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Toward Cultural Bias Evaluation Datasets: The Case of Bengali Gender, Religious, and National Identity

Dipto Das, Shion Guha, Bryan Semaan

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Abstract

Critical studies found NLP systems to bias based on gender and racial identities. However, few studies focused on identities defined by cultural factors like religion and nationality. Compared to English, such research efforts are even further limited in major languages like Bengali due to the unavailability of labeled datasets. This paper describes a process for developing a bias evaluation dataset highlighting cultural influences on identity. We also provide a Bengali dataset as an artifact outcome that can contribute to future critical research.

Topics & Concepts

BengaliUnavailabilityNationalityArtifact (error)Identity (music)Process (computing)Cultural identityComputer scienceNatural language processingArtificial intelligencePsychologySocial psychologyPolitical scienceStatisticsMathematicsImmigrationAestheticsPhilosophyLawFeelingOperating systemHate Speech and Cyberbullying Detection