Responsible Data Management

Julia Stoyanovich, Bill Howe, H. V. Jagadish

    Research output: Contribution to journalArticlepeer-review

    Abstract

    The need for responsible data management intensifies with the growing impact of data on society. One central locus of the societal impact of data are Automated Decision Systems (ADS), socio-legal-technical systems that are used broadly in industry, non-profits, and government. ADS process data about people, help make decisions that are consequential to people’s lives, are designed with the stated goals of improving efficiency and promoting equitable access to opportunity, involve a combination of human and automated decision making, and are subject to auditing for legal compliance and to public disclosure. They may or may not use AI, and may or may not operate with a high degree of autonomy, but they rely heavily on data. In this article, we argue that the data management community is uniquely positioned to lead the responsible design, development, use, and oversight of ADS. We outline a technical research agenda that requires that we step outside our comfort zone of engineering for efficiency and accuracy, to also incorporate reasoning about values and beliefs. This seems high-risk, but one of the upsides is being able to explain to our children what we do and why it matters.

    Original languageEnglish (US)
    Pages (from-to)3474-3488
    Number of pages15
    JournalProceedings of the VLDB Endowment
    Volume13
    Issue number12
    DOIs
    StatePublished - 2020

    ASJC Scopus subject areas

    • Computer Science (miscellaneous)
    • Computer Science(all)

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