Ethics and Transparency in Game Data

Erica Kleinmann, Magy Seif El-Nasr, Johannes Pfau, Simone Kriglstein, Günter Wallner, David Melhart, Georgios N. Yannakakis, Jichen Zhu, Benjamin Watson, Casper Harteveld

    Research output: Chapter in Book or Conference ProceedingsConference Proceedings with Oral Presentationpeer-review

    Abstract

    While existing work has discussed ethics and fairness in relation to data generally, and a small number of papers have raised the same issues within games specifically, work on addressing fairness and ethical issues with game data collection and usage is still rare. With game AI, LLM integration, data analytics, and machine learning on the rise, a new dimension to the responsible and ethical treatment of data opens up, comprising factors unique to video games. Our goal for this workshop is, thus, to bring together researchers and professionals working in the spaces of game human–computer interaction (HCI), game data and AI, and ethics in both games and AI to discuss and identify interdisciplinary research opportunities and devise potential solutions to existing problems.
    Original languageEnglish
    Title of host publicationCompanion Proceedings of the 2024 Annual Symposium on Computer-Human Interaction in Play
    Place of PublicationNew York, USA
    PublisherAssociation for Computing Machinery (ACM)
    Pages466-470
    ISBN (Print)979-8-4007-0692-9
    DOIs
    Publication statusPublished - 14 Oct 2024
    EventCHI PLAY '24: The Annual Symposium on Computer-Human Interaction in Play - Tampere, Finland
    Duration: 14 Oct 202417 Oct 2024
    https://chiplay.acm.org/2024/

    Publication series

    NameCHI PLAY Companion '24
    PublisherAssociation for Computing Machinery

    Conference

    ConferenceCHI PLAY '24: The Annual Symposium on Computer-Human Interaction in Play
    Abbreviated titleCHI Play 2024
    Country/TerritoryFinland
    CityTampere
    Period14/10/2417/10/24
    Internet address

    Research Field

    • Former Research Field - Experience Business Transformation

    Keywords

    • AI
    • Machine Learning
    • ethics
    • game AI
    • game data
    • transparency

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