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  1. Artificial intelligence vs COVID-19: limitations, constraints and pitfalls.Wim Naudé - 2020 - AI and Society 35 (3):761-765.
    This paper provides an early evaluation of Artificial Intelligence against COVID-19. The main areas where AI can contribute to the fight against COVID-19 are discussed. It is concluded that AI has not yet been impactful against COVID-19. Its use is hampered by a lack of data, and by too much data. Overcoming these constraints will require a careful balance between data privacy and public health, and rigorous human-AI interaction. It is unlikely that these will be addressed in time to be (...)
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  • From judgment to calculation.Mike Cooley - 2007 - AI and Society 21 (4):395-409.
    We only regard a system or a process as being “scientific” if it displays the three predominant characteristics of the natural sciences: predictability, repeatability and quantifiability. This by definition precludes intuition, subjective judgement, tacit knowledge, heuristics, dreams, etc. in other words, those attributes which are peculiarly human. Furthermore, this is resulting in a shift from judgment to calculation giving rise, in some cases, to an abject dependency on the machine and an inability to disagree with the outcome or even question (...)
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