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The efficiency of the planned human trafficking intervention is contingent on the quality of the effort exerted by every individual involved. The group mobilization for implementation, in this case, would mean arranging training sessions for as many employees as possible. The objective of the training should be raising awareness about the issue at hand, teaching personal initiative, and providing comprehensive step-by-step guides applicable to diverse situations. Renzetti et al. (2015) investigated the efficiency of human trafficking training programs in the US. The researcher concluded that a properly organized program raises awareness of human trafficking, increases the likelihood of identifying and reporting suspected cases, and helps to disseminate the knowledge further.
Training sessions cannot be too vague or uniform: ideally, they should be customized depending on the type of the expected audience – Uber managers or drivers. The rationale for Uber managers to mobilize against the problem is not only ethical but also monetary: each dismissed human trafficking case has the potential to ruin the company’s reputation. The motivation for drivers to participate in the intervention may be more complex. In the perfect world, they would want to help others out of altruism, but in reality, individuals often prefer to pursue personal interests.
Drawing on this distinction, one may assume that the contents of training and planning sessions for the management board should overview higher-order administrative tasks. For instance, during such meetings, managers can discuss an updated support system that processes human trafficking reports in real-time and refers them to authorities. Another administrative task to discuss is researching relevant legislation in operating countries to see possibilities for helping to propagate the cause. Drivers also play an important role in making the intervention possible as they have the closest contact possible to potential victims. In training sessions, employees need to learn how to detect the subtle signs of a person being trafficked and report to authorities.
During this process, intercultural communication is crucial: it helps to pull all the teams and departments together and keeps everyone on track. At this stage, Uber needs to ensure constant communication both within subdivisions and between them (Srivastava, 2015). Within subdivisions, it is advisable to build interdisciplinary “tower teams” consisting of people with different responsibilities for overviewing the process (Brown, Deletic & Wong, 2015). For instance, in one subdivision, there could be a team of an HR manager, developer, risk management specialist, and others. As for communication between subdivisions, there should be regular reporting in place and potentially a common database.
When it comes to handling a complex phenomenon such as human trafficking, the conceptualization of quality assurance can be quite a difficult task. The question arises as to what metrics could be the most indicative of the success of the campaign. Firstly, Uber might want to include the number of reported human trafficking cases in its yearly safety reports. This way, larger numbers should be interpreted as a positive change: this will mean that more employees are helping to detect suspected cases. Subsequently, Uber should collect data on human trafficking in the years to come and pinpoint any positive trends. Another metric that is not quantitative is the reputation of Uber as an agent in fighting against human trafficking. If the American company establishes itself as reliable and diligent in this regard, other human rights organizations will come forward for collaboration.
References
Brown, R. R., Deletic, A., & Wong, T. H. (2015). Interdisciplinarity: How to catalyse collaboration. Nature News, 525(7569), 315.
Renzetti, C. M., Bush, A., Castellanos, M., & Hunt, G. (2015). Does training make a difference? An evaluation of a specialized human trafficking training module for law enforcement officers. Journal of crime and justice, 38(3), 334-350.
Srivastava, S. B. (2015). Intraorganizational network dynamics in times of ambiguity. Organization Science, 26(5), 1365-1380.
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