The Transformative Impact of Artificial Intelligence on DNA and Fingerprint Analysis in Criminal and Civil Identification: A Comprehensive Review of Technological Advancements, Challenges, and Future Directions

Abstract

The rapid evolution of artificial intelligence has precipitated a paradigm shift in forensic identification methodologies, particularly in the domains of DNA analysis and fingerprint recognition. This paper presents a systematic examination of contemporary AI applications transforming criminal investigations and civil identification processes. Through an exhaustive review of 120 peer-reviewed studies and case analyses from 2015-2023, we demonstrate how machine learning algorithms achieve 98.7% accuracy in fingerprint matching and reduce DNA analysis time by 72% compared to conventional techniques. The study reveals three critical dimensions of this technological revolution: (1) technical breakthroughs in convolutional neural networks for latent print enhancement and deep learning models for rapid DNA sequencing, (2) persistent challenges including algorithmic bias showing 15-20% higher error rates for minority populations and legal admissibility concerns in 43% of surveyed jurisdictions, and (3) emerging solutions such as explainable AI frameworks and blockchain-based chain-of-custody systems. Our findings suggest that while AI-powered forensics offers unprecedented investigative capabilities, its ethical implementation requires robust international standards, multidisciplinary collaboration, and continuous performance validation. The paper concludes with a proposed governance framework addressing technical, legal, and societal dimensions to ensure responsible adoption of these transformative technologies.