Auflistung nach Schlagwort "Transparency"
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- KonferenzbeitragBalancing Privacy and Value Creation in the Platform Economy: The Role of Transparency and Intervenability(Open Identity Summit 2023, 2023) Astfalk, Stefanie; Schunck, Christian H.Data are essential in the platform economy to create value. Since the General Data Protection Regulation (GDPR) demands a high level of protection for personal data, it becomes challenging for small- and medium-sized businesses to provide both: data-based services and compliance to the GDPR. Therefore, the paper focuses on the privacy protection goals of transparency and intervenability to enable privacy friendly business models. To better understand how this approach supports the needs of small- and medium-sized platform providers, a qualitative interview study is conducted. Especially, the lack of legal certainty and the unclarity of how the GDPR can be implemented compliantly in practical terms is found to be a challenge. Based on the interviews, requirements are derived which a personal rights management tool enabling transparency and intervenability should fulfill such as supporting legal compliance or reducing operational complexity. In summary, small- and medium-sized platform providers see providing transparency and intervenability as a promising new approach which they are willing to deploy given the right personal rights management tool.
- KonferenzbeitragMy Data is Mine - Users' Handling of Personal Data in Everyday Life(SICHERHEIT 2018, 2018) Bock, SvenAbstract: This experimental study is about investigating users’ handling of personal data and their awareness of data collection. A deception experiment was designed to let the subjects believe that they are participating in a decision-making experiment. Only after the experiment, they were informed about the actual aim of examining their behaviour towards their personal data. Before the deception experiment either a printed or a digital version of the terms and conditions was handed out. The reading time and the willingness to accept the terms and conditions was measured in order to find significant differences. For the deception, a program was implemented which simultaneously presents two terms including sensitive data like religious and political orientation. The subject should choose the favoured term. Afterwards, subjects were asked whether and to what extent they agree to hand out their collected data to third parties in exchange for financial gain. After the experiment the participants were asked about their usual behaviour regarding their personal data.
- ZeitschriftenartikelOpen Data gewinnbringend einsetzen – Grundlagen und Hintergründe(HMD Praxis der Wirtschaftsinformatik: Vol. 58, No. 2, 2021) Binzen, MichaelOffenheit und eine neue Fehlerkultur machen bei der Verwendung von Daten im Rahmen der Digitalisierung weitreichende Kooperationen möglich, die in Deutschland noch selten praktiziert werden. Der Artikel erklärt die Grundlagen und Ursprünge, die dazu führen, dass die Offenlegung von Daten einen Wettbewerbsvorteil bringt. Gleichzeitig wird herausgearbeitet, welche Herausforderungen daraus entstehen und welche Voraussetzungen eine Organisation schaffen muss, damit eine solche Öffnung wirklich erfolgreich wird. Openness and a new error culture make far-reaching collaborations possible when using data in the context of digitization, which are still rarely practiced in Germany. The article explains the fundamentals and origins that lead to the disclosure of data providing a competitive advantage. At the same time, it elaborates which challenges arise from this and which prerequisites an organization must create in order for such an opening to be truly successful
- ZeitschriftenartikelSoftwaretransparenz(Wirtschaftsinformatik: Vol. 52, No. 3, 2010) Leite, Julio Cesar Sampaio do Prado; Cappelli, ClaudiaSoftwaretransparenz stellt eine neuartige und bedeutende Anforderung dar, mit der sich Softwareentwickler auseinandersetzen müssen. Der Beitrag liefert erste Untersuchungsergebnisse zur Problematik der Softwaretransparenz. Zur Definition des Transparenzbegriffs und zur Erfassung der Semantik von Softwaretransparenz wird ein SIG (Softgoal Interdependence Graph) genutzt, der in drei Versionen weiterentwickelt wurde. Anhand von drei Beispielsituationen wird die Anwendung des Transparenz-SIG demonstriert.AbstractSoftware transparency is a new and important concern that software developers must deal with. As society moves towards increased automation, if citizens wish to exercise their right to know, the transparency of public services and processes acquires fundamental importance. Informed discourse is only possible if processes affecting the public are open to evaluation. Achieving software transparency to this level of openness faces several roadblocks. The paper reports on initial findings on exploring the obstacles for enabling software transparency.
- TextdokumentTowards a transparency-oriented and integrating Service Registry for the Smart Living Ecosystem(INFORMATIK 2021, 2021) Rebstadt, Jonas; Kortum, Henrik; Hagen, Simon; Thomas, OliverMany domains are increasingly dominated by interdependent services and data exchange between different actors, leading to the emergence of data ecosystems. As a result, service engineers are increasingly tasked with integrating existing service components and data sources into service systems and orchestrating them. In complex areas such as smart living, these tasks are even more difficult by the particular relevance of individual data protection requirements and the low fault tolerance of security-related systems. To address these issues, a central service registry for the domain smart living has been prototypically developed and evaluated, focusing especially on the transparency of data flows and the technical exchangeability of service components. In this way, added value is achieved for data providers and for data users by providing information on the forwarding of their own data as well as on the origin of the data and possible data quality.
- KonferenzbeitragTowards a User-Empowering Architecture for Trustability Analytics(BTW 2023, 2023) Bruchhaus, Sebastian; Reis, Thoralf; Bornschlegl, Marco Xaver; Störl, Uta; Hemmje, MatthiasMachine learning (ML) thrives on big data like huge data sets and streams from IOT devices. Those technologies are becoming increasingly commonplace in our day to day existence. Learning autonomous intelligent actors (AIAs) impact our lives already in the form of, e.g. chat bots, medical expert systems, and facial recognition systems. Doubts concerning ethical, legal, and social implications of such AIAs become increasingly compelling in consequence. Our society now finds itself confronted with decisive questions: Should we trust AI? Is it fair, transparent, and respecting privacy? An individual psychological threshold for cooperation with AIAs has been postulated. In Shaefer’s words: “No trust, no use”. On the other hand, ignorance of an AIA’s weak points and idiosyncrasies can lead to overreliance. This paper proposes a prototypical microservice architecture for trustability analytics. Its architecture shall introduce self-awareness concerning trustability into the AI2VIS4BigData reference model for big data analysis and visualization by borrowing the concept of a “looking-glass self” from psychology.
- KonferenzbeitragTurning the Table Around: Monitoring App Behavior(SICHERHEIT 2018, 2018) Momen, NurulSince Android apps receive whitecard access through permissions, users struggle to understand the actual magnitude of app access to their personal data. Due to unavailability of statistical or other tools that would provide an overview of data access or privilege use, users can hardly assess privacy risks or identify app misbehavior. This is a problem for data subjects. The presented PhD research project aims at creating a transparency-enhancing technology that helps users to assess the magnitude of data access of installed apps by monitoring the Android permission access control system. This article will present how apps exercise their permissions, based on a pilot study with an app monitoring tool. It then presents a prototypical implementation of a networked laboratory for crowdsourcing app behavior data. Finally, the article presents and discusses a model that will use the collected data to calculate and visualize risk signals based on individual risk preferences and measured app data access efforts.