The article discusses how biodiversity data, while crucial for global conservation efforts, often reflect historical social and political inequities. It highlights that biodiversity data are disproportionately collected from high-income countries and areas with stable political environments, leading to biased representations of biodiversity. These biases can influence policy decisions and global conservation strategies, potentially entrenching existing inequalities. The authors argue that while more data and better statistical methods can help, they are not sufficient to address systemic biases without considering the social, political, and economic contexts in which data are collected. The paper emphasizes the need for interdisciplinary collaboration and inclusive processes to ensure that biodiversity data and policies align with equity goals. It calls for a shift from technocratic solutions to community-based monitoring and knowledge generation, which can provide more accurate and representative data. The authors also stress the importance of acknowledging and addressing the historical legacies embedded in biodiversity data, such as colonialism, racial discrimination, and armed conflict, to develop more equitable conservation strategies. The article concludes that effective biodiversity monitoring requires not only technological advancements but also a commitment to social justice and inclusive decision-making processes. By integrating local knowledge and community-based monitoring systems, the conservation community can better address the disparities in biodiversity data and ensure that global conservation efforts are equitable and effective.The article discusses how biodiversity data, while crucial for global conservation efforts, often reflect historical social and political inequities. It highlights that biodiversity data are disproportionately collected from high-income countries and areas with stable political environments, leading to biased representations of biodiversity. These biases can influence policy decisions and global conservation strategies, potentially entrenching existing inequalities. The authors argue that while more data and better statistical methods can help, they are not sufficient to address systemic biases without considering the social, political, and economic contexts in which data are collected. The paper emphasizes the need for interdisciplinary collaboration and inclusive processes to ensure that biodiversity data and policies align with equity goals. It calls for a shift from technocratic solutions to community-based monitoring and knowledge generation, which can provide more accurate and representative data. The authors also stress the importance of acknowledging and addressing the historical legacies embedded in biodiversity data, such as colonialism, racial discrimination, and armed conflict, to develop more equitable conservation strategies. The article concludes that effective biodiversity monitoring requires not only technological advancements but also a commitment to social justice and inclusive decision-making processes. By integrating local knowledge and community-based monitoring systems, the conservation community can better address the disparities in biodiversity data and ensure that global conservation efforts are equitable and effective.