The responsibility challenge for data

H. V. Jagadish, Lise Getoor, Francesco Bonchi, Krishna Gummadi, Tina Eliassi-Rad, Julia Stoyanovich

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    As data science and artificial intelligence become ubiquitous, they have an increasing impact on society. While many of these impacts are beneficial, others may not be. So understanding and managing these impacts is required of every responsible data scientist. Nevertheless, most human decision-makers use algorithms for efficiency purposes and not to make a better (i.e., fairer) decisions. Even the task of risk assessment in the criminal justice system enables efficiency instead of (and often at the expense of) fairness. So we need to frame the problem with fairness, and other societal impacts, as primary objectives.

    Original languageEnglish (US)
    Title of host publicationSIGMOD 2019 - Proceedings of the 2019 International Conference on Management of Data
    PublisherAssociation for Computing Machinery
    Pages412-414
    Number of pages3
    ISBN (Electronic)9781450356435
    DOIs
    StatePublished - Jun 25 2019
    Event2019 International Conference on Management of Data, SIGMOD 2019 - Amsterdam, Netherlands
    Duration: Jun 30 2019Jul 5 2019

    Publication series

    NameProceedings of the ACM SIGMOD International Conference on Management of Data
    ISSN (Print)0730-8078

    Conference

    Conference2019 International Conference on Management of Data, SIGMOD 2019
    CountryNetherlands
    CityAmsterdam
    Period6/30/197/5/19

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    ASJC Scopus subject areas

    • Software
    • Information Systems

    Cite this

    Jagadish, H. V., Getoor, L., Bonchi, F., Gummadi, K., Eliassi-Rad, T., & Stoyanovich, J. (2019). The responsibility challenge for data. In SIGMOD 2019 - Proceedings of the 2019 International Conference on Management of Data (pp. 412-414). (Proceedings of the ACM SIGMOD International Conference on Management of Data). Association for Computing Machinery. https://doi.org/10.1145/3299869.3300079