The fields of artificial intelligence, human-robot interaction, and social-ecological systems modeling are witnessing significant developments in human-AI collaboration and social intelligence. Recent research has highlighted the importance of epistemic trust, weak-to-strong generalization frameworks, and diagnostic methodologies for assessing AI knowledge claims. The development of multi-agent systems, collaborative multi-agent debate protocols, and socio-cognitive frameworks for evaluating proactive agents in multi-party negotiation are also noteworthy. Furthermore, the use of large language models, embodied systems, and role-playing mechanics are being explored to enhance operational efficiency, maximize cooperative mechanisms, and improve human-AI interaction. The integration of human-led interaction modes, divergent and convergent thinking personas, and creativity support systems are also being investigated to improve idea quality, preserve diversity and ownership, and provide design principles for human-AI co-creation. Overall, the field of human-AI collaboration and social intelligence is advancing rapidly, with significant potential for impact in a wide range of areas, including decision-making, problem-solving, communication, and research writing.