In today's digital age, the exponential growth of data from diverse sources has paved the way for remarkable advancements in artificial intelligence, machine learning, and predictive analytics. Amidst this rapid evolution, ethically-aligned AI has garnered significant attention, becoming a crucial concept that encompasses the development and deployment of AI systems aligned with ethical principles and values. One of the major concerns surrounding AI is its potential to perpetuate biases or discrimination present in the data it is trained on. For instance, facial recognition systems have been found to exhibit racial and gender biases due to biased datasets. Moreover, the collection and use of personal data raise privacy concerns, increasing the risk of misuse. Former Google Design Ethicist Tristan Harris has emphasized the importance of coordinating efforts and implementing safety measures in AI development to avert potential tragedies. The complexity of balancing specific objectives with broader societal goals, such as fairness and safety, poses challenges for institutions in handling ethical considerations.