Jadon White
CYSE 201s
Article Review #1
The Intersection of AI and Cybercrime: A Cyber-Routine Activities Perspective
This article will provide you with an understanding of the double-sided game of machine learning in
cybercrimes: While on one side it strengthens cybersecurity, the possibilities that criminals can exploit
systems also increase. Applying Routine Activity Theory (RAT) as a frame, the article argues that AI
transforms the cybercrime landscape by increasing prediction and intervention efficacy on one end of
criminal activity spectrum and rendering it less predictable and more accessible on another.
Applicability to Social Sciences
Building upon insights from criminology and sociology especially Rational Action Theory (RAT), this work
examines how AI alters the opportunities for engaging in cybercrime. RAT provides that a crime will
occur when three factors converge: A motivated offender and suitable target come together in the
absence of a capable guardian. Aside from the Guardian role (threat detection), AI is also a trap for
cybercriminals like we have it with AI-powered malware. In this context, the way in which people and AI
operate holds a key to the issue of cybercrime as well, with psychological and sociological impacts
playing an equally major role.
Statement of Research Questions or Hypotheses
The study primarily tries to answer, “How AI changes the game in fighting cybercrime and whether AIdriven solutions can help minimize the threats?” The idea behind AI as an attack vector is that the entire
house of cards crumbles, as fast or faster than it arises,… oh…. and by the way…the key aspect for AI is
security…but the hypothesis goes like this: …….the general conjecture promotes security on one side
while breaking it in another… This is a major point that concerns how AI dreams of being able to
enhance cybersecurity and yet also significantly dampen all through the plague.
Research Methods
That is a lit review article where authors have analyzed various research papers and editors opinion on
AI in cybersecurity arenas. This approach is useful, as it provides a high-level perspective on the current
state of play and thereby informs both the trade space as well as areas for future research when
studying AI against AI in cyber-enabled crime.
Data and Analysis
Data from actual research articles and reviews, reports and case studies are used in the study. Using
thematic analysis which revealed patterns such as AI in relation to phishing and malware attacks, and
how it is used in cybersecurity defenses. This approach demonstrates the way AI is reworking
cybercrime.
Relation to Course Concepts
As such, this article is closely aligned with course discussions related to AI and cybersecurity. Second, it
calls attention to the need for AI in making threat detection more effective on the one hand and the
danger for future unethical consequences of large scale use of AI itself against us all and hence makes a
small dent in some overly positive views (including ours) relating to AI into security.
Impact on Marginalized Groups
The piece further delves into how AI-powered cybercrime can disproportionately impact the most
vulnerable communities because of cyber-attacks to essential systems, like healthcare or financial
services. Failure to safeguard against AI bias in cybersecurity systems would not only exacerbate social
inequalities, but also more seriously expose vulnerable populations to attacks.
Contributions to Society
In general our study points out the necessity of trading off between AI benefits and risks. It hints that
there is a pathway for policy makers and how they should look at these vulnerabilities that AI brings,
while leveraging the strengths of the technology to build stronger cyber security. We also identified
areas for future research, particularly the search for practical methods to avoid any misuse of AI and
thus keep it far from cybercrime.
Conclusion
The article ends by giving a balanced perspective of the focus AI attracts in cybersecurity, on either side.
While it does depend on existing research, the paper provides good overview of the double-edged
sword nature of AI. The construction of additional empirical research on these theories is required

References
Shetty, S. , Choi, K. & Park, I. (2024). Investigating the Intersection of AI and Cybercrime: Risks, Trends,
and Countermeasures. International Journal of
Scharre, P., & Chilukuri, V. (2024, March 5). What an American approach to AI regulation should look
like. Time. Retrieved from https://time.com/6848922/ai-regulation/