公平的人工智能:揭示高等教育决策中潜在的人类偏见

Tasha Austin, Bharat S. Rawal, Alexandra Diehl, Jonathan Cosme
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引用次数: 0

摘要

本研究的目的是展示人工智能如何作为一种评估工具,在高等教育学生的决策中检测潜在的人类偏见。利用学生申请数据,我们进行了一项小型研究,并应用一组算法来进行深度学习分析,并在确定奖学金获得者时评估人类行为。我们使用这些数据对该组织的领导人进行了采访,以了解他们确定奖学金获得者的标准和期望,并共同探索使用这些算法发现的见解。通过与那些获得奖学金的人进行比较,我们确定了组织实施定量框架的机会-一套可重复的算法,以帮助识别潜在的偏见,然后再授予未来的奖学金获得者。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
AI for Equity: Unpacking Potential Human Bias in Decision Making in Higher Education
The purpose of this study is to show how AI can serve as an assessment tool to detect potential human bias in decision making for students in higher education. Using student application data, we conduct a small study and apply a set of algorithms to perform deep learning analyses and assess human behaviors when identifying scholarship recipients. We conduct an interview with the organization’s leaders using this data to understand their criteria and expectations for identifying scholarship recipients and collectively explore the insights uncovered using these algorithms. Upon comparison to those recipients awarded the scholarships, we identify opportunities for the organization to implement a quantitative framework—a repeatable set of algorithms to help identify potential bias before awarding future scholarship recipients. 
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