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What is Algorithmic Fairness Measure/Metric

Overcoming Cognitive Biases in Strategic Management and Decision Making
A quantitative indicator to assess whether predictions exhibit algorithmic bias.
Published in Chapter:
Decoding Algorithmic Bias: Definitions, Sources, and Mitigation Strategies
Ozgur Aksoy (Istanbul Universitesi, Turkey)
DOI: 10.4018/979-8-3693-1766-2.ch013
Abstract
Predictive algorithms are increasingly used to assist decision-making for efficiency gains. However, it is essential to acknowledge that algorithms can mirror systemic biases in their predictions in a way that favors certain groups over others, even if they are immune to cognitive biases. The notion of algorithms generating unfair predictions is referred to as “algorithmic bias.” Addressing cognitive biases in humans might not always be an effective solution to mitigate algorithmic bias. Therefore, it is essential to understand when and how quantitative technical mitigation methods can address this issue. This chapter explores the fundamental concepts of algorithmic bias, its sources, and technical mitigation strategies. In a world where humans and AI are intertwined, it is our responsibility to ensure a fair digital future. Addressing algorithmic bias is critical to achieving this goal.
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