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When something goes wrong: Who is responsible for errors in ML decision-making?
(Springer, 2023)
Because of its practical advantages, machine learning (ML) is increasingly used for decision-making in numerous sectors. This paper demonstrates that the integral characteristics of ML, such as semi-autonomy, complexity, ...
Friend or Foe? Rethinking Epistemic Trespassing
(London: Taylor & Francis, 12-12-2023)
In this paper, we reconsider the notion of epistemic trespassing and attempt to explore possible scenarios in which it could lead to positive outcomes in scientific research and information dissemination. As we will point ...