arXiv Open Access 2020

Active Fairness Instead of Unawareness

Boris Ruf Marcin Detyniecki

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Abstrak

The possible risk that AI systems could promote discrimination by reproducing and enforcing unwanted bias in data has been broadly discussed in research and society. Many current legal standards demand to remove sensitive attributes from data in order to achieve "fairness through unawareness". We argue that this approach is obsolete in the era of big data where large datasets with highly correlated attributes are common. In the contrary, we propose the active use of sensitive attributes with the purpose of observing and controlling any kind of discrimination, and thus leading to fair results.

Topik & Kata Kunci

cs.AI

Penulis (2)

Boris Ruf

Marcin Detyniecki

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APA MLA BibTeX

Ruf, B., Detyniecki, M. (2020). Active Fairness Instead of Unawareness. https://arxiv.org/abs/2009.06251

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Informasi Jurnal

Tahun Terbit: 2020
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓