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  1. Mapping Ethical Artificial Intelligence Policy Landscape: A Mixed Method Analysis.Tahereh Saheb - 2024 - Science and Engineering Ethics 30 (2):1-26.
    As more national governments adopt policies addressing the ethical implications of artificial intelligence, a comparative analysis of policy documents on these topics can provide valuable insights into emerging concerns and areas of shared importance. This study critically examines 57 policy documents pertaining to ethical AI originating from 24 distinct countries, employing a combination of computational text mining methods and qualitative content analysis. The primary objective is to methodically identify common themes throughout these policy documents and perform a comparative analysis of (...)
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  • Encrypting human rights: The intertwining of resistant voices in the UK state surveillance debate.James Allen-Robertson & Amy Stevens - 2021 - Big Data and Society 8 (1).
    The Snowden revelations in 2013 redrew the lines of debate surrounding surveillance, exposing the extent of state surveillance across multiple nations and triggering legislative reform in many. In the UK, this was in the form of the Investigatory Powers Act. As a contribution to understanding resistance to expanding state surveillance activities, this article reveals the intertwining of diverse interests and voices which speak in opposition to UK state surveillance. Through a computational topic modelling-based mixed methods analysis of the submissions made (...)
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  • Identifying and characterizing scientific authority-related misinformation discourse about hydroxychloroquine on twitter using unsupervised machine learning.Tim K. Mackey, Jiawei Li & Michael Robert Haupt - 2021 - Big Data and Society 8 (1).
    This study investigates the types of misinformation spread on Twitter that evokes scientific authority or evidence when making false claims about the antimalarial drug hydroxychloroquine as a treatment for COVID-19. Specifically, we examined tweets generated after former U.S. President Donald Trump retweeted misinformation about the drug using an unsupervised machine learning approach called the biterm topic model that is used to cluster tweets into misinformation topics based on textual similarity. The top 10 tweets from each topic cluster were content coded (...)
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  • Knowing when to act: A call for an open misinformation library to guide actionable surveillance.Kenneth D. Mandl, Amalie Dyda, Maryke Steffens & Adam G. Dunn - 2021 - Big Data and Society 8 (1).
    The design and reporting of data-driven studies seeking to measure misinformation are patchy and inconsistent, and these studies rarely measure associations with, or effects on, behaviour. The consequence is that data-driven misinformation studies are not yet useful as an empirical basis for guiding when to act on emerging misinformation threats, or for deciding when it is more appropriate to do nothing to avoid inadvertently amplifying misinformation. In a narrative review focused on examples of health-related misinformation, we take a critical perspective (...)
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