Lisa Maria Herzog
University of Groningen
In more and more contexts, human decision-making is replaced by algorithmic decision-making. While promising to deliver efficient and objective decisions, algorithmic decision systems have specific weaknesses, some of which are particularly dangerous if data are collected and processed by profit-oriented companies. In this paper, I focus on two problems that are at the root of the logic of algorithmic decision-making: tolerance for ambiguity, and instantiations of Campbell’s law, i. e. of indicators that are used for “social decision-making” being subject to “corruption pressures” and tending to “distort and corrupt” the underlying social processes. As a result, algorithmic decision-making can risk missing the point of the social practice in question. These problems are intertwined with problems of structural injustice; hence, if algorithms are to deliver on their promises of efficiency and objectivity, accountability and critical scrutiny are needed.
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DOI 10.1515/dzph-2021-0016
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References found in this work BETA

Thinking, Fast and Slow.Daniel Kahneman - 2011 - New York: Farrar, Straus & Giroux.
Responsibility for Justice.Iris Marion Young - 2011 - Oxford University Press USA.
Collective Intentionality.David P. Schweikard & Hans Bernhard Schmid - 2012 - Stanford Encyclopedia of Philosophy.

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