management
• Reviews the use of AI in data handling
• Reviews anomaly detection in companies
• Evaluated the use of AI in legal assistance
• Covers emotion and sentiment analysis by AI in criminal matters