The field of artificial intelligence is rapidly evolving, with a growing focus on human-AI collaboration and AI literacy. Recent research has highlighted the need for standardized evaluation of AI-augmented cognitive capabilities, and novel frameworks have been proposed to assess an individual's capacity to effectively collaborate with and leverage AI systems. The development of AI literacy as a measurable construct has significant implications for education, workforce development, and social equity. Additionally, the integration of AI education into established curricula has become increasingly necessary, with problem-based learning approaches showing promise in enhancing critical thinking and real-world knowledge application among students. Noteworthy papers in this area include the introduction of the Artificial Intelligence Quotient (AIQ) framework, which provides a comprehensive framework for quantifying human-AI collaborative intelligence. Another significant contribution is the establishment of a psychometric framework for AI literacy, which provides a coherent and measurable construct for understanding AI literacy. Furthermore, research on user perception and satisfaction with AI systems has emphasized the importance of user-centric approaches in AI development, highlighting the need for effective user training, support, and high-quality information to enhance user experience.