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 ...

    • Innovation under Pressure: Implications for Data Privacy during the Covid-19 Pandemic 

      Newlands, Gemma Elisabeth Marjorie; Lutz, Christoph; Tamò-Larrieux, Aurelia; Fosch Villaronga, Eduard; Harasgama, Rehana; Scheitlin, Gil (Journal article; Peer reviewed, 2020)
      The global Covid-19 pandemic has resulted in social and economic disruption unprecedented in the modern era. Many countries have introduced severe measures to contain the virus, including travel restrictions, public event ...

    • Making sense of algorithmic profiling: User perceptions on Facebook 

      Büchi, Moritz; Fosch-Villaronga, Eduard; Lutz, Christoph; Tamò-Larrieux, Aurelia; Velidi, Shruthi (Journal article; Peer reviewed, 2021)
      Algorithmic profiling has become increasingly prevalent in many social fields and practices, including finance, marketing, law, cultural consumption and production, and social engagement. Although researchers have begun ...

    • Overtrusting robots: Setting a research agenda to mitigate overtrust in automation 

      Sætra, Henrik Skaug; Aroyo, Alexander M.; Bruyne, Jan de; Dheu, Orian; Fosch-Villaronga, Eduard; Gudkov, Aleksei; Hoch, Holly; Lutz, Christoph; Solberg, Mads; Tamò-Larrieux, Aurelia (Journal article; Peer reviewed, 2021)
      There is increasing attention given to the concept of trustworthiness for artificial intelligence and robotics. However, trust is highly context-dependent, varies among cultures, and requires reflection on others’ ...

    • Overtrusting Robots: Setting a Research Agenda to Mitigate Overtrust in Automation 

      Aroyo, Alexander; De Bruyne, Jan; Dheu, Orian; Fosch-Villaronga, Eduard; Gudkov, Aleksei; Hoch, Holly; Jones, Steve; Lutz, Christoph; Sætra, Henrik Skaug; Solberg, Mads; Tamò-Larrieux, Aurelia (Journal article; Peer reviewed, 2021)
      There is increasing attention given to the concept of trustworthiness for artificial intelligence and robotics. However, trust is highly context-dependent, varies among cultures, and requires reflection on others’ ...

    • 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, ...

    • Towards Transparency by Design for Artificial Intelligence 

      Felzmann, Heike; Fosch Villaronga, Eduard; Lutz, Christoph; Tamò-Larrieux, Aurelia (Journal article; Peer reviewed, 2020)
      In this article, we develop the concept of Transparency by Design that serves as practical guidance in helping promote the beneficial functions of transparency while mitigating its challenges in automated-decision making ...

    • 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 ...