Paper Title
Harnassing AI in Criminal Justice: Transforming Predictive Policing and Forensic Evidence Analysis
Article Identifiers
Authors
Komal Goswami , Malavika Murali
Keywords
AI Algorithms, Bias Mitigation, Criminal Justice Ethics, Forensic Evidence Analysis, Predictive Policing.
Abstract
Artificial intelligence (AI) has become a significant factor in the criminal justice system, particularly in predictive policing and forensic evidence analysis. Predictive policing is the use of AI algorithms to analyse previous crime data, detecting patterns and trends that assist law enforcement organisations in forecasting where future crimes are likely to occur. This proactive method strives to optimise police resource allocation, reduce crime, and improve public safety. The promise of predictive policing stems from its ability to reduce crime rates through data-driven initiatives. However, this technology raises serious issues about privacy, civil liberties, and the possibility of reinforcing existing biases in policing procedures. AI algorithms in predictive policing frequently rely on data that may reflect historical preconceptions, resulting in biased decisions. For example, if some neighbourhoods are overrepresented in the data, the AI model may unfairly target those places, repeating a cycle of over policing and mistrust. To solve these concerns, it is critical to create effective bias detection and mitigation approaches, enhance AI algorithm transparency, and retain human oversight to prevent discriminatory practices. In addition to predictive policing, AI has transformed forensic evidence analysis, increasing the accuracy and efficiency of investigations. AI-powered systems can analyse complicated data sets, such as DNA, fingerprints, and digital evidence, with greater accuracy than traditional approaches. AI algorithms, for example, can quickly evaluate massive amounts of DNA samples, discovering matches and offering crucial leads in criminal investigations. Similarly, AI can help with digital forensics by analyzing massive amounts of digital data like emails, social media activity, and electronic transactions to find evidence of criminal conduct. Artificial intelligence offers substantial advantages in forensic evidence analysis. By automating mundane processes and giving complex analytical skills, AI can eliminate human error, speed up case processing, and improve the reliability of forensic evidence. However, integrating AI into forensic analysis raises certain obstacles. Ensuring the legitimacy and reliability of AI-generated evidence is critical, because errors or biases in the analysis could have serious consequences for justice. To ensure fair trial standards, courts must be able to scrutinize AI methodology and comprehend the limitations of AI-generated evidence. Ethical and legal considerations are critical to the use of AI in criminal justice. Establishing clear norms and guidelines is critical for governing the use of AI technologies, protecting individual rights, and maintaining public trust. This includes creating explainable AI models that bring transparency into decision-making processes, as well as adopting rigorous auditing procedures to assure accountability. To summarise, AI shows significant promise for improving predictive policing and forensic evidence analysis in the criminal justice system. However, realizing this promise necessitates careful consideration of the ethical, legal, and societal consequences. By emphasizing openness, accountability, and fairness, the criminal justice system can use AI technology to improve outcomes while upholding the concepts of justice and equity.
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How To Cite
"Harnassing AI in Criminal Justice: Transforming Predictive Policing and Forensic Evidence Analysis", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.9, Issue 8, page no.e181-e192, August-2024, Available :https://ijnrd.org/papers/IJNRD2408416.pdf
Issue
Volume 9 Issue 8, August-2024
Pages : e181-e192
Other Publication Details
Paper Reg. ID: IJNRD_227265
Published Paper Id: IJNRD2408416
Downloads: 000121165
Research Area: Other
Country: Bengaluru, Karnataka, India
Published Paper PDF: https://ijnrd.org/papers/IJNRD2408416.pdf
Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2408416
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Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)
ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
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