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Discrimination in machine learning algorithms

Roberta Pappadà
•
Francesco Pauli
2018
  • book part

Abstract
Machine learning algorithms are routinely used for business decisions which may directly affect individuals: for example, because a credit scoring algorithm refuses them a loan. It is then relevant from an ethical (and legal) point of view to ensure that these algorithms do not discriminate based on sensitive attributes (sex, race), which may occur unwittingly and unknowingly by the operator and the management. Statistical tools and methods are then required to detect and eliminate such potential biases.
Archivio
http://hdl.handle.net/11368/2929374
https://it.pearson.com/content/dam/region-core/italy/pearson-italy/pdf/Dirigenti e istituzioni/ISTITUZIONI - HE - PDF - SIS V4.pdf
Diritti
closed access
license:copyright editore
FVG url
https://arts.units.it/request-item?handle=11368/2929374
Soggetti
  • machine learning

  • CEM

  • protected categorie

  • sensible attribute

Visualizzazioni
1
Data di acquisizione
Apr 19, 2024
Vedi dettagli
google-scholar
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