Mas e Deg ee in
In o ma ion Managemen
E hical In eg a ion o Biome ic Da a in Public Se ices:
Empowe ing E iciency, Secu i y, and P i acy h ough AI-based
Sel -Se ice Technologies
Balancing Inno a ion, Cos -e ec i eness, and Da a Righ s o
Enhanced Public Sec o Ope a ions
José Ca los Ba e Eusébio Sequei a
Mas e Thesis
p esen ed as pa ial equi emen o ob aining he Mas e Deg ee in In o ma ion Managemen
NOVA In o ma ion Managemen School
Ins i u o Supe io de Es a ís ica e Ges ão de In o mação
Uni e sidade No a de Lisboa
MGI
NOVA In o ma ion Managemen School
Ins i u o Supe io de Es a ís ica e Ges ão de In o mação
Uni e sidade No a de Lisboa
ETHICAL INTEGRATION OF BIOMETRIC DATA IN PUBLIC SERVICES:
EMPOWERING EFFICIENCY, SECURITY, AND PRIVACY THROUGH AI-
BASED SELF-SERVICE TECHNOLOGIES
Balancing Inno a ion, Cos -e ec i eness, and Da a Righ s o
Enhanced Public Sec o Ope a ions
by
José Ca los Ba e Eusébio Sequei a
Mas e Thesis p esen ed as pa ial equi emen o ob aining he Mas e ’s deg ee in In o ma ion
Managemen , wi h a specializa ion in Knowledge Managemen and Business In elligence.
Supe ised by
P o esso Mijail Juano ich Na anjo Zolo o , PhD, NOVA In o ma ion Managemen School
11 2023
i
STATEMENT OF INTEGRITY
I he eby decla e ha ing conduc ed his academic wo k wi h in eg i y. I con i m ha I ha e no used
plagia ism o any o m o undue use o in o ma ion o alsi ica ion o esul s along he p ocess leading
o i s elabo a ion. I u he decla e ha I ha e ully acknowledged he Rules o Conduc and Code o
Hono om he NOVA In o ma ion Managemen School.
José Ca los Ba e Eusébio Sequei a
Lisboa, 13/11/2023
ii
DEDICATION
I app ecia e he ema kable educa ional jou ney ha Uni e sidade No a de Lisboa, pa icula ly NOVA
IMS, has p o ided me. The nu u ing academic a mosphe e, combined wi h he unwa e ing suppo
o he acul y and s a , has played a pi o al ole in shaping my pe sonal g ow h and accomplishmen s.
To NOVA IMS, a beacon o knowledge and inno a ion, I ex end my hea el g a i ude o impa ing a
p o ound comp ehension o my ield and equipping me wi h he skills o na iga e i s in icacies. You
s ead as dedica ion o excellence has laid he co ne s one o my academic pu sui s and u u e
endea ou s.
I wan o exp ess my since es g a i ude o my supe iso , P o esso Mijail Juano ich Na anjo Zolo o .
You guidance and wisdom ha e been in aluable h oughou my mas e 's jou ney. You un elen ing
dedica ion o he pu sui o knowledge, as well as you pa ien men o ing, ha e had a signi ican
impac on bo h my academic and pe sonal g ow h.
To my amily, whose boundless lo e and unwa e ing suppo ha e been my cons an mo i a ion, I
ex end my deepes hanks o belie ing in me e en when he pa h seemed daun ing. You sac i ices
and encou agemen ha e illumina ed my pa h.
And o my che ished iends, you companionship and sha ed expe iences ha e b ough joy and
equilib ium o he demanding academic landscape. Thank you o being my pilla s o s eng h and o
he coun less momen s o laugh e ha ha e made his jou ney un o ge able.
As I dedica e his wo k, I honou he commi men o lea ning and explo a ion ha Uni e sidade No a
de Lisboa and NOVA IMS exempli y. May his hesis se e as a es amen o he collec i e pu sui o
knowledge and inno a ion.
Wi h p o ound g a i ude,
José Sequei a.
iii
ABSTRACT
In ecen yea s, AI-based sel -se ice echnology (SST) has expe ienced ema kable g ow h and
ans o ma ion wi hin he public sec o . This su ge in adop ion is d i en by he my iad ad an ages i
o e s, such as inc eased adap abili y, pe sonalized use expe iences, and imp o ed e iciency, cos -
e ec i eness, and o e all se ice quali y. The deploymen o AI-d i en SST has p o en o be a
signi ican change, os e ing mo e seamless in e ac ions wi h ci izens, and p o iding go e nmen s wi h
oppo uni ies o e olu ionize hei se ice deli e y. This esea ch en u es in o uncha ed e i o y by
explo ing he un apped po en ial lying a he in e sec ion o SST and biome ic echnology. By
in eg a ing biome ic da a in o he SST amewo k, a p o ound shi in he public sec o 's capabili ies
becomes appa en . The syne gy be ween hese wo echnologies p omises o p opel SST o an
unp eceden ed le el, o e ing a no el dimension o i s applica ions and bene i s. The s udy del es in o
he mul i ace ed landscape o his amalgama ion, p o iding an in-dep h analysis o he p o ound
bene i s i o e s o he public sec o . Th ough igo ous examina ion, i has become e iden ha he
usion o biome ic echnology wi h SST acili a es a ans o ma i e leap in e iciency and he use
expe ience. This symbio ic ela ionship ede ines public se ices, op imizing hem o he digi al age.
Among he no able indings o his esea ch, i is e iden ha his in eg a ion enhances ope a ional
e iciency wi hin he public sec o , s eamlining p ocesses, and educing cos s. I also os e s a highe
le el o secu i y, c i ical o sa egua ding sensi i e da a, as he s udy disco e ed ha AI-d i en SST,
wi h biome ic da a, signi ican ly imp o es secu i y measu es. In summa y, he amalgama ion o
biome ic echnology and SST signi ies a ema kable leap in he capabili ies o he public sec o . The
esul ing e iciency gains, coupled wi h he p omise o an enhanced use expe ience, demons a e he
po en ial o his in eg a ion. This esea ch o e s in aluable insigh s o public sec o s akeholde s
seeking o na iga e he e e -e ol ing landscape o go e nmen se ices. By emb acing hese
echnologies, go e nmen s can unlock a p omising u u e whe e inno a ion con e ges wi h he
e ol ing needs o bo h he go e nmen and i s ci izens.
KEYWORDS
Biome ic Da a; A i icial In elligence (AI); Sel Se ice Technologies (SSTs); AI-SST

i
Sus ainable De elopmen Goals (SDGs):
TABLE OF CONTENTS
1. INTRODUCTION ............................................................................................................ 1
2. LITERATURE REVIEW ..................................................................................................... 3
2.1. AI-based SST .......................................................................................................... 4
2.2. Challenges o AI in public sec o ........................................................................... 5
2.3. Bene i s o ai in public sec o ................................................................................ 6
2.4. Regula o y amewo ks o he collec ion and use o biome ic da a .................. 7
2.5. Knowledge gap ...................................................................................................... 8
3. MODEL AND HYPOTHESES BUILDING ........................................................................... 9
3.1. EMPIRIC STUDY .................................................................................................... 10
3.2. Da a O e iew ..................................................................................................... 12
3.2.1. Da a Collec ion P ocess ................................................................................ 12
3.2.2. Sample Size ................................................................................................... 12
3.2.3. Ques ionnai e ............................................................................................... 12
4. RESULTS AND DISCUSSION ......................................................................................... 14
4.1. Findings ................................................................................................................ 15
4.2. Pa ial Leas squa es (PLS) Analysis ..................................................................... 15
4.3. Boo s ap Tes o signi icance analysis ................................................................ 18
4.4. Resul s Analysis ................................................................................................... 20
4.4.1. Mul icollinea i y Valida ion .......................................................................... 20
4.4.2. Hypo hesis Con i ma ion .............................................................................. 20
5. CONCLUSIONS AND FUTURE WORK ........................................................................... 23
5.1. Key Findings ......................................................................................................... 23
5.2. Con ibu ions o he Field ................................................................................... 24
5.3. Add essing he Resea ch Que y .......................................................................... 25
5.4. IMPLICATIONS ..................................................................................................... 27
5.5. LIMITATIONS ........................................................................................................ 27
5.6. FUTURE AVENUES FOR RESEARCH ...................................................................... 28
5.7. FINAL REMARKS ................................................................................................... 28
BIBLIOGRAPHICAL REFERENCES ...................................................................................... 29
APPENDIX A ..................................................................................................................... 34
ANNEXES .......................................................................................................................... 42
i
LIST OF FIGURES
Figu e 3.1 - Concep ual F amewo k ......................................................................................... 10
Figu e 4.1 - BTS Model ............................................................................................................. 19
ii
LIST OF TABLES
Table 1 - AI-based SST ................................................................................................................ 4
Table 2 - AI in Public Sec o Challenges ..................................................................................... 5
Table 3 - AI in Public Sec o Bene i s .......................................................................................... 6
Table 4 - Regula o y F amewo ks o Biome ic Da a ................................................................ 7
Table 5 - Ques ionai e Sample Cha ac e is ics ....................................................................... 14
Table 6 - Co ela ion, c onbach’s alpha, composi e eliabili y (CR), a e age a iance ex ac ed
(AVE) and R-squa e........................................................................................................... 16
Table 7 - Loadings and C oss-loadings ..................................................................................... 17
Table 8 - He e o ai -mono ai a io o co ela ions (HTMT) ................................................. 17
Table 9 - Pa h Coe icien s........................................................................................................ 18
Table 10 - To al e ec s esul s ................................................................................................. 19
Table 11 - Collinea i y S a is ics (VIF) ....................................................................................... 20
Table 12 - Resea ch hypo hesis s a us a e he empi ical esul s ha e been analysed ......... 22
Table 13 - Resea ch Ques ion Findings Summa y ................................................................... 26
5
2.2. CHALLENGES OF AI IN PUBLIC SECTOR
The in eg a ion o AI wi hin he public sec o ca ies he po en ial o ele a e e iciency, e ec i eness,
and ci izen sa is ac ion. Ne e heless, i does no come wi hou i s sha e o challenges. A ho ough
li e a u e e iew conce ning AI's ole in he public sec o unde lines e hical and legal dilemmas as
conce ns. The AI usage o en aises pe inen ques ions abou p i acy, secu i y, and anspa ency.
Addi ionally, echnical hu dles, such as da a a ailabili y and quali y, coupled wi h he in icacies o AI
sys ems, p esen o midable challenges (Plan inga, 2022).
Resis ance o change eme ges as a ecu en issue, pa icula ly as some employees wi hin he public
sec o may pe cei e he au oma ion o hei oles as a po en ial h ea . Simila ly, he de elopmen ,
implemen a ion, and main enance o AI sys ems can p o e cos ly. Mo eo e , he lack o public us in
AI's abili y o make unbiased decisions can compound he challenges (Plan inga, 2022). I is c i ical o
inco po a e go e nance and accoun abili y in o AI sys ems used in he public sec o . Plus, o gua an ee
jus ice, openness, and accoun abili y, clea s anda ds and policies mus be es ablished (Wi z e al.,
2019).
In summa y, he li e a u e e iew unde sco es he c i ical impo ance o add essing he challenges
linked o AI's adop ion in he public sec o , plus he u gency o conduc ing u he esea ch o de elop
bes p ac ices and guidelines o he design, implemen a ion, and e alua ion o AI sys ems. The aim is
o ha ness he po en ial o AI while upholding e hical and legal s anda ds, p omo ing anspa ency,
and ensu ing he deli e y o enhanced public se ices.
Table 2 - AI in Public Sec o Challenges
Topic
Main S udies
Key Poin s
AI in Public
Sec o Challenges
(Plan inga, 2022; Sob ino-Ga cía,
2021; Wi z e al., 2019; Wi z &
Mülle , 2019)
E hical and legal dilemmas ela ed o
p i acy, secu i y, and anspa ency
(Plan inga, 2022; Wi z e al., 2019;
Wi z & Mülle , 2019)
Technical obs acles including da a
a ailabili y and complexi y o AI
sys ems
(Plan inga, 2022; Wi z e al., 2019;
Wi z & Mülle , 2019)
Resis ance o change and pe cep ion
o job au oma ion as a h ea
(Plan inga, 2022; Wi z e al., 2019;
Wi z & Mülle , 2019)
Cos o de elopmen , implemen a ion,
and main enance
(Plan inga, 2022; Sob ino-Ga cía,
2021; Wi z e al., 2019; Wi z &
Mülle , 2019)
Lack o public us in AI's unbiased
decision-making

6
2.3. BENEFITS OF AI IN PUBLIC SECTOR
The applica ion o AI in he public sec o can signi ican ly enhance he e ec i eness, e iciency, and
o e all sa is ac ion o ci izens. S udies on AI's ole wi hin he public sec o consis en ly e eal se e al
ad an ages associa ed wi h i s in eg a ion. One no able ad an age lies in he ealm o enhanced
e iciency. AI's capabili y o manage epe i i e and ime-consuming asks ees up human esou ces,
enabling hem o ocus on mo e in ica e and alue-d i en esponsibili ies. As a esul , o al
p oduc i i y in he public sec o inc eases. Addi ionally, AI's abili y o handle massi e amoun s o da a
enables i o deli e insigh s ha in luence decision-making p ocesses, esul ing in be e -in o med,
e idence-based conclusions (Chen e al., 2019, 2021).
Mo eo e , AI sys ems p o ide pe sonalized and e icien se ices o ci izens, subsequen ly ele a ing
sa is ac ion le els wi h public se ices. Simul aneously, hey educe cos s by au oma ing asks and
diminishing he eliance on human esou ces (Wi z & Mülle , 2019). AI can also play a pi o al ole in
moni o ing and analysing da a ele an o public sa e y, including c ime a es and a ic pa e ns,
which ansla es in o mo e e icien and e ec i e public sa e y measu es. Fu he mo e, AI sys ems can
o e se ices ha a e inclusi e and accessible o indi iduals wi h disabili ies, such as oice ecogni ion
sys ems ailo ed o hose wi h isual impai men s.
In summa y, he li e a u e e iew unde sco es he as po en ial bene i s o AI in he public sec o ,
encompassing augmen ed e iciency, imp o ed decision-making, ele a ed ci izen sa is ac ion, cos
sa ings, bols e ed public sa e y, and enhanced accessibili y. Howe e , o ealize hese bene i s, i is
impe a i e o g apple wi h he challenges associa ed wi h AI in he public sec o , including e hical and
legal conside a ions, echnical limi a ions, and he need o cul i a e public con idence. Ex ensi e
u he esea ch is equi ed o gauge he e ec i eness o AI sys ems wi hin he public sec o and o
es ablish bes p ac ices o hei implemen a ion and e alua ion.
Table 3 - AI in Public Sec o Bene i s
Topic
Main S udies
Key Poin s
AI in Public
Sec o Bene i s
(Be yhill e al., 2019; Chen e al., 2019,
2021; Valle-C uz e al., 2019)
Enhanced e iciency h ough
au oma ion o asks
(Be yhill e al., 2019; Chen e al., 2019,
2021; Valle-C uz e al., 2019)
Imp o ed decision-making based on
da a insigh s
(Be yhill e al., 2019; Valle-C uz e al.,
2019; Wi z & Mülle , 2019)
Pe sonalized and e icien se ices
o ci izens
(Be yhill e al., 2019; Chen e al., 2021;
Wi z & Mülle , 2019)
Cos sa ings h ough ask
au oma ion
(Valle-C uz e al., 2019; Wi z & Mülle ,
2019)
Imp o ed public sa e y measu es
h ough da a moni o ing
7
2.4. REGULATORY FRAMEWORKS FOR THE COLLECTION AND USE OF BIOMETRIC DATA
A obus egula o y amewo k exis s o p o ec indi idual p i acy and secu i y in he collec ion and
usage o biome ic da a wi hin he public sec o . A comp ehensi e e iew o hese egula ions e eals
se e al o e a ching hemes (Da endeli, 2023; Villegas-Ch & Ga cía-O iz, 2023).
Fi s , hese egula ions sa egua d da a p i acy by manda ing ha biome ic da a is collec ed and used
in a law ul, anspa en manne , wi h indi iduals' in o med consen and awa eness. Fu he mo e, he
equi emen s ocus on sa e da a s o age, p e en ing illici access o o exploi a ion o such da a.
Secondly, he egula o y amewo k g an s indi idual’s speci ic igh s o e hei biome ic da a,
including he igh o access, con ol, and, when necessa y, eques co ec ions o dele ions. Thi dly,
anspa ency and accoun abili y a e cen al ene s o hese egula ions, necessi a ing ha clea and
comp ehensible in o ma ion abou he pu pose and usage o biome ic da a is p o ided, coupled wi h
he s ic en o cemen o da a p o ec ion egula ions. Fou hly, he egula ions dic a e ha biome ic
da a should only be collec ed and used o well-de ined, law ul pu poses and only wi h he exp ess
consen o indi iduals. Las ly, hese egula ions exhibi e hical unde pinning, add essing conce ns such
as he po en ial o disc imina ion o s igma iza ion in he handling o biome ic da a.
Con inued s udy is equi ed o examine he e icacy o hese ules and o c ea e bes p ac ices o hei
implemen a ion and assessmen . As he landscape o biome ic da a and AI-based echnologies
e ol es, egula o y amewo ks mus emain adap able and obus o p o ec indi idual igh s and he
esponsible use o such da a wi hin he public sec o .
Table 4 - Regula o y F amewo ks o Biome ic Da a
Topic
Main S udies
Key Poin s
Regula o y F amewo ks
o Biome ic Da a
(Da endeli, 2023; No h-
Sama dzic, 2020; Villegas-Ch &
Ga cía-O iz, 2023)
P o ec ion o da a p i acy,
consen , and law ul usage
(Da endeli, 2023; No h-
Sama dzic, 2020; Villegas-Ch &
Ga cía-O iz, 2023)
Secu e s o age and p e en ion o
unau ho ized access
(Da endeli, 2023; No h-
Sama dzic, 2020; Villegas-Ch &
Ga cía-O iz, 2023)
Indi iduals' igh s o access,
con ol, and co ec hei
biome ic da a
(Da endeli, 2023; No h-
Sama dzic, 2020; Villegas-Ch &
Ga cía-O iz, 2023)
T anspa ency, accoun abili y, and
clea in o ma ion on da a usage
(Da endeli, 2023; No h-
Sama dzic, 2020; Villegas-Ch &
Ga cía-O iz, 2023)
E hical conside a ions and
p e en ion o disc imina ion
8
2.5. KNOWLEDGE GAP
While a subs an ial body o esea ch exis s on he usage o biome ic da a in he public sec o h ough
AI-based SST, he e emain signi ican gaps in ou cu en unde s anding (Jain e al., 2022; Leslie, 2019;
Siau & Wang, 2020; Wi z e al., 2020). One no able limi a ion lies in he dea h o comp ehensi e,
long- e m s udies ha examine he adop ion and impac o his echnology o e ime. This gap
impedes he abili y o ho oughly assess he echnology's bene i s and d awbacks, including i s
implica ions o p i acy and secu i y (Jain e al., 2022).
Fu he mo e, li le a en ion o he cul u al and sociological implica ions o biome ic da a usage was
gi en, such as he in luence on p i acy and pe sonal igh s, as well as he e hical conce ns connec ed
wi h employing biome ic da a in go e nmen se ices (Leslie, 2019; Siau & Wang, 2020), which is a
c i ical aspec as i del es in o he b oade socie al implica ions o his echnology.
Ano he a ea o conce n e ol es a ound he in eg a ion o AI-based SST in o go e nmen p ocedu es
and sys ems, which in ol es conside a ions o he equi ed in as uc u e and he de elopmen o
necessa y echnical skills o e ec i ely suppo and main ain he echnology (Wi z e al., 2020). The
implemen a ion o AI-based SST also aises issues abou ci izen us in go e nmen ac ions and he
po en ial o biases wi hin he da a o algo i hms used o p ocess his da a (Jain e al., 2022; Siau &
Wang, 2020). These conce ns a e in eg al o ensu ing equi y and ai ness in he echnology applica ion.
Las ly, while he e may be po en ial cos sa ings h ough he au oma ion o asks and he educed
eliance on human esou ces, i is impe a i e o conduc a ho ough e alua ion o he economic
implica ions associa ed wi h AI-based SST (Jain e al., 2022).
In conclusion, u he esea ch is necessa y o b idge hese knowledge gaps and p o ide a
comp ehensi e unde s anding o he po en ial bene i s and d awbacks inhe en in AI-based SST
implemen a ion wi hin he public sec o . Such esea ch will no only acili a e he de elopmen o bes
p ac ices bu also ensu e ha he in eg a ion o AI-based SST aligns wi h b oade socie al alues and
he o e all well-being o ci izens.
9
3. MODEL AND HYPOTHESES BUILDING
The Technology Accep ance Model (TAM) is a enowned heo y wi hin he in o ma ion echnology
ealm. In oduced by Da is in 1989 and de i ed om he easoned ac ion "p oposed by Fishbein and
Ajzen (1975) in he ield o Social Psychology" (Ka doyo e al., 2015; Ma ono e al., 2020), TAM is a
well-es ablished amewo k o comp ehending how indi iduals pe cei e and engage wi h new
echnology. I unde sco es he signi icance o pe cei ed use ulness and ease o use as pi o al ac o s
in luencing use s' a i udes and in en ions owa d echnology adop ion (Ma ono e al., 2020).
Wi hin he con ex o he public sec o and he u iliza ion o biome ic da a h ough AI-based SST, TAM
p o es in aluable in analysing he adop ion and usage o his echnology. I p o ides a solid ounda ion
o examining he accep ance and applica ion o biome ic da a. The objec i e o his s udy is o
iden i y he ba ie s and acili a o s in luencing echnology accep ance and usage, o e ing
ecommenda ions o enhancemen . By le e aging TAM as a heo e ical amewo k, his s udy
con ibu es o he exis ing knowledge in he ield by deepening he unde s anding o he accep ance
and u iliza ion o AI-based SST in he public sec o .
P e ious esea ch has employed al e na i e models, such as he Di usion o Inno a ions Theo y (DoI)
and he Uni ied Theo y o Accep ance and Use o Technology (UTAUT), o sc u inize he accep abili y
and usage o no el echnologies. DoI elucida es he di usion o concep s, p oduc s, and se ices ac oss
di e en indus ies and posi s a i e-s age p ocess encompassing awa eness, in e es , assessmen ,
ial, and accep ance. On he o he hand, UTAUT ac o s in elemen s like pe o mance expec ancy,
e o expec ancy, social in luence, and acili a ing condi ions o elucida e he mo i a ions behind
echnology u iliza ion. Bo h DoI and UTAUT ep esen c edible choices wi hin he ield o in o ma ion
echnology. Howe e , o his s udy, TAM was chosen due o i s simplici y and ex ensi e applicabili y,
ende ing i well-sui ed o a b oad spec um o echnological domains.
To comp ehensi ely g asp he ac o s go e ning he adop ion and u iliza ion o biome ic da a wi hin
he public sec o h ough AI-based SST, an amalgama ion o he Technology Accep ance Model (TAM),
In o ma ion Sys em Success Model (ISSM), and Consume Value Theo y (CVT) eme ges as a obus
amewo k. ISSM unde sco es ha he iumph o an in o ma ion sys em hinges on sys em quali y,
in o ma ion quali y, and se ice quali y, collec i ely in luencing use sa is ac ion wi h he sys em
(Adeyemi & Issa, 2020). Meanwhile, CVT cen es on he pe cei ed alue o echnology in use s'
decision-making p ocesses, con empla ing he bene i s, sac i ices, and pe cei ed quali y o he
echnological sys em (Tu el e al., 2010).
Howe e , his in eg a ed amewo k, despi e i s comp ehensi e na u e, is no de oid o limi a ions. I
may appea in ica e, especially o indi iduals un amilia wi h i s unde lying p inciples. Concep ual
o e lap be ween he heo ies migh in oduce con usion and complica e he iden i ica ion o dis inc
elemen s. Addi ionally, he amewo k's applicabili y may be con ex -dependen , wi h i s e ec i eness
in o ecas ing echnology adop ion po en ially a ying acco ding o he ci cums ances.
In eg a ing h ee dis inc heo ies, each wi h i s assump ions and limi a ions, p esen s a unique
challenge. Ne e heless, despi e i s d awbacks, he amalgama ion o TAM, ISSM, and CVT o e s a mo e
holis ic amewo k o dissec ing he adop ion and usage o biome ic da a in he public sec o ia AI-
based SST compa ed o o he models such as DoI. Howe e , alida ing he e ec i eness o his
10
in eg a ed model empi ically, especially conce ning i s p edic i e capabili ies o echnology adop ion
wi hin he public sec o h ough AI-based SST, may pose challenges.
In conclusion, he in eg a ion o TAM wi h ISSM and CVT p o ides a mo e comp ehensi e amewo k
o unde s anding he adop ion and usage o biome ic da a in he public sec o h ough AI-based SST
compa ed o o he models such as DoI, no wi hs anding i s limi a ions.
3.1. EMPIRIC STUDY
In his sec ion, we emba k on an empi ical jou ney designed o alida e and elucida e he hypo heses
a he hea o ou model. These hypo heses, me iculously c a ed and inspi ed by ex ensi e li e a u e
and heo e ical amewo ks, aim o illumina e he in ica e ela ionships among pi o al ac o s shaping
he adop ion landscape o biome ic echnology wi hin he public sec o .
The hypo heses un old as ollows:
H1a: Biome ic Technology Awa eness posi i ely shapes use s' expe iences, in en ions, and
pe cei ed u ili y
The s udy elies on ex ensi e li e a u e o examine he in luence o Biome ic Technology Awa eness
on Pe cei ed U ili y, which sugges s ha inc eased awa eness posi i ely co ela es wi h use s'
pe cep ions o he echnology's u ili y. Indi iduals who ha e a ho ough g asp o biome ic echnology
a e mo e likely o ecognise i s p ac ical bene i s, in luencing hei judgemen o i s use ulness.
Figu e 3.1 - Concep ual F amewo k

11
H1b: Use s who ha e a ho ough g asp o biome ic echnology a e mo e likely o ind i simple o
use
G ea e Biome ic Technology Awa eness adds a ou ably o he imp ession o Ease o Use, based on
insigh s om he Technology Accep ance Model (TAM) and he Uni ied Theo y o Accep ance and Use
o Technology (UTAUT). Use s who a e al eady amilia wi h biome ic echnology should ind i mo e
use - iendly, i ing smoo hly wi h hei cogni i e expec a ions.
H2a: Use s who ha e mo e ai h in echnology a e mo e likely o ind i bene icial
T us appea s as a c i ical ac o in moulding consume s' imp essions. Use s a e mo e likely o ega d
biome ic echnology as aluable as hei us g ows. T us ac s as a ca alys , c ea ing a pleasan
en i onmen ha inc eases he pe cei ed alue o he echnology.
H2b: Use s who ha e ai h in echnology will ega d i as mo e accessible and use - iendly
In he same way ha us in luences pe cei ed use ulness, us in echnology impac s pe cei ed ease
o use. Use s who ha e a g ea e le el o us a e mo e likely o ind he echnology use - iendly and
easie o use.
H3: When use s iew a echnology o be bene icial, hey a e mo e inclined o adop i
TAM's co ne s one o pe cei ed use ulness di ec ly a ec s consume s' p opensi y o emb ace
biome ic echnologies. A good sense o use ulness is expec ed o ansla e in o a s onge desi e o
adop echnology in he public sec o .
H4: Easy- o-use sys ems a e mo e likely o gene a e a good in en ion o emb ace he echnology
Acco ding o TAM p inciples, Ease o Use di ec ly in luences consume s' In en ion o Use. A use -
iendly sys em is mo e likely o os e a a ou able desi e o use he echnology, ma ching he na u al
inclina ion o use - iendly sys ems.
H5: People who ha e a a ou able desi e o use biome ic echnology a e mo e inclined o us
go e nmen agencies ha ha e adop ed i
Finally, he complex ela ionship be ween consume s' In en ion o Use and T us in Go e nmen a e
in es iga ed. A a ou able desi e o use biome ic echnology is expec ed o inc ease us in
go e nmen en i ies ha employ he echnology, o ming a symbio ic connec ion.
This esea ch employs quan i a i e me hod me hodology, by using quan i a i e su eys, cap u ing
nume ical da a on a iables such as awa eness, us , pe cei ed u ili y, ease o use, and in en ion o
use. The s udy pu posely includes a a ied sample o public sec o use s a ge ed by biome ic
echnology implemen a ions, chosen s a egically based on hei exposu e o o p ospec i e
engagemen wi h biome ic sys ems inside go e nmen al se ices. The quan i a i e da a is subjec ed
o igo ous s a is ical s udies, including eg ession analysis, o de e mine he s eng h and signi icance
o co ela ions be ween a iables. Simul aneous hema ic analysis o quali a i e da a p o ides a
de ailed knowledge o pa icipan s' iewpoin s.
12
While he en i e da a analysis is ongoing, p elimina y indings sugges ea ly indica o s ha ag ee wi h
heo e ical assump ions. As we go in o he nex phase o da a analysis, he comple e esul s o e no
only s a is ics bu also a deep g asp o he complica ed web o ac o s d i ing biome ic echnology
adop ion in he public sec o .
3.2. DATA OVERVIEW
3.2.1. Da a Collec ion P ocess
I is i al o gi e insigh in o he da a collec ion p ocedu e o app ecia e he indings o he s udy and
hei implica ions. So, da a collec ion p ocedu es we e planned o p o ide a comp ehensi e iew o
he use o biome ic da a in he public sec o ia AI-powe ed sel -se ice pla o ms:
▪ Su ey Ins umen De elopmen : A sys ema ic ques ionnai e was designed o ga he
iewpoin s and expe iences. The s udy issue and i s ela ed componen s we e he ocus
o his ques ionnai e, which included Biome ic Technology Awa eness (BTA), Ease o
Use (EU), In en ion o Use (IU), Pe cei ed Use ulness (PU), T us in Go e nmen (TG),
and T us in Technology (TT).
▪ Da a Collec ion: The ques ionnai e was dis ibu ed elec onically using social media
pla o ms, like LinkedIn, and also h ough he uni e si y email and Moodle, assu ing
anonymi y and con iden iali y while os e ing candid and open esponses.
▪ Da a Analysis: The amassed da a unde wen igo ous analysis using PLS modelling
echniques. This obus s a is ical app oach is well-sui ed o modelling in ica e
ela ionships be ween la en cons uc s and obse able a iables, ackling he
mul i ace ed esea ch ques ion.
3.2.2. Sample Size
The signi icance and alidi y o he esea ch indings a e connec ed o he sample size and
ep esen a i eness. In his ega d, he s udy me iculously in ol ed a di e se and su icien ly
subs an ial sample size, comp ising 224 pa icipan s. This sample size was no only adequa e bu also
obus , a o ding a con idence ha he esul s and insigh s gene a ed a e dependable and di ec ly
pe inen o he esea ch ques ion.
3.2.3. Ques ionnai e
The ques ionnai e, he da a collec ion ins umen , was c i ical in gene a ing esponses ela ing o
concep s linked wi h biome ic da a usage in he public sec o . This igo ously de eloped ques ionnai e
included opics o assess pa icipan s' pe spec i es, expe iences, and a i udes abou biome ic
echnology usage in go e nmen p ocesses.
The ques ionnai e is s uc u ed in o sec ions encompassing:
▪ A eas o Usage (AU)
▪ Biome ic Technology Awa eness (BTA)
▪ Demog aphics (DG)
▪ Ease o Use (EU)
▪ In en ion o Use (IU)
▪ Pe cei ed Use ulness (PU)
13
▪ P i acy (P)
▪ Sys em Quali y (SQ)
▪ T us in Go e nmen (TG)
▪ T us in Technology (TT)
▪ Use Expe ience (UE)
▪ Use Sa is ac ion (US)
Each sec ion ea u ed mul iple i ems ha p omp ed esponden s o p o ide a ings o answe s,
acili a ing a comp ehensi e assessmen o hei iewpoin s on hese pi o al cons uc s. In he
subsequen sec ions o his chap e , we will p esen he analysis and engage in a discussion o he key
indings de i ed om his da a collec ion p ocess, enabling o d aw meaning ul insigh s and each
conclusions ha di ec ly add ess he esea ch ques ion.
14
4. RESULTS AND DISCUSSION
This s udy e ol es a ound a undamen al ques ion ha se es as i s guiding p inciple: "How can
biome ic da a be used e icien ly and e hically in he public sec o h ough AI-based sel -se ice
echnologies o enhance e iciency, educe cos s, and heigh en secu i y, all while p ese ing
indi iduals' p i acy and da a igh s?" This ques ion s ands a he co e o he ex ensi e examina ion o
biome ic da a usage wi hin he public sec o . The signi icance o his esea ch eme ges as i
endea ou s o b idge he e e -widening chasm be ween ad ancing echnology and he e hical,
e icien , and secu e assimila ion o biome ic da a in o public sec o ope a ions.
In an e a ha inc easingly elies on da a-d i en decision-making, his s udy g apples wi h he in ica e
challenge o ha monizing he p essing need o ampli ied e iciency, cos educ ion, and heigh ened
secu i y wi h he impe a i es o p ese ing indi idual p i acy and da a igh s. I p o ides in aluable
insigh s ha ha e he po en ial o shape he design and execu ion o AI-based sel -se ice echnologies
ha pi o on he use o biome ic da a.
Table 5 - Ques ionai e Sample Cha ac e is ics
Cha ac e is ic
Desc ip ion
F equency (n)
Pe cen age (%)
To al Sample Size
224
100%
Gende
- Female
Female Pa icipan s
58
25.9%
- Male
Male Pa icipan s
82
36.6%
- O he
1
0.45%
- Blank
Pa icipan s ha no answe ed
83
37.1%
Age
- 18-24
Pa icipan s aged 18-24
15
6.7%
- 25-34
Pa icipan s aged 25-34
43
19.2%
- 35-44
Pa icipan s aged 35-44
36
16.07%
- 45-54
Pa icipan s aged 45-54
32
14.29%
- 55-64
Pa icipan s aged 55-64
14
6.25%
- 75-84
Pa icipan s aged 75-84
1
0.45%
- Blank
Pa icipan s ha no answe ed
83
37.1%
Educa ion Le el
- High School
Pa icipan s wi h High School
12
5.36%
- Bachelo ’s Deg ee
Pa icipan s wi h Bachelo ’s Deg ee
50
22.32%
- Mas e ’s Deg ee
Pa icipan s wi h Mas e ’s Deg ee
68
30.36%
- Doc o a e
Pa icipan s wi h Doc o a e
11
4.91%
- Blank
Pa icipan s ha no answe ed
83
37.1%
21
he impac o us in echnology on use s' pe cep ion o he u ili y o biome ic sys ems, highligh ing
us as a pi o al ac o in enhancing pe cei ed use ulness.
TT posi i ely in luences EU (H2b):
The empi ical analysis p o ides suppo o H2b. The posi i e pa h coe icien obse ed in he
ela ionship be ween T us in Technology (TT) and Ease o Use (EU) is s a is ically signi ican , indica ing
a obus connec ion be ween use s' us in echnology and hei pe cep ion o he echnology's ease
o use.
PU posi i ely in luences IU (H3):
The empi ical analysis con i ms he alidi y o H3. The posi i e pa h coe icien obse ed in he
ela ionship be ween Pe cei ed Use ulness (PU) and In en ion o Use (IU) is s a is ically signi ican ,
indica ing a s ong and posi i e connec ion be ween use s' pe cep ion o he echnology's use ulness
and hei in en ion o use i .
EU posi i ely in luences IU (H4):
The empi ical analysis suppo s he asse ion o H4. The posi i e pa h coe icien obse ed in he
ela ionship be ween Ease o Use (EU) and In en ion o Use (IU) is s a is ically signi ican , p o iding
empi ical e idence ha use - iendliness plays a pi o al ole in shaping use s' in en ions o adop
biome ic echnology in he public sec o .
IU posi i ely in luences TG (H5):
The empi ical in es iga ion a i ms he alidi y o H5. The obus posi i e ela ionship, indica ed by a
signi ican pa h coe icien be ween In en ion o Use (IU) and T us in Go e nmen (TG), p o ides
empi ical suppo o he hypo hesis.

22
Table 12 - Resea ch hypo hesis s a us a e he empi ical esul s ha e been analysed
The indings, consis en wi h heo e ical expec a ions, alida e all he hypo heses. The in ica e
ela ionships be ween awa eness, use - iendliness, us , and in en ion unde sco e he nuanced
ac o s in luencing he adop ion o biome ic echnology in he public sec o . These insigh s, gleaned
om a me iculous analysis o he p o ided da a, hold implica ions o u u e esea ch and p ac ical
implemen a ions in he domain o biome ic echnology adop ion.
Code
Hypo hesis
S a us
H1a
Biome ic Technology Awa eness posi i ely shapes use s' expe iences,
in en ions, and pe cei ed u ili y.
Con i med
H1b
Use s who ha e a ho ough g asp o biome ic echnology a e mo e likely
o ind i simple o use.
Con i med
H2a
Use s who ha e mo e ai h in echnology a e mo e likely o ind i
bene icial.
Con i med
H2b
Use s who ha e ai h in echnology will ega d i as mo e accessible and
use - iendly.
Con i med
H3
When use s iew a echnology o be bene icial, hey a e mo e inclined o
adop i .
Con i med
H4
Easy- o-use sys ems a e mo e likely o gene a e a good in en ion o
emb ace he echnology.
Con i med
H5
People who ha e a a ou able desi e o use biome ic echnology a e
mo e inclined o us go e nmen agencies ha ha e adop ed i .
Con i med
23
5. CONCLUSIONS AND FUTURE WORK
This sec ion ac s as a ligh house, showcasing he key insigh s and signi ican conclusions ob ained om
his esea ch's ex ensi e jou ney. The esea ch ocused on he in e sec ion be ween AI-d i en sel -
se ice echnology and he complex wo ld o biome ic da a in he public sec o . Ou jou ney ac oss
his di e se en i onmen e eals a ich apes y o oppo uni y plus equally in ica e p oblems. The
con e gence o hese echnologies de ines a di e se ecosys em in which echnical de elopmen mee s
he complica ed demands o go e nmen and public se ice.
The in es iga ion ook a pa h ha examined he e ec i eness and ope a ional bene i s o hese
inno a i e echnologies bu also he e hical issues in e wined wi h hei applica ion. I e ealed a
s o y highligh ed by he p omise o simpli ied p ocedu es, esou ce e iciency, and se ice accessibili y
on he one hand and he c i ical na u e o p i acy measu es, e hical conce ns, and da a igh s
implica ions on he o he . This syn hesis, whe e echnology mee s go e nance, p o ides a complex ye
exci ing pic u e in which he equi emen o main ain e hical and secu e p ac ises is igh ly linked.
Th ough his lens, ou in es iga ion a e sed he landscapes o echnological in eg a ion, explo ing
he imp o emen s and complexi ies o esponsible implemen a ion ha e e be a e ac oss a ange o
legal, e hical, and socie al iews.
5.1. KEY FINDINGS
We look in o he signi ican insigh s gained om he public sec o 's in eg a ion o biome ic da a and
AI-based sel -se ice echnologies. The esea ch in es iga ed he ans o ma ional in luence o his
echnology, disco e ing a shi ha imp o es ope a ional e iciency, s eng hens secu i y amewo ks,
and necessi a es in ensi e e hical sc u iny. These indings gi e a na a i e ha no only e eals he
po en ial o go e nance echnology bu also highligh s he signi icance o a e sing his landscape
wi h an unwa e ing commi men o e hical in eg i y.
E iciency and Cos Sa ings
The syne gis ic combina ion o biome ic da a wi h AI-d i en sel -se ice pla o ms has eme ged as a
game-changing app oach in he public sec o (Chen e al., 2021). This in eg a ion d i es p ocess
e iciency and e inemen , esul ing in signi ican gains in esou ce alloca ion and usage. Public
en e p ises bene i signi ican ly om biome ic da a in ope a ional e iciency and economic p udence
(Owusu-Owa e & E ah, 2022). These de elopmen s poin o a undamen al shi in he sec o 's
unc ionali y, indica ing a signi ican mo e owa ds simpli ied ope a ions and enhanced se ice
deli e y (Hekal e al., 2023; He nandez-de-Menendez e al., 2021).
Ampli ied Secu i y Measu es
Biome ic da a usage in conjunc ion wi h AI-d i en sys ems is a c i ical componen in s eng hening
secu i y p ocesses wi hin public sec o companies. This in eg a ion ensu es pe ec iden i y
e i ica ion, s eng hened da a p ocessing, and he igo ous imposi ion o access con ol measu es,
esul ing in a s ong and secu e en i onmen (A o a & Bha ia, 2022; Khan & E hymiou, 2021). This
s eng hened secu i y amewo k is c i ical in secu ing sensi i e in o ma ion and os e ing ci izen us
in bo h go e nmen ins i u ions and he deployed echnical in as uc u e (Biming, 2023).
24
E hical and Legal Implica ions
The mul idimensional e ain o in eg a ing biome ic echnology in he public sec o delica ely
in e wines wi h a web o e hical and legal p oblems. This de ailed analysis highligh s he c i ical need
o gain in o med pe mission, apply da a educ ion echniques, es ablish e ec i e secu i y measu es,
and adhe e o egula o y no ms wi hou ail (Shi, 2023). The igo ous a en ion o hese de ails
emphasises he e hical and app op ia e biome ic echnology usage (Melzi e al., 2022). Main aining
indi idual p i acy and da a igh s becomes he co ne s one o adop ing biome ic solu ions in he
public sec o , sus aining us and e hical in eg i y wi hin he echnology-d i en en i onmen o
go e nance (Liyanaa achchi e al., 2023; Na gunana han e al., 2016).
5.2. CONTRIBUTIONS TO THE FIELD
This hesis ep esen s a signi ican con ibu ion o he ield, ocusing on he e ec i eness and e hical
use o biome ic da a in he public sec o h ough AI-d i en sel -se ice pla o ms. The s udy has made
speci ic con ibu ions and yielded esh insigh s, wi h p ac ical implica ions o a ious s akeholde s.
Connec ing Technology and E hics:
▪ Con ibu ion: This esea ch b idges he di ide be ween echnological inno a ion and
e hical conside a ions, add essing a p essing con empo a y issue. I unde sco es he
impo ance o enhancing ope a ional e iciency and secu i y while sa egua ding
indi idual p i acy and da a igh s wi hin an e hical amewo k.
▪ Impo ance: This emphasis on e hical echnology adop ion p o ides a holis ic
pe spec i e, ecognizing ha echnology should no comp omise undamen al
p inciples.
Comp ehensi e Theo e ical F amewo k:
▪ Con ibu ion: The usion o he TAM, ISSM, and CVT c ea es a obus amewo k o
examining biome ic echnology adop ion in he public sec o .
▪ Impo ance: This comp ehensi e amewo k o e s a nuanced app oach o
unde s anding he complexi ies o biome ic echnology adop ion, going beyond me e
e iciency enhancemen s.
Empi ical Insigh s and Recommenda ions:
▪ Con ibu ion: The esea ch p o ides aluable empi ical insigh s in o he d i e s o
biome ic echnology adop ion and i s implica ions o he public sec o .
▪ Impo ance: P ac ical ecommenda ions a ising om he s udy o e guidance o public
sec o o ganiza ions, policymake s, and echnology de elope s o he e icien and
e hical deploymen o biome ic echnology.
25
Emphasis on E hics and P i acy:
▪ Con ibu ion: The esea ch ocuses on e hical conside a ions, encompassing aspec s
such as in o med consen , da a minimiza ion, secu e da a p ocessing, and egula o y
compliance.
▪ Impo ance: This e hical emphasis unde sco es he signi icance o p ese ing indi idual
p i acy and da a igh s, p o iding a oadmap o public sec o o ganiza ions in hei
echnological implemen a ions.
Fu u e Resea ch A enues:
▪ Con ibu ion: The hesis ou lines a ious p ospec i e esea ch a eas, add essing
limi a ions and cha ing he cou se o u he de elopmen s in he ield.
▪ Impo ance: These u u e esea ch di ec ions se e as a guide o del ing deepe in o
he mul i ace ed ealm o biome ic da a u iliza ion, ensu ing equi able, secu e, and
e icien echnology adop ion.
T us in Go e nmen and Technology:
▪ Con ibu ion: The s udy highligh s he in e connec ed na u e o us domains,
demons a ing ha con idence in go e nmen can in luence us in echnology wi hin
public sec o con ex s.
▪ Impo ance: This insigh aids in comp ehending how us dynamics may impac
echnology adop ion and unde sco es he need o cul i a e public us h ough secu e
echnology implemen a ions.
Awa eness and Educa ion:
▪ Con ibu ion: The esea ch emphasizes he impo ance o educa ional e o s in
echnology adop ion, showing a posi i e co ela ion be ween knowledge o biome ic
echnology and i s ease o use.
▪ Impo ance: Public sec o o ganiza ions can le e age his inding o s ee awa eness
campaigns p omo ing he usabili y o sel -se ice applica ions.
These con ibu ions exempli y he signi icance o he esea ch in ad ancing he ield and add essing
he c i ical challenges su ounding biome ic da a in eg a ion in he public sec o . The s udy se es as
a aluable esou ce o hose na iga ing he e ol ing landscape o biome ic echnology in he public
sec o by ocusing on he con e gence o echnology and e hics, p o iding a comp ehensi e heo e ical
amewo k, and o e ing p ac ical guidance.
5.3. ADDRESSING THE RESEARCH QUERY
The p ima y goal o his hesis was o add ess he ques ion, "How can biome ic da a be used e icien ly
and e hically in he public sec o h ough AI-based sel -se ice echnologies o enhance e iciency,
educe cos s, and heigh en secu i y, all while p ese ing indi iduals' p i acy and da a igh s?" The
s udy was me iculously designed o analyse and ackle his complex issue, leading o subs an ial
indings ha p o ide c i ical insigh s in o his mul i ace ed opic.
26
Resea ch Ques ion
Findings
Explana ion
How can biome ic da a be
used e icien ly and e hically
in he public sec o h ough
AI-based sel -se ice
echnologies o enhance
e iciency, educe cos s, and
heigh en secu i y, all while
p ese ing indi iduals' p i acy
and da a igh s?
E iciency
Enhancemen
In eg a ing biome ic da a wi h AI-d i en
sel -se ice pla o ms signi ican ly enhances
ope a ional e iciency in he public sec o .
By au oma ing iden i y e i ica ion and
s eamlining p ocesses, hese echnologies
educe he ime and esou ces equi ed o
se ice deli e y, leading o cos sa ings, and
imp o ed public se ice accessibili y.
Cos Reduc ion
Biome ic da a usage and AI echnology
educe cos s associa ed wi h manual
p ocessing and human e o s. Au oma ion
minimizes he need o ex ensi e human
labou and educes he likelihood o aud
and inaccu acies, esul ing in inancial
sa ings o public sec o o ganiza ions.
Heigh ened
Secu i y
Biome ic da a usage, combined wi h AI-
based sel -se ice echnology, leads o
no able enhancemen s in secu i y
measu es. Biome ic iden i ie s (e.g.,
inge p in s, and acial ecogni ion) p o ide
a highe le el o secu i y compa ed o
adi ional me hods, making i ha de o
unau ho ized indi iduals o gain access.
P ese ing P i acy
and Da a Righ s
E hical conside a ions and sa egua ds a e
c ucial o p o ec ing p i acy and da a
igh s. Implemen ing obus p i acy
measu es, such as enc yp ion and
anonymiza ion, ensu es ha indi iduals'
biome ic da a is p o ec ed om misuse and
b eaches. Policies and amewo ks mus be
de eloped o uphold da a igh s and gain
public us .
T us Es ablishmen
Es ablishing us ela ionships be ween he
public and go e nmen is i al o
echnology accep ance. Building public
con idence h ough anspa ency,
accoun abili y, and clea communica ion
abou he bene i s and sa egua ds o
biome ic echnologies enhances us in
bo h he go e nmen and he echnology.
P ac ical
Recommenda ions
The s udy o e s p ac ical ecommenda ions
o public sec o o ganiza ions,
policymake s, and echnology de elope s.
Recommenda ions include adop ing
comp ehensi e p i acy policies, in es ing in
secu e biome ic sys ems, and conduc ing
egula audi s o ensu e compliance wi h
e hical s anda ds.
Table 13 - Resea ch Ques ion Findings Summa y

27
In conclusion, he s udy e ec i ely add essed he cen al esea ch ques ion, demons a ing ha
biome ic da a can be employed e icien ly and e hically in he public sec o h ough AI-based sel -
se ice echnology. The indings unde sco e he po en ial o enhanced ope a ional e iciency,
secu i y, p i acy, and da a igh s, p o iding a oadmap o u u e esea ch and p ac ical
ecommenda ions o implemen a ion.
5.4. IMPLICATIONS
This s udy's indings ha e signi ican implica ions o public policy, he p i a e sec o , and u u e
esea ch.
Fo public policy, public sec o en i ies can imp o e e iciency and educe cos s h ough biome ic da a
in eg a ion wi h AI-d i en sel -se ice solu ions (Chen e al., 2021). Policymake s should de elop
amewo ks o acili a e his adop ion, leading o s eamlined se ice deli e y (Hekal e al., 2023).
Au ho i ies should p io i ize obus p i acy laws o biome ic da a usage in he public sec o , balancing
indi idual igh s and echnology deploymen (Shi, 2023).
In he p i a e sec o , echnology p o ide s should ecognize oppo uni ies in AI-d i en sel -se ice
solu ions o he public sec o , os e ing pa ne ships and ad ancemen s (He nandez-de-Menendez e
al., 2021). P i a e en i ies should ocus on ailo ed cybe secu i y solu ions o p o ec biome ic da a in
he public sec o (Š i ilis e al., 2023).
Fu u e esea ch should explo e e hical dimensions o biome ic da a use, including consen and da a
minimiza ion. S udies should in es iga e public a i udes owa d biome ic echnologies o ensu e
socially esponsible implemen a ion. Compa a i e esea ch ac oss egions can o e insigh s in o he
global applicabili y o biome ic da a usage. Resea ch should also examine how biome ic da a usage
a ec s ma ginalized communi ies o p omo e equi able echnology adop ion.
In conclusion, he s udy highligh s he po en ial o imp o ed public se ice deli e y h ough biome ic
da a and AI-d i en echnologies, emphasizing he need o e hical conside a ions and p i acy igh s.
The p i a e sec o can align inno a ions wi h public sec o needs, os e ing collabo a ion. Fu u e
esea ch should add ess e hical issues and explo e new dimensions o biome ic da a usage.
5.5. LIMITATIONS
Add essing he limi a ions iden i ied is c ucial o u u e esea ch c edibili y. Fu u e s udies should
in ol e la ge and mo e di e se samples o imp o e gene alizabili y. In eg a ing sel - epo ed da a
wi h beha iou al da a can enhance esul accu acy. Longi udinal s udies can ack changes o e ime,
p o iding dynamic insigh s. Fu u e esea ch should explo e biome ic da a usage ac oss di e se egions
and cul u es. Compa a i e legal s udies can p o ide insigh s in o how di e en laws impac biome ic
da a usage.
Fu u e esea ch should add ess hese limi a ions o a mo e obus unde s anding o biome ic da a
u iliza ion in he public sec o .
28
5.6. FUTURE AVENUES FOR RESEARCH
This s udy lays he ounda ion o u he esea ch in o biome ic da a usage in he public sec o
h ough AI-d i en sel -se ice pla o ms.
Con inuous moni o ing can p o ide a dynamic iew o echnology adop ion. Expanding samples o
include a ious public sec o o ganiza ions can o e b oade insigh s. Compa a i e esea ch can
explo e he in luence o di e en legal amewo ks and cul u al no ms. Combining sel - epo ed da a
wi h beha iou al da a o e s a holis ic unde s anding o echnology adop ion. Resea ch should explo e
da a p i acy in icacies wi hin he public sec o . Unde s anding public a i udes and conce ns can guide
e ec i e implemen a ion s a egies. Resea ch should ensu e echnology adop ion is inclusi e and
equi able. Examining di e en legal amewo ks can iden i y bes p ac ices and ha monize egula o y
s anda ds.
Fu u e esea ch will enhance he unde s anding o biome ic da a u iliza ion, add essing limi a ions
and explo ing new dimensions o esponsible implemen a ion.
5.7. FINAL REMARKS
This hesis explo ed biome ic da a usage in he public sec o , ocusing on AI-d i en sel -se ice
echnologies. The p ima y ques ion was how o employ biome ic da a e icien ly and e hically o
enhance e iciency, educe cos s, and s eng hen secu i y while sa egua ding p i acy and da a igh s.
The indings highligh subs an ial po en ial o imp o ing e iciency and secu i y, emphasizing he need
o e hical conside a ions. The implica ions guide public sec o en i ies in enhancing ope a ions and
unde sco e he impo ance o public us h ough secu e da a managemen .
This esea ch con ibu es o he e ol ing landscape o echnology adop ion and go e nance, p o iding
a ounda ion o u u e s udies, policy de elopmen , and in o med decision-making in he public
sec o . The jou ney o biome ic da a usage con inues, guided by p og ess and e hics, shaping a
esponsible and inno a i e u u e.
29
BIBLIOGRAPHICAL REFERENCES
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I1.2020.69-79
A o a, S., & Bha ia, M. P. S. (2022). Challenges and oppo uni ies in biome ic secu i y: A su ey.
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Be yhill, J., Heang, K. K., Cloghe , R., & McB ide, K. (2019). Hello, Wo ld: A i icial in elligence and i s
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Biming, B. (2023). Unlocking he Fu u e: Explo ing Biome ic Applica ions o Enhanced Secu i y and
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Chen, T., Guo, W., Gao, X., & Liang, Z. (2021). AI-based sel -se ice echnology in public se ice
deli e y: Use expe ience and in luencing ac o s. Go e nmen In o ma ion Qua e ly, 38(4),
101520. h ps://doi.o g/10.1016/j.giq.2020.101520
Chen, T., Ran, L., & Gao, X. (2019). AI inno a ion o ad ancing public se ice: The case o China’s i s
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Digi al Go e nmen Resea ch, 100–108. h ps://doi.o g/10.1145/3325112.3325243
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om he AI on ie : Insigh s om hund eds o use cases. McKinsey Global Ins i u e.
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Da endeli, F. (2023). The P o ec ion o Biome ic Da a in he E a o A i icial In elligence Technology in
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and bo de p o ec ion (CBP). In e na ional Jou nal o In o ma ion Managemen Da a
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37
Q7 P i acy
1
(S ongly
Disag ee)
(1)
2
(2)
3
(3)
4
(4)
5
(5)
6
(6)
7
(S ongly
Ag ee) (7)
I’m conce ned ha my pe sonal
in o ma ion will be sha ed o sold o
o he s when I en e AI-based SSTs ha
use Biome ic Da a. (1)
o
o
o
o
o
o
o
I am conce ned abou he po en ial loss
caused by p i acy in asion. (2)
o
o
o
o
o
o
o
I wo y ha o he s may iew my
biome ic in o ma ion. (3)
o
o
o
o
o
o
o
Q8 Pe cei e Use ulness
1
(S ongly
Disag ee) (1)
2
(2)
3
(3)
4
(4)
5
(5)
6
(6)
7
(S ongly
Ag ee) (7)
The use o AI-based SST ha use
Biome ic Da a sa es me ime when
dealing wi h public se ices. (1)
o
o
o
o
o
o
o
The use o AI-based SSTs ha use
Biome ic Da a gi es me ull con ol
when dealing wi h public se ices. (2)
o
o
o
o
o
o
o
The use o AI-based SST ha use
Biome ic Da a gi es me lexibili y
when dealing wi h public se ices. (3)
o
o
o
o
o
o
o

38
Q9 Easy o Use
1
(S ongly
Disag ee) (1)
2
(2)
3
(3)
4
(4)
5
(5)
6
(6)
7
(S ongly
Ag ee) (7)
I I wan ed o use AI-based SST ha
uses Biome ic Da a, i would be
easy o me. (1)
o
o
o
o
o
o
o
I I wan ed o use AI-based SST ha
uses Biome ic Da a, i would be
simple o me. (2)
o
o
o
o
o
o
o
I I wan ed o use AI-based SST ha
uses Biome ic Da a, I would ha e
no p oblems. (3)
o
o
o
o
o
o
o
Q10 Use Expe ience
1
(S ongly
Disag ee) (1)
2
(2)
3
(3)
4
(4)
5
(5)
6
(6)
7
(S ongly
Ag ee) (7)
AI-based SST ha uses Biome ic
Da a is easy o unde s and. (1)
o
o
o
o
o
o
o
Use eels in con ol when
in e ac ing wi h AI-based SST ha
uses Biome ic Da a. (2)
o
o
o
o
o
o
o
AI-based SST ha uses Biome ic
Da a is as and e icien o use. (3)
o
o
o
o
o
o
o
39
Q11 T us in Go e nmen
1
(S ongly
Disag ee)
(1)
2
(2)
3
(3)
4
(4)
5
(5)
6
(6)
7
(S ongly
Ag ee) (7)
I us ha pa liamen is managing AI-
based SST ha uses Biome ic Da a well.
(1)
o
o
o
o
o
o
o
I us ha he go e nmen is using AI-
based SST ha uses Biome ic Da a in he
igh way. (2)
o
o
o
o
o
o
o
The cen al go e nmen /municipali y will
do i s bes o implemen AI-based SST
ha use Biome ic Da a. (3)
o
o
o
o
o
o
o
Q12 In en ion o Use
1
(S ongly
Disag ee) (1)
2
(2)
3
(3)
4
(4)
5
(5)
6
(6)
7
(S ongly
Ag ee) (7)
I in end o use AI-based SST ha
uses Biome ic Da a in he nea
u u e. (1)
o
o
o
o
o
o
o
I will use AI-based SST ha uses
Biome ic Da a e e y ime I ha e he
oppo uni y. (2)
o
o
o
o
o
o
o
I plan o use AI-based SSTs ha use
Biome ic Da a in public se ices. (3)
o
o
o
o
o
o
o
40
Q13 Use Sa is ac ion
1
(S ongly
Disag ee) (1)
2
(2)
3
(3)
4
(4)
5
(5)
6
(6)
7
(S ongly
Ag ee) (7)
I hink AI-based SSTs ha use
Biome ic Da a a e use ul. (1)
o
o
o
o
o
o
o
I hink AI-based SSTs ha use
Biome ic Da a a e wo h he ime
and e o equi ed o use hem. (2)
o
o
o
o
o
o
o
O e all, you a e sa is ied wi h AI-
based SSTs ha use Biome ic Da a.
(3)
o
o
o
o
o
o
o
Q14 Base on pas expe ience, which public se ices would bene i om he implemen a ion and use
o AI-based SST ha use Biome ic Da a?
(You can selec mo e han one)
▢ Heal hca e (1)
▢ Educa ion (2)
▢ T anspo a ion (3)
▢ Social Wel a e (4)
▢ O he (please speci y) (5)
__________________________________________________
41
Q15 Wha is you gende ?
o Male (1)
o Female (2)
o Non-bina y / hi d gende (3)
o P e e no o say (4)
Q16 How old a e you?
o 18 - 24 (1)
o 25 - 34 (2)
o 35 - 44 (3)
o 45 - 54 (4)
o 55 - 64 (5)
o 65 - 74 (6)
o 75 - 84 (7)
o 85 o olde (8)
Q17 Wha is you educa ion le el?
o Less han high school (1)
o High school g adua e (2)
o Bachelo Deg ee (3)
o Mas e Deg ee (4)
o Doc o a e (5)
42
ANNEXES
E hics Commi ee App o al
NOVA IMS | E hics Commi ee - APPROVED
Qual ics Su ey So wa e <no eply@qemailse e .com>
sex, 19/05/2023 18:22
Pa a:Jose Ca los Ba e Eusebio Sequei a (R2014489) < 2014489@no aims.unl.p >
This is o ce i y ha
P ojec No.: INFSYS2023-5-192033
P ojec Ti le: Usage o biome ic da a in he Public Sec o using A i icial In elligence based Sel -
Se ice Technologies (AI-based SST)
P incipal Resea che : José Ca los Ba e Eusébio Sequei a
acco ding o he egula ions o he E hics Commi ee o NOVA IMS and MagIC Resea ch Cen e his
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app o ed.
The P incipal Resea che is equi ed o no i y he E hics Commi ee, ia amendmen o p og ess
epo , o
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