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  1. The explanation game: a formal framework for interpretable machine learning.David S. Watson & Luciano Floridi - forthcoming - Synthese:1-32.
    We propose a formal framework for interpretable machine learning. Combining elements from statistical learning, causal interventionism, and decision theory, we design an idealised explanation game in which players collaborate to find the best explanation for a given algorithmic prediction. Through an iterative procedure of questions and answers, the players establish a three-dimensional Pareto frontier that describes the optimal trade-offs between explanatory accuracy, simplicity, and relevance. Multiple rounds are played at different levels of abstraction, allowing the players to explore overlapping causal (...)
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  • The Rhetoric and Reality of Anthropomorphism in Artificial Intelligence.David S. Watson - 2019 - Minds and Machines 29 (3):417-440.
    Artificial intelligence has historically been conceptualized in anthropomorphic terms. Some algorithms deploy biomimetic designs in a deliberate attempt to effect a sort of digital isomorphism of the human brain. Others leverage more general learning strategies that happen to coincide with popular theories of cognitive science and social epistemology. In this paper, I challenge the anthropomorphic credentials of the neural network algorithm, whose similarities to human cognition I argue are vastly overstated and narrowly construed. I submit that three alternative supervised learning (...)
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  • Citizen Science and Scientific Objectivity: Mapping Out Epistemic Risks and Benefits.Baptiste Bedessem & Stéphanie Ruphy - 2020 - Perspectives on Science 28 (5):630-654.
    Given the importance of the issue of scientific objectivity in our democratic societies and the significant development of citizen science, it is crucial to investigate how citizen science may either undermine or foster scientific objectivity. This paper identifies a variety of epistemic risks and benefits that participation of lay citizens in scientific inquiries may bring. It also discusses concrete actions and pending issues that should be addressed in order to foster objectivity in citizen science programs.
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  • Citizen Science and Post-Normal Science in a Post-Truth Era: Democratising Knowledge; Socialising Responsibility.Michael A. Peters & Tina Besley - 2019 - Educational Philosophy and Theory 51 (13):1293-1303.
    Volume 51, Issue 13, December 2019, Page 1293-1303.
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