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Part 1: Quoting

Required source: A professional journal article from the list  presented in the Library section of the classroom as explained above. Do  not look for quotes already presented in the article; your mission is  to find direct statements in the article and quote them yourself.

Quotation 1: Parenthetical citation

  • Choose a meaningful statement of 25–39 words from the article and  quote it without introduction, using in-text citation after the  end-quotation mark and before the final sentence punctuation.

Quotation 2: Narrative citation

  • Choose a different meaningful statement of 25–39 words from the same  article and quote it properly, starting your sentence with “According  to” or a similar introduction, and inserting proper citation as  explained in the reading.

Required adjustment:

  • Edit just one of your two quotes by correctly using brackets, an ellipsis, or [sic]. These techniques are explained in the reading.
  • If the original does not have an error, you cannot use [sic]  and must instead employ either brackets for a clarification or an  ellipsis to delete words. Note that British English spellings are not  considered errors.

Reference entry:

  • Provide a full 7th edition APA-standard reference entry for this journal article.

Part 2: Paraphrasing From Two Other Articles

Choose two other journal articles from the same Library list. It is  recommended that you pick articles that are relatively easy for you to  understand, especially if you are new to the technology field. Find a  section of each article that interests you and write paraphrases.

For each of your two paraphrases, separately:

  • Compose a descriptive title (a phrase) in your own words. Use title case.
  • Write a paraphrase of 170–220 words. If it is difficult to meet the  minimum length or to avoid writing more than the maximum, then a more  suitable section (or section size) from the original article must be  chosen.
  • Do not include any quotes.
  • Write the paraphrases in paragraph form (no lists).
  • Include proper citation as explained in the reading.
  • Provide a full 7th edition APA-standard reference entry.

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110 British Journal of Community Nursing March 2021 Vol 26, No 3

Impact of technology on
community nursing during
the pandemic
Kathryn Rose Grindle
Advanced Nurse Practitioner, Liverpool John Moores University

[email protected]

The COVID-19 pandemic has been described by Vannabouathong et al (2020) as the largest and most rapidly spreading threat to global health since the
Spanish flu of 1918, which is estimated to have killed over
50 million people. Fauci et al (2020) reported the disease as a
global, life-threatening viral infection affecting the respiratory,
gastrointestinal and neurological systems. There is minimal
literature that can specifically define all characteristics of
the virus, as its epidemiological characterisation remains in
the nascent stage. In a study discussing genetic mutation,
Grubaugh et al (2020) described the SARS-CoV-2 virus as
causing ever-changing infection, and they further suggested
there is no cure. In their recent article for Lancet Infectious
Diseases, Baud et al (2020) reported that the global mortality
rates from March to May 2020 increased by 5.7% solely due
to the virus.

International evidence presented by Comas-Herrera et
al (2020) and McMichael et al (2020) showed that patients
residing in care homes are a particularly vulnerable group
for severe COVID-19 infections, due to the nature of them
having multiple underlying chronic and long-term conditions
resulting in them requiring 24-hour care. At the height of

the pandemic in the weeks of 1–17 April 2020, Field et al
(2020) reported that the death rate in UK care homes had
risen by 500% due to COVID-19. This statistic is of utmost
importance in understanding the required rapid rollout of
new assessment processes for the vulnerable. Rekatsina et al
(2020) described key factors shown to have affected some of
the most vulnerable members of society during the COVID-
19 pandemic, including the severity of the virus and extremely
high rates of mortality, coupled with the large volume of staff
sickness resulting in care homes becoming overwhelmed and
unable to provide care for their residents.

Recommendations made in a study relating to the reduction
of patient and staff exposure to viruses via the use of telephone
assessment strongly suggested the alternative use of telephone
or virtual consultation for assessment (Milusheva, 2020).
This has also been recommended by Shehata et al (2020),
who described the emphasis clinical commissioning groups
(CCGs) across the UK have placed on the importance of
other mediums of assessment in the current climate. The use
of other assessment mediums are evidenced as dating back as
early as 1876. Pierce et al (2020) described the introduction
of the telephone as being revolutionary within healthcare.
The first incidence of it being used to seek medical attention
was by the inventor himself, Alexander Graham Bell, when he
used it to seek help after spilling sulphuric acid on himself; by
1970, enthusiasts described the telephone as being as much a
part of the standard equipment for a clinician as a stethoscope.
Greenhalgh et al (2020) stated that telephone triage and
assessment have now become the first line in the provision
of healthcare in the community in the wake of the COVID-
19 pandemic. Several groups emphasised the importance of
using telemedicine to limit exposure and alleviate the burden
placed on healthcare systems by the COVID-19 pandemic
(Eurosurveillance Editorial Team, 2020; Reeves et al, 2020;
Zhou et al, 2020). These were further supported by Smith
et al (2020), who implored the prioritisation of moving all
patient-facing assessments to triage via a telephone or video
consultation to limit unnecessary exposure of staff and patients
to the virus. Duffy and Lee (2018) went further in suggesting
that in-person visits should be the second or third option
in reducing the exposure and potential spread of infectious

ABSTRACT
The purpose of this article is critical analysis, reflection and discussion
in regards to the uses and impacts technology has had in community
settings, specifically care homes during the COVID-19 pandemic. This will
be investigated and supported with special emphasis on virtual assessment
platforms and their use within the care homes settings, furthermore
reviewing specific data collected in relation to the usage within community
care homes. The article will outline the positive attributes and critically
reflect upon the benefits of using audio and video conferencing when
assessing patients and the beneficial impacts this has had on patients and
the wider health community. While conversely addressing the obstacles and
threats faced by clinicians in the use of assessment software.

KEY WORDS
w Community w Care homes w Attend Anywhere w Infection risk
w Emergency

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British Journal of Community Nursing March 2021 Vol 26, No 3 111

diseases, and they emphasised the protection of the most
vulnerable members of society and the public by decreasing
the required movement of symptomatic individuals.

Attend Anywhere
In community nursing, a strong emphasis has been placed
on the use of telephone triage followed by video assessment
to reduce exposure to staff and patients, further preventing
an increase in the prolific ‘reproductive number,’ which is
indicative of the infection rate. In a qualitative study by
Donaghy et al (2019) investigating the use of telemedicine,
the results showed a positive reaction to the use of technology
to decentralise the patient-centric model and allow it to catch
up with the more modern requirements.

Attend Anywhere is a video conferencing medium
that supports the visual and audio assessment of a patient,
while limiting footfall in high-risk areas. This platform was
implemented nationwide by NHS England in 2018 and
has spread across 45 trusts and has been used effectively
since its inception in Melbourne, Australia, in 1998. In an
Australian study by Corden et al (2020) on the use of remote
assessments, the authors credited the lower infection rate to
remote assessing, and they recommended the use of remote
assessment mediums. They reported on their experience in
a dermatology setting, where 800 patients could be triaged,
assessed and treated using video assessment, which reduced
footfall and decreased the exposure risks and improved
patient satisfaction.

Due to the COVID-19 pandemic, trusts throughout the
UK were supported to rapidly roll out the Attend Anywhere
tool, which was funded by NHS England. The goal was to use
this medium amid the crisis, coinciding with Government
regulations for the vulnerable to shield. Beland et al (2020)
recounted the guidance of the banning of all but essential
visits into care homes across the UK due to the pandemic.
This guidance has only ever been encouraged on this scale
once before, amid a norovirus outbreak in Scotland (Currie et
al, 2016). With this being the new normal for the foreseeable
future, most trusts were required to continue to provide
nursing services, but had to be innovative in their delivery to
protect staff and patients. This is how virtual assessments in
care homes were born. However, this new way of working
was met with trepidation and apprehension by many staff who
found working through a pandemic already overwhelming
without the added pressure of a new assessment medium
being implemented. Therefore, the uses and effectiveness of
virtual assessment mediums were assessed during this time.

Evaluation of effectiveness
A recent evaluation of the provision of healthcare was
conducted over a 2-week period with an emphasis on
Attend Anywhere in care homes and a predominant focus on
community matron assessment. According to the findings, a
total of 30 visits were requested via the single point of contact
service between 20 and 31 July 2020. Some 23.333% patients
were seen in person; 60% were assessed via the telephone
and 16.66% were seen via Attend Anywhere. The 66.66% of
assessments completed via telephone or Attend Anywhere

represented a vast reduction in the footfall when compared
with previous audits, which had showed that 79% of visits
completed before March 2020 had been completed in person.

The results of this small snapshot of nursing care using
a video conferencing platform suggested a reduction in
footfall within the predominantly at-risk areas via the use
of telephone and video conferencing. These data indicate
that, during this time period, the use of such platforms was
positive and effective in enabling assessment and reduction
of exposure of both staff and patients, as face-to-face visits
were not required.

The avoidance of face-to-face visits is paramount. Many
care homes house patients with cognitive deficits, such as
dementia or Alzheimer’s disease, which warrant one-to-
one supervision (Livingston et al, 2017). In most cases, this
cannot be provided, and, therefore, the use of large communal
living spaces is required to ensure resident safety when they
wander through the home, experience agitation when
trying to redirect attention, attempt to physically engage
with other residents and touch various objects, which could
be dangerous. It has been suggested that these activities by
people with cognitive impairments significantly increase the
risk of rapid disease transmission (Killen et al, 2020; Suzuki
et al, 2020). Therefore, all recommended guidance for the
protection of vulnerable patients should be strictly adhered to.
Brown et al (2020) supported the use of alternative assessment
mediums in these cases. Corden et al (2020) went further
to highly recommend video assessment for complaints that
could be assessed visually, such as eye infections, rashes in areas
that will not indecently expose patients, infected wounds and
some new wounds (to give dressing advice). However, they
said that home visits were generally required in the case of
complaints that required audible assessment, such as a chest
infection or possible bowel obstruction, which also required
a manual assessment, including palpation (Corden et al, 2020).

Barriers to telemedicine
When reviewing wider data from the health community,
Unadkat et al (2020) reported that video consultation systems
can be impersonal, and difficulties with the speed of the IT
system were reported. Conversely, Connor et al (2020) highly
recommended the use of video assessment mediums, such as
Attend Anywhere or Telehealth, in the provision of healthcare
by allowing remote assessment of patients using electronic
communication tools. The authors said that such systems are
crucial in avoiding unnecessary attendance to hospitals and,
therefore, reduce contamination risk. In addition, there is the
benefit of not having to cancel appointments en masse to
adhere to regulations.

The morality of offering patients a diagnosis over a video
consultation, however, has been questioned by Humphreys et
al (2020), who considered the ethical implications of offering
a diagnosis without the usual support of specialist nurses or
other appropriate persons. Family members banned from visits
as per Government guidance cannot offer moral support or a
more simplified explanation to their loved ones (Gardner et
al, 2020). Consequently, Sorinmade (2020) proposed that this
must be considered by the diagnosing clinician, who must be

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sympathetic and conscious as to what is appropriate to discuss
over a video consultation. Further, family members joining
the call where appropriate must be supported in relation to
consent and lasting power of attorney (NHS England and
NHS Improvement, 2020).

Further obstacles to the use of video assessments have also
been described by staff and echoed by Gann (2020) and
Hammersly et al (2019), who reported that COVID-19 has
identified some communities, predominantly those of older
people living in care homes, as experiencing social, economic
and digital deprivation. To combat this, there are many digital
initiatives across the UK during the pandemic, such as Attend
Anywhere, telemedicine and IMedicine, which are supplying
devices and education in relation to digital skills, in order to
support the agenda that NHS England has implemented and
reduce footfall in care homes to limit exposure (Hollis et al,
2015). However, deprivation in care home communities is a
prevalent risk, and the complexities in different demographics
correlate with access to digital technology. This has been
highlighted by Holmes Finch and Hernández Finch (2020);
despite this being an American study, the data translate and
reflect the narrative in the global health community. The
authors described how more affluent areas have access to
modern technology supporting digital assessment as well as
having the means to financially support high internet usage.
Financial constraints when using virtual assessments have
been addressed (Brouwer et al, 2017), where it has been
reported that the technology is widely whitelisted, meaning
that large telephonic and broadband companies allow the
access of these digital services to be provided free so as not
to disadvantage anyone. Most recently, Vodaphone and 02
have whitelisted Attend Anywhere in the UK, making it free
to access.

Another barrier to the effective usage of the digital
consultation system is staff members’ literacy and IT skills.
Robinson et al (2020) and Visca et al (2020) reported on
the impact of digital inequalities in different healthcare
sectors in relation to the education level, and argued that
there is a consequent impact on patient vulnerability to
disparate healthcare. This is supported by earlier evidence,
which suggested that people with poor literacy skills do not
receive as effective healthcare, due to lack of understanding
or lack of ability to implement healthcare plans owing to
comprehension difficulty (Taylor et al, 2013). With regard
to telemedicine, it can be the case that patients are being
managed by staff who do not have compatible IT skills, and
this could be one of many obstacles in the provision of care
to the vulnerable (Blackburn et al, 2005).

The final threat to the implementation of the video
conferencing system is change management for healthcare
providers. Irrespective of sector, if change is to be effectively
implemented and successful, leaders in the field must be
advocates, lead by example and encourage usage (Zaman
et al, 2020). Opinions offered by some are that there is
evidence of positive digital leadership within trusts, but this
is not reflected at team level. Sheninger (2019) discussed the
importance of leaders in encouraging change and the use of
technology in the best interest of patients.

Sellars et al (2020) encouraged leaders to share positive
outcomes and opportunities with staff. In their review of the
use of virtual consultation mediums, they reported very few
patients as having difficulties with technology, and attendance
for virtual appointments was very high; in fact, it was higher
than that for face-to-face appointments. Further, 6685 miles
of travel, equivalent to 148 hours of travelling time, were saved
for patients, with savings for the total number of patients
amounting to £1767, not including the approximately
£33.56 that each patient may have saved by preventing loss
of earnings. Additionally, the environmental impacts were
massive, as carbon emissions were lowered by 4659 lb, which
is the equivalent of over 250 000 charges of a smartphone.

Ziebland and Wyke (2012) proposed sharing good news,
which positively impacts patients, and using it as a vehicle
to encourage change. Further, they suggested that sharing
data empowers the recipient to support change. Mannion
and Goddard (2001), however, warned that, although sharing
of data works positively in positive cultures, this practice in
some areas in which there is a lack of professional belief in
relation to the perception of the quality of data may have
the opposite effect to the one desired. They concluded that
informal verbal information is often better received and well
thought of in the encouragement of change. The collaborative
sharing of data should be a common practice according to the
Nursing and Midwifery Council (NMC) (2018), and change
is best supported with strong leadership and encouragement,
evidence of positive results and caution in areas in which the
validity of data will be questioned.

Summary
Virtual consultations allow face-to-face visits to be completed
in a safe way and in accordance with national guidance.
Overall, the evaluation of virtual consultation usage was found
to be positive, and was in line with feedback from the wider
health community. The reduced exposure risk to patients and
staff was paramount and outweighed any problems faced.
Problems such as connectivity issues could be rectified. A
recommendation from this evaluation is that other nurses
within the community nursing sphere should endeavour to
use virtual consultation mediums as an alternative whenever
it is possible and safe, in order to reduce exposure risk. Threats
to safe usage should be risk assessed, and appropriate action
should be taken to minimise risk.

Conclusion
The COVID-19 pandemic has forced the NHS to be
progressive and innovative in its delivery of healthcare. The
fatal nature of the SARS-CoV-2 virus is reflected in the
volume of care home deaths. To prevent further risk and
exposure, consultation mediums have to change and reflect
what is now required to keep patients safe. The evidence
shows that telephone and video assessment, which have been
in place for many years and have been used effectively, are a
possible option. Video assessment is relevant, now more than
ever, for staff working through a pandemic and attempting to
remain safe, as well as for vulnerable patients. The economic,
environmental and physical benefits of video assessments

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KEY POINTS
w The use of telephone triage and assessment and video assessment has
been present for much longer worldwide than it has been in the UK

w The use of technology, in particular platforms supporting the audio and
video assessment of a patient, reduce the risk to the patient or the wider
nursing community by reducing foot fall into care homed

w At the author’s trust, a video consulting platform called Attend Anywhere
provided positive outcomes for patients, while also providing cost efficacy

w A consideration is that the lack of face-to-face appointments would
increase the vulnerability of patients with digitally deprivation, which is a
worldwide risk

w The widespread use of technology in healthcare must be supported by
effective change management, which must be driven by leaders

outweigh any risks, which can be managed effectively for
the patients who reside in care homes. Thus, such alternative
assessments methods should be encouraged wherever safe.
Moving forward in an uncertain world, technology will be
the basis of many healthcare assessments. As the famous author
Matt Mullenweg once wrote, ‘Technology is best when it
brings people together,’ and this technology will certainly
allow people to come together in a new way. BJCN

Accepted for publication: January 2021

Conflicts of interest: none

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CPD REFLECTIVE QUESTIONS
w What are the benefits and disadvantages of providing assessments over
video consultations?

w How can your trust support the use of technology in assessments?

w What tasks within the remit of your role would you be able to complete
over video? For what tasks might video consulting be inapplicable?

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vol. 17, no. 3, March 2021, pp. 276-288

DOI: 10.23940/ijpe.21.03.p3.276288

* Corresponding author.

E-mail address: [email protected]; [email protected]

Code Confusion in White Box Crowdsourced Software Testing

Run Luo*, Song Huang*, Hao Chen, and MingYu Chen

Command and Control Engineering College, Army Engineering University of PLA, Nanjing, 210007, China

Abstract

In recent years, crowdsourcing software testing as a new testing service mode has been widely concerned. However, white box

crowdsourcing software testing is often regarded as an insecure testing service mode. The main threat comes from unknown attacks in the

crowdsourcing environment, which leads to the risk of source code leakage in white box testing. This paper discusses the weakness of white

box software testing in crowdsourcing software testing, as well as the possible mode of attack. This paper proposes to use code obfuscation

technology as a solution to this kind of attack and analyzes the impact of code obfuscation technology on crowdsourcing testing. This paper

is the first attempt at using code obfuscation technology in white box crowdsourcing software test task protection.

Keywords: crowdsourcing software testing; code confusion; software security; safety evaluation

© 2021 Totem Publisher, Inc. All rights reserved.

1. Introduction

In recent years, crowdsourcing software testing has gained more and more attention in the field of black box software testing,

such as web testing [1], APP testing [2-3], and QoE testing [4]. Because software testing needs a lot of manpower, time, and

money, crowdsourcing mode can provide a lot of cheap labor, and a lot of attention is conducive to quickly finding all kinds

of software problems. A lot of practice has proven that crowdsourcing software testing has a good effect in improving product

quality and finding software defects [5-7]. Compared with black box software testing, the research progress of white box

software testing in crowdsourcing software testing field is slower. The main reason is that white box crowdsourcing software

testing requires more testing workers, and white box testing also lacks a credible testing environment.

White box crowdsourcing software testing, by calling crowdsourcing testing workers, uses crowdsourcing platform

testing tools to design, write and execute test cases. The employer’s distrust of the crowdsourcing software testing environment

has become a major factor restricting white box crowdsourcing software testing. This distrust comes from the ignorance of

potential attackers in crowdsourcing software testing platform. These attackers can sneak in crowdsourcing workers to steal

the information of the project to be tested. Presently, the relevant research on crowdsourcing software testers mainly focuses

on the research of the workers’ ability, that is, the task is pushed to the right people to complete. It is a long-term and arduous

task to study the credibility of test workers, which needs crowdsourcing test platforms for long-term monitoring [8-9].

We believe that the crowdsourcing test platform and the employer should establish such an understanding: “don’t

completely trust the crowdsourcing test workers”, so this paper is more inclined to use relevant technical means to “encrypt”

the test items before the crowdsourcing test tasks are distributed, that is, targeted transformation test items.

Code security is a big challenge in the field of white box crowdsourcing software testing. White box testing needs to

release software source code to testers to meet the basic conditions of white box testing. Under this condition, white box

crowdsourcing software testing usually decomposes the original project, builds multiple test task packages, and then

distributes these task packages to test workers. The main idea of this kind of method is to break the whole into parts, disclose

the parts and protect the whole. However, there are some defects in code protection by only decomposing the original project,

which will be discussed in Section 3.

Code Confusion in White Box Crowdsourced Software Testing 277

In order to further enhance the security of white box crowdsourcing software testing, this paper proposes to apply the

idea and technology of code obfuscation to the field of white box crowdsourcing software testing. At the same time, in order

to explain the reliability of our method, we also design a brute force cracking algorithm for white box crowdsourcing software

test package and a restore algorithm based on clue search. By comparing the restoration effect of the project before and after

the confusion, we can find that the task package after the confusion is much more difficult to restore than the original task. At

the same time, in order to verify the impact of code obfuscation on test results, this paper also compares the reusability of test

cases before and after obfuscation, and it finds that the reusability of test code will decrease with an increase in obfuscation

intensity.

2. Background

White box crowdsourcing software testing is a new crowdsourcing software testing service mode. This mode aims to use the

testing workers and testing resources provided by crowdsourcing software testing platform to carry out software testing such

as unit testing, code review, performance testing, etc. [10]., which need to read the source code. At present, the research on

crowdsourcing software testing application is often carried out in the field of black box testing, such as web crowdsourcing,

mobile crowdsourcing, GUI crowdsourcing [11], etc. At the same time, the related research on crowdsourcing software testing

process itself mainly focuses on crowdsourcing task design, crowdsourcing workers call, test report de duplication and so on.

The main goal of these studies is to improve testing efficiency [12-13]. Few people pay attention to the security risks in

crowdsourcing software testing.

Compared with white box crowdsourcing testing, black box crowdsourcing testing has excellent security, except for the

reason that the training cost of black box crowdsourcing is lower than that of white box crowdsourcing. From the perspective

of security, the related technology of code protection for black box programs has been relatively mature. Through the research

of software encryption and decryption, we find that code protection technologies such as digital watermarking [14], instruction

set modification, and virtualization are often used to create an encrypted black box software to prevent the code information

obtained by the cracker [15]. However, white box testing directly exposes the code, and these traditional black box and “shell”

technologies are difficult to apply to the current white box crowdsourcing testing scenarios. Therefore, to ensure the security

of white box test code in crowdsourcing mode, we need to study specific protection technology.

White box crowdsourcing software testing highlights the security risks in crowdsourcing software testing. The employer

needs to release the relevant code required for testing to the crowdsourcing software testing platform. Because the workers

participating in the test are unknown groups scattered in the Internet, the crowdsourcing platform can not guarantee the

reliability of personnel. In the black box crowdsourcing software testing scenario, the employer allows the testing workers to

test the whole software to be tested. In the white box crowdsourcing software testing scenario, in order to prevent the testing

workers from divulging all the employer’s code, the employer decomposes the testing task into several smaller subtasks by

decomposing the original project. Each worker is only allowed to test part of the code that has been allocated. For example,

as shown in Figure 1, a complex program can be decomposed into multiple test tasks. This kind of method is called code

segmentation under white box crowdsourcing testing. The idea of code segmentation is mainly used to hide the relationship

between the local code and the whole code in the program, and to create information fragments to protect the security of the

whole program. At the same time, the split program can be more suitable for the small task mode of crowdsourcing platform.

Figure 1. Code segmentation

For the convenience of analysis, the example language selected in this paper is the golang programming language (later

called Go language) designed by Google, which is known as the 21st century C language. Golang is a static strongly typed,

compiled, parallel programming language with garbage collection function [16]. There is no concept of class and inheritance

278 Run Luo, Song Huang, Hao Chen, and MingYu Chen

in golang’s design. It mainly uses the concept of interface to realize polymorphism. At the syntax level, the reuse of golang is

based on the package, that is, the main package where the main() function is located is used as the entry of the program.

Whenever a function calls a function under this package, it is called directly by the function name. When it needs to call the

function of another package, it needs to import the package and use “imported package name + function name” to call.

The minimum test unit of Go program is function. Go functions can be divided into two categories: one is called methods

with callers and the other is functions without callers. For a function f to be tested, its package is p and its dependent package

set is DP (dependent package). The function can be tested and run under the following conditions: F itself is complete, the

declaration called by F under its package P is complete, and the declaration called by F in its dependency set DP is complete.

Therefore, the most important components of Go program are declaration and package. For statically typed languages, code

segmentation can prune the package P and its dependent package set DP where the function under test f is located through

static analysis technology. It can delete the related declarations that f does not use to get a new package Pd and a new dependent

package set DPd. Then, the code to be tested and its dependencies are encapsulated as a crowdsourcing test task and put into

the crowdsourcing software test environment as a test task.

3. Weaknesses of Code Segmentation

In this section, we will analyze the defect of the code segmentation idea and further illustrate how attackers can use this defect

to restore the decomposed program to the original program. White box crowdsourcing software test code segmentation mainly

refers to: the employer can extract the software fragments that can be tested through static analysis [17-19] and other related

technologies. These fragments are mainly composed of one or more functions to be tested and contain the dependent modules

required by these functions to ensure that they can be tested in a given test environment [20]. However, there are some defects

in decomposing source code to design task package:

1) The number of task packages that can be decomposed is limited by the size of the software to be tested. Fewer test
units means smaller subcontracting, which also means reduction of the difficulty of restoration.

2) Only after segmentation without other processing, as long as all the task packages can be collected in the crowd
testing environment, can the original project be restored.

3.1. Crowdsourcing Task Restoration based on Clues

Suppose a go program contains n test units, then the program can build up to n test tasks. Through code segmentation

technology, these n task packages only contain necessary program information. However, without modifying the program

code, these n tasks contain all the declarations of the original program, which means that the original program can be restored

as long as the declarations are arranged in a certain order. An ideal condition for restoring the original program is that the

original program is divided directly without modifying the original code.

The task package after code segmentation often contains a lot of clues because crowdsourcing employer does not modify

the original code. For example, different task packages contain the same function, or different task packages use the same

declaration, or some similar code style. For example, task package A contains structure graph and defines and functions

addvex and AddEdge. Task package B also contains structure graph and defines functions deletevex and deleteedge.

Obviously, these two task packages are splitting the same go code package. Based on such clues, attackers can quickly merge

task packages to restore the original program (Figure 2). This kind of algorithm analyzes the relationship between task

packages by comparing the statements in n task packages.

Figure 2. Code restore

Code Confusion in White Box Crowdsourced Software Testing 279

It can be seen that although the code segmentation idea decomposes the program into smaller sub fragments, there are

many clues between these sub fragments, which can effectively guide the attacker to restore the original program. Attackers

can use their own unlimited personal time to piece together the code. In order to improve code segmentation, we first need to

analyze the difficulty and cost of code being restored. Thread based restoration can piece smaller program fragments into

larger ones. But when there is no clue or the clue is not obvious, it is often difficult to restore the program. Especially for

thread based restoration, because the thread is a static module such as name and variable, it needs to be manually reconfirmed

by the attacker, so a large part of the overhead is spent on the time of manual confirmation.

3.2. Crowdsourcing Task Restoration based on Directed Acyclic Graph

Crowdsourcing task restoration based on directed acyclic graph is essentially a violent restoration method, which can ignore

the clues between program fragments. It is known that a go program with n declarations is put into the crowdsourcing software

testing environment after code segmentation. Suppose that an attacker obtains all the task packages. Then, the attacker has the

ability to restore the original go language program. First of all, go program can be regarded as a directed acyclic graph

composed of multiple packages. Arrow A points to B, indicating that package B depends on package A. As long as the

corresponding declaration is put into the corresponding package, the original program can be restored. The attacker can regard

the program as a labeled directed acyclic graph with m different points and k edges, and fill n statements into m points. In

many permutations, there must be effective permutations so that the new program is equivalent or completely consistent with

the original program.

Suppose the attacker obtains three non-duplicate statements A, B, and C, and now puts these statements into a package

arrangement. There are 5 cases where the declarations are arranged into packages (Figure 3): 3 in the same package, 3 in 2

packages and 3 in 1 package. A go program with n declarations contains at least one package and at most N packages. When

the attacker doesn’t know the distribution of claims, he first needs to determine the number of packets M. After the number of

packages m is determined, the declaration restore will be changed to put n declarations into m packages. At this time, the

dependencies between packages have not been considered. These packages can be regarded as the same lattice, but the

declarations are different from each other. The problem can be seen as n different balls filling into m identical baskets. The

number of permutation combinations produced by such permutations is called Stirling number (S):

S(n,m)=S(n-1,m-1)+S(n-1,m)*m (n>1,1<=m<n)

Figure 3. Declaration in different packages

Table 1. Package generation algorithm

Algorithm: package generation algorithm

function: DeclInPkgs

Input: declaration list of N declarations

Output: package list of M packages

1. func DeclInPkgs (str [ ]string, m int) [ ][ ][ ]string{
2. var result [ ][ ][ ]string
3. n:=len(str)
4. split(n,m) // Decomposing a positive integer n into m positive integers (recursion)
5. newstr:=wholeArrange(str) // The str is fully arranged to generate a newstr [] string
6. for _,i:=range newstr{
7. According to the M numbers, extract the declaration from the declaration list I and package it into a package
8. Put the generated new package into the package list }
9. return result
10. }

280 Run Luo, Song Huang, Hao Chen, and MingYu Chen

The Stirling number represents the kind of N declarations into m packages. The specific permutation process is calculated

by an O (n!) permutation function. If n statements are put into m packages, it can be regarded as the solution of decomposing

positive integer n into m positive integers. For example, if 4 declarations are put into 2 packages, there are two results: two

packages can have 2 declarations each; or one package can have 3 declarations, and the other package can have 1 declaration.

The specific packet arrangement algorithm is shown in the following Table 1.

Figure 4 shows that a change of packet permutation results in the interval of packet number ∈ [1, ] and the second
Stirling number composed of positive integer n and m with the increase of declaration number n. This method of using

permutation and combination to construct the declaration as a package can be used to sort violently regardless of the clues in

the program. The main cost of the algorithm is to make a full permutation of the declaration sort, so the problem can be solved

in polynomial time.

Figure 4. Relationship between declaration, package and Stirling number

After all the packages are determined, we only need to further establish the dependency graph relationship between

packages to restore the program. The essence of dependency graph of go language program is a directed acyclic graph. The

calculation formula of the kind of directed acyclic graph with n nodes is as follows:

( ) = ∑ (−1) +1 (

)

0≤ ≤

⋅ 2 ( − ) ⋅ −

Given that a directed acyclic graph has n vertices, then the number of edges in the graph is = [0,
( −1)

2
]. For example,

the result of a directed acyclic graph with two points is shown in Figure 5. The number of edges in a directed acyclic graph

with N + 1 vertices is = [0,
( +1)

2
]. A directed acyclic graph with N + 1 vertices can be regarded as a directed acyclic graph

with n vertices and m edges added with [0, n-1] edges. Figure 6 shows the result of adding a point to a directed acyclic graph

from A to B.

Figure 5. Directed acyclic graphs with two points

When a directed acyclic graph with n-1 points is extended to n points, the relationship between the nth point and the

existing n-1 points has three cases: the new point to the existing points, the existing points point to the new point, and there

is no edge between the two points. There are 3 −1 kinds of such relationships, and the relationships of these edges can be
represented by a trigeminal tree. The Table 2 shows the Directed Acyclic Graph Create Algorithm , and the trigeminal tree

shown in the graph represented by Figure 7 shows an increase of edges of a directed acyclic graph with A pointing to B in C.

The left child of the tree indicates that the new point points to the existing point, the middle child of the tree indicates boundless,

and the right child indicates that the existing point points to the new point. A path from the root node to the lowest leaf node

0

50

100

150

200

250

300

350

400

0

1

2

3

4

5

6

7

8

1 3 5 7 9 11 13 15 17 19 21 23 25 27

declaration package Stirling

Code Confusion in White Box Crowdsourced Software Testing 281

is the relationship of edges in a new graph. And obviously, the automatic generation of directed acyclic graph with n points

is a recursive process. Every time an existing graph generates a batch of new graphs, it will perform 3 −1 calculations.

Therefore, to complete all the directed acyclic graph calculations of [1, n], 3
( +1)

2 calculations are performed, that is, the time

complexity of the algorithm is O( ).

Figure 6. Three points constitute a directed acyclic graph

Table 2. Directed Acyclic Graph Create Algorithm

Algorithm: Directed Acyclic Graph Create

Function: DAGCreate

Input: Directed acyclic graph olddag with n-1 vertices

Output: The set newdag of directed acyclic graphs with n vertices

1. func DAGCreate (OldDAG *OLGraph) []*OLGraph{

2. result []*OLGraph

3. Create Trie(n-1) // Create a trident tree
4. NewEdges=SearchTree() //Each edge relation of the tree is stored in the frontier series table

5. for _,i:=range NewEdges{

6. g=CopyOLGraph(OldDAG) //Copy the Graph

7. NewDAG=AddNewEdges(g)// Add all new edges
8. if nocyc(NewDAG){ // Judge whether there is a cycle
9. result=append(result,NewDAG)}

10. }

11. return result

12. }

Figure 7. Trigeminal tree represents the relationship between two points

According to the above analysis, it can be seen that the reduction of statements to packages and the generation of directed

acyclic graphs from the relations between packages are solvable in super polynomial time without using clue analysis program.

As the number of claims increases, the cost of violent restoration will increase rapidly. The number of final programs b(n)

consists of two parts: one is the number of packets that can be composed of declaration numbers, and the other is the total

number of labeled directed acyclic graphs [21] that can be composed of these packets.

( ) = ∑

=1

( , ) ⋅ ( ) ( ≥ 1)

The difficulty of restoration can be regarded as the reciprocal of the proportion of the graph that makes the program

equivalent to the original program in all graphs. The essence of clue based restoration is to find the relationship between

statements by searching, so as to generate the corresponding subgraph, which reduces the amount of calculation. Therefore,

the main shortcomings of the segmentation idea are:

1) The code can be restored after segmentation, and the difficulty of restoration is related to the number of fragments
that can be decomposed by the program itself.

282 Run Luo, Song Huang, Hao Chen, and MingYu Chen

2) After segmentation, the clues between codes will greatly reduce the difficulty of restoration. The main reason is to
determine the position of the unknown point (declaration package) and the edge (dependency) in the graph, thus

reducing the uncertainty of the graph. The ability to find clues depends on the efficiency of the attacker’s analysis

algorithm.

4. Approach

In the previous section, we pointed out the shortcomings of the code decomposition idea. Attackers can restore it according

to clues or violence by collecting task packages. In this section, in order to increase the difficulty of cracking and even affect

the results of cracking, we propose to introduce code obfuscation based on existing subcontracting to improve the security of

white box crowdsourcing software testing tasks.

4.1. Code Obfuscation Theory

Definition of code obfuscation[15]: code obfuscation is to convert program P into an equivalent program T(P) through

obfuscation transformation T. Let i be an element of the set I of all the inputs of program P, only if ∀ⅈ : ( )(ⅈ) = (ⅈ) then
the obfuscation transformation T for program P is correct (Figure 8). Correct confusion also means that if P is wrongly

terminated or cannot be terminated, then T(P) is wrongly terminated or cannot be terminated. Otherwise, T(P) must abort and

produce the same output as P. In the white box crowdsourcing software test environment, code obfuscation must guarantee

the UT of P test set: ∀ⅈ : ( )(ⅈ) = (ⅈ).

Figure 8. Code Obfuscation

Common code obfuscation methods are: (1) layout obfuscation – changing the readability of source code by modifying

function name and variable name. (2) Control flow confusion mainly refers to modifying loop statements – judging statements

and providing opaque predicates to change the control flow to a certain extent. (3) Data obfuscation refers to the obfuscation

of numerical value or data structure in program operation. (4) Preventive obfuscation, through the study of some known anti

obfuscation software, provides some improvement programs for existing obfuscation. The common preventive obfuscation is

to create a special instruction set in the virtual machine.

By modifying the source code, code obfuscation can effectively resist the cracking of the source code by reverse tools.

Generally speaking, code obfuscation mainly acts on the completed program and is mainly used to add “shell” to the black

box program. We think that its special idea can also be used in the special environment of white box crowdsourcing software

testing.

Obfuscated Target: any form of code protection that cannot achieve comprehensive protection, the defender designs

the corresponding protection scheme according to the known attack means. Therefore, before code obfuscation, we must first

identify the object or target to be protected. The main purpose of white box crowdsourcing software testing is to hope that

testers can write test cases. We are willing to complete the part that workers are assigned, but we are opposed to attackers

getting larger units. A larger unit means a more complete module of the original program, so the obfuscation goal is to hide

the relationship between these modules so that the computational cost of restoration is greater and even the original program

cannot be restored. The test cases obtained in crowdsourcing software testing environment can effectively affect the

unambiguous programs.

Confusion evaluation index: the traditional evaluation index of code confusion is mainly proposed by Collberg, which

is composed of Intensity, Flexibility, Concealment and Cost [15,22]. Intensity mainly refers to the complexity of the

program after confusion, which will be more complex. Elasticity refers to the resistance of the program to the analyzer after

obfuscation. The stronger the resistance, the better the obfuscation algorithm. The stronger the concealment, the less likely

the analyst is to realize that the program is confused. The cost refers to the additional cost of the confused program when

Code Confusion in White Box Crowdsourced Software Testing 283

compared with the original program. This value will not be less than the cost of the unambiguous program itself. Therefore,

the cost should be a small difference to prevent the confusion of the program running too much cost.

In the new scenario of white box crowdsourcing software testing, new requirements for code obfuscation are put forward.

1) Intensity: first of all, the intensity needs to be paid special attention in this environment. If the program is modified
too complex through code obfuscation, it will affect the test workers’ testing of the program, so the obfuscation

intensity needs to be as low as possible.

2) Flexibility: as an evaluation index of code obfuscation algorithm against analysis tools, resilience is still an important
index in the new environment.

3) Concealment: concealment, as a special index to reduce the possibility of confusion, should also be retained.
4) Calculation Cost: since the obfuscated code inserted in the program fragment may not be added to the final program,

the overhead caused by obfuscation in the test process can be ignored. Runtime overhead is not an indicator of

crowdsourcing white box software testing.

5) Crowdsourcing Cost: although we don’t pay attention to runtime overhead, it is replaced by cost, which is the cost
of crowdsourcing software testing. Here, it mainly refers to the cost of code confusion compared with unambiguous

programs. The cost is mainly the cost of time, money or manpower.

6) Test Effectiveness: the fundamental purpose of white box crowdsourcing software testing is to collect test cases.
The test cases collected by the …

Vol.:(0123456789)1 3

Journal of Business Ethics (2020) 167:433–450
https://doi.org/10.1007/s10551-019-04143-6

R E V I E W PA P E R

Biometric Technology and Ethics: Beyond Security Applications

Andrea North‑Samardzic1

Received: 14 July 2018 / Accepted: 4 March 2019 / Published online: 8 March 2019
© Springer Nature B.V. 2019

Abstract
Biometric technology was once the purview of security, with face recognition and fingerprint scans used for identification
and law enforcement. This is no longer the case; biometrics is increasingly used for commercial and civil applications.
Due to the widespread diffusion of biometrics, it is important to address the ethical issues inherent to the development and
deployment of the technology. This article explores the burgeoning research on biometrics for non-security purposes and
the ethical implications for organizations. This will be achieved by reviewing the literature on biometrics and business ethics
and drawing from disciplines such as computer ethics to inform a more robust discussion of key themes. Although there are
many ethical concerns, privacy is the key issue, with associated themes. These include definitions of privacy, the privacy
paradox, informed consent, regulatory frameworks and guidelines, and discrimination. Despite the proliferation of biometric
technology, there is little empirical research on applied biometrics and business ethics. As such, there are several avenues
for research to improve understanding of the ethical implications of using this technology.

Keywords Biometric technology · Ethics · Privacy

Introduction

Biometric technology is widely used by a variety of organi-
zations. Fingerprint scans and face recognition technology
(FRT) are commonly used to assist with surveillance and
border security. Recently, biometric technology has been
used for commercial and civil applications, such as Face-
book and iPhone, for identity management. With this evo-
lution in application, questions arise about the ethical use
of such technology within the broader field of technology
ethics. It is its own field, distinct from other technological
innovations such as artificial intelligence, three-dimensional
printing, cloud technology, data analytics, nanotechnolo-
gies, and robotics (Schuelke-Leech 2018). Like these tech-
nologies, biometrics is disruptive, as it has the capacity to
“restructure, reorganize, disrupt current social and institu-
tional norms and standards, operations, production, trends,

not limited to a particular market or industry” (Schuelke-
Leech 2018, p. 270).

Unlike other technological innovations, biometrics leads
to additional ethical concerns. Collecting biometric data
have been described as “giving up a piece of yourself”
(Alterman 2003), akin to extracting a biological sample
(Milligan 1999), making it “intrusive” (Sprokkereef and de
Hert 2012) and “invasive” (Jain and Kumar 2012) for data
subjects. With the advent of second-generation behavioral
biometrics, issues extend to covert data capture and lack of
transparency and consent (Sprokkereef and de Hert 2012).
This impinges on people’s right to control their identity
(Alterman 2003; Milligan 1999). This requires an examina-
tion and exploration of the ethical implications of the use of
biometrics in and by organizations.

This article reviews the nascent literature on biometrics
in applied organizational and business contexts, extend-
ing the themes and debates by drawing from the broader
and more longstanding fields of technology and computer
ethics. Although the literature on biometrics and business
ethics is not substantial, it raises new and troubling ques-
tions that require debate and consideration from scholars to
inform ethical business practices. While legislation covers
many aspects of the ethical issues raised in the literature,

An earlier version of this paper was accepted for the 77th
Academy of Management Meeting. 

* Andrea North-Samardzic
[email protected]

1 Department of Management, Deakin Business School,
Deakin University, 70 Elgar Road, Burwood, VIC 3125,
Australia

434 A. North-Samardzic

1 3

regulatory frameworks alone are insufficient to ensure ethical
probity in the use of biometric technology in organizations.

This article provides an overview of the nature of bio-
metric technology and its applications. Attention is given
to its evolution, from first to second generation and affor-
dances. Next, the literature on biometric technology in
applied organizational contexts, specifically business ethics,
is reviewed. As most research does not consider ethical con-
cerns for organizations, the extant literature on technology
ethics informs a discussion of the themes that emerged from
the review of the research on biometrics and business ethics,
and ethics theories and frameworks. Building on this review,
this article identifies areas for theoretical development,
empirical advancement, and practical implications for the
ethical use of biometrics. Although there is limited research
on this topic, combined with broader research on biomet-
rics and applied ethics, there are significant issues worth the
attention of business ethics researchers and organizations.

Biometrics: An Overview of Application
and Purpose

Biometric technology concerns the use of the physiological
and behavioral characteristics of individuals. Biometric data
are usually used for identity management or authentication
(Jain et al. 2000). Biometric technology uses people’s fea-
tures and characteristics to capture data such as fingerprints,
palm prints and geometry, hand vein patterns, finger knuckle
prints, face, ear shape, tongue print, iris, retina, sclera, voice,
keystroke dynamics, gait, signature (Unar et al. 2014), pulse
and DNA (Sutrop and Laas-Mikko 2012). These can include
static and moving images (Zhao et  al. 2003). Jain et  al.
(2004, p. 2) identified the four most important qualities of
biometric data:

1. universality: each person should possess the character-
istic

2. collectability: the characteristic can quantitatively meas-
ured

3. distinctiveness: the characteristic should be different
between people

4. permanence: the characteristic should be invariant over
time.

The system must also be capable of accuracy and effi-
ciency, acceptable to users, and non-susceptible to circum-
vention, such as hacking (Jain et al. 2004).

Biometrics can include medico-chemical technology
such as magnetic resonance imaging and electrocardiogram
machines (Unar et al. 2014). There is merit to recognizing
such technology, given that personal fitness devices, such as
Apple Watch and Fitbit, are considered biometric technology

and incorporate health and medical data into their functions
(Karkazis and Fishman 2017). Medico-chemical devices
used in medicine are outside the scope of this review, as they
were designed for different purposes, have separate regula-
tory frameworks, and are not used for civil applications out-
side healthcare. Thus, the ethical implications are different.

There are several notable shifts in biometric technol-
ogy, from first to second generation. The latter has a greater
focus on behaviors, as opposed to individual identifiers.
Schumacher (2012) characterizes this shift as moving from
“who you are” to “how you are.” There has also been shifts
in purpose and application, from security to safety (Norval
and Prasopoulou 2017), specifically, civilian and private sec-
tor applications (Prabhakar et al. 2003).

A 2003 literature review of the applications of FRT (Zhao
et  al. 2003) identified four main uses of the technology:
entertainment, smart cards, information security, and law
enforcement. These activities specifically include (but are
not limited to) border control, forensics, criminal identifica-
tion, access control, computer logins, e-commerce, welfare
disbursements, missing children identification, identification
cards, passports, user authentication on mobile devices, and
time and attendance monitoring systems (Bhattacharyya
et al. 2009; Unar et al. 2014). With the shift to second-gen-
eration biometrics, the technology is extending beyond iden-
tity management to group analysis, in which generalizations
about demographic categories can be made and behaviors
can be analyzed (Schumacher 2012). It has afforded the rise
of what McStay (2014, 2018) refers to as emotional surveil-
lance or “empathic media … technologies that track bodies
and react to emotions and intentions” (McStay 2016, p. 1).
These differences are summarized in Table 1.

The diffusion of biometric technology has created new
affordances outside traditional security and identity manage-
ment. Biometrics has been used to assess student engage-
ment. D’Mello et al. (D’Mello and Graesser 2010; D’Mello
et al. 2009; McDaniel et al. 2007), among others (Whitehill
et al. 2014), used FRT to evaluate the responses of students
to classroom learning. This illustrated that facial movements
predict outcomes of engagement, frustration, and learning
(Grafsgaard et al. 2013). There is considerable research on
audience evaluation in the form of laboratory studies that
sought to gauge audience responses to arts, media, and enter-
tainment (Hassib et al. 2017; Kirchberg and Tröndle 2012,
2015; Martella et al. 2015, 2017; Soleymani et al. 2014;
Wang and Cesar 2014, 2017; Wang et al. 2014, 2016; Webb
et al. 2016). Market research has used “methods such as eye
tracking, measurements of brain activity through electroen-
cephalography (EEG), and measurements of psychophysio-
logical changes via electro-dermal activity” (Gregersen et al.
2017, p. 3). This is also known as galvanic skin response.

This research shows that the use of biometrics has sig-
nificantly broadened beyond its initial applications. With

435Biometric Technology and Ethics: Beyond Security Applications

1 3

new affordances comes the potential for new or different
ethical concerns (Schumacher 2012). The abovementioned
studies are lab based. However, the question arises as to
what happens when first- and second-generation technology
is applied to organizations without ethical research guide-
lines. Given the widespread use of biometrics, the role of
organizations as developers and users requires scrutiny. How
business ethics addresses these concerns is worth examining.

Technology and Business Ethics

Before addressing biometrics and ethics in applied business
and organizational settings, it is important to first address the
existing literature on technology and business ethics so that
the relevant research can be positioned in relation to existing
debates and themes. A study of biometrics and ethics would
be situated in the broader field of applied technology and
ethics in organization technology (Buchholz and Rosenthal
2002; Loch et al. 1998; Martin and Freeman 2004). It would
sit alongside research themes such as worker surveillance
(Brown 1996; Loch et al. 1998; Martin and Freeman 2003;
West and Bowman 2016), big data ethics (Herschel and
Miori 2017; Nunan and Di Domenico 2017; Zwitter 2014),
and the ethics of algorithms (Martin 2018). One of the main
questions raised about technology, ethics, and organiza-
tions by business ethicists is “who should be accountable
for the ethical implications of technologies? (Martin and
Freeman 2004)” There is consensus that the organizations
that deploy the technology should be accountable (Martin
and Freeman 2003; West and Bowman 2016). Martin (2018)
argues that developers of algorithms should be responsible
for constructing software with ethical principles in mind.
The nature of this accountability does not always align with
ethical concepts, such as privacy as dynamic in practice
(Brown 1996). In addition, the role of the software in the
decision being made (either small or large) and the implica-
tions of the decision on society (ranging from minimal to
pivotal, such as access to public goods) affect the nature of
the responsibility (Martin 2018).

The ethics of technology and business have been well
established by scholars, which begs the question of whether
new ethical concerns arise when biometrics is used for non-
security applications. Johnson (2001 in Martin and Free-
man 2003) suggests that new technologies do not raise new
ethical issues, simply new behaviors. For example, worker
surveillance is common. Using biometric technology for this
purpose may not change the nature of existing ethical con-
cerns or create new ones. However, it is important to review
the literature to ascertain if the use of biometric technol-
ogy by businesses poses new or different ethical matters for
researchers and organizations. Biometric scholars, such as
Schumacher (2012), contend that it engenders new ethical
considerations.

To advance this inquiry, an important step is to recognize
one of the fundamental assumptions underpinning debates
about technology and business ethics; that is, the relation-
ship society has with technology. The traditional view con-
siders the relationship either socially or technologically
determined, representing two ends of a spectrum (Martin
and Freeman 2004, p. 354). For Martin and Freeman (2004),
this binary approach is limited, as people’s relationship with
technology is neither fully technologically deterministic
(i.e., people are controlled by technological artifacts) nor
socially determined (i.e., technology is neutral and socially
controlled). This approach perpetuates Martin and Free-
man’s (2004) separation thesis of business and ethics, in
which business is detached from ethics. Instead, they advo-
cate a socio-technical systems approach, in which people’s
relationship with technology is a natural social interaction
and cannot be appropriately captured by binary opposites;
people both shape and are shaped by technology (Martin and
Freeman 2004). As such, it is simplistic to cast technology
as either value-laden or morally neutral. In practice, people
have constant and dynamic interactions with technology and,
as such, ethics and technology, like ethics and business, are
intertwined (Martin and Freeman 2003).

However, Martin and Freeman (2004) argue that a socio-
technical systems approach alone is insufficient for a robust
understanding of the situated nature of technology within

Table 1 Comparison of first- and second-generation biometrics

First generation Second generation

Purpose Who are you? How are you?
Application Identity management and authentication Safety and behavioral assessment
Context Government and security Civil and private sector
Level of analysis Individual Groups
Primary ethical concern Privacy risks Discrimination power
Example Fingerprint or face recognition for law

enforcement or consumer device identity
management

Voice recognition to understand individual affect and face recognition
to assess group demographic characteristics such as age, gender, and
race

436 A. North-Samardzic

1 3

organizations. They extend this view to account for business
ethics concerns. Martin and Freeman (2004) take a prag-
matic perspective and draw from their earlier work (Martin
and Freeman 2003) that proposes a framework for ethical
analysis. This is particularly useful for examining the ethi-
cal implications of technology within organizations, which
appreciates the situated and relational nature of technology
and business ethics. This includes an analysis of the tradi-
tional moral concepts of self, relationships with others, com-
munity, and property (Martin and Freeman 2003). Regarding
the concepts of self, relationships with others, and commu-
nity, they are surrounded by moral rights and duties such
as freedom, privacy, respect, and responsibility. Similarly,
property has associated concepts of responsibility, use and
ownership, and voluntary agreement.

Whether the literature on biometrics and business eth-
ics engages with these themes and frameworks is of inter-
est to this article. Although this is not an in-depth review
of the scholarship on technology and business ethics, this
discussion provides an overview of themes and concerns to
facilitate a comparison with the review of the biometrics and
business ethics literature. The following section provides
a review of the research into, and ethical concerns about,
biometrics for non-security purposes.

Literature Review

Biometric technology has been in existence for over six
decades (Royakkers et al. 2018), making for an expansive
body of literature. This creates a challenge for determin-
ing the research to be considered to develop a cohesive and
comprehensive—although not exhaustive—foundation for
biometrics and business ethics scholarship. Three databases
were searched (Business Source Complete, ProQuest Cen-
tral, and ScienceDirect) using the terms “biometric” and
“ethics.” Thousands of peer-reviewed journal articles were
returned. A cursory examination revealed that a substantial
number were irrelevant, as they were unrelated, consisted of
book reviews, or were from business publications. To refine
the fields, each database was considered separately.

Thirty articles were returned from Business Source Pre-
mier, with 15 from scholarly journals. These were scanned
to determine if they discussed biometrics or ethics, or merely
used the terms as examples. This resulted in six articles that
addressed applied organizational, business or management
contexts, or non-security applications such as consumer
products, worker surveillance, or professional ethics. The
search of ProQuest Central resulted in 13,365 peer-reviewed
academic articles in scholarly journals. Given the signifi-
cant number of articles returned, the search was refined
to be limited to articles with biometrics and ethics in the
abstract; this elicited 26 articles. As ProQuest Central is a

multidisciplinary database, 11 medical research articles were
returned and removed from the list, leaving 15 articles, with
a subsequent article removed due to relevancy. Two were
found in the search from Business Source Premier. A review
of these articles resulted in an additional three identified as
addressing biometrics and ethics in a business context.

It was concerning that the articles that were returned did
not account for relevant technology and ethics journals such
as Surveillance and Society, Ethics and Information Tech-
nology, Science and Engineering Ethics, Journal of Infor-
mation, Communication and Ethics in Society, and Journal
of Business Ethics. An additional search of these journals
using the terms “biometric” and “ethics” returned 87 arti-
cles. To refine this search to those that were most relevant to
business ethics scholarship, they were scanned to discover
if they substantively addressed biometrics and ethics. If the
words “biometric” or “ethics” were used only once or twice
as illustrative examples of technology but were not actively
discussed, the article was removed from the list. Business
publications or book reviews were removed. This resulted in
a list of 63 articles. These articles were scanned to ascertain
if they discussed biometrics and ethics in an applied busi-
ness or organizational context. This resulted in an additional
six articles added to the list.

The search of ScienceDirect resulted in 2870 articles that
mentioned “biometric” and “ethics.” Similar to the ProQuest
Central database, this was refined by searching for articles
with these terms in the title or abstract. Only two were
returned, both of which were in public health. As such, none
of the search returns from this database were included. The
final list of 15 articles that address biometrics and ethics in
an organizational or business context is included in Table 2.1
These articles were reviewed to ascertain key elements such
as whether the article was empirical or conceptual, the topic
of the article, whether biometrics was the main technological
focus, if it encompassed first or second biometric technology
(see Table 1), the ethical theories included, the ethical issues
raised, and the organizational context in which biometrics
was applied.

As observed in Table 2, there are commonalities between
the literature on applied biometrics and ethics in business.
Most research is conceptual, rather than empirical, which
means that evaluation of the applications of the technology
and the ethical implications is necessary. First-generation
biometrics for identity management is addressed, in addition
to second-generation behavioral biometrics. The context in
which the technology is applied is varied, with a number of
articles exploring the ethical issues associated with biomet-
rics related to customers, such as consumer products (Cor-
coran and Costache 2016; Park and Skoric 2017; Shi and Wu

1 This review was updated in October 2018.

437Biometric Technology and Ethics: Beyond Security Applications

1 3

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438 A. North-Samardzic

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439Biometric Technology and Ethics: Beyond Security Applications

1 3

2017), retail (Trocchia and Ainscough 2006), and marketing
(Ulman et al. 2015). These authors go beyond addressing
biometrics for consumer identity management to address
how the technology can be used to extract behavioral infor-
mation. This issue was also explored in the context of per-
formance data from athletes as employees and the associated
ethical implications (Evans et al. 2017). Although biometrics
for authentication in libraries (Dixon 2008) is acknowledged,
the remaining articles discuss the ethical implications for
business and organizations broadly, rather than in relation to
specific applications or contexts. For example, Ball (2005)
unpacks the ethical concerns if biometrics is used for organi-
zational surveillance in general.

As evidenced in Table 2, less than half the articles used
ethics theories or frameworks to inform their analyses, with
little convergence; only Habermas’ discursive approach was
mentioned more than once. The absence of a theoretical or
conceptual grounding in the literature is notable and will
be discussed later. Many similar ethical themes were raised
throughout the articles, indicating an opportunity for unify-
ing theories, concepts, and frameworks to be employed in
future research.

The themes identified from the articles in Table  2 are
conceptualization of privacy, the privacy paradox, informed
consent, legal frameworks, and discrimination. However, 15
articles are …

IT513 1

Unit 2 Assignment

Student’s name: Roger Dominguez

Today’s date:

Quotes

Parenthetical style quote

“In order to deter the opponent cyber-provocation and to gain dominance in the cyber-
warfare, we must collect information, make decisions, and act before the enemy” (Kim et
al., 2018, p. 76).

Narrative style quote

However, it was stated by Kim et al. (2018) “It is necessary to change the traditional
defensive cyber warfare strategy […] with the future cyber battlefield environment”
(p. 79).

Reference entry

S.K. Kim, S.P. Cheon, & J.H Eom (2018, October 5). A leading cyber warfare strategy according
to the evolution of cyber technology after the fourth industrial revolution. International
Journal of Advanced Computer Research, Vol. 9 Issue 40, p72-80.

First Paraphrase

Descriptive title:

Using Virtual Reality for Drivers with PTSD

Paraphrase

A study was conducted in the United States and data was shown that following a car
accident many drivers suffer from a form of PTSD. Drivers have a phobia to continue
driving after their accidents. The psychology department at the University of Würzburg,
has tried to implement virtual reality to treat these drivers of their fears. Their regiment
included a medical and psychological evaluation. It proceeded with two preparatory
therapy sessions to get the patients ready. The focus of the treatment was to get the
afflicted to do five virtual exposure sessions, meaning a virtual driving simulation. If they
completed five successfully, they were then given a final Behavioral Avoidance Test

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IT513 Assignment 2 2

(BAT). This final test was done on the physical road. Once they completed the full
treatment, they were given a closing evaluation and two follow-up calls in six-week
increments. According to the researchers Kaussner et al (2020), the results showed that
out of the fourteen drivers that this method was tested, seventy-one percent had achieved
the minimum requirement measured by their driving instructor. A greater percentage of
ninety-three percent were able to maintain the treatment’s effects following their final
phone call in the program (p.8). The end results showed that virtual reality as a form of
simulated assistance has promise to treat driver phobia.

Reference entry

Y. Kaussner, A.M Kuraszkiewicz, S. Schoch, P. Markel, S. Hoffman, R. Baurstreubel, R.
Kenntner-Mabiala & P. Pauli (2020, January 7). Treating patients with driving phobia by
virtual reality exposure therapy – a pilot study. PLoS ONE. Vol. 15 Issue 1, p1-14. 14p

Second Paraphrase

Descriptive title:

The History and Impact of Artificial Intelligence

Paraphrase

The history of artificial intelligence is one that is longer by imagination and shorter if
referencing when it was used in practice. The start of AI dated back to the 1940s but only
in fiction. Science fiction writer Isaac Asimov wrote a story about a robot who operated
on the principles of AI such as self-learning. The actual term itself was not coined until
more than ten years later by Marvin Minsky and John McCarthy for a workshop they
held surrounding the field at Dartmouth College. This conference furthered advancement
in the field, but the United States government saw no value in how expensive it was to
conduct this research with how slow it was progressing. The advancement of computers
was able to revive AI research in the 1990s and the computing power that was lacking in
the past brought new possibilities moving into the future. The modern era of AI has
adapted to be able to input billions of megabytes of information for big data storage. The
authors Haenlein and Kaplan (2019) highlight major issues going forward, revolve
around the necessity for AI and how dependent humans may become on it. The evolution
of AI has moved rapidly over the past twenty years that a new problem of, how does one
regulate an industry with swift evolution (p.9)?

Reference entry

M. Haenlein & A. Kaplan (2019). A Brief History of Artificial Intelligence: On the Past, Present
and Future of Artificial Intelligence. California Management Review. Vol. 61 Issue 4, p5-
14. 10p.

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