Algorithms: Avoiding the Implementation of Institutional Biases
- Published in
- Public Library Quarterly, Vol 37, No. 3
- Authors
- Lori Ayre & Jim Craner
- Date
- 2018
Computer 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.
Available to PLQ subscribers here: Public Library Quarterly
Also available here.
Topics: algorithms, algorithmic decision-making, bias, filter bubble, inadvertent injustice, institutional bias, machine learning