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A Federated Future: Mapping of the future directions towards the Cloud Edge IoT from IoT and Edge community provides a comprehensive analysis of key trends and priorities in IoT technology. The report analyses 6 Strategic Research and Innovation Actions (SRIAs) under the NGIoT initiative using meta-analysis and mapping using a variety of criteria to provide a comparative assessment including: Type: priority area, application, technology Theme: common priority Position within the EU IoT framework: layer, context The report further analyses key insights and highlights focusing on: Main trends across the SRIAs within the development and maturation of new technologies, industry trends and strategic policy, e.g. Green ICT Priority themes evolution and positioning between the initial analysis and current ranking, e.g. reliability and trustworthy AI A Federated Future is an essential resource for anyone interested in understanding how IoT technology is likely to evolve in the coming years. It provides valuable insights into key trends and priorities that will be useful for policymakers, researchers, innovators, and other stakeholders involved in shaping the future of this exciting field.

TheEuropeanUnion has a globally prominent role to play, shaping the regulatory landscape that balances the freedoms that lead to innovation with the protection of the rights of citizens and businesses while attempting toprovide legal certainty.The past decade has been one in which European political leaders have navigated a myriad of societal and economic challenges that have demanded measures that increase Europe’s resilience to systemic shocks and ability to compete in a less stable global political environment. Shared Digital Futures provides an in-depth analysis of the impact of key European legislation and proposals on the IoT and Edge community focusing on: Proposal for Data Act Proposal for Cybersecurity Resilience Act Proposal for Artificial Intelligence Act Digital Markets Act Digital Services Act The NG-IoT community is diverse in terms of stakeholders, domains, technologies and applications. The report provides a brief summary of key impacts of the new regulatory framework: The most salient rights and obligations that may have an impact on the organisations that will form part of the NG-IoT. Key figures across the new regulatory framework The cost of non-compliance. Part of D2.6: NGIoT Roadmap and Policy Recommendations, theShared Digital Future: Impact of key European legislation and proposals on the IoT and Edge communitydeliverable provides acomprehensive overview of the implications of European legislations on the EU IoT and edge community ensuring all stakeholders are up-to-date on European digital policy developments.&nbsp

Cet article rend compte de la relance de l’utilisation de ressources numériques dans l’enseignement supérieur ivoirien depuis le premier cas de coronavirus enregistré en mars 2020. Il fait d’abord un rappel de l’institutionnalisation de la politique numérique dans l’enseignement supérieur ivoirien. Ensuite, il relève les impacts possibles de la diffusion massive de l’enseignement numérique universitaire en Côte d’Ivoire., This article reports on the revival of the use of digital resources in Ivorian higher education since the first recorded case of coronavirus in March 2020. It first provides a reminder of the institutionalization of the policy development in Ivorian higher education. Then, it notes the possible impacts of the massive diffusion of digital university education in Côte d’Ivoire.

Datafication and the use of algorithmic systems increasingly blur distinctions between policy fields. In the financial sector, for example, algorithms are used in credit scoring, money has become transactional data sought after by large data-driven companies, while financial technologies (FinTech) are emerging as a locus of information warfare. To grasp the context specificity of algorithmic governance and the assumptions on which its evaluation within different domains is based, we comparatively study the sociotechnical imaginaries of algorithmic governance in European Union (EU) policy on online disinformation and FinTech. We find that sociotechnical imaginaries prevalent in EU policy documents on disinformation and FinTech are highly divergent. While the first can be characterized as an algorithm-facilitated attempt to return to the presupposed status quo (absence of manipulation) without a defined future imaginary, the latter places technological innovation at the centre of realizing a globally competitive Digital Single Market.

Ambivalenzen prägen den Zugang zur Politikfeldanalyse im Bereich Digitalpolitik: Einerseits findet die Entstehung von neuen Politikfeldern sowie die Ausbildung innerer Strukturen wenig Beachtung auf theoretischer Ebene. Andererseits nimmt die Kategorie des Politikfeldes eine selbstverständliche Rolle innerhalb der Policy-Analyse ein. Ausgehend vom Feld der Digitalpolitik argumentiert der Beitrag, dass eine detaillierte Betrachtung entstehender Politikfelder lohnt. Am Beispiel der KI-Politik wird nachgezeichnet, dass hier bereits ein eigenes Segment innerhalb des Politikfeldes Digitalpolitik entsteht. Mit Hilfe von inhaltsanalytischen Auswertungen von Policy-Dokumenten sowie der Durchführung von Expert*innen-Interviews können schließlich für den Zeitraum der 19. Legislaturperiode die zentralen Akteure und ihre Aktivitäten auf Bundes- und Länderebene identifiziert werden. Für die Bundesländer ergibt sich hierbei eine Dreiteilung entsprechend der Intensität ihrer Bemühungen. Schließlich können erste Strukturen der Bearbeitung des Themas nachgezeichnet werden, die besonders deren Querschnittscharakter betonen. Technologischer Wandel und Politikfeldwandel im Sinne der Ausdifferenzierung gehen in diesem Fall eng miteinander einher. Ambivalences characterize the approach to policy analysis in digital policy: While the emergence of new policy fields receives little attention at the theoretical level, the policy field as a category has a self-evident role within policy analysis. Taking the field of digital policy as a starting point, the paper argues that a detailed consideration of emerging policy fields is worthwhile. For the case of AI policy in Germany, the paper traces how a separate segment within the policy field of digital policy has emerged. Applying content analysis to different policy documents and expert interviews, the key actors, their activities, and initial structures at the federal and state levels can be identified. The analysis shows that the German federal states are grouped into three categories with varying levels of activity in AI policy. Overall, in this case, technological change and change in policy field go hand in hand.

Public administrations are investing in the digital transformation of their citizen-oriented services and internal administrative processes. They are using co-production approaches and include different types of stakeholders into these transformative processes to increase service quality and generate public value. In this study, we investigate how these co-production approaches are implemented in both digital strategy formulation and implementation in Denmark. We identify four different types of public value: citizen, economic, administrative and societal public value.

Automated decision-making (ADM) systems may affect multiple aspects of our lives. In particular, they can result in systematic discrimination of specific population groups, in violation of the EU Charter of Fundamental Rights. One of the potential causes of discriminative behavior, i.e., unfairness, lies in the quality of the data used to train such ADM systems. Using a data quality measurement approach combined with risk management, both defined in ISO standards, we focus on balance characteristics and we aim to understand how balance indexes (Gini, Simpson, Shannon, Imbalance Ratio) identify discrimination risk in six large datasets containing the classification output of ADM systems. The best result is achieved using the Imbalance Ratio index. Gini and Shannon indexes tend to assume high values and for this reason they have modest results in both aspects: further experimentation with different thresholds is needed. In terms of policies, the risk-based approach is a core element of the EU approach to regulate algorithmic systems: in this context, balance measures can be easily assumed as risk indicators of propagation – or even amplification – of bias in the input data of ADM systems.

This article attempts to describe the state of "cultural policy" at a time of fundamental reinvention. While the digital transition has transformed culture, cultural policies have adapted only slowly to this new reality. Reviewing the main work and studies published in recent years, the article describes this fundamental shift in cultural policy as a result of the digital transition. It also looks at other ongoing changes, from the rise of the cultural industries to cultural diversity, not forgetting the ecological transition. Ultimately, the article observes a broadening of the notion of "cultural policy" and describes its different — and new — components: arts policy, the economy of culture and of course the cultural industries, digital policy and platform regulation; new philanthropy; arts education; algorithmics; creative cities; social networks; cultural start-ups; cultural diplomacy; the creative class; soft power, etc. This widened approach to "cultural policy" contributes to reconsidering the role of public and private actors and the place of artists in a digital society. (January 2020), + ID: 578386

Learning health systems (LHS) use digital health and care data to improve care, shorten the timeframe of improvement projects, and ensure these are based on real‐world data. In the United Kingdom, policymakers are depending on digital innovation, driven by better use of data about current health service performance, to enable service transformation and a more sustainable health system. This paper examines what would be needed to develop LHS in the United Kingdom, considering national policy implications and actions, which local organisations and health systems could take. The paper draws on a seminar attended by academics, policymakers, and practitioners, a brief literature review, and feedback from policy experts and National Health Service (NHS) stakeholders. Although there are examples of some aspects of LHS in the UK NHS, it is hard to find examples where there is a continuous cycle of improvement driven by information and where analysis of data and implementing improvements is part of usual ways of working. The seminar and literature identified a number of barriers. Incentives and capacity to develop LHS are limited, and requires a shift in analytic capacity from regulation and performance, to quality improvement and transformation. The balance in priority given to research compared with implementation also needs to change. Policy initiatives are underway which address some barriers, including building analytical capacity, developing infrastructure, and data standards. The NHS and research partners are investing in infrastructure which could support LHS, although clinical buy in is needed to bring about improvement or address operational challenges. We identify a number of opportunities for local NHS organisations and systems to make better use of health data, and for ways that national policy could promote the collaboration and greater use of analytics which underpin the LHS concept.