Chapter 1: A new era of digital governance

Tan, Evrim; Crompvoets, Joep

doi:10.3920/978-90-8686-930-5_1

Cited by 5 publications

(5 citation statements)

References 42 publications

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“…Our findings were based on the use of advanced analytics in fraud detection and relied on the perception of the Belgian stakeholders. However, the theoretical conformity of our findings with other studies on technology adoption in public sector organizations suggests that we can draw some lessons for digital transformation strategies concerning new digital technologies (Tan and Crompvoets, 2022). In summary, the following points are crucial for developing reliable and pertinent digital transformation strategies: (a) trust and interoperability conditions, (b) the perceived benefits of digital technologies in administrative systems and policy objectives, (c) the match of socio-cultural conditions with the characteristics of the digital technologies and their ease of adoption in the existing data governance processes, and (d) the interplay between policy priorities, technological maturity, associated resources and digital skills in the digital governance domain, comprehensiveness of the regulative framework, public values, and perceived risks associated with the implications of digital technologies for public administration and society.…”

Section: Discussionsupporting

confidence: 83%

“…Scholars and practitioners across information sciences, administrative and social sciences are studying the impact and implications of data-driven technologies such as artificial intelligence (AI), big data analytics, machine learning, and blockchain on managerial and organizational systems and practices (Tan and Taeihagh, 2021; Dickinson et al, 2021; Leiman, 2021; Radu, 2021; Taeihagh, 2021; Ulnicane et al, 2021). These technologies are overhauling the existing administrative systems and practices into new types of interactions between humans and machines, which is sometimes called algorithmic bureaucracy (Vogl et al, 2020; Tan and Crompvoets, 2022). However, the adoption of new digital technologies is challenging for public sector organizations due to various value-laden reservations driven by perceived technical, systemic, administrative, and regulative barriers inside and outside of organizations (Tan et al, 2022; Bullock et al, 2020; Vogl et al, 2020; Tangi et al, 2021, Sun and Medaglia, 2019).…”

Section: Introductionmentioning

confidence: 99%

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Artificial intelligence and algorithmic decisions in fraud detection: An interpretive structural model

Tan

Jean

Simonofski³

et al. 2023

Data & Policy

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The use of artificial intelligence and algorithmic decision-making in public policy processes is influenced by a range of diverse drivers. This article provides a comprehensive view of 13 drivers and their interrelationships, identified through empirical findings from the taxation and social security domains in Belgium. These drivers are organized into five hierarchical layers that policy designers need to focus on when introducing advanced analytics in fraud detection: (a) trust layer, (b) interoperability layer, (c) perceived benefits layer, (d) data governance layer, and (e) digital governance layer. The layered approach enables a holistic view of assessing adoption challenges concerning new digital technologies. The research uses thematic analysis and interpretive structural modeling.

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Section: Discussionsupporting

confidence: 83%

Section: Introductionmentioning

confidence: 99%

Artificial intelligence and algorithmic decisions in fraud detection: An interpretive structural model

Tan

Jean

Simonofski³

et al. 2023

Data & Policy

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“…During the last years, the discussion on data-driven innovation developed closely with both technological advancements and the governments’ diverse efforts to catch up with the evolving concept of digital government/governance (Charalabidis et al , 2019). Such discourse has shifted from a focus on ICT adoption towards a data-centric perspective (Charalabidis et al , 2019; Tan and Crompvoets, 2022). This development might explain the emergence of a broad and explicit interest in data-driven innovation for policymaking, which coalesced into a dedicated, yet fragmented, field (Suominen and Hajikhani, 2021; Verhulst et al , 2019) while previously being addressed by dedicated discussions (Longo et al , 2015).…”

Section: Contemporary Discussion On Data-driven Innovation For Policy...mentioning

confidence: 99%

Section: Data-centric Public Services As a Source Of Policy Knowledgementioning

confidence: 99%

“…The first era of digital governance in the public sector revolved around adopting information and communication technologies (ICTs) (Tan and Crompvoets, 2022). ICTs enabled a generation of information-intensive digital services, which are today progressively automated and data-centric (Engin and Treleaven, 2019; Tan and Crompvoets, 2022). Being both material and performative (Orlikowski and Scott, 2015), this service generation is concretised by their technological infrastructures, physical touchpoints and service providers’ and users’ activities.…”

Section: Data-centric Public Services As a Source Of Policy Knowledgementioning

confidence: 99%

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Data-centric public services as potential source of policy knowledge. Can “design for policy” help?

Leoni

Carraro²,

McAuliffe³

et al. 2023

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Purpose The purpose of this paper is three-fold. Firstly, through selected case studies, to provide an overview of how non-traditional data from digital public services were used as a source of knowledge for policymaking. Secondly, to argue for a design for policy approach to support the successful integration of non-traditional data into policymaking practice, thus supporting data-driven innovation for policymaking. Thirdly, to encourage a vision of the relation between data-driven innovation and public policy that considers policymaking outside the authoritative instrumental logic perspective. Design/methodology/approach A qualitative small-N case study analysis based on desk research data was developed to provide an overview of how data-centric public services could become a source of knowledge for policymaking. The analysis was based on an original theoretical-conceptual framework that merges the policy cycle model and the policy capacity framework. Findings This paper identifies three potential areas of contribution of a design for policy approach in a scenario of data-driven innovation for policymaking practice: the development of sensemaking and prefiguring activities to shape a shared rationale behind intra-/inter-organisational data sharing and data collaboratives; the realisation of collaborative experimentations for enhancing the systemic policy analytical capacity of a governing body, e.g. by integrating non-traditional data into new and trusted indicators for policy evaluation; and service design as approach for data-centric public services that connects policy decisions to the socio-technical context in which data are collected. Research limitations/implications The small-N sample (four cases) selected is not representative of a broader population but isolates exemplary initiatives. Moreover, the analysis was based on secondary sources, limiting the assessment quality of the real use of non-traditional data for policymaking. This level of empirical understanding is considered sufficient for an explorative analysis that supports the original perspective proposed here. Future research will need to collect primary data about the potential and dynamics of how data from data-centric public services can inform policymaking and substantiate the proposed areas of a design for policy contribution with practical experimentations and cases. Originality/value This paper proposes a convergence, yet largely underexplored, between the two emerging perspectives on innovation in policymaking: data for policy and design for policy. This convergence helps to address the designing of data-driven innovations for policymaking, while considering pragmatic indications of socially acceptable practices in this space for practitioners.

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Ethics and Development of Advanced Technology Systems in Public Administration

Alexandre¹

2023

Ethics and Responsible Research and Innovation in Practice

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This article analyses aspects related to the implementation of advanced technology systems in Public Administration, taking into account the scope of action of its entities and services, as well as its main distinction with the private sector, which lies in the pursuit of the public interest, understood as justification for the execution of public policies, but also in the broader scope of the human development index. The difficulties and resistance to the adoption and use of technology in Public Administration will be examined, also in the light of practical situations whose implementation proved to be inadequate, resulting in the analysis of ideas for the future. We approach the evolution of public management models that are emerging through the action of technology. We prepare the ground for machine ethics in Public Administration by framing ethics in public services in general terms, with reference to AI systems designed in line with mainstream ethics. Of the various ethical issues that arise in this domain, we pay attention to the issue of privacy and the balance that needs to be achieved so that the use of data can contribute to ethical, beneficial and reliable technologies. We sound alerts in the field of discrimination and prejudice that the bias of technology can show. The explainability and transparency of technological systems provide confidence to decision-makers and citizens, helping to clarify responsibilities in the decisions of Public Administration agents, and the researchers working for them .

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Chapter 1: A new era of digital governance

Cited by 5 publications

References 42 publications

Artificial intelligence and algorithmic decisions in fraud detection: An interpretive structural model

Artificial intelligence and algorithmic decisions in fraud detection: An interpretive structural model

Data-centric public services as potential source of policy knowledge. Can “design for policy” help?

Ethics and Development of Advanced Technology Systems in Public Administration

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