Title: Developing an artificial intelligence readiness framework for citizen-centred public governance (J5-50165)
Head of the research group: prof. dr. Aleksander Aristovnik
The project’s mission is to improve the public administration’s functioning and strengthen hybrid public governance by providing a framework for PA to be able to measure their AI readiness and act accordingly to exploit the potential held by AI. A comprehensive methodological framework driven by a mixed-methods design will thus be developed, serving as holistic guidance for public administration to assess their readiness for artificial intelligence technologies adoption by public administration. Specifically, the innovative and comprehensive framework will be based on an original methodology from the existing AI/smart/digital readiness assessment frameworks and will build on the theories of technology adoption – upgraded to AI-specific and extended Leavitt’s diamond model, while observant of the contemporary overlapping of public governance principles. The proposed framework is to be tailored to the specific features of the Slovenian public administration, involving public governance, stakeholder and environment dimensions, and developed in line with an extensive set of the main public governance practices (neo-Weberian governance, post-NPM, good governance and hybrid public governance) and their corresponding principles. Due to the complexity of the problem domain, interdisciplinary approaches are foreseen. A series of remarkable research results is therefore expected, contributing to the scientific and practical development of the field of public administration.
The research project will develop a comprehensive interdisciplinary methodological framework that will permit the measurement of readiness in public administration to be assessed with respect to various sub-dimensions. The methodological framework is to be based on quantitative (e.g., closed-ended surveys, microdata etc.) and qualitative (e.g., semi-structured interviews, focus groups) data analysed using several methods (bibliometric analysis, data mining, content analysis, expert reviews, dynamic methods etc.). Intensive use of the proposed comprehensive framework will enable public administration to make better informed and more reliable data-driven decisions and, even more importantly, to make public administration of greater value to the public. The complex nature of AI technologies will be addressed by the interdisciplinary approach, facilitating the hitherto still not achieved systemic way of measuring AI readiness for citizen-centred public governance. This will lay important foundations for public administration’s further modernisation and for its stakeholders to suitably adapt to the challenges of the ongoing digital transformation.
Duration (from/to):
1. 10. 2023 – 30. 9. 2026
Contracting Authority:
Slovenian Research and Innovation Agency
Financing:
The project is being financed with 2571 yearly hours (A price category) for 3 years.
Members of the research group:
prof. dr. Aleksander Aristovnik (head)
dr. Matej Babšek (from 15.1.2024)
dr. Zoran Aralica (from 11.3.2024)
Project phases and their realization
The work programme consists of five work packages, which will assist in thoroughly checking the work during the research project. A summary of the work programme is presented in Table 1.
| Work packages | Tasks | Milestones | Methodology |
|
WP1: Landscape of comprehensive AI readiness framework factors and elements for public administration |
T1.1: Bibliometric and content analysis concerning AI technologies in public administration
T1.2: Data mining of public databases T1.3: Content analysis on AI technologies in public administration
T1.4 Review meeting with public administration experts
|
MS1: A compiled and final list of factors determining the readiness of PA on AI |
– Bibliometric analysis – Content analysis – Data mining – Expert reviews |
|
WP2: Framework development |
T2.1: Framework Design
T2.2: Development of framework criteria
T2.3: Development of framework assessment rules
T2.4: Framework testing
|
MS2: An initial set of sub-dimensions for evaluating the readiness of PA on AI |
– Expert-based decision-making – Qualitative methods – Dynamic methods |
| WP3: Framework application and validation in public administration | T3.1: Identification of stakeholders and use cases
T3.2: Data collection and pre-processing
T3.3: Content-based validation of statistically indicated framework
T3.4: Framework modification and finalisation |
MS3: The final set of validated sub-dimensions for evaluating the readiness of PA on AI | – Qualitative methods
– Quantitative methods – Mixed methods – Framework revision |
| WP4: Design of a comprehensive framework | T4.1: Sub-dimensions and framework integration into a tool
T4.2: Proposed actions for public administration stakeholders |
MS4: An integrated and comprehensive tool supplemented with proposed management actions for public administration stakeholders | – Framework synthesis
– Open-source programming – Decision support systems – Reference values setting |
| WP5: Dissemination and promotion | T5.1: An (inter)national promotional event and a manual
T5.2: Professional publications and practical implications
T5.3: High-quality research publications |
MS5: Professional and scientific events and publications on AI technologies in public administration | – (Inter)national events
– Conferences – Multiple diffusion channels |