نوع مقاله : مقاله پژوهشی
نویسندگان
گروه جزا و جرمشناسی. دانشکده حقوق. دانشگاه شهید بهشتی. تهران. ایران.
چکیده
کلیدواژهها
موضوعات
عنوان مقاله [English]
نویسندگان [English]
With the expansion of big data and the datafication of human life, crime prevention has increasingly shifted toward the management of probabilistic behaviors. Concurrently, the entry of non-human actors and the growing reliance on artificial intelligence algorithms have transformed the role of human agents in risk assessment and preventive decision-making, moving away from classical causal and experience-based reasoning toward a data-driven logic grounded in correlation. A key consequence of these transformations in the domain of individual-oriented crime prevention is the emergence of the novel concept of "algorithmic crime" as a central organizing notion in AI-driven crime prevention. This concept, in turn, reshapes related theoretical constructs, including the notions of the offender and responsibility.
Accordingly, this study adopts a descriptive-analytical approach to examine the evolving theoretical landscape and to analyze three core concepts: algorithmic crime, algorithmic offender, and predictive responsibility. Algorithmic crime is conceptualized as a dynamic and continuously updated process; the algorithmic offender is understood as a data-driven representation of the individual in the form of a risk profile; and predictive responsibility is framed as a justificatory basis for preventive interventions grounded in the attribution of risk to a specific individual.
Finally, through a critical perspective, the article demonstrates that, in the absence of adequate regulation and precise legal rules, reliance on algorithmic assessments may lead to the expansion of selective interventions, the erosion of the presumption of innocence, and the restriction of fundamental rights and freedoms, thereby blurring the boundary between preventive measures and punitive responses.
کلیدواژهها [English]
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