2020
DOI: 10.1007/s00146-020-01024-9
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The epistemic opacity of autonomous systems and the ethical consequences

Abstract: This paper takes stock of all the various factors that cause the design-time opacity of autonomous systems behaviour. The factors include embodiment effects, design-time knowledge gap, human factors, emergent behaviour and tacit knowledge. This situation is contrasted with the usual representation of moral dilemmas that assume perfect information. Since perfect information is not achievable, the traditional moral dilemma representations are not valid and the whole problem of ethical autonomous systems design p… Show more

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Cited by 6 publications
(4 citation statements)
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“…In fact, it is our professional responsibility to not miss them. Practically, this means that research teams conducting work on AI in science education need members with a deep technical knowledge base that allows for epistemic transparency (Héder, 2020) of algorithms and what they are doing. A key part of this knowledge is the ability to translate between the mathematical representations of the world in the models and algorithms used and the substantive understanding of the world.…”
Section: Discussionmentioning
confidence: 99%
“…In fact, it is our professional responsibility to not miss them. Practically, this means that research teams conducting work on AI in science education need members with a deep technical knowledge base that allows for epistemic transparency (Héder, 2020) of algorithms and what they are doing. A key part of this knowledge is the ability to translate between the mathematical representations of the world in the models and algorithms used and the substantive understanding of the world.…”
Section: Discussionmentioning
confidence: 99%
“…Yet, in order for such data to be useful, it needs to be established that the measurements are relevant to the actual design decisions. This is yet to be done (Dewitt et al 2019;Jaques 2020;Héder 2020). Even if they were, the separate ethical question is whether it is the right thing to implement the most popular expectations.…”
Section: The Specificity Of the Concerns In Aigusmentioning
confidence: 99%
“…Their number may not grow in absolute terms, but in relative terms by gradually shaping a new working class that can be labeled 'blue collar with tie. ' While machines initially served only a passive, i.e., physical and cognitive supporting, function in technical work environments, nowadays machines predict (Gill 2020), recommend (Milano et al 2020), create artistically (Elgammal et al 2017), and even decide autonomously (Héder 2020) 1 throughout crucial instances of value creation processes. Machines are more and more seamlessly coupled to each other and even learn automatically without human intervention.…”
Section: Introductionmentioning
confidence: 99%