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David M. Berry1, M. Beatrice Fazi1, Michael Dieter2, Ben Roberts1, Caroline Bassett1, Andrew Salway1, Nathaniel Tkacz2
1University of Sussex, United Kingdom; 2University of Warwick, United Kingdom
This panel explores the relationship between complexities in knowledge and method. One of the perennial debates related to the problematic raised by computation is that knowledge and its processing is enveloped within a black-boxed structure which obscures or hides the internal workings of the machine. This has implications not just for programmers, but also for those who rely on computational techniques, such as the digital humanities. Moreover, as algorithms continue to penetrate into broader society, major difficulties are raised when important decisions are made which cannot be understood or checked – this has democratic implications. But not only are decisions and the decision-making process often obscured, the form of knowledge and mode of thought itself are often veiled. These debates have been given greater intensity with the rise of machine-learning systems that are fully able to automate much more complex decision-making processes than the previous generation of algorithms.