# Integrating Accessibility in a Mobile App Development Course

Jaskaran Singh Bhatia  BITS Pilani, KK Birla Goa CampusGoaIndia403726 ,
Parthasarathy P D  BITS Pilani, KK Birla Goa CampusGoaIndia403726 ,  Snigdha
Tiwari  BITS Pilani, KK Birla Goa CampusGoaIndia403726 ,  Dhruv Nagpal  BITS
Pilani, KK Birla Goa CampusGoaIndia403726 and  Swaroop Joshi
<EMAIL_ADDRESS>0000-0003-4536-2446 BITS Pilani, KK Birla Goa
CampusGoaIndia403726

(2023)

###### Abstract.

The growing interest in accessible software reflects in computing educators’
and education researchers’ efforts to include accessibility in core computing
education. We integrated accessibility in a junior/senior-level Android app
development course at a large private university in India. The course
introduced three accessibility-related topics using various interventions:
Accessibility Awareness (a guest lecture by a legal expert), Technical
Knowledge (lectures on Android accessibility guidelines and testing practices
and graded components for implementing accessibility in programming
assignments), and Empathy (an activity that required students to blindfold
themselves and interact with their phones using a screen-reader). We evaluated
their impact on student learning using three instruments: (A) A pre/post-
course questionnaire, (B) Reflective questions on each of the four programming
assignments, and (C) Midterm and Final exam questions. Our findings
demonstrate that: (A) significantly more ($p<.05$) students considered
disabilities when designing an app after taking this course, (B) many students
developed empathy towards the challenges persons with disabilities face while
using inaccessible apps, and (C) all students could correctly identify at
least one accessibility issue in the user interface of a real-world app given
its screenshot and 90% of them could provide a correct solution to fix it.

accessibility, mobile app development, computing education, global computing
education

††copyright: acmcopyright††journalyear: 2023††doi: 10.1145/TBA††conference:
SIGCSE ’23: ACM Technical Symposium on Computer Science Education; March
15–18, 2023; Toronto, Canada††booktitle: SIGCSE ’23: ACM Technical Symposium
on Computer Science Education, March 15–85, 2023, Toronto, Canada††price:
15.00††isbn: 978-1-4503-XXXX-X/18/06††ccs: Social and professional topics
Computing education††ccs: Human-centered computing Accessibility

##  1\. Introduction

Despite an increasing awareness in the software industry about accessibility
over the past few years, many mainstream software products fall short of
meeting accessibility criteria (Ross et al., 2020; Agrawal et al., 2021; Fok
et al., 2022; Balaji and Kuppusamy, 2016; Kuppusamy and Balaji, 2021).
Software professionals point to a lack of relevant knowledge and skills in
computing education for this gap in implementing accessibility (Patel et al.,
2020). According to the computing (CS) faculty, the main barriers to teaching
accessibility include the lack of clear learning objectives about
accessibility and their lack of knowledge about accessibility (Shinohara et
al., 2018; Soares Guedes and Landoni, 2020). Also, most instructors who teach
accessibility have a background in human-computer interaction (HCI) and
related fields and teach these topics in specialized electives (Shinohara et
al., 2018). This indicates that other instructors may find it challenging to
build their expertise and incorporate accessibility topics in the “mainstream”
CS courses. Our work contributes to the literature that aims to bridge this
gap by developing relevant course material, resources, and assignments that
other instructors can readily integrate into their courses without much prior
knowledge about accessibility and without diluting the “core” learning
objectives.

We report on our experience integrating accessibility topics in a mobile app
development elective for junior/senior undergraduate CS students. All
resources, including slides, video lectures, assignments, starter codes, and
exam questions, are available online at
https://swaroopjoshi.in/project/sugamyata/. We describe the course (Sec. 3),
the instruments we used to evaluate the effects of integrating these topics
and our findings (Sec. 4), and discuss the results (Sec. 5) and directions for
future work (Sec. 6) in the rest of this paper.

##  2\. Related Work

Educators have reported on teaching accessibility in special topics courses
such as assistive technology (Matausch et al., 2006) and universal access
(Kurniawan et al., 2010) and developing specialized modules for graduate
programs (Wald, 2008). Some others have integrated accessibility topics in
existing courses such as web development (Rosmaita, 2006; Freire et al., 2013;
Wang, 2012), artificial intelligence (Tseng et al., 2022), software
engineering (Ludi, 2007; El-Glaly, 2020; Ross et al., 2017), HCI (Palan et
al., 2017; Poor et al., 2012), and introduction to programming (CS1/CS2) (Jia
et al., 2021; Ross et al., 2017; Cohen et al., 2005). Such courses mainly
focus on teaching: (i) Accessibility awareness, (ii) Technical knowledge like
tools for accessibility testing, (iii) Empathy, and (iv) Potential endeavours
using various instructional methods such as in-class activities, projects,
lectures, assignments, videos, simulated disabilities, interaction with people
with disabilities, guest lectures, and research (Baker et al., 2020). Other
instructor resources include materials by the AccessComputing initiative (Ko
and Ladner, 2016), Accessibility guidelines like WCAG 2.0 (ben, 2008),
Accessibility Learning Labs (El-Glaly et al., 2020), the Mobile inclusive
learning kit (El-Glaly et al., 2018), and games for accessibility awareness
(Kletenik and Adler, 2022).

Our work differs from the existing literature in that, to our knowledge, this
is the first report on a mobile app development course with accessibility as
an underlying theme (Baker et al., 2020), with multiple assignments and
evaluative components assessing the accessibility knowledge of students
throughout the semester. Another contribution is the Inclusive Thinking
Questionnaire, which can be used in other contexts to assess whether the
respondents consider various inclusivity criteria when designing software.

##  3\. The Course

We report on the Fall 2021 offering of a junior/senior-level Mobile App
Development elective at a private university in India. This course focuses on
Android app development using Java. Most of the students were CS majors with
prior coursework in Object-oriented programming, UML, and software engineering
fundamentals. One of the stated learning objectives was “Understand the
importance of developing accessible software and demonstrate integrating
accessibility components in Android apps.” The course was conducted online due
to the COVID-19 pandemic via the Google Meet platform. The class was taught in
a “flipped” mode: pre-recorded video lectures were made available to the
students before the class, and the class meeting hours were used for several
in-class active-learning activities. It covered the basics of mobile app
development and various Android-specific topics such as activity lifecycle,
fragments, navigation components, services, background tasks, data
persistence, permissions, and sensors. It also introduced cross-platform
development using Flutter towards the end. The course had four programming
assignments worth 30% of the final grades and two exams worth 25% and 30%,
respectively. The remaining 15% were for in-class activities. One of the
authors of this work was the instructor, and another author was an
undergraduate teaching assistant of the course.

###  3.1. Interventions

While the primary focus of the course was on software engineering concepts and
Android features, we introduced the following interventions to incorporate
Accessibility Awareness, Accessibility Knowledge, and Empathy towards persons
with disabilities among the students.

####  3.1.1. Guest Lectures

To raise awareness about the existing laws about disabilities and expose
students to the challenges persons with disabilities may face in their day-to-
day lives, a guest lecture by a lawyer with expertise in the field was
organized. He talked about the Rights of Persons with Disabilities (RPD), 2016
act of the Indian Parliament (Ministry of Social Justice and Empowerment,
Government of India, 2016), recounted his work on the relevant cases, and
shared his thoughts on how computing graduates can make an impact in the field
of accessibility. He answered several student questions at the end.

####  3.1.2. Classroom Lectures

Accessibility was introduced early on in the course. In the third week of
classes, after having introduced the basics of Android app development and the
fundamentals of testing, the instructor talked about the statistics on
disabilities and the need for developing accessible software. Next, the
instructor presented the Android Accessibility Guidelines
111https://developer.android.com/guide/topics/ui/accessibility and
demonstrated Talk Back and Accessibility Scanner, two softwares from the
Android Accessibility Suite to evaluate the accessibility features of an app
under development. The former is a screen reader developers can use to check
how their app _feels_ to a visually impaired user, and the latter is a tool
that scans the UI of an app and produces reports on its compliance with
certain accessibility guidelines like the minimum size of interactive widgets.
Later, methods for running accessibility checks via automated UI testing using
the Espresso framework were introduced.

####  3.1.3. Programming Assignments

Four programming assignments spread across the semester assessed how well
students implemented various features of Android app development. In addition,
we added some accessibility-related tasks to assess students’ accessibility
knowledge (See Sec. 4.2).

###  3.2. Participants

The course instructor, who is also a co-author of this paper, explained the
purpose of the research to the students and shared the informed consent form
approved by the institute’s Human Ethical Committee (HEC) with them. 50 out of
the 72 enrolled students consented to participate in the study. Data from
these students were anonymized and handed over to the researchers over secure
cloud storage for analysis. All participants were junior or senior year
undergraduate students aged 18 to 22. Forty-seven of them were males, and
three were females.

##  4\. Methods and Findings

We used the following three instruments to measure the impact on Accessibility
Awareness, Technical Skills, and Empathy of the students:

A:

An Inclusive Thinking Questionnaire at the start and end of the course,

B:

Reflective questions on accessibility as part of the programming assignments,
and

C:

Questions on accessibility in both the exams.

We discuss each in detail below.

###  4.1. Inclusive Thinking Questionnaire (A)

This instrument, adapted from Ludi’s voting kiosk scenario (Ludi, 2007; Palan
et al., 2017), was used to understand the change in Accessibility Awareness of
the students due to exposure to the interventions in the course. The
questionnaire asked the participants to design a hypothetical “COVID-19
vaccination verification” and posed three open-ended questions about the
design and testing of the app prototype. The text of the questionnaire is as
follows:

> Let us consider a hypothetical scenario: After the successful COVID-19
> vaccination of most adults, the government has decided to relax all
> restrictions – no lockdowns anymore! But, for almost everything that
> requires interaction with someone outside your household, one may be asked
> to present proof of vaccination. You are hired to design a software solution
> that enables (a) producing the proof of vaccination when asked and (b)
> verifying a ‘proof’. Remember, anyone and everyone should be able to do both
> these things – a shopkeeper can ask a customer for proof and deny entry if
> it’s not verified, for example.
>
> Now, answer these three questions to the best of your abilities and in as
> much detail as possible.
>
>   1. (1)
>
> Discuss some key points of the design of this system (interfaces, input-
> output, etc.).
>
>   2. (2)
>
> What potential challenges do you see in the large-scale adoption of this
> solution?
>
>   3. (3)
>
> Who will be your potential users for testing your prototype to gain feedback
> on the design?
>
>

The first and the third question are the design and evaluation questions from
Ludi’s questionnaire. The second question was added to nudge the participants
to think about various inclusivity issues in the large-scale adaption of the
system. The questionnaire was first administered at the start of the course,
even before any accessibility topics were mentioned, and again in the week
before the final exams.

####  4.1.1. Data and Analysis

The data was collected via a google form at the start and the end of the
semester. After removing responses from participants who did not complete both
the pre- and post-course questionnaire, two coders analyzed data from 40
participants. We followed the methods of Saldaña (Saldaña, 2021, pp. 115–121)
to perform a Two-pass Mangnitude Coding on this data. Two researchers
independently identified codes from 10% of the sample and agreed on the
definitions of the codes before classifying the rest of the data using these
codes:

  * •

INFRA: considers the infrastructural limitations, for instance, the lack of
availability of high-speed internet in some areas.

  * •

TECH: considers the limitations due to lack of affordability or comfort using
technology.

  * •

LANG: considers the language barrier, particularly the lack of English
proficiency.

  * •

LITERACY: considers making the proposed solution usable by people with varying
degrees of basic literacy.

  * •

AGE: considers older people when designing or testing the solution.

  * •

IMPL-DIV: considers various diversities in society, even implicitly, for
instance, by stating that the testing should be done with various socio-
economic groups.

  * •

DIS: considers persons with disabilities when designing or testing the
solution.

The codes were then synthesized into these three categories:

  * •

Infrastructure Barriers: INFRA

  * •

Diversity: TECH, LANG, LITERACY, AGE, IMPL-DIV

  * •

Accessibility: DIS

####  4.1.2. Findings

Category | Pre | Post | a | b | c | d | $p$
---|---|---|---|---|---|---|---
Infrastructure Barriers | 10 | 17 | 4 | 13 | 6 | 17 | .168668
Diversity | 25 | 27 | 19 | 8 | 6 | 7 | .789268
Accessibility | 1 | 17 | 1 | 16 | 0 | 23 | .000177
Table 1. Categorywise responses to the Inclusive Thinking Questionnaire
($N=40$) with $p$-values using McNemar’s test. $a$ and $d$ are the concordant
cells and $b$ and $c$ are the discordant cells.

Table 1 shows the results for each category in the pre- and post-course
questionnaire ($N=40$). Columns $a$ and $d$ are concordant: $a$ is the number
of participants whose response shows the presence of the codes in a category
in both measurements, and $d$ is the number of participants whose response
shows the absence of the codes in both. $b$ and $c$ are discordant: the former
is the number of participants whose response showed the absence of that
category in the pre-test but presence in the post-test, while the latter is
the opposite. To illustrate, only one student considered disabilities in both
measurements, while 23 did not consider disabilities in either. Sixteen
students did not consider disabilities in the first measurement but did so in
the second, and there was no student who considered disabilities in the pre-
test but did not consider it in the post-test.

Since we have dichotomous dependent variables in each category —either the
participants ‘considered’ the category or they ‘did not consider’ it— and we
have taken repeated measurements, we use McNemar’s test (Pembury Smith and
Ruxton, 2020) to determine if there was a significant difference between the
two measurements in each category. The difference in the accessibility
category is statistically significant: $p=.000177$. However, no significant
difference is observed in the other two categories.

###  4.2. Accessibility Evaluation on Programming Assignments (B)

Four programming assignments assessed students on various features of Android
and software engineering concepts introduced throughout the semester. Students
were provided with a starter code for each assignment via GitHub Classroom.
The first three assignments had explicit requirements for accessibility, worth
5, 10, or 15 points out of 100, as shown below. The fourth assignment did not
have an explicit accessibility-related task as we wanted to check if students
implement accessibility even without a ‘grade incentive’. All four assessments
had open-ended questions on experiences of using the accessibility tools.

####  4.2.1. Assignment 1

Students implemented a “single-screen app” that asks the user to enter a date
and reports the day of the week (Monday, Tuesday, etc.) for that date. It
required some error checking for dates that do not exist (e.g., 31 April).
Accessibility tasks were worth 5 points. Reflective questions:

  * •

Run the app with your eyes closed, using Talk Back. Write a paragraph about
your experience doing so.

  * •

Run Accessibility Scanner on your app. List all the suggestions it identifies
to make your app more accessible (it should find at least one222The starter
code violated some accessibility requirements by design.). Modify your app so
that the next run of Accessibility Scanner cannot find any suggestions.
Briefly describe how you fixed the problems it first identified.

Learning objectives for the accessibility tasks (with the corresponding
Revised Bloom Taxonomy (Krathwohl, 2002) verb underlined):

  * •

LO1: Understand difficulties that a user with visual impairments might
encounter when using inaccessible apps.

  * •

LO2: Apply the assistive technology tools Talk Back and Accessibility Scanner.

  * •

LO3: Create a more accessible version of a given app.

####  4.2.2. Assignment 2

A dice-game that awarded the player points on guessing some properties of the
dice throws (e.g., the player gets 5 points if they correctly guess whether
the sum of the dice faces after the throw will be an even number).
Accessibility tasks were worth 15% points on this assignment. Questions:

  * •

Run the app with your eyes closed, using Talk Back. Write a paragraph about
your experience doing so.

  * •

This time, you will test your app’s accessibility by integrating it with
Espresso. Write at least four Espresso test cases that interact with different
UI elements.

Learning objectives for the accessibility tasks:

  * •

LO4: Understand difficulties that a user with visual impairments might
encounter when using inaccessible apps.

  * •

LO5: Apply the assistive technology tool Talk Back.

  * •

LO6: Create automated tests for an Android app in Java using Espresso.

  * •

LO7: Analyze an app using Espresso.

####  4.2.3. Assignment 3

A “Journal” for recording user’s daily activities that uses a local database.
Accessibility tasks were worth 10 points. Questions:

  * •

You will again test your app’s accessibility by integrating it with Espresso,
as you did in A2. You don’t have to write any new code for this, except for
the appropriate annotations.

Learning objectives for the accessibility tasks:

  * •

LO8: Create automated tests for an Android app in Java using Espresso.

  * •

LO9: Analyze an app using Espresso.

####  4.2.4. Assignment 4

The fourth assignment was a two-player Tic-Tac-Toe game implemented using
Google’s Firebase as the backend. There were no explicit tasks for
accessibility and no grade points. Questions:

  * •

Did you consider testing and accessibility? Please mention what you did, if
you did it. Please mention that you didn’t, even if you didn’t.

####  4.2.5. Data and Analysis

For each assignment, in response to the open-ended questions, students self-
reported their experience using one or more of the three tools for testing the
accessibility of the apps they developed. We performed Magnitude Coding on
these responses as described in the previous section with these codes:

  * •

TB: Accessibility testing was done using the Talk Back tool,

  * •

AS: Accessibility testing was done using the Accessibility Scanner tool,

  * •

ESP: Accessibility testing was done using Espresso instrumented tests, and

  * •

NONE: Accessibility testing was not done.

####  4.2.6. Findings

Code | A1 | A2 | A3 | A4
---|---|---|---|---
TB | 49 | 35 | 7 | 4
AS | 49 | 8 | 6 | 8
ESP | NA | 33 | 15 | 9
NONE | 1 | 6 | 35 | 41
Points for accessibility tasks | 5 | 15 | 10 | 0
Table 2. Accessibility testing in programming assignments ($N=50$). (NA: the
topic was not introduced yet)

Table 2 shows the number of student responses per code per assignment
($N=50$). Note, Espresso was not introduced to the students at the time of A1.

49 and 44 students out of 50 have used the required accessibility testing
tools in the first two assignments, respectively. These assignments had
explicit accessibility-related tasks: using Talk Back and Accessibility
Scanner in the first assignment and using Talk Back and Espresso annotated
tests in the second. Eight students voluntarily used Accessibility Scanner in
A2 even when it was not a stated requirement. Similarly, in A3, seven students
used Talk Back and six Accessibility Scanner even though that was not a stated
requirement. However, the number of students who used Espresso is only 15 out
of 50. We surmise this is because the third assignment had a lot of
“technical” requirements like designing and implementing a database and using
navigation components and menu bar actions in the app. And, with only 10 out
of 100 points for accessibility testing, some students might have focused on
the other requirements of the app.

In A4, although there was no stated accessibility requirement and hence no
points for using any of these tools, nine students reported that they had
tested their apps for accessibility, and eight others stated that they had
planned to but could not do so due to lack of time.

###  4.3. Exam questions (C)

The midterm and final exams had questions to assess the students’
Accessibility Knowledge.

####  4.3.1. Midterm question

The midterm exam presented the students with a screenshot of a banking app
(Fig. 1) and asked them to “identify at least three UI elements that are
likely to have accessibility issues and explain how you will fix those
issues”.

Learning objectives:

  * •

LO1: Remember the accessibility guidelines for mobile apps.

  * •

LO2: Analyze the given real-life example app for potential accessibility
issues.

  * •

LO3: Create a more accessible version of a given software.

A banking app interface with potential accessibility issues. Certain details
blocked for privacy.

Figure 1. A banking app interface with potential accessibility issues. Certain
details blocked for privacy.

The students were expected to identify these issues:

  * •

Color contrast in the search bar seems very low (can be checked with
Accessibility Scanner and fixed by setting it to the recommended $4.5:1$),

  * •

Size of interactive widgets like the ‘cheque’ or ‘email’ button is possibly
smaller than the required $48\times 48$ dp (can be tested using Accessibility
Scanner and fixed by increasing the widget size in the XML specification of
the UI), and

  * •

The interactive widgets, such as the ‘search button’ may be missing
appropriate labels (can be tested using Talk Back and fixed by adding the XML
attribute in the UI).

####  4.3.2. Final exam question

The final exam question presented an XML code representing the UI with two
input text boxes for the title and author of a book and a clickable button to
add this information to the book database and posed these two subquestions:

  1. (1)

Suppose you run this app through Talk Back. Name _two_ possible accessibility
issues it _will_ highlight.

  2. (2)

Name _one_ accessibility issue Talk Back _will not_ highlight.

Learning objectives:

  * •

LO4: Remember the accessibility guidelines for mobile apps.

  * •

LO5: Evaluate (critique) an assistive technology tool (Talk Back).

The expected answer to the first subquestion, i.e., the two problems Talk Back
will help catch are: (a) Since the XML code for the input boxes do not have a
hint-text or content-description, Talk Back cannot give a meaningful
information about these to the user, and (b) Content-description of the ‘Add
Book’ button says “Click to add book”. Talk Back already adds “Click” when
announcing interactive buttons. So it will say “Click Click to add book” which
is confusing for a visually impaired user.

The XML code did not specify dimensions for the clickable widget and students
had experienced in class that the default size is smaller than the recommended
$48\times 48$ dp. Similarly, the default color contrast for the button labels
is less than the recommended $4.5:1$. However, Talk Back is not able to catch
these problems. For the second subquestion, students were expected to identify
either of these two issues.

Both exams were open-book, open-internet and conducted online via GitHub
Classroom.

####  4.3.3. Findings

26 students identified all three accessibility issues in the midterm exam,
while the remaining 24 identified one or two of the issues ($N=50$). Forty
students proposed a valid solution to the issue(s) they identified.

For the first subquestion on the final exam, 49 participants correctly
identified that Talk Back can highlight the missing hint text or content
descriptions on the input boxes. But only one student was able to identify the
issue with inappropriate content description. 18 students have misidentified
that Talk Back will highlight low color contrast and small widget sizes.

For the second subquestion, 32 students correctly answered that Talk Back
cannot identify the issue with small touch targets and 23 answered that it
cannot identify the issue with low color contrast (a total of 42 unique
students answered this correctly). Nine of them mentioned Accessibility
Scanner can catch these problems. However, 11 students misidentified that Talk
Back _cannot_ identify the improper content description.

##  5\. Discussion

###  5.1. Accessibility Awareness

We used the pre-post questionnaire to assess accessibility awareness in the
participants. As expected, many participants had taken into account
infrastructure barriers and diversity due to age, literacy, etc., when
designing the hypothetical COVID-19 vaccine verification app at the start of
the course. This is due to the fact that students are exposed to such
diversity in their daily lives. Only one student had considered users with
disabilities while designing or testing the solution at the start of the
course. Sixteen other students mentioned this after completing the course,
confirming that a significant change in awareness about accessibility
considerations in software development has been achieved.

A rise in motivation to consider accessibility is also visible in Assignment
4. Over a third of the participants ($9+8=17$ out of 50) demonstrated
intrinsic goal orientation by either performing accessibility tests or
expressing their plans to do so on the last assignment even when it was not a
stated requirement. Intrinsic or mastery goal orientation is “the degree to
which a student values learning for the sake of personal growth” (as against
for the sake of other factors such as grades) and is generally associated with
“greater success in academic situations” (Lishinski and Yadav, 2019).

###  5.2. Technical Knowledge

Instruments $B$ and $C$, the programming assignments and exam questions,
evaluate the technical knowledge of students about accessibility
implementation and testing. These instruments have accessibility related
learning objectives that cover all six levels of the revised Bloom’s Taxonomy
(Sec. 4.2 and 4.3). Our findings demonstrate that the interventions helped
students develop their technical knowledge related to implementing and testing
accessibility in mobile app development.

On the midterm question, over half of the students identified all three
accessibility issues by looking at the UI of a popular banking app, and the
remaining half identified at least one issue. 90% of the students were able to
suggest a valid fix to the accessibility issues they found.

On the final exam question, although nearly everyone correctly pointed out
that Talk Back can be used to catch the problem with missing hint-text or
content description, only one student pointed out its use to catch the
inappropriate label where verbs like ‘click’ will be repeated. This is most
likely because although this use of Talk Back was discussed in class, the
examples in class exposed them only to missing labels and not to such
‘inappropriate’ labels. Final exam answers also revealed that about two-fifths
of the students have misconceptions about the abilities and limitations of the
assistive technology tool Talk Back.

###  5.3. Empathy

Although we do not have an instrument to measure empathy, responses to
reflective questions on assignments 1 and 2 reveal that after using Talk Back
blindfolded, many students empathized with the difficulties faced by persons
with disabilities (PWDs) in using software that is not accessible. For
instance, a participant stated that s/he “…realized why [this exercise] is
important as using Talk Back people with disabilities can also use the
applications.” Since doing this exercise in A1, some students started using
appropriate accessibility best practices proactively and reported the ease
with which they could now use Talk Back: “Using Talk Back was a fun experience
this time as I had added contentDescription for the various views before doing
this test.” Similarly, another student stated she started adding appropriate
contentDescriptions wherever required to ensure that “my app will be
accessible for visually impaired or people with weaker eyesight as well.” This
is consistent with existing literature that suggests such empathy helps
students understand the importance of developing accessible software (El-Glaly
et al., 2020).

##  6\. Limitations and Future Work

The accessibility topics in this offering of the course covered visual
impairments. In future iterations of the course, other disabilities like
hearing, motor, and cognitive impairments should also be considered.

This work needs to be replicated in varied contexts: ours was a class of
junior/senior undergraduate students in an engineering institute, but mobile
app development is taught in a variety of computing education programs at
undergrad and graduate levels (e.g., a Bachelor of Computer Science or Master
of Computer Applications program in India). It will be interesting to see if
our results remain consistent across such variations.

Since most of our students learn Java in their sophomore year, the course is
designed to use Java for Android programming. However, there is a growing
demand for moving to Kotlin and covering cross-platform development using
React Native and Flutter. New course material should be developed to cover
accessibility topics using these platforms.

Interacting with PWDs can substantially impact student empathy and motivation
to build accessible software (Zhao et al., 2020). Since this course iteration
was online due to the pandemic, it was impossible to include PWDs in the
design or testing of the assignments. In a future offering, we will like to
arrange for such interactions between students and PWDs and study their
effects on student learning.

It should be noted that while the exam data are actual student answers, the
assignment data are self-reported responses to reflective questions. Analyzing
actual student code to see how they have implemented and tested accessibility
features can reveal some interesting findings.

We also plan to interview students who considered accessibility in the last
assignment even though it was not a stated requirement and those who did not
consider accessibility in other assignments to understand the challenges they
possibly faced.

##  7\. Conclusion

This work reports on our experience integrating accessibility in a regular
mobile app development course that uses Java-based Android programming. Our
findings demonstrate that: (a) students’ awareness about considering
accessibility when designing, developing, and testing software has increased
after completing the course, (b) students acquired technical knowledge about
accessibility guidelines, tools to test for accessibility features, and best
practices for implementing accessibility in Android apps, and (c) empathy-
creating exercises like interacting with the mobile device blindfolded using a
screen reader resulted in increased empathy for challenges faced by persons
with disabilities when using inaccessible software. Other educators can teach
accessibility topics in similar courses without diluting their core learning
objectives and without much prior knowledge about accessibility. All course
material and resources are publicly available at
https://swaroopjoshi.in/project/sugamyata/.

###### Acknowledgements.

This work is supported by Birla Institute of Technology and Science, Pilani
under grants BPGC/RIG/2020-21/04-2021/02 and GOA/ACG/2021-2022/Nov/05.

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11institutetext: Department of Information Security and Communication
Technology, Norwegian University of Science and Technology, Norway
11email: {mohamed.abomhara, sule.yildirim, anne.nymoen,
<EMAIL_ADDRESS>22institutetext: National University
of Public Service, Faculty of Law Enforcement, Hungary
22email<EMAIL_ADDRESS>
# How to do it right: A framework for biometrics supported border control

Mohamed Abomhara 11 Sule Yildirim Yayilgan 11 Anne Hilde Nymoen 11 Marina
Shalaginova 11 Zoltán Székely 22 Ogerta Elezaj 11

###### Abstract

Complying with the European Union (EU) perspective on human rights goes or
should go together with handling ethical, social and legal challenges arising
due to the use of biometrics technology as border control technology. While
there is no doubt that the biometrics technology at European borders is a
valuable element of border control systems, these technologies lead to issues
of fundamental rights and personal privacy, among others. This paper discusses
various ethical, social and legal challenges arising due to the use of
biometrics technology in border control. First, a set of specific challenges
and values affected were identified and then, generic considerations related
to mitigation of these issues within a framework is provided. The framework is
expected to meet the emergent need for supplying interoperability among
multiple information systems used for border control.

###### Keywords:

Biometrics Border Control Ethical challenges Legal challenges Social
challenges.

##  1 Introduction

Biometrics technology [18, 20] refer to automated methods of identification
and verification of the identity of individuals based on their physiological
or behavioral attributes. Examples of biometrics include fingerprints, facial
features, iris scans, etc. They are used to support the border police on
making decisions by providing automated identification, verification and
cross-checking of individuals based on their biological and behavioral traits
[5]. Identification is a process to associate a person with an identity (who
are you?). Verification is a process to determine whether someone is who
he/she claims to be (are you who you claim to be?). Cross-checking is a
process of verifying information by using alternative European Union (EU)
information systems. Biometrics technology is increasingly being used by
countries worldwide and is a highly adopted technology at the EU borders [12,
32]. It aim is to help achieving an automated, rapid and highly secure border
clearance process, such that an increasing passenger throughput does not
compromise border control reliability.

On the one hand, biometrics technology has been proven to be cost-effective to
enhance border security, detect fraud and help to improve border crossing
efficiency as well as facilitate an effective migration control and
enforcement. On the other hand, biometrics technology can lead to some
challenges and conflicts with fundamental human rights and can be a cause of
ethical, social and legal challenges [11, 32]. The key challenge is related to
individual rights, such as respect for personal privacy [38, 37], human
dignity [16], bodily integrity [26], equity and personal liberty [31, 36].
Personal data protection is also an issue, especially when biometrics
information is stored in centralized databases [29, 8].

Another major concern with biometrics technology is the seemingly immutable
link between biometric traits and persistent personal information storage
about individuals [9]. The tight link between personal records and biometrics
can have both positive and negative consequences for individuals and the
society overall. Recent research [10] on biometrics data shows that it can
reveal personal information, such as gender, age, ethnicity and even critical
health problems like diabetes, vision problems, Alzheimer’s disease, etc. Such
confidential information might be used for example to discriminate among
individuals when it comes to border crossing enforcement.

People have the right to choose to what extent and how to engage with the
systems and devices (e.g., biometric sensors). For example, some people may
refuse to have their photographs taken by a face recognition system due to the
concerns about the purpose of the use of the images [9]. Moreover, others may
refuse to or feel uncomfortable to undergo iris scans or provide fingerprints
due to permanent or temporary disability. A study of biometric enrollment and
verification in the United Kingdom showed that 0.62% of the sample group of
people with disabilities were unable to enroll any of the three biometrics
tested: fingerprints, facial scans, and iris scans [25]. Moreover, according
to the European health and social integration survey (EHSIS), in 2012 there
were 70 million people with disabilities in EU [15]. If 0.62% of all disabled
in EU were unable to provide this data, approximately 434000 Europeans would
be unable to provide any of the three most common types of biometric data.
Such concerns may impact these people and also people belonging to different
groups with varying cultural beliefs, values and specific behaviors on how
they interpret the requirements of being exposed to biometrics technologies.
In general, a range of complex and interconnected issues must be addressed
while deciding on the use of biometrics as a technology for border control
[30]. Also, ethics guidelines and a regulatory framework for the use of
biometrics technology in border control must be formulated in order to avoid
any harmful impact on the society while allowing for the continuous
development of this technology to benefit the society [11].

In this paper, section 2 discusses the potential benefits of using biometrics
in EU borders and the ethical theories around it. Section 3 investigates the
key ethical, social and legal challenges of using biometrics technology and
demonstrates vulnerabilities and risks related to these challenge categories,
followed by a discussion of moral considerations with regards to human rights,
right to privacy, right to data protection etc. Section 4 presents a
discussion on ethical reasoning and decision making. Section 5 concludes the
study.

##  2 Background

This section provides a background of benefits of biometrics in EU borders and
a discussion on moral, ethics and ethical theories.

###  2.1 Potential benefits of using biometrics in EU borders

Freedom of movement is restricted by closed or controlled borders in order to
protect other fundamental rights such as security or health, national or
regional political, societal, cultural or economic interests of the political
entities within that bordered area. The Schengen Border Code (SBC) (Regulation
(EU) 2016/399) and its amendment (Regulation (EU) 2017/458) set out the rules
governing the movement of people across EU’s internal and external borders.
The main aim of border checks is to ensure that the persons and goods crossing
the border are entering or leaving the area with the permission
(authorization) of the political entity of SBC. This permission for travel is
currently manifested in a travel document having a physical form as well as a
record on the authorization in the national travel document database.

Identification and verification procedures at the border are to ensure that
entry-to or exit-from a country will be granted to the right persons. In
recent years, Member States have seen an increased use of biometric
identification and authentication systems at EU’s borders including airports
and land borders [24, 2]. More significantly, the large-scale EU information
systems such as Visa Information System (VIS), Second-generation Schengen
Information System (SIS II), European Asylum Dactyloscopy Database (EURODAC)
and Entry Exit System (EES) etc. [22] employ biometrics for migration and
border control and management. Such systems involve several highly complex
processes, leading to a number of ethics and privacy challenges [31, 11]. The
integration of biometric at border control provides benefits for travelers,
political entities (states), authorities responsible for border control as
well as individual border guards. Such benefits include accuracy, integrity,
robustness and efficiency.

  * •

Accuracy: Accuracy of travelers’ identification and verification means the
ability to recognize genies person and reject imposters person correctly [17].
During manual border checks, border guards seek to gain knowledge about the
subject (traveler) and associate it with his/her identity. For example, the
border guard looks at the traveler and verifies with the picture on the travel
document (on bio-data page) to determine if the person standing in front of
him/her is the same that is pictured in the travel document. However, the
accuracy of identification and verification depends on lighting, age of the
picture, perception capabilities, tiredness, make-up etc. In addition,
spreading culture of having aesthetic surgery poses a further challenge to
manual identification. Moreover, a human border guard is usually very
efficient during the start of the shift, then diminishing attention appears as
the officer gets tired. In this case, biometrics can enhance and support these
practices. A selective and differentiated application of multimodal biometrics
identification results in a higher average accuracy during the whole shift as
well as facilitates cross-checking of personal data with greater accuracy
[17].

  * •

Integrity: Integrity of the identification is the ability to confirm that the
collected data and its components (e.g., passport picture and passport
information) have not been altered from that created by the issuing State or
organization [17]. Use of biometrics enhances the reduction of identity fraud
impersonation ( e.g., fake IDs and passports) as the identification and
verification processes do not rely on the human agent. To the best of our
knowledge, a reduction in fraud means an increase in accuracy. Therefore,
using biometrics eliminates a quite considerable integrity threat that the
border guards face and benefits the authority responsible for border control.

  * •

Robustness: Biometrics systems are easy to operate, maintain, update, replace,
redeploy or decommission compared to border control units/booths consisting of
human agents only. Long years to achieve full competence and repetitive
training is not required and experience is not lost with a single unit. From
the traveler’s view, utilizing multimodal biometrics allows the traveler to
(theoretically) decide which biometric modality (e.g., fingerprints, face,
iris) will be used for identification based on his/her preferences.

  * •

Efficiency: The processing capacity of Automated Border Control (ABC) gates is
sustained over time as ABCs don’t get tired. Additionally, ABCs conduct an
objective repeatable set of checks to complete identity and document
verification can be more accurate and quicker to complete than similar checks
conducted by humans [17]. This results in a higher number of low-risk
travelers’ throughput without losing accuracy or integrity and allows human
resources to be focused on potentially higher-risk travelers.

As these benefits are all potential, the actual benefits highly depend on how
biometric systems are integrated into the border management and how control
systems help facilitate the correct identification and verification of persons
and contribute to fighting identity fraud.

###  2.2 Moral, ethics and code of ethics

Morals are the general views, thoughts and convictions of people in making
judgments about what is right or wrong. According to Kizza [23], morality is
defined as “a set of rules (code) of conduct that governs human behavior in
matters of right and wrong, good and bad.” Ethics, on the other hand, concerns
the way we can come to moral judgments of what is right and wrong for
individuals and society. The ethical judgment of what is good or bad and right
or wrong is often based on a set of shared rules, principles, and duties
applicable to all in a group or society and this is called code of ethics. A
code of ethics is a written set of ethical principles and guidelines that
govern decisions and behaviors in an organization (e.g., border management
authorities) according to its primary values and ethical standards and
theories [6, 3].

There are many ethical theories, each of which emphasizes different points,
such as predicting an outcome and carrying out one’s duties to others to reach
an ethically correct decision. Consequentialism theory (result-based ethics)
emphasizes the consequences of human actions, whether good or bad, right or
wrong. Deontological ethics does not concern the consequences of an action but
rather it considers the will and the motivation for undertaking an action [21,
28, 23]. It is sometimes described as duty-based or rule-based ethics. Even
though the distinction between deontological and consequentialism is often
clear, the two theories are fundamentally different. They are both normative,
and as a result, code of ethics are formulated as guidelines rather than
prescriptions and prohibitions. The aim of the code of ethics is to provide a
moral basis for emerging professional choices and provide adequate protection
for all those who act in a statutory manner, and to recognize the unworthy
practices associated with the police profession. The following are examples of
the ethical principles for border guards which provide moral guidance during
service shifts and out of service shifts.

  1. 1.

Respect of dignity and rights: Respecting the rights of every person and avoid
the use of torture, inhuman or degrading treatment.

  2. 2.

Fairness: Treating of persons must be equal and having no preference, bias or
prejudices based on race, background, ethnicity, gender, religion, personal
and social status or property status etc.

  3. 3.

Duty of confidentiality: Respecting for privacy and guaranteeing the security
of the data and the information obtained.

  4. 4.

Responsibility: Taking responsibility for actions and decisions in legal and
moral terms. If misconduct takes place, take steps to ensure it is not
repeated.

##  3 The “how to do it right” framework

This section presents a framework (Figure 1) which helps to point out the
types of challenges, the specific vulnerabilities and risks which the stated
concerns/challenges lead to and the generic considerations for handling these
challenges raising due to the use of biometric technologies. The focus on
ethical, social and legal challenges constitute the topmost layer of the
framework. The next layer of the framework is the values affected due to the
presence or uprising of the challenges. The third layer from the top is the
impact assessment layer. That is, what are the consequences of a value being
affected? What vulnerabilities and risks arise correspondingly and what are
the mitigation plans? Then, the bottom most layer lists the corresponding
considerations that the border control police are expected to comply with. The
framework provides a what to do and how to do it right guideline for border
control police when various challenges are met by providing a link from the
challenge, to the value(s) affected and an impact assessment on the values
affected as well as pointing out the considerations that must be in place.
Below, we provide examples of which values maybe affected under varying
challenges and how.

Figure 1: The proposed framework for specifying biometric technologies related
challenges and the considerations

###  3.1 Challenges level

Biometrics technology is acknowledged to potentially raise critical ethical,
social and legal challenges. Ethical challenges generate situations that
requires a person or organization to choose between alternatives that must be
evaluated as right (ethical) or wrong (unethical). Social challenges create
problems that engaging in normal social behaviors and may influence a large
number of individuals within a society. Legal challenges refer to formal
questioning of the legality of an act and whether or not the act is being
taken in accordance with the law.

Challenges layer provides information to help border officer or border
authorities think through basic ethical, social and legal concepts and
considerations. It will not provide specific answers for the specific
challenges but will help bring to conscious awareness some understandings that
help in thinking through these issues.

###  3.2 Values level and examples of how values are affected by ethics,
social and legal challenges

Below, we give examples of how several values may be affected due to the
arisen of such challenges.

  1. (I)

Human dignity: The capability to verify travelers’ identities is extremely
important and regards human dignity [31, 16, 23]. People may feel
uncomfortable (or humiliated to some extent) when authorities like the border
police are recording body features algorithmically. Many factors, for example
physical work or physical incapacity (e.g., physical disabilities, sight
impairment and mental health problems), can make it hard for some people to
provide biometrics or they may simply be unwilling to do so. For instance,
damaged fingers due to manual work can impact the way people are treated when
providing fingerprint data [13]. In these cases, challenges with collecting
biometrics data and remaining respectful of human dignity may emerge. People
who cannot provide fingerprints or other biometrics data sometimes face a
greater risk of negative consequences than people who can [25].

Biometrics data collection from vulnerable persons including those with
disabilities requires particular attention. Human dignity is evidently a
complex notion of the individual and biometrics data is strictly linked to the
human body, whose integrity (physical and psychological) constitutes a key
element of human dignity.

  2. (II)

Social inclusion/exclusion and risk of discrimination: The introduction of
biometrics to improve identity verification at land borders raises serious
objections to the potential to facilitate discriminatory social profiling
[36]. For example, the biometrics enrollment of injured and disabled travelers
could lead to higher false rejection rates than average. Moreover, senior
citizens and children who have particular problems with using biometrics
enrollment devices (e.g., fingerprint scanner, iris recognition reader) may
face enrollment difficulties. Although discrimination of vulnerable
individuals might be involuntary and unintentional, it may deeply affect them
and impact the principle of equity. Furthermore, religious aspects (e.g.,
beard, headscarf) or interpersonal contact (e.g., photographs, touching,
exposing parts of the body) may render a biometrics system an unacceptable
intrusion. For example, those of faith who wear head or face coverings have
difficulties with enrolling facial biometrics. Verification of such biometrics
in public (e.g., at the border crossing points) may lead to embarrassment or
offense, causing avoidance of situations where this is necessary. Therefore,
mandatory encouraged use of such system may undermine religious authority and
create de facto discrimination against certain groups whose members are not
allowed to travel freely or obtain certain services without violating their
religious beliefs and privacy. In positive terms, respecting a person’s
intrinsic worth requires recognizing that the person is always entitled to
participate in social and community life regardless of age, beliefs,
disability, health, etc.

  3. (III)

Children rights: Biometric technology also present several ethical questions
regarding children’s rights. These include the right to information, the right
to privacy, security and the right to no discrimination, etc. With respect to
children and biometric technology, the main concern is that children will not
fully know or understand the implications of the accessibility to, and
subsequent use of the data collected. While children (and indeed their
parents) may be aware of basic privacy settings and risks, even sophisticated
users face great difficulties. Moreover, child identification introduces the
requirement for greater levels of care. The problem is that there are several
reasons why not all biometrics can be used for child identification and
biometric recognition of toddlers. For example, a study by Basak et al. [4]
found that “capturing fingerprints for children less than three years is hard
due to very small fingerprint area, smooth skin, and thin fingers.” Therefore,
very young kids with small fingerprints might not be identified efficiently.

Furthermore, children are particularly entitled to effective privacy
protection. This is because children cannot develop privacy expectations for
reasonable legal protection. Moreover, biometric match accuracy diminishes as
children grow. Fingerprinting young children affects the quality and
reliability of future matches to the initial fingerprints [19]. The risk of a
wrong match increases when the fingerprints or facial images are compared more
than five years after the initial collection.

  4. (IV)

Purpose misuse: Function or purpose creep occurs when the biometrics data is
collected for one specific purpose and subsequently used for another
unintended or unauthorized purpose without the user’s consent. A famous
example of a large-scale biometric function creep is the European Dactyloscopy
(EURODAC) fingerprint database. The original purpose of this EURODAC was to
compare fingerprints for the effective application of the Dublin convention.
It enables EU countries to identify asylum applicants as well as illegal
immigrants within the EU. However, soon after the database was established,
other police and law enforcement agencies were also granted access. Similar
concerns may also arise in the case of other large-scale, centralized EU
national and international databases, such as SIS II, VIS and EES. Biometrics
are likely to strengthen the potential for function creep due to the very
sensitive nature of the data collected and the possibility to use centrally
stored biometric data for purposes other than the original purpose.

  5. (V)

Right to privacy and data protection: Every individual has the right to
privacy protection and personal data protection when his/her data is collected
and shared. The use of biometrics technology as a border control tools
introduces problems with maintaining individuals’ privacy and protection of
their personal data. Such a technology will probably increase the risk of
available information misuse as a result of unethical and/or illegal practices
if personal data are not protected adequately.

The main concerns include unnecessary and unauthorized collection of
biometrics data for traveler identification and verification [8, 38]. GDPR
[35], among other legislation, state that to best preserve an individual’s
privacy and right for data protection, the amount of personal data collected
should always be kept to a minimum. Moreover, personal data like biometrics
data should only be used when individuals or authorities will benefit from the
collection. Cameras, for instance, are now widely used to monitor our everyday
life. People often benefit from such monitoring, especially at borders to
control people flows and detect suspicious activities (e.g., illegal border
crossing). However, extensive data collection and analysis can also lead to
privacy violations.

Information linkage and compromise of anonymity is another concern [38].
Various kinds of information about individuals stored in a range of databases
(e.g., SIS II and VIS) have the potential to become yet another means through
which information can be linked to purposes ranging from commercial marketing
to law enforcement. Recent research [10] explores the possibility of
extracting supplementary information from primary biometric traits, face,
fingerprints, hand geometry and the iris. Such information includes personal
attributes like gender, age, ethnicity, hair color, height, weight and so on.

Despite all the benefits of using biometrics technology in border control,
privacy concerns have become widespread because each time a person’s biometric
data is checked, a trace is left that could reveal personal and confidential
information. Biometric data should essentially be well-protected against
unnecessary and unauthorized collection, access and disclosure etc..

###  3.3 Impact assessment level

Table LABEL:impactTable summarizes values that may be affected and maps them
to vulnerabilities, risks and possible mitigation measures in comparison to
the current systems authorized in EU border control and other solutions
already on the market.

Table 1: Values and the corresponding vulnerabilities, risks and mitigation measures. Values |  Vulnerability |  Risk |  Potential mitigation measure
---|---|---|---
Respect to human dignity |  Current systems do not afford individual a choice of what biometrics data they prefer to enroll or use. |  Violation of right to human dignity, cultural or religious customs etc. |  Border control biometrics must provide information about what and why biometrics used as well as allow choice policies and procedures, unless choice is inapplicable.
Right to the person integrity |  Current systems do not adapt or lack informed consent policies. |  Violation of the right to integrity. |  Border control biometrics must ensures a collection of free and informed consent form individuals according to rules laid down by regulations such as GDPR.
Right to person liberty |  Current systems may lack of policy, procedures and ethical guidelines for data collection and processing or may allow unauthorized processing of individuals data; e.g., use of force to collect biometrics data. |  Violation of the right to liberty of an individuals. |  Border control biometrics must apply policy to restrict the procedures of data collection and processing, balancing between lawful interest and personal liberty.
Right of protection for children |  Current systems does not address/deal with children vulnerability and special needs |  Violation of the children rights which may lead to high levels of discrimination due to children lack of knowledge about the systems. |  Border control biometrics must envisages adoption of devices and procedures to ensure children’ needs. Also, the biometric data of children should be treated with enormous care and the procedures need to comply with data protection legislation such as GDPR [35]. Parents must always be notified when their children’s biometric data is to be collected or used, and written consent must be obtained in advance.
Right to no discrimination |  Current systems may be discriminated based on sex, race, ethnic or social origin, genetic features, religion or belief, political opinion, disability, age or sexual orientation etc. |  Discrimination, social inclusion/exclusion and social sorting of individuals. |  Border control biometrics must ensure nondiscrimination policy that comply with human rights legislation.
Respect for private and family life |  Current systems do not adapt an adequate family related consent and procedures. |  Violation of right to respect for private and family life. |  Border control biometrics must adopt appropriate measures for family consent and procedures.
Right to no information tracking |  Current systems lack of notices and information about tracking of individuals. |  Violation of personal right and legitimate purpose requirements leading to surveillance of individuals and/or other members of the family. |  If within the purpose and the law, surveillance should be authorized and consistent with EU and national laws.
Right to personal data protection |  Current systems may allow personal data to fall into the wrong hands or/and shared across organizations. |  Violation of right to security principles such as confidentiality, integrity, and availability. |  Border control biometrics must ensure Security by Design to guarantee the ongoing confidentiality, integrity, availability and resilience of processing systems and services.
Right to privacy and confidentiality |  Current systems may breach confidentiality, allowing unauthorized disclosure of personal information. |  Violation of personal privacy. |  Border control biometrics must ensures implementation of privacy-enhancing technologies to protect data in accordance with the law.

###  3.4 Considerations Level

This section presnets ethical, social and legal considerations.

  1. 1.

Ethical considerations for human rights: According to Article 7, Regulation
(EU) 2016/399 (amended in Regulation (EU) 2017/458), competent authorities
should ensure that the human dignity and integrity of persons whose data are
requested are respected and should not discriminate against persons on grounds
of sex,religion, disability, age etc. Thus, biometric platform at border
should be designed to support human right-compliant systems, related to
technological, ethical and sociological aspects. For biometric technologies to
be successful with its use and actual implementation, they should not only
consider the security and privacy of personal data, but it also need to
guarantee that the users can interact with the systems and make the user
experience acceptable. To do so, system designers and policy makers must
consider all challenges, vulnerabilities and risks (Table LABEL:impactTable)
related to the system design. Moreover, border control biometrics platforms
must pay particular attention to minors, whether traveling accompanied or
unaccompanied and must respect the specific needs of children and their
interests must be protected in ways supplementary to the general treatment of
adult subjects.

  2. 2.

Considerations for travelers with physical or mental impairment: As mentioned
above, EU Regulation (EU) 2016/399 specifies equal rights for border crossing.
Therefore, border control biometrics platforms should consider travelers with
special needs/categories including individuals who physically or mentally
impaired etc. An extra attention should be given to, among many others:

    1. (a)

People with temporary injuries who might have difficulties to provide
biometric sample due to temporary wound (e.g., injured face and/or broken
arm/fingers) [25]. In this case, Border control biometrics platforms should
not discriminate against such people and shall use biometric devices (e.g.,
fingerprints scanner) which perform acquisition in a greater number of
situations.

    2. (b)

People with total permanent disability whom have difficulties to freely move
their limbs due to sensory damage and/or muscle damage. For example, in case
of fingerprints verification, travelers with a hand disability may lack the
ability to place the required finger and keep it steady for a sufficient time
on the fingerprints scanner. Moreover, in case of face recognition/iris
scanning, people with neck disabilities may have difficulties in correctly
placing their face near the iris scanning device/face recognition camera.
Thus, border control biometrics devices should be able to work in off-axis
acquisitions and be adjustable to support such people with biometrics
recognition and make it more comfort.

    3. (c)

People with technological illiteracy, for example, elderly people and children
who lack knowledge of using technology/tools (e.g., automated border control
gates) would have a difficulty to use and interact with devices. In this case,
border control biometrics devices should design an interface that taking into
consideration elder’s and kids’ needs.

  3. 3.

Considerations for privacy and data protection: As mentioned earlier,
biometric data can be used to recognize individuals automatically with greater
accuracy. On the other hand, a misuse of such biometric data can have
dangerous consequences which pose several security and privacy challenges such
data destruction and/or unauthorized disclosure of, or access to personal
data, to name a few. Thus, border control biometrics platforms should be
designed to support privacy-compliant biometric systems. Perceived risks are
related to how people view the biometric technology, whether they trust it,
and whether they like to use it. With respect to this, EU regulation (e.g.,
GDPR [35]) prohibit the use of special categories personal data such as
biometric data without the user’s awareness and permission. Also, prohibit the
use of the biometric data different from the purpose of the system (purpose
misuse issue discussed in section 3.2). For example, biometric data stored in
e-passports can only be used for issuing electronic documents and verification
of document holder (Regulation (EC) 444/2009).

Border control biometrics platforms should consider several privacy aspects
for protecting the privacy of personal data. These aspects include:

    1. (a)

The purpose of biometric data: The legitimate purpose of biometric data
collection and processing used only for verifying the identity of the
individual during the border crossing procedure. Article. 13 (1) of the GDPR
stipulates that “information to be provided to data subject where personal
data are collected from the data subject.” This information shall include,
purpose of the system, the enrolment and verification processes, and the
methods used for data protection, among other.

    2. (b)

People control of their personal data: According to Article. 32 (2) of the
GDPR [35], the data subject has the right to ask for removal or erasure of
biometric data in electronic documents. Also, the data subject should have the
possibility to decide when he/she no longer be authenticated and verified
using the biometrics system and choice to proceed with manual checks (when
applicable).

    3. (c)

Data protection measures: Article. 32 (2) of the GDPR stipulates that “the
controller and processor must implement appropriate technical and
organizational measures to protect personal data against destruction, loss,
alteration, unauthorized disclosure of, or access to personal data
transmitted, stored or otherwise processed and against all other unlawful
forms of processing.” Therefore, border control biometrics system shall deploy
a privacy enhancing technologies and secure access control techniques to avoid
any misuse of personal data.

    4. (d)

Reuse of data for law-enforcement purposes: According to Regulation (EU)
2016/399 and its amendment Regulation (EU) 2017/458, citizens should be
checked in criminal databases such as SIS II and SLTD on a systematic and non-
systematic basis. As the majority of these travelers are presumably innocent
individuals. Therefore, saving and cross checking their data on a systematic
basis with law-enforcement databases would be disproportionate. Any reuse of
personal data done for the purpose of law enforcement should be done in
accordance with Directive (EU) 2016/680 [1], which aims to ensure more
consistent and higher level of protection of the personal data of natural
persons in the areas of criminal matters and public security.

##  4 Discussion on ethical reasoning and decision making

In view of the ethical theories (discussed in section 2.2) and the open
dilemma of what is right and what is wrong, it is clear that the situation is
similar, particularly surrounding the use of biometric technology. On the one
hand, one group of people (travelers, border officers etc.) may see biometrics
technology used in border control as a liberator, believing in the power of
technology to bring convenience (e.g., avoid queues) and efficiency (e.g., cut
costs) and increase mobility (e.g., convenient border-crossing for citizens).
This group may also welcome more powerful surveillance to improve border
security (e.g., monitor migration, combat identity theft and fraud etc). We
may agree with this group. First and foremost, the use of biometrics in the
border control aims to improve security and detect fraud (discussed in section
2.1) which will leads to maximizing the benefits for the society (e.g.,
travelers) and minimizing the human workload (e.g., border police officers).
With respect to the consequentialism theory (discussed in section 2.2), every
society member (travelers, border police officers etc.) must benefit the same
and it is not specific to any individual. Furthermore, the reason one
individual must promote the overall good is the same reason why anyone else
has to promote the good. Hence, it can be said that the ethics of the border
control biometrics is related to consequentialism. The consequentialism theory
places a group’s interest and happiness above those of an individual for the
good of many.

On the other hand, other groups of people may object and perceive biometrics
technology as a threat to their personal life and privacy. Such groups might
believe that surveillance technology is untrustworthy and destructive to
liberty, dignity and privacy. For example, collecting biometric data such as
iris scanning from veiled Muslim women [27] in stressful situations (e.g.,
inappropriate police behavior due to exhaustion or stress) may undermine the
dignity of the women being scanned. An FRA report “Under watchful eyes:
Biometrics, EU IT systems and fundamental rights” [14] showed that
disproportionate force has been used when fingerprinting asylum seekers and
migrants in irregular situations. Considering deontological ethics (duty-based
or rule-based ethics discussed in section 2.2) and given the vulnerability of
the people concerned as well as the obligation to use the least invasive
means, it is difficult to justify the use of physical or psychological force
solely to obtain biometrics for the purpose of identification and
verification. When it comes to border control and border rules, ethical
theories might change according to circumstance. Border officers have a duty
to do the right thing (verify the identity of a traveler before
entering/exiting the border etc.) even if it produces an undesirable outcome.
In the case of veiled Muslim women or any other cases, it would be difficult
to judge the action of an officer based on the outcome.

From the review, it could be concluded that ethics are not absolute, and
clearly, views on biometrics technology vary according to the differing needs
of people and institutions. However, different perceptions of biometrics
technology reflect the diverse value judgments as influenced by many factors:
age, gender, cultural beliefs, education, moral imagination etc. Remarks over
the use of biometrics technology for large populations, especially if the
consequences lead to social exclusion, either as a result of the individual
being unable to reliably enroll or verify their data, or simply not having
confidence in the system and avoiding having to interact with it. Certainly,
when it comes to border control and the use of biometrics technology to
increase border security, monitor migration and combat identity theft and
fraud etc., the argument is essentially utilitarian (consequentialism theory)
where the collective right of a group (group interest) is balanced against the
rights of the individual. It makes the individual simply a means to the ends
of the majority. However, this could be a wrong argument. Wickins in [36] and
Townend in [34] argue that public interest must be judged by considering the
balance between individuals, i.e. the rights of single individuals must be
balanced against other single individuals if individuals are not to be used
instrumentally.

##  5 Conclusions

An important conclusion to this paper is that we are not attempting to provide
an answer to what is ethical and what is not, or what is right and what is
not. We see biometrics technology usage in border control with two sides. One
side is the main intention and aim of biometrics technology to improve border
control management and enhance people flow etc. The other side represents the
risk of violating personal rights. As said, conflicts with decisions based on
what to choose (e.g., privacy versus security, autonomy versus solidarity)
make it difficult to have a broad and consistent position in favor of, or
against expanding or restricting biometric technologies.

Individual acceptance of biometrics technology should be actively promoted
through ensuring transparency of decision-making, clear policy regarding the
purpose of biometric technology and how it is used, as well as increased
measures dedicated to preserve personal rights and personal data protection.
Since greater use of personal data impacts upon human rights, there needs to
be an honest and assertive study of what the risks are to personal rights and
privacy as well as how these risks are mitigated. Border control biometrics
should comply with human rights legislation to encourage respect for
fundamental rights in the implementation of biometrics technologies. Also,
they should respect human dignity and protect personal integrity, preserve
individual freedom and self-determination (i.e., choice and consent with
respect to which biometrics data he/she prefers to use), respect privacy and
family life, and safeguard against harm and unreasonable force for data
processing. Moreover, border control biometrics should comply with security
requirements and data protection legislation to ensure data confidentiality,
integrity and availability when collecting and processing personal related
data.

In the future, we shall investigate the use of ontologies for knowledge
representation and enhancement of knowledge discovering using machine learning
techniques. Ontologies provide a formal, explicit specification of a shared
conceptualization of a domain that can be communicated between people and
heterogeneous and widely spread application systems [33]. We aim to propose a
semantic based framework for biometrics integration in border control systems
relying on ontologies and machine learning techniques [7] to tackle ethical,
social and legal challenges.

## ACKNOWLEDGEMENTS

This work is carried out in the EU-funded project SMILE (Project ID: 740931),
[H2020-DS-2016-2017] SEC-14-BES-2016 towards reducing the cost of technologies
in land border security applications.

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