Blar i BI Open på forfatter "Tamò-Larrieux, Aurelia"
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The Chilling Effects of Algorithmic Profiling: Mapping the Issues
Büchi, Moritz; Fosch Villaronga, Eduard; Lutz, Christoph; Tamò-Larrieux, Aurelia; Velidi, Shruthi; Viljoen, Salome (Journal article; Peer reviewed, 2019)In this article, we provide an overview of the literature on chilling effects and corporate profiling, while also connecting the two topics. We start by explaining how profiling, in an increasingly data-rich environment, ... -
Gathering Expert Opinions for Social Robots' Ethical, Legal, and Societal Concerns: Findings from Four International Workshops
Fosch Villaronga, Eduard; Lutz, Christoph; Tamò-Larrieux, Aurelia (Journal article; Peer reviewed, 2019)Social robots, those that exhibit personality and communicate with us using high-level dialogue and natural cues, will soon be part of our daily lives. In this paper, we gather expert opinions from different international ... -
Robots and Transparency: The Multiple Dimensions of Transparency in the Context of Robot Technologies
Felzmann, Heike; Fosch Villaronga, Eduard; Lutz, Christoph; Tamò-Larrieux, Aurelia (Journal article; Peer reviewed, 2019)Transparency is often seen as a means to provide accountability and show that something is done with due diligence. This approach to transparency regards it as a remedy to hidden (potentially malevolent) practices. We, ... -
The Robot Privacy Paradox: Understanding How Privacy Concerns Shape Intentions to Use Social Robots
Lutz, Christoph; Tamò-Larrieux, Aurelia (Journal article, 2020)Conceptual research on robots and privacy has increased but we lack empirical evidence about the prevalence, antecedents, and outcomes of different privacy concerns about social robots. To fill this gap, we present a survey, ... -
Transparency You Can Trust: Transparency Requirements for Artificial Intelligence between Legal Norms and Contextual Concerns
Felzmann, Heike; Fosch Villaronga, Eduard; Lutz, Christoph; Tamò-Larrieux, Aurelia (Journal article; Peer reviewed, 2019)Transparency is now a fundamental principle for data processing under the General Data Protection Regulation. We explore what this requirement entails for artificial intelligence and automated decision-making systems. We ...