The computational bioacoustic Artificial Intelligence (AI) combines machine learning with bioacoustic data to assess animal vocalizations for conservation actions and ecological monitoring. This technological development raised the importance of societal and ethical issues. Privacy is a key concern since sensors put in natural environments may inadvertently record human noises. This is because there is a risk of data exploitation and spying. In addition, problems with animal privacy and the ethical treatment of species arise, especially when invasive techniques such as tagging are employed. Ownership of the data is an additional significant factor, particularly when performing research in areas where indigenous communities reside. The use of bioacoustic data comes from the particular location should maintain the control over it to ensure the importance of the data. The spices or ecosystem which has received less attention will face the risk of biasing conversation effects, compared to the species models which are trained largely for a particular face. In order to improve the conservation efforts at the societal level through the use of bioacoustic AI, by providing a real time data to support environmental regulation. The developed countries and universities may lead this field due to difference in admission of technology which could downgrade the researchers from developing nations. Once the researchers performed the AI automates the events and offers a new opening for AI experts in conservation and increase the concerns about job displacement. Intensive use of AI operations has huge data processing with a carbon impact on environment that needs to be balance with sustainability goals. To ensure a control AI development and usage, ethical outlines under the governance point of view needs to be established. Hence, the transparency in decision-making process, inclusive community engagement, and accountability for AI-driven results are important. The public awareness of conservation shall be done through educational platforms but ensure that inaccurate information does not spread. Apart from benefits of studying biodiversity, the development and implementation of computational bioacoustic AI ultimately frame a strong ethical foundation for the benefit of both the scientific community and the general public profit. This chapter explores the positive approach of bioacoustic AI for both scientific discovery and environmental sustainability by determining the issues related to data ownership and access, privacy, algorithm bias, and community involvement. Addressing these issues can ensure that the social impacts are positive and bioacoustic AI will serve both ecological and social welfare.