Identification and Lossy Reconstruction in Noisy Databases

A high-dimensional database system is studied where the noisy versions of the underlying feature vectors are observed in both the enrollment and query phases. The noisy observations are compressed before being stored in the database, and the user wishes to both identify the correct entry corresponding to the noisy query vector and reconstruct the original feature vector within a desired distortion level. A fundamental capacity-storage-distortion tradeoff is identified for this system in the form of single-letter information theoretic expressions. The relation of this problem to the classical Wyner-Ziv rate-distortion problem is shown, where the noisy query vector acts as the correlated side information available only in the lossy reconstruction of the feature vector. \ua9 1963-2012 IEEE

Smart Government – Partizipation und Empowerment der Bürger im Zeitalter von Big Data und personalisierter Algorithmen

Anhand zwei konkreter Fallbeispiele beschreibt der vorliegende Artikel anschaulich wie staatliche Behörden und öffentliche Organisationen die heutigen Potenziale der Digitalisierung und integrierter Sensorsysteme zu nutzen versuchen. Unter dem Stichwort „Smart Goverment“ werden neuartige IT-Initiativen lanciert, welche mehr als „E-Government“ auf eine ganzheitliche Vernetzung von physischen, digitalen, öffentlichen und privaten Lebensräumen abzielen. Dabei spielt die aktive und passive Partizipation von Bürgern und anderen Stakeholdern eine wesentliche Rolle. Nur so können die für die algorithmische Entscheidungsfindung notwendigen Daten generiert werden, welche für die personalisierte Interaktion mit Bürgern oder zur real-time Steuerung öffentlicher Infrastrukturen benötigt werden. Der Artikel schließt mit einer kritischen Diskussion über die Möglichkeiten und Grenzen von Smart Government Initiativen und deren Einfluss auf das Privatleben der Bürger und die öffentliche Politikgestaltung

Strategically Constructed Narratives on Artificial Intelligence: What Stories Are Told in Governmental AI Policies?

What stories are told in national artificial intelligence (AI) policies? Combining the novel technique of structural topic modeling (STM) and qualitative narrative analysis, this paper explores and examines the policy narratives in 33 countries’ national AI policies. We uncover six common narratives that are dominating the political agenda concerning AI. Our findings show that the policy narratives’ salience vary across time and countries. The paper makes several contributions. First, our narratives describe well‐grounded, supportable conceptions of AI in governments, so as to contextualize and order a novel, multilayered, and controversial phenomenon. Building on the premise that human sensemaking is best represented and supported by narration, the paper addresses the applied rhetoric of governments to either belittle the risks or exalt the opportunities of AI. Second, we uncover the three prominent roles governments aim to take with regard to AI implementation, these are the role as enabler, leader, or regulator. Third, we make a methodological contribution toward data-driven computationally intensive theory development. Our methodological approach and identified narratives present key starting points for further research

The role of trust in the adoption of cooperative arrangements of e-credential markets

The interest in digital identities has increased considerably in academia and practice in recent years. This can be seen by the many electronic identity projects worldwide and the numerous published studies that provide insightful narratives and descriptive case findings about success factors and barriers to the adoption of national authentication infrastructures. In this paper, we take a closer look to the role of trust on the design and implementation of a nation-wide e-credential market. We argue that trust in political and economic institutions can be an important factor to explain differences in the chosen cooperative arrangement which can range from monopolistic, purely state-controlled e-credential markets, to polypolistic, decentralized e-credential markets where also private vendors offer state recognized e-ID on their own or in partnership with the government. Following an inductive reasoning process, we develop three testable propositions which may inspire further empirical research and offer practitioners a new angle to rethink e-credential markets in the light of citizen trust in political and economic institutions

From SuisseID to SwissID: Overcoming the key challenges in Switzerland\u27s e-credential market

This teaching case explores the political, socio-technical, and business-related challenges of the introduction of a state-recognized electronic identity (e-ID) in Switzerland. Based on real-life events, the case puts every student in the shoes of a board member of SwissSign Group, a joint venture between 20 of the most influential public and private companies in Switzerland. This conglomerate faces three major challenges. To solve these challenges they need, among others, to learn from the past failures of SuisseID, the previous unsuccessful attempt to launch a nationwide e-ID infrastructure. Students must also analyze current political and regulatory events that impact on the e-credential market and need to develop a business model for the new solution, SwissID. This teaching case is designed for students from the undergraduate level upward. The content may be suitable for courses or modules relating to e-government, the platform economy, business models, value co-creation, information ethics, digitalization, PPPs, information security, and privacy

Managerial Challenges and Tasks in Multirational Public Organizations

This paper explores multirationality of public organizations from the perspective of systems theory. In the tradition of this theoretical approach, it focuses on how communication may be used in explaining and understanding the hybridity of these organizations. It argues that faced with a variety of different rationalities of function systems in their environment, public organizations are responding, inter alia, by becoming more complex internally. In other words, they import different rationalities from their environment into their own house. Classifying public organizations as being comprised of highly autonomous subsystems, where each subsystem uses a specific type of specialized communication to process a subsystem specific rationality, this paper sheds light on associated tensions and conflicts within public organizations. It discusses managerial challenges and tasks deriving from multirationality within public organizations. The paper finally concludes that proper communication requires greater theoretical and practical consideration when explaining and dealing with conflicts stemming from the hybridity of public organizations

Same same but different: How policies frame societal-level digital transformation

The digital transformation (DT) is not only forcing companies to rethink their business models but is also challenging governments to address the question of how information technology will change society today and in the future. By setting the legal boundaries and acting as an investor and promoter of the domestic digital economy, governments actively influence in which ways this transformational process takes place. The vision and objectives how DT should be realized on state level is portrayed in well-crafted DT policies. Yet, little is known how governments, as strategic actors, see their role in the DT and how they frame these documents. In this paper, we argue that policymaking about DT is isomorphic in the global context, rather than a differentiator for countries to gain a competitive edge. Using machine learning to analyze a vast text corpus of policy documents, we identify the common repertoire of narratives used by governments from all around the globe to picture their vision of the DT and show that DT policies appear to be almost context-free due to their high similarity