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  1. Towards Transparency by Design for Artificial Intelligence.Heike Felzmann, Eduard Fosch-Villaronga, Christoph Lutz & Aurelia Tamò-Larrieux - 2020 - Science and Engineering Ethics 26 (6):3333-3361.
    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 environments. With the rise of artificial intelligence and the ability of AI systems to make automated and self-learned decisions, a call for transparency of how such systems reach decisions has echoed within academic and policy circles. The term transparency, however, relates to multiple concepts, fulfills many functions, and holds different (...)
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  • The Ethnographer and the Algorithm: Beyond the Black Box.Angèle Christin - 2020 - Theory and Society 49 (5-6):897-918.
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  • Mass Personalization: Predictive Marketing Algorithms and the Reshaping of Consumer Knowledge.Baptiste Kotras - 2020 - Big Data and Society 7 (2).
    This paper focuses on the conception and use of machine-learning algorithms for marketing. In the last years, specialized service providers as well as in-house data scientists have been increasingly using machine learning to predict consumer behavior for large companies. Predictive marketing thus revives the old dream of one-to-one, perfectly adjusted selling techniques, now at an unprecedented scale. How do predictive marketing devices change the way corporations know and model their customers? Drawing from STS and the sociology of quantification, I propose (...)
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