• Algorithmic management in a work context 

      Jarrahi, Mohammad Hossein; Newlands, Gemma Elisabeth Marjorie; Lee, Min Kyung; Wolf, Christine; Kinder, Eliscia; Sutherland, Will (Journal article; Peer reviewed, 2021)
      The rapid development of machine-learning algorithms, which underpin contemporary artificial intelligence systems, has created new opportunities for the automation of work processes and management functions. While algorithmic ...
    • Artificial Intelligence, Human Intelligence and Hybrid Intelligence Based on Mutual Augmentation 

      Jarrahi, Mohammad Hossein; Lutz, Christoph; Newlands, Gemma Elisabeth Marjorie (Peer reviewed; Journal article, 2022)
      There is little consensus on what artificial intelligence (AI) systems may or may not embrace. While this may point to multiplicity of interpretations and backgrounds, a lack of conceptual clarity could thwart development ...
    • 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 ...
    • Lifting the curtain: Strategic visibility of human labour in AI-as-a-Service 

      Newlands, Gemma Elisabeth Marjorie (Peer reviewed; Journal article, 2021)
      Artificial Intelligence-as-a-Service (AIaaS) empowers individuals and organisations to access AI on-demand, in either tailored or ‘off-the-shelf’ forms. However, institutional separation between development, training and ...
    • 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 ...