1. Running head: HUMAN TRAFFICKING
Human Trafficking: A Perspective from
Computer Science and Organizational Leadership
Turner Sparks
Texas Tech University

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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. Repko’s 10 step Interdisciplinary Research Process was used to provide a better
understanding of the issue. Based on an extensive literature review, 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.

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Human trafficking is an issue in today’s society that many people are not aware of. It is
astounding how bad this problem is and how little people know about it. Even law enforcement
officers aren’t well educated on the subject (Grubb and Bennett, 2012). There are policies and
laws forbidding human trafficking, but that doesn’t seem to stop the criminals partaking in the
trafficking activities. Therefore, this problem needs to be addressed from an interdisciplinary
perspective.
STEP 1: Stating the Focus Question
Grubb and Bennett (2012) stated “since the 1990’s, human trafficking or ‘trafficking in
persons’ has been brought to the forefront of criminal justice issues, sparking international anti-
trafficking efforts among human rights proponents, government entities and law enforcement
agencies throughout the world.” Since human trafficking is still a problem that is rampant in our
society, we can conclude that the anti-trafficking efforts made thus far are not adequate in
subduing the criminal activity. We then need to ask ourselves what more can we do to help solve
the issue. With advancements in technology, I propose approaching the problem by utilizing the
tools we have at hand. For example, there are security cameras in place as well as traffic
cameras, ATM cameras, webcams, and camera phones all around the country. There is also
software that can track people by facial recognition. Therefore, my focus question would be:
How are leaders in law enforcement utilizing surveillance and tracking software to track
whereabouts of possible victims or suspects involved with human trafficking?
STEP 2: Justify Using an Interdisciplinary Approach
Human trafficking is such a difficult problem to solve because it is a major issue across
all socio-economic groups and no current policies or actions taken by law enforcement have had

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a significant effect. Therefore, if the disciplines of political science and law are not enough to
make a change, then perhaps the insight of other disciplines is necessary. As stated in step 1,
technology can aid us in solving the problem of human trafficking. A major discipline in the
field of technology is Computer Science. Another helpful field could be Organizational
Leadership. Leaders in law enforcement need training on how to use the tracking and
surveillance systems created. More importantly, they need to know how to apply those systems
to areas such as human trafficking. With the combined efforts and synthesis of these disciplines
there might be a better chance of rescuing victims or capturing suspects before it is too late.
STEP 3 and 4: Identify Relevant Disciplines and Conduct a Literature Search
To address the problem of human trafficking, the disciplines of public policy, sociology,
law, and human sciences could all potentially be used for obvious reasons. However, to better
apply the research to the focus question, the disciplines of Computer Science and Organizational
Leadership will be used.
Remember, the focus question is ‘How are leaders in law enforcement utilizing
surveillance and tracking software to track whereabouts of possible victims or suspects involved
with human trafficking?’ Computer Science should give a good idea of the software available for
surveillance and facial recognition. Organizational Leadership will help discover how this
software is, or can be used in law enforcement. Problems arose when trying to find information
from the Computer Science perspective for human trafficking as most of the research available
favors perspectives from public policy and sociology. More information was discovered by
shifting the search from human trafficking, to surveillance. Other literature was also found that
indicates surveillance software has been successfully used by law enforcement, however, there
are now the ethical concerns of invasion of privacy. Since the technology is still relatively new,

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and hasn’t widely been adopted for human trafficking use, there is no policy for regulating its
use to ensure citizens’ rights of privacy are not infringed.
STEP 5: Develop Adequacy in Each Relevant Discipline
In order to address the focus question using perspectives from both Computer Science,
and Organizational Leadership, one must have adequacy in both fields. “By adequacy
interdisciplinarians mean knowing enough about the discipline to have a basic understanding of
how it approaches, as well as illuminates and characterizes, the problem” (Repko, 2012, p. 102).
Computer Science is primarily programming software by writing thousands of lines of
code to tell the hardware components what to do. One of the main principles of Computer
Science is understanding that computers have to be told to do EVERYTHING. Software
developers develop code by first developing algorithms to solve the problems at hand. An
algorithm is simply a step-by-step process for performing a task or solving a problem. The
developer takes those steps and begins implementing them by translating into code, which the
computer can interpret and execute. Based on the advancement of cameras and computer video
processing, software developers will always be able to develop more efficient algorithms for
facial recognition and surveillance software. In this discipline, there aren’t really any
foundational theories that can be used for this application.
Most of the research done in Computer Science consists of experimental research, as it
falls in the STEM (Science, Technology, Engineering, and Math) field. Organizational
Leadership, however, can have research of all types, because it is what’s known as an
interdiscipline. For the purposes of this paper, most of the research gathered contains quantitative
studies. One of the concepts of Organizational Leadership is making sure the right people are in
their suitable leadership positions. This ensures the maximum effectiveness and efficiency in

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which an organization operates. There are a few theories that help determine whether a person is
capable of being a leader. One of which is Functional Theory. Guzman (2015) says “Functional
Theory argues that leaders’ primary responsibility is to assess what their followers need and
ensure that those needs are met.” He goes on to say that leaders also monitor their environment,
train, motivate, and provide jobs for their workers, and participate in group activities. This type
of leadership could be astoundingly helpful in helping officers combat human trafficking.
Combining these disciplines, we can help leaders of law enforcement organizations attain
the best tools and the best training available for tracking suspects or possible victims using facial
and human behavioral recognition.
STEP 6: Analyze the Problem and Evaluate Each Insight into It
“Closely associated with achieving adequacy in the relevant disciplines is analyzing the
problem from the perspective of each relevant discipline and evaluating each important insight
into itAnalyzing the problem requires viewing it through the lens of each disciplinary perspective
primarily in terms of its insights and theories” (Repko, 2012, p. 129226). In the case of this
study, perspectives from Computer Science and Organizational Leadership will be applied to
look at how leaders in law enforcement are utilizing surveillance and tracking software to track
obtain whereabouts of possible victims or suspects involved with human trafficking.
In order to answer this question using insights from the Computer Science perspective,
we must first askit is necessary to determine what software is already available that is capable of
tracking and surveillance. Then, we will ask how this software can be improved. Computer
Science is going to look purely at the programming involved with tracking systems. All of the
research done for the Computer Science portion of this paper was performed at the
developmental and experimental stages.

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Lin, Seo, Gen, and Cheng (2009) talk about the importance of human tracking and human
behavior recognition software. According to their article, more possibilities are opening up to
develop better tracking software due to the increasing availability of video sensors and high
performance video processing software. The researchersLin, Seo, Gen, and Cheng (2009) use a
3D modeling algorithm to track multiple people’s behavior and make predictions based on their
behavior. Using a modified Gaussian function, they were able to find normal patterns in behavior
and then recognize unusual human behavior (Lin, Seo, Gen, and Cheng, 2009). This type of
research can provide a unique insight to the problem of human trafficking. By detecting unusual
behavior, the system can flag possible cases of human trafficking in places such as airports and
bus stations.
The next article by Szpak and Tapamo (2011) discusses safety concerns in coastal
countries and the waters surrounding them. The author’s recommend ships implement computer
surveillance systems that analyzes images to find sea vessels instead of using radar.and
experiments Szpak and Tapamo (2011) experiment using with such systems in the maritime
environment. The complication with this application is the dynamic background of the seas. The
water is constantly moving and, therefore, it is harder for cameras and tracking software to detect
whether it is a ship moving, or just a wave. Radar has proved problematic because it cannot
detect smaller ships, which pirates and smugglers tend to use. In the experiment, boats used
ranged from jet-skis to tankers and ferries. By mapping the contour of the images based on
contrast, the software was able to differentiate between waves and boats. While the technology is
not perfect, as it also picked up some larger sea animals, it is developing and could prove to be
useful in tracking vessels suspected of being involved in human trafficking (Szpak, 2011).

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The final article used for the Computer Science section of this paper discusses the
challenges faced with today’s facial recognition systems. According to Hassaballah (2015), the
success we see with facial recognition is in controlled experiments. However, in the real world,
many factors can cause these systems to fail. How lighting affects an image can be one of those
factors. Another real world problem is that a person may not be looking towards the camera or
may have his/her face partially covered, thus preventing an accurate recognition. Hassaballah
suggests these tracking and recognition systems are going to require significant steps forward in
terms of technology in order to be of real benefit in the war against crime.
This research demonstrates how useful the insights of computers science can be in
addressing the problem of human trafficking. Though there are many challenges with tracking
systems, advancements in technology will allow the creation of better tracking systems. For the
discipline of Organizational Leadership, there were articles pertaining to law enforcement’s use
of these tracking and surveillance systems.
According to Grubb and Bennett (2012), leadership in law enforcement is not providing
sufficient training on how to address human trafficking. Using Likert-scaled responses, they
found that officers felt they weren’t prepared if they happened to be first responders to a human
trafficking incident. The officers also weren’t adequately trained on how to recognize human
trafficking if it were to happen around them. Grubb and Bennett (2012) suggested officer
training needs to include more information on human trafficking, including how to recognize and
deal with a possible human trafficking situation.
Lochner (2013) discusses regulating law enforcements use of video surveillance and
facial recognition technology. The system Lochner says is used by law enforcement is called
Mobile Offender Recognition and Information System (MORIS). This system was used in the

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2001 Super Bowl to run spectators facial images. Many believe this is an invasion of privacy and
think the untargeted use of MORIS should be unlawful. According to Lochner, MORIS needs to
be regulated by implementing policy to avoid breaching the fourth amendment.
There are also ethical and moral concerns with untargeted and target surveillance.
Hadjimatheou (2014) claims victims of untargeted surveillance are stigmatized because it makes
people feel like suspects. Even if the stigmatization was concealed, you still have the problem of
untargeted surveillance treating people like suspects. Hadjimatheou also argues the intrusion of
privacy weakens the effectiveness of democracy for our society as a whole.
STEP 7: Identifying conflicts between insights
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). One of the conflicts involved with this study is the
assumptions that may be made. “An assumption is something taken for granted, a supposition”
(Repko, 2012, p. 139). In this case, the assumption is that a person’s face will be adequately
visible by the cameras used in the facial recognition software. All of the research reviewed for
this paper was done in controlled environments. In the real world, it will be much harder to
replicate the results due to the variations in lighting and the realization that people can cover
their faces or wear disguises (Hassaballah, 2015). This contradicts the articles from Lin , Seo,
Gen, and Cheng and Szpak and Tapamoet al. b because they talk about their success in their
experiments and claim it can be directly applied to the real world.
There is also a conflict between insights in Computer Science and Organizational
Leadership. While there has been success in using facial recognition software in the Computer

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Science field, leaders are more concerned with the privacy issues that have arisen with this new
technology. It is believed that untargeted surveillance treats people like suspects, stigmatizing
them with the idea they have done something wrong (Hadjimatheou, 2014). Computer scientists,
on the other hand, believe this is not a problem if the people have nothing to hide. If this invasion
of privacy is indeed wrong, it is a necessary evil to ensure the safety and wellbeing of our
society.
STEP 8: Create Common Ground
Newell (2006) provides four techniques for creating common ground. These include
redefinition, extension, organization, and transformation. “Extension in an interdisciplinary sense
refers to increasing the scope of the [concept] that we are talking about” (Repko, 2012, p. 340).
A fifth technique is added by Repko. Repko (2008) calls this technique theory expansion and it is
“used to modify a theory so that it can address all of the causation insights pertaining to a
problem” (p. 281). Using this technique, the problem of a camera being affected by uncontrolled
variables in the real world can be looked at by expanding extending the concept of ever-evolving
technology our view to include the improvements made in the hardware used in facial
recognition systems. When the extension of this concept is applied, we can expect the video
sensors used in surveillance systems to get better and overcome the lighting and environmental
issues that may arise. the issue that current hardware is not good enough is expanded with the
theory that better hardware is always being developed, then the issue can simply be resolved over
time. With the proper leadership in place, both the hardware and software can be improved to the
point that these real world variables do not affect the quality of the tracking systems to a degree
in which they cannot be used effectively.

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To address the conflict with privacy and facial recognition, the technique of redefinition
will be used. “Redefinition involves modifying or redefining concepts in different texts and
contexts to bring out a common meaning” (Repko, 2012, p. 336). People protesting the use of
facial recognition claim this software is an invasion of privacy. This implies the concept that
your face is private. To find common ground here, this concept will be modified to suggest one’s
face is not private. The justification for this modification is simple. When a person willingly
walks into public, the public can see his/her face. Therefore, the face is no longer private, but
public. If a coworker can spot you at a bus station and recognize who you are, then how can
someone say it is an invasion of privacy for software to be able to do the same thing?
STEP 9: Construct a More Comprehensive Understanding
After creating common ground in Step 8, it is now possible to integrate the insights from
Computer Science and Organizational Leadership to develop a new insight to address the
problem of human trafficking.
Insights of Organizational Leadership include placing leaders in the proper positions to
accomplish goals more efficiently and more effectively. Computer Science’s insights involve
looking at a problem or task in an abstract sense and developing algorithms that allow more
efficient code to be written to solve that problem or task. Currently, there have been efforts made
by leaders to implement facial recognition and other types of video surveillance, but the
limitations of the hardware and software available today make these systems fairly unreliable
(Hassaballah, 2015).
Now, to address the focus question, “How are leaders in law enforcement utilizing
surveillance and tracking software to track whereabouts of possible victims or suspects involved
with human trafficking”, the insights of Organizational Leadership and Computer Science need

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to be melded together. 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. Possible places of interest
would be airports, bus stations, train stations, border crossings, and ports. Through the
integration of this new insight, an efficient and reliable system for accurately tracking individuals
involved in human trafficking could be created and implemented.
According to HadjmatheouHadjimatheou (2014), there is a lot of controversy when using
these facial recognition systems. with this method. Many people are not comfortable with
untargeted scanning and tracking of their faces. As determined in STEP 8, 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.
STEP 10: Communicating the Results
Initially, the study started with the focus question, “How are leaders in law enforcement
utilizing surveillance and tracking software to track whereabouts of possible victims or suspects
involved with human trafficking?” To answer the question, the insights from Computer Science
and Organizational Leadership were integrated. 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 in the two disciplines, 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.

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Future efforts for this research could be focused on getting better video sensors to have
more depth and resolution to make tracking objects 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 video surveillance systems out there. 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 the integration of insights from Organizational Leadership and
Computer Science, these systems could soon be a viable solution to the wicked problem of
human trafficking.

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References
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trafficking efforts: an assessment of human trafficking training and awareness of local,
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Guzman, O. (2015) Organizational Leadership theories. Retrieved from
http://smallbusiness.chron.com/organizational-leadership-theories-284.html
Hadjimatheou, K. (2014). The relative moral risks of untargeted and targeted surveillance.
Ethical Theory & Moral Practice, 17(2), 187-207.
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 Engineering, 56(3), 1137-1153.
Lochner, S. A. (2013 Saving face: Regulating law enforcement’s use of mobile facial recognition
technology and iris scans. Arizona Law Review, 55(1), 201-233.
Repko, A. (2012). Interdisciplinary research: Process and theory. Los Angeles, CA, Sage.
Szpak, Z., & Tapamo, J. (2011). Maritime surveillance: Tracking ships inside a dynamic
background using a fast level-set. Expert Systems With Applications, 38(6), 6669-6680.