Accountability of Algorithmic Systems: How We Can Control What We Can’t Exactly Measure

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Accountability of Algorithmic Systems: How We Can Control What We Can’t Exactly Measure

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Posted March 11, 2019 in Business Technology & Digital Transformation Strategies, Data Analytics & Digital Technologies Cutter Business Technology Journal


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Yiannis Kanellopoulos addresses a key issue that we need to satisfactorily tackle: the accountability of algorithmic systems. Automated decision making can go seriously wrong, and hence, evaluating an algorithmic system and the organization that utilizes it in terms of their accountability and transparency assumes ever greater importance.