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arXiv · 1702.05437

Quantifying Program Bias

Aws Albarghouthi·Loris D'Antoni·Samuel Drews·Aditya Nori
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Abstract

With the range and sensitivity of algorithmic decisions expanding at a break-neck speed, it is imperative that we aggressively investigate whether programs are biased. We propose a novel probabilistic program analysis technique and apply it to quantifying bias in decision-making programs. Specifically, we (i) present a sound and complete automated verification technique for proving quantitative properties of probabilistic programs; (ii) show that certain notions of bias, recently proposed in the fairness literature, can be phrased as quantitative correctness properties; and (iii) present FairSquare, the first verification tool for quantifying program bias, and evaluate it on a range of decision-making programs.

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Aws Albarghouthi, Loris D'Antoni, Samuel Drews, Aditya Nori. 2017-02-17. Quantifying Program Bias. https://arxiv.org/abs/1702.05437

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