Social computing applies algorithmic tools and frameworks to explore how human societies function—examining behaviors, organizational formations, systemic patterns, and their effects. As innovations like the Metaverse and pretrained large language models evolve, they introduce unpredictable dynamics into cyber-physical-social systems, making traditional oversight methods insufficient. A human-centered social computing strategy, based on the human-centered AI (HCAI) approach, is therefore viewed as the essential, if not sole, solution. This chapter recommends a multidisciplinary framework that bridges virtual environments, real-world hardware, and social interactions. It involves simulating digital populations, profiling users’ personalities, modeling individual decision-making processes, and running computationally driven deliberation experiments. By employing these elements, researchers can conduct trustworthy trials in systems where humans are integral to feedback loops. The goal is exploiting artificial intelligence and other emerging technologies in an adaptable, dependable, and seamless way in human participation, ultimately serving humans and developing human-centered AI systems.