| dc.description.abstract | Tthis research will endeavor to bring on board the use
of AI in countering Human Trafficking utilizing the
criminological theories to enhance the effectiveness of
the methods being employed in the fight against this
heinous crime. Hereby, applying the Routine Activity
Theory (RAT), Social Learning Theory (SLT) and Strain
Theory (ST) and the research is capable of illustrating
directions where the AI can improve the architecture
applied in the detection, prevention and intervention of
the trafficking activities. Therefore, this paper is aimed
at engaging the systematic literature review framework
in order to evaluate the current literature and case
studies in relation to AI in Human Trafficking. As
clearly explained by authors in the indexes of the
articles, the application of AI which includes; machine
learning(ML), Natural Language Processing (NLP),
and Social Network Analysis (SNA) enhance the
strength of policing and decision making organizations.
First of all, it can target parts of the problem, byl
knowing where it is most likely to occur and can track it
endlessly, both of which will improve resource
management and early responding. However, it also
states that the utility of AI have to be backed by ethical
aspects which the paper identifies as privacy, bias, and
accountability. Therefore, it should be noted that the
integration of AI with the principles of the
criminological theory can present ways of combating
human trafficking, but such a process must be
accompanied by the investigation of attainable
problematic elements and the development of strategies
to enforce the positive impacts of integrating AI while
minimizing detrimental effects. | en_US |
