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arXiv:1809.07842cs.AI

Bias Amplification in Artificial Intelligence Systems

Kirsten Lloyd

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Abstract

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.

arXiv comments
Presented at AAAI FSS-18: Artificial Intelligence in Government and Public Sector, Arlington, Virginia, USA
Journal reference
DOI
Subjects
cs.AIArtificial Intelligence

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Discussed in comments1 thread

    • Yes; automated approaches amplify bias[0]. Moreover, automated approaches launder bias; in the general population, people view computers and algorithms as "unbiased", so imagine biased results to be more accurate than humans, because a computer did them. 0…

      freeone3000View on HNParent context

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