Over the years, forensic science has undergone a significant transition from “trust the examiner” to “trust the scientific method”.
This transition has been driven by technological advancements involving DNA analysis, artificial intelligence (AI), and three-dimensional (3D) reconstruction strategies. The current article highlights the top five technologies revolutionizing forensic science today.
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DNA Phenotyping
DNA extracted from biological samples recovered in the course of criminal investigations is powerful evidence because if the DNA profiles of the samples match with those present in the DNA database, it can help identify the perpetrator. In standard forensic DNA profiling, short tandem repeat (STR) polymorphisms help identify individuals from DNA samples obtained at crime sites.
Forensic DNA phenotyping (FDP) goes beyond standard forensic DNA profiling by enabling the prediction of an individual’s physical appearance, age, and biogeographic ancestry based on DNA samples.1 Therefore, FDP provides information that helps investigators detect unknown perpetrators, which is not possible by forensic STR-profiling alone.
FDP techniques are based on single nucleotide polymorphism (SNP) markers statistically associated with particular characteristics via genome-wide association studies.
In comparison to other physiological characteristics, human pigmentation traits are influenced by a relatively small number of genes. FDP focuses on pigmentation traits, including eye, hair, and skin color, using forensically validated IrisPlex, HirisPlex-S, and HIrisPlex assays.
FDP can be used in criminal cases where there are no eyewitnesses. It can also corroborate an eyewitness testimony, which is important because eyewitnesses can testify falsely for multiple reasons.
Investigators have successfully used FDP to solve many cold cases. For example, in 2017, they were able to solve the rape and murder case of Milica van Doorn that occurred in 1992.
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AI Empowering Digital Forensics
Digital forensics has been defined as the process of finding, collecting, validating, documenting, analyzing, interpreting, and presenting digital evidence linked to cybercrime. The advent of AI has significantly empowered digital forensics by enabling the screening of enormous amounts of digital evidence via automated searches of videos, images, language, and audio files to identify relevant data.2
AI algorithms, through the combination of Machine Learning (ML) and Natural Language Processing (NLP) enable the identification of patterns and anomalies that could be otherwise difficult to detect. AI allows real-time analysis of transactions, enabling rapid response to fraudulent activities. ML can dynamically adapt to new fraud tactics via continual learning and improvement in effectiveness over time.
The key advantage of AI-driven digital forensics is the rapid analysis of large volumes of data and the identification of subtle correlations and nuanced irregularities that were highly unlikely to be detected by traditional manual analysis.
Furthermore, AI’s automation and learning help streamline time-consuming tasks, such as data collection and report generation, thereby offering investigators more time to devote to investigation work.
Next-Generation Fingerprint Analysis
The Next Generation Identification (NGI) system is developed and maintained by the FBI’s Criminal Justice Information Services (CJIS) Division.3 This system is considered one of the largest biometrics databases in the world, and it includes fingerprints, palmprints, faces, iris, and tattoos.
The primary purpose of the NGI system is to identify unknown latent prints against a large repository of known records using the Multi-Biometric Identification System (MBIS) or the Universal Latent Workstation (ULW) software.
Since its inception in 2013, the NGI system has continued to grow to enhance its functionalities. The incorporation of the latent print matching algorithm in the NGI system has significantly improved search strategies.
Nanotechnology has been used to improve DNA fingerprint analysis, particularly when prints are mild or faded. Fluorescence nanoparticles have been used in forensic science to develop latent fingerprints.4 Nanotechnology has been further explored to detect poisons and gun residues in trace levels.
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Forensic Genealogy
Over the years, DNA analysis technology has undergone significant improvement. An increase in public interest in using genetics for genealogical research has substantially enhanced the publicly available databases.5
When genealogical research is conducted by experienced and ethical researchers, credible conclusions can be reached regarding an individual’s family lineage.
Over the years, novel techniques developed to find ancestors using commercial databases have been exploited to determine perpetrators of unsolved criminal cases.
Forensic Genealogy (FG), also commonly referred to as Investigative Genetic Genealogy (IGG) or Forensic Genetic Genealogy (FGG), is a novel investigative tool that combines the field of forensic genetics with genetic and conventional genealogy.6
FG uses non-DNA genealogical methods to identify or find heirs. Investigators use this approach to identify living descendants of fallen soldiers for their repatriation, as well as other historical investigations. It is also used to identify unidentified human remains (UHRs) or perpetrators of violent crimes. In 2018, FG was used to resolve the identity of the Golden State Killer.
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3D Crime Scene Reconstruction
Various imaging techniques, such as postmortem computed tomography (PMCT) and magnetic resonance (MR) scanning, photogrammetry, and surface scanning, serve as examination tools in forensic pathology and crime scene investigations.7 These imaging techniques offer non-invasive and non-destructive documentation of individuals and crime scenes.
The detailed documentation of external and internal features of bodies and crime scene evidence allows the generation of high-resolution and precise 3D models.
Incorporating 3D models of victims, the crime scene, and perpetrators into a single virtual environment helps investigators to test their hypotheses in the investigation stage. Furthermore, digitally stored crime scene images can be assessed at any time by investigators, facilitating the review of cold cases and enabling virtual crime scene reconstructions.
Future Trends in Technologies Used in Forensic Science
Scientific breakthroughs driven by technological advancements have revolutionized the field of forensic science. Amongst different technologies, automation has significantly contributed to reshaping the landscape of forensic science.
Automation in DNA analysis, ballistic and fingerprinting analysis, and recreation of crime scenes have meaningfully assisted investigators with rapid and comprehensive analysis of evidence. Several studies have also indicated the use of omics techniques in forensic research.
Reference
- Schneider PM, Prainsack B, Kayser M. The Use of Forensic DNA Phenotyping in Predicting Appearance and Biogeographic Ancestry. Dtsch Arztebl Int. 2019;51-52(51-52):873-880. doi: 10.3238/arztebl.2019.0873.
- Tynan P. The integration and implications of artificial intelligence in forensic science. Forensic Sci Med Pathol. 2024;20(3):1103-1105. doi: 10.1007/s12024-023-00772-6.
- Tom KR, Knorr KB, Davis CE. Next Generation Identification system: Latent print matching algorithm and casework practices. Forensic Sci Int. 2022;332:111180. doi: 10.1016/j.forsciint.2022.111180.
- Wang M, Li M, Yu A, Zhu Y, Yang M, Mao C. Fluorescent Nanomaterials for the Development of Latent Fingerprints in Forensic Sciences. Adv Funct Mater. 2017 Apr 11;27(14):1606243. doi: 10.1002/adfm.201606243.
- Tuazon OM, Wickenheiser RA, Ansell R, Guerrini CJ, Zwenne GJ, Custers B. Law enforcement use of genetic genealogy databases in criminal investigations: Nomenclature, definition and scope. Forensic Sci Int Synerg. 2024;8:100460. doi: 10.1016/j.fsisyn.2024.100460.
- Glynn CL. Bridging Disciplines to Form a New One: The Emergence of Forensic Genetic Genealogy. Genes (Basel). 2022;13(8):1381. doi: 10.3390/genes13081381.
- Carew RM, French J, Morgan RM. 3D forensic science: A new field integrating 3D imaging and 3D printing in crime reconstruction. Forensic Sci Int Synerg. 2021;3:100205. doi: 10.1016/j.fsisyn.2021.100205.