The legitimacy of evidence obtained from artificial intelligence and its validity in criminal evidence.

Amid the accelerating digital transformations shaping our era, artificial intelligence (AI) has emerged as a central technological force impacting nearly every field including the realm of criminal justice. This research arises from a critical legal question: To what extent can AI generated evidence be considered lawful and reliable proof for establishing criminal liability under current procedural regulations and fundamental legal safeguards? Unlike traditional evidence derived from human testimony or direct documentation AI based evidence is extracted through complex algorithmic systems whose mechanisms may be opaque even to investigators or judges. The study explores the role of AI in contemporary security practices, presenting types of digital evidence it yields: facial recognition outputs, behavioral pattern analyses, emotional recognition in public spaces, and probabilistic crime prediction based on big data profiles. The study concludes that AI-derived evidence can serve as effective proof in criminal proceedings if certain legal and technical safeguards are met, including algorithmic transparency, challengeability of digital outputs, traceability of data sources, and sufficient judicial training. It recommends legislative reforms to define the scope, standards, and accountability surrounding the use of AI-driven evidence, ensuring a fair balance between technological efficiency and the preservation of justice.