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ThinkMind // CENTRIC 2020, The Thirteenth International Conference on Advances in Human-oriented and Personalized Mechanisms, Technologies, and Services // View article centric_2020_1_10_30004


Bias – A Lurking Danger that Can Convert Algorithmic Systems into Discriminatory Entities

Authors:
Thea Gasser
Eduard Klein
Lasse Seppänen

Keywords: Bias; Algorithm; Artificial intelligence; AI-safety; Algorithmic system.

Abstract:
Bias in algorithmic systems is a major cause of unfair and discriminatory decisions in the use of such systems. Cognitive bias is very likely to be reflected in algorithmic systems as humankind aims to map Human Intelligence (HI) to Artificial Intelligence (AI). An extensive literature review on the identification and mitigation of bias leads to precise measures for project teams building AI-systems. Aspects like AI-responsibility, AI-fairness and AI-safety are addressed by developing a framework that can be used as a guideline for project teams. It proposes measures in the form of checklists to identify and mitigate bias in algorithmic systems considering all steps during system design, implementation and application.

Pages: 1 to 7

Copyright: Copyright (c) IARIA, 2020

Publication date: October 18, 2020

Published in: conference

ISSN: 2308-3492

ISBN: 978-1-61208-829-7

Location: Porto, Portugal

Dates: from October 18, 2020 to October 22, 2020

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