Gamified Text Testing for Sustainable Fairness

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Date

2023

Authors

Takan, Savas
Ergun, Duygu
Katipoglu, Goekmen

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Mdpi

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Abstract

AI fairness is an essential topic as regards its topical and social-societal implications. However, there are many challenges posed by automating AI fairness. Based on the challenges around automating fairness in texts, our study aims to create a new fairness testing paradigm that can gather disparate proposals on fairness on a single platform, test them, and develop the most effective method, thereby contributing to the general orientation on fairness. To ensure and sustain mass participation in solving the fairness problem, gamification elements are used to mobilize individuals' motivation. In this framework, gamification in the design allows participants to see their progress and compare it with other players. It uses extrinsic motivation elements, i.e., rewarding participants by publicizing their achievements to the masses. The validity of the design is demonstrated through the example scenario. Our design represents a platform for the development of practices on fairness and can be instrumental in making contributions to this issue sustainable. We plan to further realize a plot application of this structure designed with the gamification method in future studies.

Description

takan, savas/0000-0002-7718-9476; Ergun, Duygu/0000-0002-5639-8615

Keywords

artificial intelligence fairness, gamification, testing, fair-test, zero-suppression decision diagram, centrality, confusion matrix, mutation test

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1

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15

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3

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