Technology has increasingly been used in committing a crime and also in law enforcement agencies. However, there is a need to develop more sophisticated technology to curb the increasingly high tech crime and also ensure that the right decision is made that give assurance of justice. Many procedures in the law enforcement department have been used in suspect identification including lineups, showups, and identification using photographs. However, the use of these methods has in some instances proved unsatisfactory. Therefore, some innovations and modifications have been considered to ensure more accurate identification
The use of the Big Data trend in the criminal expert department for suspect identification (Hummer & Byrne, 375). Apart from helping to recognize crime trends, Big data allows for the storage of in the database that can be used in the identification of suspects. In the United States, this can be achieved by law enforcement agencies reporting in the National Incidence Based System (NIBRS) to increase transparency and allow for a clear view of the crime.
Rapid Identification System which has improved as a result of the development of Big data enables a police officer to view the history of a criminal fast through a basic search. The FBI's Next Generation Identification System (NGI) system uses biometrics such as fingerprints, palm prints to match up suspects with their criminal history information (National Research Council, 146).
A recommendation to implement the double-blind lineup and procedures of photo Array (National Research Council, 146). Double blinding will assist minimize the risk that an experiment might mistakably bias the research outcome by finding only the things they already expect to see. Double blinding reduces bias in a way that the administrator is not made known the composition of the lineup or photo array. Therefore, if the administrator becomes unaware, then it means that the witness cannot be influenced in making a choice.
The good faith exception is a legal principle that provides exception to the exclusionary rule. The exception is that the illegally gathered evidence can be accepted at trial when the police have reason to trust their action is legal. Additionally, the rule permits the court to take into consideration the mental state of the officer. Exclusionary rule protects individuals from mistakes of police officers. The rule causes the evidence that was wrongly taken not acceptable in court but the good faith rule work as an exception to it.
Conclusion
To conclude, the police department is aware that there is a necessity to adopt technology trends to improve n their operations. Suspect identification is not abandoned when it comes to technology adaptation. The technologies proposed and some already taken include the use of big data, the rapid identification system and the recommendation to adopt the double line up process of suspect identification. The original exclusionary rule held police officer strictly responsible for the destruction of the constitutional laws but the good faith is an exception in such case.
Works Cited
Hummer, Don, and James Byrne. "Technology, innovation and twenty-first-century policing." The Routledge Handbook of Technology, Crime and Justice. Taylor and Francis, 2017. 375-389.
National Research Council. Identifying the culprit: Assessing eyewitness identification. National Academies Press, 2015.
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Essay Example on Tech Crime: Balancing Justice and Security With New Technologies. (2022, Dec 27). Retrieved from https://proessays.net/essays/essay-example-on-tech-crime-balancing-justice-and-security-with-new-technologies
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