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Corporate Disruption in the Science of Machine Learning

Sam Work

Published 2016 in arXiv.org

ABSTRACT

This MSc dissertation considers the effects of the current corporate interest on researchers in the field of machine learning. Situated within the field's cyclical history of academic, public and corporate interest, this dissertation investigates how current researchers view recent developments and negotiate their own research practices within an environment of increased commercial interest and funding. The original research consists of in-depth interviews with 12 machine learning researchers working in both academia and industry. Building on theory from science, technology and society studies, this dissertation problematizes the traditional narratives of the neoliberalization of academic research by allowing the researchers themselves to discuss how their career choices, working environments and interactions with others in the field have been affected by the reinvigorated corporate interest of recent years.

PUBLICATION RECORD

  • Publication year

    2016

  • Venue

    arXiv.org

  • Publication date

    2016-12-13

  • Fields of study

    Sociology, Business, Computer Science

  • Identifiers
    arXiv 1612.04108
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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