  With the rapid proliferation of artificial intelligence, there is growing
concern over its potential to exacerbate existing biases and societal
disparities and introduce novel ones. This issue has prompted widespread
attention from academia, policymakers, industry, and civil society. While
evidence suggests that integrating human perspectives can mitigate bias-related
issues in AI systems, it also introduces challenges associated with cognitive
biases inherent in human decision-making. Our research focuses on reviewing
existing methodologies and ongoing investigations aimed at understanding
annotation attributes that contribute to bias.
