Algorithms: avoiding the implementation of institutional biases |
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| Authors: | Lori Ayre Jim Craner |
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| Institution: | 1. The Galecia Group, Petaluma, CA, USAlori.ayre@galecia.com;3. The Galecia Group, Petaluma, CA, USA |
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| Abstract: | ABSTRACTComputer algorithms, the logic and code that power automated decision-making programs, increasingly dominate many aspects of modern society. There are already many examples of institutional biases – including ideological bias, racism, sexism, ableism – being solidified in algorithms, causing harm to already underprivileged populations. This article explores library-specific and society-wide examples as well as efforts to prevent the implementation of these biases in the future. |
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| Keywords: | Algorithmic decision-making algorithms bias filter bubble inadvertent injustice institutional bias machine learning |
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