Towards Deconfounding the Influence of Subject's Demographic Characteristics in Question Answering

• URL: http://arxiv.org/abs/2104.07571v1
• Date: Thu, 15 Apr 2021 16:26:54 GMT
• Title: Towards Deconfounding the Influence of Subject's Demographic Characteristics in Question Answering
• Authors: Maharshi Gor, Kellie Webster, and Jordan Boyd-Graber
• Abstract summary: Question Answering tasks are used as benchmarks of general machine intelligence. Major QA datasets have skewed distributions over gender, profession, and nationality. We find little evidence that accuracy is lower for people based on gender or nationality.
• Score: 4.540236408836132
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Question Answering (QA) tasks are used as benchmarks of general machine intelligence. Therefore, robust QA evaluation is critical, and metrics should indicate how models will answer any question. However, major QA datasets have skewed distributions over gender, profession, and nationality. Despite that skew, models generalize -- we find little evidence that accuracy is lower for people based on gender or nationality. Instead, there is more variation in question topic and question ambiguity. Adequately accessing the generalization of QA systems requires more representative datasets.

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