IEEE Standard for Algorithmic Bias Considerations
2024
The processes and methodologies to help users address issues of bias in the creation of algorithms are described in this standard. Elements include but are not limited to: criteria for the selection of validation data sets for bias quality control, guidelines on establishing and communicating the application boundaries for which the algorithm has been designed and validated to guard against unintended consequences arising from out-of-bound application of algorithms, and suggestions for user expectation management to help mitigate bias due to incorrect interpretation of systems outputs by users (e.g., correlation vs. causation). (The PDF of this standard is available at no cost at https://ieeexplore.ieee.org/browse/standards/get-program/page/series?id=93)