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

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

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.

About The Author
Yiannis Kanellopoulos
Yiannis Kanellopoulos has spent the better part of two decades analyzing and evaluating software systems to help organizations address any potential risks and flaws, which he believes is always due to human involvement. He is the founder of Code4Thought, which aims to democratize technology by rendering algorithms transparent and helping organizations become accountable. Dr. Kanellopoulos earned a PhD in data mining from the University of… Read More
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