Theories of "Sexuality" in Natural Language Processing Bias Research
NeutralArtificial Intelligence
- Recent research highlights the need for a deeper understanding of how queer sexualities are represented in Natural Language Processing (NLP) systems, revealing significant gaps in existing literature. The analysis of 55 articles indicates that many studies lack clear definitions of sexuality, often defaulting to normative assumptions.
- This development is crucial as it underscores the importance of inclusivity in NLP research, particularly as language models become more integrated into various applications. Addressing these biases is essential for the ethical deployment of AI technologies.
- The findings resonate with ongoing discussions about bias in NLP, particularly regarding annotation practices in multilingual contexts. As NLP continues to evolve, the need for comprehensive frameworks that account for diverse sexual identities becomes increasingly important to mitigate bias and enhance fairness in AI systems.
— via World Pulse Now AI Editorial System
