mlsanityData to 7 Oct 2026

Bias Amplification in Artificial Intelligence Systems

arXiv 1809.07842 ↗First posted 20 Sep 2018cs.AIcited by 15

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Abstract (arXiv)

As Artificial Intelligence (AI) technologies proliferate, concern has centered around the long-term dangers of job loss or threats of machines causing harm to humans. All of this concern, however, detracts from the more pertinent and already existing threats posed by AI today: its ability to amplify bias found in training datasets, and swiftly impact marginalized populations at scale. Government and public sector institutions have a responsibility to citizens to establish a dialogue with technology developers and release thoughtful policy around data standards to ensure diverse representation in datasets to prevent bias amplification and ensure that AI systems are built with inclusion in mind.

Key facts. Cited by 15 papers in the map (data through 7 Oct 2026). First posted on arXiv 20 Sep 2018.

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Citing papers per year: 2021: 2; 2022: 3; 2023: 5; 2024: 3; 2025: 0; 2026: 2.

15 papers.

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