IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i3p2292-d1047534.html
   My bibliography  Save this article

Gamified Text Testing for Sustainable Fairness

Author

Listed:
  • Savaş Takan

    (Department of Artificial Intelligence and Data Engineering, Faculty of Engineering, Ankara University, 06830 Ankara, Turkey
    These authors contributed equally to this work.)

  • Duygu Ergün

    (School of Fine Arts Design and Architecture, Atılım University, 06830 Ankara, Turkey
    These authors contributed equally to this work.)

  • Gökmen Katipoğlu

    (Department of Computer Engineering, Faculty of Engineering, Kafkas University, 36100 Kars, Turkey)

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.

Suggested Citation

  • Savaş Takan & Duygu Ergün & Gökmen Katipoğlu, 2023. "Gamified Text Testing for Sustainable Fairness," Sustainability, MDPI, vol. 15(3), pages 1-14, January.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:3:p:2292-:d:1047534
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/3/2292/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/3/2292/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Lily Hu & Yiling Chen, 2017. "A Short-term Intervention for Long-term Fairness in the Labor Market," Papers 1712.00064, arXiv.org, revised Feb 2018.
    2. Kavisha Duggal & Lovi Raj Gupta & Parminder Singh, 2021. "Gamification and Machine Learning Inspired Approach for Classroom Engagement and Learning," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-18, May.
    3. Rocsana Bucea-Manea-Țoniş & Valentin Kuleto & Simona Corina Dobre Gudei & Costin Lianu & Cosmin Lianu & Milena P. Ilić & Dan Păun, 2022. "Artificial Intelligence Potential in Higher Education Institutions Enhanced Learning Environment in Romania and Serbia," Sustainability, MDPI, vol. 14(10), pages 1-18, May.
    4. James Jennings, 2004. "Urban Planning, Community Participation, and the Roxbury Master Plan in Boston," The ANNALS of the American Academy of Political and Social Science, , vol. 594(1), pages 12-33, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Asif Ali Wagan & Abdullah Ayub Khan & Yen-Lin Chen & Por Lip Yee & Jing Yang & Asif Ali Laghari, 2023. "Artificial Intelligence-Enabled Game-Based Learning and Quality of Experience: A Novel and Secure Framework (B-AIQoE)," Sustainability, MDPI, vol. 15(6), pages 1-12, March.
    2. Lydia T. Liu & Ashia Wilson & Nika Haghtalab & Adam Tauman Kalai & Christian Borgs & Jennifer Chayes, 2019. "The Disparate Equilibria of Algorithmic Decision Making when Individuals Invest Rationally," Papers 1910.04123, arXiv.org.
    3. Sampath Kannan & Mingzi Niu & Aaron Roth & Rakesh Vohra, 2021. "Best vs. All: Equity and Accuracy of Standardized Test Score Reporting," Papers 2102.07809, arXiv.org.
    4. Soheil Ghili & Ehsan Kazemi & Amin Karbasi, 2019. "Eliminating Latent Discrimination: Train Then Mask," Cowles Foundation Discussion Papers 2157, Cowles Foundation for Research in Economics, Yale University.
    5. Akter, Shahriar & Dwivedi, Yogesh K. & Sajib, Shahriar & Biswas, Kumar & Bandara, Ruwan J. & Michael, Katina, 2022. "Algorithmic bias in machine learning-based marketing models," Journal of Business Research, Elsevier, vol. 144(C), pages 201-216.
    6. Christopher Jung & Sampath Kannan & Changhwa Lee & Mallesh M. Pai & Aaron Roth & Rakesh Vohra, 2020. "Fair Prediction with Endogenous Behavior," Papers 2002.07147, arXiv.org.
    7. Xiaoli Zhao & Yu Ren & Kenny S. L. Cheah, 2023. "Leading Virtual Reality (VR) and Augmented Reality (AR) in Education: Bibliometric and Content Analysis From the Web of Science (2018–2022)," SAGE Open, , vol. 13(3), pages 21582440231, August.
    8. Elizabeth Gearin & Carletta S. Hurt, 2024. "Making Space: A New Way for Community Engagement in the Urban Planning Process," Sustainability, MDPI, vol. 16(5), pages 1-18, February.
    9. In-Seong Jeon & Shin-Yu Kim & Seong-Joo Kang, 2024. "Developing Standards for Educational Datasets by School Level: A Framework for Sustainable K-12 Education," Sustainability, MDPI, vol. 16(12), pages 1-17, June.
    10. Lily Morse & Mike Horia M. Teodorescu & Yazeed Awwad & Gerald C. Kane, 2022. "Do the Ends Justify the Means? Variation in the Distributive and Procedural Fairness of Machine Learning Algorithms," Journal of Business Ethics, Springer, vol. 181(4), pages 1083-1095, December.
    11. Nikola Milicevic & Branimir Kalas & Nenad Djokic & Borka Malcic & Ines Djokic, 2024. "Students’ Intention toward Artificial Intelligence in the Context of Digital Transformation," Sustainability, MDPI, vol. 16(9), pages 1-15, April.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:15:y:2023:i:3:p:2292-:d:1047534. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.