1. Human Trafficking: A Perspective from Computer Science and
Organizational Leadership
Turner Sparks
University Studies
Abstract
With human trafficking plaguing our society, it is obvious the measures taken thus far are
not adequate in solving the problem. An interdisciplinary technique is necessary to address
human trafficking, because it is a complex issue that is a serious societal concern and has
not been resolved. It was found that perspectives from Computer Science and
Organizational Leadership together can provide valuable insights. Better surveillance and
tracking software can be developed, and appropriate strategies can be created to utilize the
software to the best potential. The current software works well in controlled environments,
but the video sensors we have today are not ideal for real world applications. Law
enforcement officers do not have adequate training in dealing with human trafficking, and
there aren’t many regulations to protect citizens’ privacy and safety when it comes to
video surveillance. In order to overcome these obstacles, further development of video
surveillance technology and more extensive training in regards to human trafficking
should be the focus for future research and development on this topic.
Focus Question
How is law enforcement utilizing surveillance and tracking software to track the
whereabouts of possible victims or suspects involved with human trafficking?
Conclusions
During the research process, it was discovered that law
enforcement has implemented types of tracking surveillance software
before and other types of video tracking were being tested, but were not
reliable enough for use in the field. By integrating insights from
Computer Science and Organizational Leadership, it could be possible to
develop better video tracking systems and have leaders implement them
to be used in tracking suspects and victims of human trafficking.
Future efforts for this research could be focused on getting better
video sensors to have more depth and resolution to make tracking
subjects easier. Also, developing better tracking algorithms could
improve the accuracy and reliability of the tracking systems’ results. The
weaknesses in today’s tracking systems are brought about by the video
sensors not being able to differentiate objects in adverse lighting
conditions and the software not being able to handle all of the raw data
that is accumulated on all of the available video surveillance systems.
Future study should look at how to overcome these obstacles.
Once a more reliable system has been developed, it could be
implemented as a real world solution by placing these systems in
strategic locations such as airports, bus and train stations, border
crossings, and ports. With these insights in mind, video surveillance
systems could soon be an invaluable tool for addressing the wicked
problem of human trafficking.
Repko’s 10 Steps
A. Drawing on disciplinary insights
1. Define the problem or state the research question
2. Justify using an interdisciplinary approach
3. Identify relevant disciplines
4. Conduct the literature search
5. Develop adequacy in each relevant discipline
6. Analyze the problem and evaluate each insight or theory
B. Integrating disciplinary insights
7. Identify conflicts between insights and their sources
8. Create common ground between concepts and theories
9. Construct a more comprehensive understanding
10. Reflect on, test, and communicate the understanding
Conflicts
When looking at a problem from the perspectives of different disciplines, conflicts
can occur between or within the insights of those disciplines. It is necessary to identify
these conflicts “because [they] stand in the way of creating common ground and, thus, of
achieving integration” (Repko, 2012, p. 294).
Conflicts within the discipline of Computer Science:
• Lin et al. (2009) and Szpak and Tapamo (2011) claim success using video surveillance
and behavior recognition.
• Hassaballah (2015) argues variations in lighting and the use of masks will make these
systems useless.
Conflicts between the disciplines of Computer Science and Organizational Leadership:
• Hadjimatheou (2014) discusses privacy concerns with using untargeted facial
recognition. He argues this will make innocent people feel like suspects.
• Computer Scientists believe the face is not private and even if this is an invasion of
privacy, it is necessary to ensure the safety and wellbeing of our citizens.
A More Comprehensive Understanding
Creating Common Ground
• Extending the concept of ever-evolving technology, it is expected that hardware will
improve making the video surveillance systems be more reliable in the future.
• When addressing the privacy concerns with facial recognition, the concept that one’s
face is private is redefined. By acknowledging a person’s face is not private when that
person is in a public place with his/her face uncovered, there can be no claim to an
invasion of privacy when using facial recognition in public areas.
• To create a more comprehensive understanding, the insights of Computer Science and
Organizational Leadership need to be synthesized. The new integrative insight will
focus on placing the appropriate leaders in the necessary positions to ensure updated,
more reliable tracking software can be developed and then given to leaders in law
enforcement to utilize in the field.
• Many people are not comfortable with untargeted scanning and tracking of their faces.
However, it has been determined the face is not private. Photo ID is already required to
purchase certain goods or to take advantage of certain services available to us. It is not
practical or logical to believe it is acceptable to use our faces for these purposes, but not
for improving security and ensuring our safety and wellbeing.

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Hassaballah, M., & Aly, S. (2015). Face recognition: challenges, achievements and future directions. IET Computer Vision, 9(4), 614-626.
Lin, L., Seo, Y., Gen, M., & Cheng, R. (2009). Unusual human behavior recognition using evolutionary technique. Computers & Industrial
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Lochner, S. A. (2013 Saving face: Regulating law enforcement’s use of mobile facial recognition technology and iris scans. Arizona Law Review,
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Szpak, Z., & Tapamo, J. (2011). Maritime surveillance: Tracking ships inside a dynamic background using a fast level-set. Expert Systems With
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The Vancouver Canucks Fan Zone (2011, June 15). Retrieved from http://www.gigapixel.com/image/gigapan-canucks-g7.html
References