Digitale Infrastrukturen in der Demokratie

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    Handling the hype: Implications of AI hype for public interest tech projects
    (2023) Züger, Theresa; Kuper, Freia; Fassbender, Judith; Katzy-Reinshagen, Anna; Kühnlein, Irina
    Based on theories of expectations of technology and empirical data from expert interviews and case studies, this research article explores how actors in the field of public interest technologies relate to and within the dynamics of AI hype. On an affirmative note, practitioners and experts see the potential that AI hype can serve their own purposes, e.g., through improved funding and support structures. At the same time, public interest tech actors distance themselves from the dynamics of AI hype and criticize it explicitly. Finally, the article discusses how engagement with AI hype and its impact affects society as a whole and, more specifically, society’s ability to develop and use technologies in response to societal problems.
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    In Palantir we trust? Regulation of data analysis platforms in public security
    (2024) Ulbricht, Lena; Egbert, Simon
    Organizations increasingly rely on digital technologies to perform tasks. To do so, they have to integrate data banks to make the data usable. We argue that there is a growing, academically underexplored market consisting of data integration and analysis platforms. We explain that, especially in the public sector, the regulatory implications of data integration and analysis must be studied because they affect vulnerable citizens and because it is not just a matter of state agencies overseeing technology companies but also of the state overseeing itself. We propose a platform-theory-based conceptual approach that directs our attention towards the specific characteristics of platforms—such as datafication, modularity, and multilaterality and the associated regulatory challenges. Due to a scarcity of empirical analyses about how public sector platforms are regulated, we undertake an in-depth case study of a data integration and analysis platform operated by Palantir Technologies in the German federal state of Hesse. Our analysis of the regulatory activities and conflicts uncovers many obstacles to effective platform regulation. Drawing on recent initiatives to improve intermediary liability, we ultimately point to additional paths for regulating public sector platforms. Our findings also highlight the importance of political factors in platform regulation-as-a-practice. We conclude that platform regulation in the public sector is not only about technology-specific regulation but also about general mechanisms of democratic control, such as the separation of power, public transparency, and civil rights.
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    Website blocking in the European Union: Network interference from the perspective of Open Internet
    (2024) Ververis, Vasilis; Lasota, Lucas; Ermakova, Tatiana; Fabian, Benjamin
    By establishing an infrastructure for monitoring and blocking networks in accordance with European Union (EU) law on preventive measures against the spread of information, EU member states have also made it easier to block websites and services and monitor information. While relevant studies have documented Internet censorship in non‐European countries, as well as the use of such infrastructures for political reasons, this study examines network interference practices such as website blocking against the backdrop of an almost complete lack of EU‐related research. Specifically, it performs and demonstrates an analysis for the total of 27 EU countries based on three different sources. They include first, tens of millions of historical network measurements collected in 2020 by Open Observatory of Network Interference volunteers from around the world; second, the publicly available blocking lists used by EU member states; and third, the reports issued by network regulators in each country from May 2020 to April 2021. Our results show that authorities issue multiple types of blocklists. Internet Service Providers limit access to different types and categories of websites and services. Such resources are sometimes blocked for unknown reasons and not included in any of the publicly available blocklists. The study concludes with the hurdles related to network measurements and the nontransparency from regulators regarding specifying website addresses in blocking activities.
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    Process model forecasting and change exploration using time series analysis of event sequence data
    (2023) De Smedt, Johannes; Yeshchenko, Anton; Polyvyanyy, Artem; De Weerdt, Jochen; Mendling, Jan
    Process analytics is a collection of data-driven techniques for, among others, making predictions for individual process instances or overall process models. At the instance level, various novel techniques have been recently devised, tackling analytical tasks such as next activity, remaining time, or outcome prediction. However, there is a notable void regarding predictions at the process model level. It is the ambition of this article to fill this gap. More specifically, we develop a technique to forecast the entire process model from historical event data. A forecasted model is a will-be process model representing a probable description of the overall process for a given period in the future. Such a forecast helps, for instance, to anticipate and prepare for the consequences of upcoming process drifts and emerging bottlenecks. Our technique builds on a representation of event data as multiple time series, each capturing the evolution of a behavioural aspect of the process model, such that corresponding time series forecasting techniques can be applied. Our implementation demonstrates the feasibility of process model forecasting using real-world event data. A user study using our Process Change Exploration tool confirms the usefulness and ease of use of the produced process model forecasts.
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    Performance of the flood warning system in Germany in July 2021 – insights from affected residents
    (2023) Thieken, Annegret H.; Bubeck, Philip; Heidenreich, Anna; Von Keyserlingk, Jennifer; Dillenardt, Lisa; Otto, Antje
    Abstract. In July 2021 intense rainfall caused devastating floods in western Europe and 184 fatalities in the German federal states of North Rhine-Westphalia (NW) and Rhineland-Palatinate (RP), calling into question their flood forecasting, warning and response system (FFWRS). Data from an online survey (n=1315) reveal that 35 % of the respondents from NW and 29 % from RP did not receive any warning. Of those who were warned, 85 % did not expect very severe flooding and 46 % reported a lack of situational knowledge on protective behaviour. Regression analysis reveals that this knowledge is influenced not only by gender and flood experience but also by the content and the source of the warning message. The results are complemented by analyses of media reports and official warnings that show shortcomings in providing adequate recommendations to people at risk. Still, the share of people who did not report any emergency response is low and comparable to other flood events. However, the perceived effectiveness of the protective behaviour was low and mainly compromised by high water levels and the perceived level of surprise about the flood magnitude. Good situational knowledge and a higher number of previously experienced floods were linked to performing more effective loss-reducing action. Dissemination of warnings, clearer communication of the expected flood magnitude and recommendations on adequate responses to a severe flood, particularly with regard to flash and pluvial floods, are seen as major entry points for improving the FFWRS in Germany.