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Towards a Universal Knowledge Accelerator

Published: 20 October 2017 Publication History

Abstract

The human mind remains an unparalleled engine of innovation, with its unique ability to make sense of complex information and find deep analogical connections driving progress in science and technology over the past millennia. The recent explosion of online information available in virtually every domain should present an opportunity for accelerating this engine; instead, it threatens to slow it as the information processing limits of individual minds are reached. In this talk I discuss our efforts towards building a universal knowledge accelerator: a system in which the sensemaking people engage in online is captured and made useful for others, leading to virtuous cycles of constantly improving information sources that in turn help people more effectively synthesize and innovate. Approximately 70 billion hours per year in the U.S. alone are spent on complex online sensemaking in domains ranging from scientific literature to health; capturing even a fraction of this could provide significant benefits. We discuss three integrated levels of research that are needed to realize this vision: at the individual level in understanding and capturing higher order cognition; at the computational level in developing new interaction systems and AI partners for human cognition; and at the social level in developing complex and creative crowdsourcing and social computing systems.

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MP4 File (p1-kittur.mp4)

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  1. Towards a Universal Knowledge Accelerator

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    cover image ACM Conferences
    UIST '17: Proceedings of the 30th Annual ACM Symposium on User Interface Software and Technology
    October 2017
    870 pages
    ISBN:9781450349819
    DOI:10.1145/3126594
    Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 20 October 2017

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    Author Tags

    1. AI
    2. crowd work
    3. crowdsourcing
    4. knowledge accelerator
    5. machine learning
    6. organizations
    7. search
    8. sensemaking
    9. social computing
    10. visualization

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    UIST '17

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    UIST '17 Paper Acceptance Rate 73 of 324 submissions, 23%;
    Overall Acceptance Rate 561 of 2,567 submissions, 22%

    Upcoming Conference

    UIST '25
    The 38th Annual ACM Symposium on User Interface Software and Technology
    September 28 - October 1, 2025
    Busan , Republic of Korea

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