Money Laundering Operations within the United States

Introduction

Developing a computer program to counter money laundering activities involves development of softwares that manages databases and this would involve the using “Big Data”. The program would involve analyzing large volume and types of information or data that describes the activities being carried out by an organization or individuals those results in money laundering. The use of the program is likely to raise various ethical issues regarding privacy of information, confidentiality and privacy of the data. The program would require analyzing information, some personal, of a large population, and then zeroing in on specific individuals whose activities that are mimicked by the determined transaction patterns. The ethical issues would arise from the fact that such a program would violate the privacy of many people while trying to identify and possibly apprehend individuals suspect of the crime.

In the consideration of the ethical and moral issues arising from analysis of private information, there various issues that should be noted. To begin with, the meaning of privacy involves rules governing the management of personal information.  The development of the program must take into account the rules governing the collection, using and storage of personal data (King & Richards, 2014).  In this case, the ethical issue relates to the use of private information using analytical systems belonging to a third-party.  The other issue involved whether private information that has been shared remain confidential. The sharing of information by the services trusted by user can raise legal issues, especially because the generation of share information does not negate the confidentiality of such data including address book and financial data.  The use of data for inferences, the ethical or moral issue concerns whether there is transparent by the organizations or individuals (King & Richards, 2014).  Where “Big Data” is involved, there can be a compromise of an identity. The analysis of big data can enable institutional surveillance, and identity can be compromised while moderating and determining the personal involved in money laundering even before they commit the crime.  These calls for the Department to consider the kind of data inferences that can be allowed and the ones that has to be disallowed.  The ethical and moral guidelines may draw various lines even if the fraud and money laundering are totally unethical (King & Richards, 2014).

 The adoption of the program would require the Department to implement “Big Data Analytics “ and the process involves the establishment of aggregated and undesirable externality since it involve a bigger surveillance system in terms of breadth of collected information . Furthermore, organizations that gather data and aggregate it are usually not visible to users (Martin, 2015).  As matter of fact, the surveillance process will totally be in conflict with a person’s need to remain unobserved, to be unique and their sense of self.   The personal space of the person allows “unconstrained, unobserved physical and intellectual movement to develop as an individual and to cultivate relationships” (Martin, 2015).  When the department adopts the computer program, it will be engaging in surveillance which may be harmful since it the personal metaphorical and personal space are compromised and violated.  Personal space is necessary for the person to develop and especially within some relationships (Martin, 2015).  The privacy of a large population will be violated if their information is exposed through the analysis process.

A major moral issue involves public knowledge that their private information is being accessed and analyzed by the Department. It can give rise to the fear of someone watching their activities and being subjected to judgment due to causes of other people criminal activities.  The space provided through the surveillance will function differently in comparison with a space that is not exposed, since individuals’ way of thinking and behavior will be changed (Someh et al 2016).  Moreover, the surveillance functions by affecting both the person being watched and those who are not under watch.  By believing that their activities are being watched, people are likely to act as if they are watched. The use of the computer program may involve use of algorithms where individuals are profiled according to their income, social class and gender while observing their transactions (Someh et al 2016). A major issue that may arise relates to self-determinism or freedom to choose how their data will be used by any organization. However, it can be argued that benefiting from such surveillance involves a cost of losing one’s privacy or even control of their information (Someh et al 2016). Another issue involves the possible control of the information by the Department when it dominates the access of personal information as they observe their transaction activities.  The possible result is the creation of knowledge asymmetries and this can lead to control of the society by the observing organization. The fact that the present guidelines and principles aimed at protecting  the privacy rights of a person is not at par with technological advancement can leave a loophole that may be exploited by rogue individuals to target others (Someh et al 2016). The issue of morality arises in that the improper use of such information can lead to abuse by those who have power for self –serving interests.

On the other hand, the use artificial intelligence to analyze data and carry out surveillance can be very beneficial in prevention and mitigating money laundering operations. The technology can be play a big role in identifying the money laundering activities and the criminals involved. The individuals involved in money laundering crimes can be identified from the available list (Hipgrave, 2013). By recognizing their transactional patterns, the integration of data from internal and external sources will enable the Department to control cases of money laundering.  The mitigation of the crime can be dealt with locally, nationally and across different countries so that the entire system is destroyed.  The department can engage the population by helping them in understanding and balancing their need for privacy and control over personal  transactional information with the benefits related with the process especially in preventing and dealing with money laundering. When the population is made aware of how their data is being used, they will support the adoption of the artificial intelligence (Hipgrave, 2013). This will ensure that economic power will not be transferred to criminals from citizens and their government.

Conclusion

The adoption of artificial intelligence is bound to raise concerns related to violation of privacy when transactional data has to be used. The process involves the use of Big Data Analytics that calls for upholding process to be moral and ethical by not allowing profiling and discrimination. The benefits of preventing and dealing money laundering are significant but the public has to be sensitized on the need to forego privacy for common good.

References

Someh, I. A., Breidbach, C. F., Davern, M. J., & Shanks, G. G. (2016,). Ethical Implications of Big Data Analytics. In ECIS (pp. Research-in).

 

Martin, K. E. (2015). Ethical issues in the big data industry. George Washington University. Retrieved from: http://misqe.org/ojs2/index.php/misqe/article/viewFile/588/394

 

Hipgrave, S. (2013). Smarter fraud investigations with big data analytics. Network Security, 2013(12), 7-9.

 

King, J. H., & Richards, N. M. (2014). What’s up with Big Data ethics? Retrieved from: https://www.forbes.com/sites/oreillymedia/2014/03/28/whats-up-with-big-data-ethics/#303ddff35913