The Myth of Complete AI-Fairness

TL;DR

This paper argues that complete fairness in AI is unattainable due to inherent ethical and practical limitations, emphasizing the importance of establishing fairness metrics and thresholds to foster trust in AI systems.

Contribution

It challenges the pursuit of perfect fairness in AI, advocating for pragmatic fairness metrics and thresholds to build trust rather than absolute fairness.

Findings

Complete fairness in AI is impossible.

Metrics and thresholds are essential for trustworthy AI.

Focus on practical fairness over idealized notions.

Abstract

The idea of fairness and justice has long and deep roots in Western civilization, and is strongly linked to ethics. It is therefore not strange that it is core to the current discussion about the ethics of development and use of AI systems. In this short paper, I wish to further motivate my position in this matter: ``I will never be completely fair. Nothing ever is. The point is not complete fairness, but the need to establish metrics and thresholds for fairness that ensure trust in AI systems".