The book presents a unique study on the Artificial Intelligence (AI) readiness of public administrations focusing on the Maltese public administration as a case study. This was conducted following the launch of the Malta AI National Strategy in 2019. Since the Maltese public administration is the driving force behind the integration of AI solutions nationwide, the research is deemed necessary to understand whether the public workforce itself is ready to face the oncoming AI revolution. The researchers applied a mixed-methods approach to gain insight and a broader perspective of the status quo concerning AI adoption. Important considerations that stem from this study include the need for increased AI knowledge among public administrators since the majority of respondents reported a lack of awareness of AI technologies and their deployment. Understanding AI-related advantages must be accompanied by a robust instructional effort at all levels of education. It was unanimously agreed that the early inclusion of AI-related courses in the Maltese educational system will aid in developing a future AI-savvy workforce. Furthermore, upskilling and reskilling the public officers will facilitate knowledgeable human capital and proficiencies required to effectively integrate AI solutions within society. The study concludes by recommending several critical reforms within governments that will improve the AI-readiness factor of any Public Administration.
Author(s): Marvic Sciberras, Alexiei Dingli
Series: Lecture Notes in Networks and Systems, 568
Publisher: Springer
Year: 2023
Language: English
Pages: 196
City: Cham
Contents
Abbreviations
List of Figures
List of Tables
1 Introduction
References
2 AI and Its Wider Impact
References
3 Public Administration and Technology in Malta
References
4 AI Adoption
References
5 AI-Readiness
References
6 Research Purpose, Question and Design—Exploratory Sequential Approach
References
7 Research Philosophy—Pragmatic Paradigm
7.1 Human Nature and Ontology
7.2 Epistemology
7.3 Pragmatic Paradigm
References
8 Research Approach—Mixed-Methods Approach
References
9 Research Analysis—Triangulation Approach
References
10 Qualitative Research and Findings
10.1 Data Collection Instrument: Semi-structured Interviews
10.2 Design of Interview Questions
10.3 Target Population—Purposive
10.4 Sampling—Total Population
10.5 Data Analysis—Inductive Thematic Analysis
10.6 Research Credibility and Trustworthiness—TACT Framework
10.7 Qualitative Research Findings
References
11 Quantitative Research
11.1 Data Collection Tool: Survey
11.2 Design of Survey Questions
11.3 Target Population—Maltese Public Administration
11.4 Sample—Total Population
11.5 Data Analysis—Graphical Interpretation
11.6 Variables
11.7 Reliability and Validity
11.8 Quantitative Research Findings
11.9 Analysis
11.9.1 Introduction
11.9.2 Understanding AI
11.9.3 Policy and Procedures
11.9.4 Data
11.9.5 Preparedness
11.9.6 Change What?
11.9.7 To Drive AI
11.9.8 In Demand
11.9.9 AI as an Asset
11.9.10 Addressing Risks
11.9.11 Future Applications of AI
11.9.12 Moving Forward
11.9.13 Conclusion
11.10 Conclusions and Recommendations
11.10.1 Conclusions
11.10.2 Recommendations
11.10.3 Future Research
References
Appendix A Consent form for Interviews
Appendix B Interview Questions
Appendix C Consent Form and Survey Questions
Appendix D Step-by-Step Breakdown of the Research Process for Auditability Purposes
Appendix E Excerpts for Overarching Theme 1: Understanding AI
Appendix F Excerpts for Overarching Theme 2: Policy and Procedures
Appendix G Excerpts for Overarching Theme 3: Data
Appendix H Excerpts for Overarching Theme 4: Preparedness
Appendix I Excerpts for Overarching Theme 5: Change What?
Appendix J Excerpts for Overarching Theme 6: In Demand
Appendix K Excerpts for Overarching Theme 7: AI as an Asset
Appendix L Excerpts for Overarching Theme 8: Addressing Risks
Appendix M Excerpts for Overarching Theme 9: Future Applications of AI
Appendix N Excerpts for Overarching Theme 10: Moving Forward
Bibliography
