Cyber Security

Chris Heckman
Old Dominion University
CYSE 201
Mr. Aslan
3/19/2024

Introduction
Digital criminal investigations stand out as one of the critical milestones in the sphere
of investigative processes, and by leveraging computer science tools, become the basis for
implementing computer science approaches, including mathematical tools, which are
intended to assist investigators with the identification and preservation of digital evidence
(Faqir, 2023). The emergence of AI in various aspects of criminal justice has taken it to the
next level. AI ushers in new criminal investigation techniques and the overall impact of the
justice system. The study Faqir provides a comprehensive method for integrating AI into
digital criminal investigations using qualitative, analytical, and descriptive approaches. It
illustrates that AI plays a pivotal role in the law enforcement infrastructure, such as
apprehension procedures, release decisions, sentencing processes, identification of criminal
activities, and the prediction of recidivism.
Relevance to social science principles
The article resonates with several social science concepts discussed in the PowerPoint
presentations. It highlights the crucial role of AI in law enforcement, encompassing aspects
such as arrest procedures, release decisions, sentencing processes, and recidivism prediction.
As discussed in the presentations, these elements directly relate to social control, where
formal and informal mechanisms uphold societal norms and values. Additionally, the study
touches upon the concept of social stratification by addressing the potential implications of
AI on marginalized groups. It emphasizes the importance of ensuring fairness and avoiding
discriminatory practices in AI-driven criminal investigations, aligning with social justice and
equality principles.
Research questions and hypothesis
The study focuses on several research objectives, including:
1) Identification of various AI methodologies employed by law enforcement agencies in
digital investigations;
2) Ascertainment of the legal status of criminal evidence procured through AI
methodologies and their admissibility in criminal adjudication proceedings;
3) Ensuring that the integration of AI methodologies into the sphere of criminal
investigation is in strict compliance with established legal and ethical guidelines and
4) They are gaining insights into AI’s potential advancements and applications in digital criminal investigations
Research methods used
The study used many methods to examine artificial intelligence in digital criminal
investigations. The organization adopted a multidimensional strategy using qualitative,
descriptive, and analytical techniques. The qualitative study allowed for the theoretical
development of an AI framework for criminal investigations. This framework matched digital
forensics with investigative research technology. The descriptive and analytical research
methods also helped analyze and comprehend the data (Faqir, 2023). Data was collected from
primary and secondary sources. The data comprised criminal procedural legislation-related
legal documents, legislative opinions, and technical resources. Secondary data sources were
used to grasp the research topic fully. A complete literature review of contemporary scholarly
publications, law journals, and online legal databases was included.
Types of data and analysis
The primary data collected for the study comprised foundational legal codes,
legislative opinions, technical and scientific resources pertinent to criminal procedural laws,
regulations, rules, and associated documentation. The secondary data sources were existing
literature. The analysis involved scrutinizing the legal dimensions and the consequential
impact of AI deployment in digital investigations. Through its literature review, the study
reviewed various scholarly articles, books, and other publications on digital investigations
and AI.
Relationship to challenges, concerns, and contributions of marginalized groups
Incorporating AI into crime investigation has challenges and controversy for
marginalized groups. The article recognizes the possibility of AI systems acting as enablers
of the existing biases and discriminatory practices, especially when the training data or
algorithms are faulty or biased. This could lead to marginalized communities being
disproportionately affected as it would amplify the existing disparities demonstrated by the
justice system. Nevertheless, the study further shows that AI enhances fairness and
objectivity in criminal investigations. AI systems can uncover and eliminate human biases
through advanced data analysis and pattern recognition abilities, ultimately generating a fairer
result. The author calls for a transparent and interpretable AI model that provides the basis for
audit and tracking all the decision-making processes.
Contributions to society
The main contribution of the research to society is through its thorough investigations
of the legal, ethical, and practical aspects of AI in digital criminal investigations.
Using defying concerns about evidence admissibility, privacy issues, and the adaptation to
legal codes, the article lays the solid platform essential for the responsible use of AI in the
criminal justice system. The study’s recommendations include focusing on high-risk cases,
employing AI for crime prediction and suspect identification, deploying biometric
identification systems, and utilizing intelligent surveillance solutions, which could help
enhance public safety and security (Faqir, 2023). Nonetheless, such principles should be well
guarded against the risk of violating individual rights or exploiting and misusing AI
technologies.
Conclusion
The study demonstrates the importance of AI in digital criminal investigations and the
potential role that AI can play in enhancing efficiency, reducing investigation times, and
safeguarding the civil rights of all parties involved. The study also raises concerns about the
need for regulatory frameworks guiding AI-based technologies and the legal implications
associated with AI use in criminal investigations. While AI deployment continues to grow
within law enforcement agencies, the provided recommendations aim to maximize the
benefits of AI while keeping the legal and ethical requirements of AI use as a top priority.

References
Faqir, R. S. A. (2023). Digital criminal investigations in the era of artificial intelligence: A comprehensive overview. International Journal of Cyber Criminology.