Online Symposium Series: Knowledge Asymmetries in the Age of Machine Learning

  • Location:
    Online

The new edition of the Writing Machine Collective (WMC_e7) concerns how to live our contemporary life as citizens of a data society that is highly black-boxed with invisible computational writing and reading processes, and yet shapes how we see, how we know, how we make everyday decisions and how we act. When major technology companies relentlessly maintain a high level of confidentiality in their working process and develop diverse services to capture all-rounded behaviour data, social supervision falls behind with technological advancement. The accumulated knowledge asymmetries in the information environment underpin the corporates’ benefits and power in reality.

A series of symposiums and workshops will cover the pervasive machine operations and the corresponding cultural implications in the age of automation that sidelines individual human intervention. We ask what factors are at work that have made coding a minority activity. If coding and computing have gradually become a pertinent part of our everyday life, how could we afford to be indifferent or remain an under-informed consumer? What potentials of computing have been hidden from us?
By unfolding the knowledge which was intentionally black-boxed and privileged to the minority, the programme aims to raise audiences’ level of attention to the social manipulation embedded in everyday technological services, as well as start responding to the knowledge imbalance via direct participation in coding. This symposium will provide a forum to reflect on the state of democracy and public participation in a technologically-mediated world.

Keynote speakers include Lauren Lee McCarthy, Btihaj Ajana, Beatrice Fazi, Adrian Weller and Frank Pasquale.

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Writing Machine Collective is a group of computational artists based in Hong Kong. Founded in 2007, the non-profit organization has used flexible strategies, including exhibitions, symposium, and workshops, to explore the relationship between art and technologies, and engage the public in a discussion of critical theory, technology, and the arts.

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Knowledge Asymmetries in the Age of Machine Learning was made possible by the Writing Machine Collective and by a project grant from the Hong Kong Arts Development Council.

Hong Kong Arts Development Council fully supports freedom of artistic expression. The views and opinions expressed in this project do not represent the stand of the Council.