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  1.  35
    Automated informed consent.Adam Andreotta & Bjorn Lundgren - 2024 - Big Data and Society 11 (4).
    Online privacy policies or terms and conditions ideally provide users with information about how their personal data are being used. The reality is that very few users read them: they are long, often hard to understand, and ubiquitous. The average internet user cannot realistically read and understand all aspects that apply to them and thus give informed consent to the companies who use their personal data. In this article, we provide a basic overview of a solution to the problem. We (...)
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  2. A feeling for the algorithm: Diversity, expertise and artificial intelligence.Catherine Stinson & Sofie Vlaad - 2024 - Big Data and Society 11 (1).
    Diversity is often announced as a solution to ethical problems in artificial intelligence (AI), but what exactly is meant by diversity and how it can solve those problems is seldom spelled out. This lack of clarity is one hurdle to motivating diversity in AI. Another hurdle is that while the most common perceptions about what diversity is are too weak to do the work set out for them, stronger notions of diversity are often defended on normative grounds that fail to (...)
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  3. Algorithmic decision-making: the right to explanation and the significance of stakes.Lauritz Munch, Jens Christian Bjerring & Jakob Mainz - 2024 - Big Data and Society.
    The stakes associated with an algorithmic decision are often said to play a role in determining whether the decision engenders a right to an explanation. More specifically, “high stakes” decisions are often said to engender such a right to explanation whereas “low stakes” or “non-high” stakes decisions do not. While the overall gist of these ideas is clear enough, the details are lacking. In this paper, we aim to provide these details through a detailed investigation of what we will call (...)
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