The literature of historical institutionalism emphasizes the path dependent character of the policy making process in which critical junctures can alter prevailing policy monopolies and put new...Show moreThe literature of historical institutionalism emphasizes the path dependent character of the policy making process in which critical junctures can alter prevailing policy monopolies and put new path dependent institutions in place, according to scholars in the field of Public Administration. However, ideational change and development of prevailing ideas in an institution could also be part of a non-punctuated institutional dynamic, because change in dominant ideas could happen overtime. In other words, institutions themselves also allow an endogenous dynamic of change. So, instead of focussing on the specific role of critical junctures on the decision-making process as scholars in the field of public administration tend to do, it is crucial to discuss the institutional environment that could be influenced by the critical juncture. This study will highlight the prevailing ideas in the EU’s institutions on the usage of Big Data and Artificial Intelligence (AI) to protect public health in the EU before and during the COVID-19 pandemic, by establishing a Union-wide framework of collecting and analysing health data. The EU advocated for the need to use such technologies in the formulated EU4Healthplan that acted as a response to COVID-19. However, this programme could also elaborate on the results and ideas of such a Union-wide health and data framework relying on the EU’s Health Programme 2014 – 2020. The latter would indicate a path of slow change in ideas within the policy cycle for EU policymakers. Therefore, this study will research the following question: ‘How did the COVID-19 pandemic influence the adoption of Big Health Data infrastructure in the policy process of the EU?’. To answer this question, the study will discuss the development of a policy monopoly concerning digital health in the European Union via a process-tracing method of analysing documents and journals provided by the European Commission, European Parliament and the Council of the European Union and it will also take the public opinion into account. As a result, the method showed that prevailing ideas of using Big Data and AI to protect the public health were already high on the European policy agenda before the COVID-19 pandemic. However, COVID-19 was a crucial factor for the implementation of a pan-European model, in terms of using Big Data and AI to protect public health. It did not radically alter the ideas within Europe but accelerated the EU policy process. In this degree of agreement with the literature on critical junctures that it causes a shift in prevailing ideas, this study opts for a measured tone towards the role of a critical juncture opening up a window of opportunity by causing a shift in prevailing ideas – at the same time – will not underestimate itShow less
The lack of adoption and use of the e-CODEX (e-Justice Communication via Online Data Exchange) system in the European justice domain mirrors the complexity of realising interoperability in Europe....Show moreThe lack of adoption and use of the e-CODEX (e-Justice Communication via Online Data Exchange) system in the European justice domain mirrors the complexity of realising interoperability in Europe. Connecting the information systems of autonomous organisations with the means of technological innovation for improved efficiency can be a difficult task, and requires cooperation between all parties involved. But what drives or holds back organisations to adopt such technological innovations? While much research has been conducted on the adoption of (technological) innovations in the public and private sector, theoretical and empirical research on innovation adoption in a cross-border and judicial context is still lacking. This qualitative explanatory study used a combination of Diffusion of Innovation (DOI) theory and Technology-Organisation-Environment (TOE) framework as foundation to examine the relationship between fourteen factors (relative advantage, compatibility, complexity, trialability, observability, top management support, slack resources, costs, championship, facilitative leadership, disposition to and readiness for collaboration, trust, external pressure of social networks and network externalities, and legislation and policy) and the adoption of interoperable electronic information sharing by judicial organisations. By using e-CODEX as a case study, this thesis contributes to the literature on IT adoption by adding the cross-border, European, and judicial contexts. E-CODEX (e-Justice Communication via Online Data Exchange) is an example of a voluntary initiative that was developed with European Union (EU) financial support by a number of Member States in 2010. It is a tool based on the principle of interoperability that enables judicial authorities to exchange information and documents in a secure way. It is interoperable because it establishes a decentralised communication network between national IT systems in cross-border civil and criminal procedures. Data was gathered from interviews with members of the e-CODEX project consortium, judicial organisations (previously) participating in e-CODEX pilots, and one organisation that is currently planning to adopt e-CODEX. The findings indicate that all proposed factors in this study seem to be relevant to at least some extent for the adoption of IEIS. However, the findings also show that some factors have greater relevance than others.Show less
The increasing reliance on ICT within the public sector has changed the working ways of governmental bureaucracies from a paper reality to a digital one, and governments are eager to use new...Show moreThe increasing reliance on ICT within the public sector has changed the working ways of governmental bureaucracies from a paper reality to a digital one, and governments are eager to use new technologies for their business operations and reap its benefits just as the private sector does. Since technological advancement is driven by the private sector, and humans are increasingly accustomed to the speed and efficiency that technology brings, citizens are expecting governments to adapt and digitize as well. As such, an important trend that is being experimented with is the usage of self-learning algorithms, particularly Artificial Intelligence or AI. Since AI runs on data, it is only logical that an organization such as the government which holds an abundance of data would like to put this to use. Data that is collected might hold certain patterns, if you can find such patterns and assume that the near future will not be much different from when the data was collected, predictions can be made. However, AI systems are often deemed opaque and inscrutable, and this can collide with the judicial accountability that governments have towards their citizens in the form of transparency. Based on the assumption that the information that is used by AI i.e. data and algorithms, is not similar to documentary information that governments are accustomed to, there are added obstacles for governments to overcome in order to achieve the desired effects of transparency. The goal of this research is to explore the barriers to transparency in governmental usage of AI in decision-making by analyzing governmental motivation towards (non-) transparency and how the complex nature of AI relates to this. The question that stems from this is: What are the obstacles related to being transparent in AI-assisted governmental decision-making? In the study, a comparison is made between the obstacles to transparency for documentary information and the obstacles that experts encounter in practice related to AI, a contribution follows. Based on the literature, it is hypothesized that governments are limited by privacy and safety issues, lack of expertise, cooperation and inadequate disclosure. The results show that the obstacles are more nuanced and an addition to the theory is appropriate. The most important findings being: that data and algorithms should not be treated as documentary information; the importance of the policy domain in determinant for the degree of transparency; that lack of cooperation causes multiple obstacles to transparency such as self-censoring, accountability issues, superficial debate, false promises, inability to explain and ill-suited systems; that more information disclosure isn’t always better; and that the public sector should rethink their overreliance on private sector business models. All these obstacles can be associated to losing sight of the fundamental function of government, serving citizens.Show less
