Quantitative Fairness -- A Framework For The Design Of Equitable Cybernetic Societies

TL;DR

This paper introduces a quantitative fairness framework for designing equitable cybernetic societies, emphasizing fairness and transparency in algorithmic decision-making to promote social cohesion and reduce inequities.

Contribution

It proposes a novel, systematic, and ideology-agnostic fairness framework addressing limitations of existing measures for equitable algorithm design in cybernetic systems.

Findings

Introduces a new quantitative fairness framework for cybernetic societies.

Highlights the importance of fairness and transparency in algorithmic design.

Addresses limitations of existing fairness measures in literature.

Abstract

Advancements in computer science, artificial intelligence, and control systems of the recent have catalyzed the emergence of cybernetic societies, where algorithms play a significant role in decision-making processes affecting the daily life of humans in almost every aspect. Algorithmic decision-making expands into almost every industry, government processes critical infrastructure, and shapes the life-reality of people and the very fabric of social interactions and communication. Besides the great potentials to improve efficiency and reduce corruption, missspecified cybernetic systems harbor the threat to create societal inequities, systematic discrimination, and dystopic, totalitarian societies. Fairness is a crucial component in the design of cybernetic systems, to promote cooperation between selfish individuals, to achieve better outcomes at the system level, to confront public resistance, to gain trust and acceptance for rules and institutions, to perforate self-reinforcing cycles of poverty through social mobility, to incentivize motivation, contribution and satisfaction of people through inclusion, to increase social-cohesion in groups, and ultimately to improve life quality. Quantitative descriptions of fairness are crucial to reflect equity into algorithms, but only few works in the fairness literature offer such measures; the existing quantitative measures in the literature are either too application-specific, suffer from undesirable characteristics, or are not ideology-agnostic. Therefore, this work proposes a quantitative, transactional, distributive fairness framework, which enables systematic design of socially feasible decision-making systems. Moreover, it emphasizes the importance of fairness and transparency when designing algorithms for equitable, cybernetic societies.