A Mulching Proposal

TL;DR

This paper applies the Fairness, Accountability, and Transparency (FAT) ethical framework to improve an algorithm addressing societal issues like food security and aging, demonstrating enhanced ethical compliance through standardized audits.

Contribution

It introduces a method for applying the FAT framework to real-world algorithms, showing how ethical adherence can be significantly improved with systematic evaluation.

Findings

Increased adherence to the FAT framework after evaluation.

Enhanced ethical and beneficent qualities of the algorithm.

Provides a practical guide for ethical algorithm development.

Abstract

he ethical implications of algorithmic systems have been much discussed in both HCI and the broader community of those interested in technology design, development and policy. In this paper, we explore the application of one prominent ethical framework - Fairness, Accountability, and Transparency - to a proposed algorithm that resolves various societal issues around food security and population ageing. Using various standardised forms of algorithmic audit and evaluation, we drastically increase the algorithm's adherence to the FAT framework, resulting in a more ethical and beneficent system. We discuss how this might serve as a guide to other researchers or practitioners looking to ensure better ethical outcomes from algorithmic systems in their line of work.