论文标题
偏见算法的平均利润
Average Profits of Prejudiced Algorithms
论文作者
论文摘要
我们研究了公司取得的成功水平，具体取决于两种常见评分算法中的哪种用于筛选属于弱势群体的合格申请人。两种算法均经过由偏见的决策者产生的数据培训，独立于公司。一种算法有利于弱势的个体，而另一种算法则体现了培训数据中的偏见。我们为公司通过一种算法比另一种算法获得更大的成功提供了敏锐的保证，具体取决于决策者的偏见水平。
We investigate the level of success a firm achieves depending on which of two common scoring algorithms is used to screen qualified applicants belonging to a disadvantaged group. Both algorithms are trained on data generated by a prejudiced decision-maker independently of the firm. One algorithm favors disadvantaged individuals, while the other algorithm exemplifies prejudice in the training data. We deliver sharp guarantees for when the firm finds more success with one algorithm over the other, depending on the prejudice level of the decision-maker.
