Cargando…
Implicit data crimes: Machine learning bias arising from misuse of public data
Although open databases are an important resource in the current deep learning (DL) era, they are sometimes used “off label”: Data published for one task are used to train algorithms for a different one. This work aims to highlight that this common practice may lead to biased, overly optimistic resu...
Autores principales: | Shimron, Efrat, Tamir, Jonathan I., Wang, Ke, Lustig, Michael |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
National Academy of Sciences
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9060447/ https://www.ncbi.nlm.nih.gov/pubmed/35312366 http://dx.doi.org/10.1073/pnas.2117203119 |
Ejemplares similares
-
Analysis of selected crime data in Nigeria
por: Oguntunde, Pelumi E., et al.
Publicado: (2018) -
Implicit bias of encoded variables: frameworks for addressing structured bias in EHR–GWAS data
por: Dueñas, Hillary R, et al.
Publicado: (2020) -
The importance of disability representation to address implicit bias in the workplace
por: Derbyshire, Daniel W., et al.
Publicado: (2023) -
Spatio-temporal Crime Analysis and Forecasting on Twitter Data Using Machine Learning Algorithms
por: Vivek, Meghashyam, et al.
Publicado: (2023) -
Implicit-Bias Remedies: Treating Discriminatory Bias as a
Public-Health Problem
por: Greenwald, Anthony G., et al.
Publicado: (2022)